Integration of Hierarchical Goal Network Planning and Autonomous Path Planning
2016-03-01
4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply...become an increasingly influential area of research in the realm of artificial intelligence . Task-based planning algorithms provide a number of...ABSTRACT UU 18. NUMBER OF PAGES 16 19a. NAME OF RESPONSIBLE PERSON Nicholas C Fung a. REPORT Unclassified b. ABSTRACT
Hierarchical robot control structure and Newton's divided difference approach to robot path planning
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A hierarchical robot control is proposed for robot soccer system. The Newton' s divided difference is utilized in robot path planning. This paper describes the problems encoutered, software design considerations, vision algorithm and controls of individual robots. The solutions.to the problems implemented are simple and di rect. It is observed that many of the ideas and solutions can be evolved based on simple theories and concepts. This paper focuses on software structure of multi-agent controls, vision algorithm and simple path planning method.
Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation
Jung, Dongwon
2007-12-01
problem is formulated by setting up geometric linear constraints as well as boundary conditions. Subsequently, we construct B-spline path templates by solving a set of distinct optimization problems. For application in UAV motion planning, the path templates are incorporated to replace parts of the entire path by the smooth B-spline paths. Each path segment is stitched together while preserving continuity to obtain a final smooth reference path to be used for path following control. The path following control for a small fixed-wing UAV to track the prescribed smooth reference path is also addressed. Assuming the UAV is equipped with an autopilot for low level control, we adopt a kinematic error model with respect to the moving Serret-Frenet frame attached to a path for tracking controller design. A kinematic path following control law that commands heading rate is presented. Backstepping is applied to derive the roll angle command by taking into account the approximate closed-loop roll dynamics. A parameter adaptation technique is employed to account for the inaccurate time constant of the closed-loop roll dynamics during actual implementation. Finally, we implement the proposed hierarchical path control of a small UAV on the actual hardware platform, which is based on an 1/5 scale R/C model airframe (Decathlon) and the autopilot hardware and software. Based on the hardware-in-the-loop (HIL) simulation environment, the proposed hierarchical path control algorithm has been validated through on-line, real-time implementation on a small micro-controller. By a seamless integration of the control algorithms for path planning, path smoothing, and path following, it has been demonstrated that the UAV equipped with a small autopilot having limited computational resources manages to accomplish the path control objective to reach the goal while avoiding obstacles with minimal human intervention.
Lai, Xue-Cheng; Ge, Shuzhi Sam; Al Mamun, Abdullah
2007-12-01
This paper studies a hierarchical approach for incrementally driving a nonholonomic mobile robot to its destination in unknown environments. The A* algorithm is modified to handle a map containing unknown information. Based on it, optimal (discrete) paths are incrementally generated with a periodically updated map. Next, accelerations in varying velocities are taken into account in predicting the robot pose and the robot trajectory resulting from a motion command. Obstacle constraints are transformed to suitable velocity limits so that the robot can move as fast as possible while avoiding collisions when needed. Then, to trace the discrete path, the system searches for a waypoint-directed optimized motion in a reduced 1-D translation or rotation velocity space. Various situations of navigation are dealt with by using different strategies rather than a single objective function. Extensive simulations and experiments verified the efficacy of the proposed approach.
融合出租车驾驶经验的层次路径规划方法%Hierarchical Path Planning Method Based on Taxi Driver Experiences
Institute of Scientific and Technical Information of China (English)
胡继华; 黄泽; 邓俊; 谢海莹
2013-01-01
The route choice behaviors of taxi drivers are usually representative because they are more familiar with urban road status. This makes it possible to use the taxi drivers' experience to support the path planning. To make the guidance result meet the drivers' expectations well, this study presents a hierarchical path planning method using the taxi driver experiences. The method consists of three steps; first, routes are recovered from the taxi trajectories; second, all roads are redefined and categorized according to the track data and the road network is classified into different experience grades using travel frequency for road segments; third, with the Dijkstra algorithm, a hierarchical path planning method is proposed. Finally, taking Guangzhou city as an example, this paper compares the paths generated by the proposed approach with the conventional algorithm's results. The experimental result shows that travel time of the paths planned by the proposed method has been effectively reduced.%出租车驾驶员对城市道路交通状况较为熟悉,他们选择的路径具有代表性,因此将出租车驾驶员路径选择经验融合到路径规划算法中,对提高出行效率具有重要的意义.本文提出一种融合出租车驾驶经验的层次路径规划方法,主要包括三部分:首先,从出租车GPS数据中提取出出租车载客行驶轨迹；然后,根据各路段出租车行驶频率高低对路网进行分层,构建基于出租车经验路径的分层路网；在此基础上,使用Dijkstra算法实现层次路径规划.最后,本文以广州市为研究区域,将该方法得到的规划路径与经典路径规划算法的结果进行比较.结果表明,融合出租车驾驶经验的路径规划方法所得路径在行程时间上占有一定的优势.
Path planning under spatial uncertainty.
Wiener, Jan M; Lafon, Matthieu; Berthoz, Alain
2008-04-01
In this article, we present experiments studying path planning under spatial uncertainties. In the main experiment, the participants' task was to navigate the shortest possible path to find an object hidden in one of four places and to bring it to the final destination. The probability of finding the object (probability matrix) was different for each of the four places and varied between conditions. Givensuch uncertainties about the object's location, planning a single path is not sufficient. Participants had to generate multiple consecutive plans (metaplans)--for example: If the object is found in A, proceed to the destination; if the object is not found, proceed to B; and so on. The optimal solution depends on the specific probability matrix. In each condition, participants learned a different probability matrix and were then asked to report the optimal metaplan. Results demonstrate effective integration of the probabilistic information about the object's location during planning. We present a hierarchical planning scheme that could account for participants' behavior, as well as for systematic errors and differences between conditions.
Path planning in dynamic environments
Berg, J.P. van den
2007-01-01
Path planning plays an important role in various fields of application, such as CAD design, computer games and virtual environments, molecular biology, and robotics. In its most general form, the path planning problem is formulated as finding a collision-free path for a moving entity between a start
Angelic Hierarchical Planning: Optimal and Online Algorithms
2008-12-06
restrict our attention to plans in I∗(Act, s0). Definition 2. ( Parr and Russell , 1998) A plan ah∗ is hierarchically optimal iff ah∗ = argmina∈I∗(Act,s0):T...Murdock, Dan Wu, and Fusun Yaman. SHOP2: An HTN planning system. JAIR, 20:379–404, 2003. Ronald Parr and Stuart Russell . Reinforcement Learning with...Angelic Hierarchical Planning: Optimal and Online Algorithms Bhaskara Marthi Stuart J. Russell Jason Wolfe Electrical Engineering and Computer
Multiresolution Path Planning for Mobile Robots,
1985-05-01
8217U’ MULTIRESOLUTION PATH PLANNING * . FOR MOBILE ROBOTS I Subbarao Kambhampati * -- Larry S. Davis Computer Vision Laboratory * Center for Automation...COUWEPARK MARVUM EP Vo Is- .. . .. CAR-TR-127 DAAK70-83-K--0018 CS-TR-1507 MAY 1085 MULTIRESOLUTION PATH PLANNING FOR MOBILE ROBOTS Subbarao Kambhampati...planning is central to mobile * robot applications. Path planning for mobile robots is in many ways different * from the more familiar case of path
Multi-level Indoor Path Planning Method
Xiong, Q.; Zhu, Q.; Zlatanova, S.; Du, Z.; Zhang, Y.; Zeng, L.
2015-01-01
Indoor navigation is increasingly widespread in complex indoor environments, and indoor path planning is the most important part of indoor navigation. Path planning generally refers to finding the most suitable path connecting two locations, while avoiding collision with obstacles. However, it is a
Strategic Team AI Path Plans: Probabilistic Pathfinding
Directory of Open Access Journals (Sweden)
Tng C. H. John
2008-01-01
Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.
Integrated assignment and path planning
Murphey, Robert A.
2005-11-01
A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact
Cooperative path planning of unmanned aerial vehicles
Tsourdos, Antonios; Shanmugavel, Madhavan
2010-01-01
An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully.
Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles
Cowlagi, Raghvendra V.
Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption
Hierarchical Task Planning for Multiarm Robot with Multiconstraint
Directory of Open Access Journals (Sweden)
Yifan Wang
2016-01-01
Full Text Available Multiarm systems become the trends of space robots, for the on-orbit servicing missions are becoming more complex and various. A hierarchical task planning method with multiconstraint for multiarm space robot is presented in this paper. The process of task planning is separated into two hierarchies: mission profile analysis and task node planning. In mission profile analysis, several kinds of primitive tasks and operators are defined. Then, a complex task can be decomposed into a sequence of primitive tasks by using hierarchical task network (HTN with those primitive tasks and operators. In task node planning, A⁎ algorithm is improved to adapt the continuous motion of manipulator. Then, some of the primitive tasks which cannot be executed directly because of constraints are further decomposed into several task nodes by using improved A⁎ algorithm. Finally, manipulators execute the task by moving from one node to another with a simple path plan algorithm. The feasibility and effectiveness of the proposed task planning method are verified by simulation.
Robot path planning using genetic algorithms
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation a dopted, to avoid the common defect of early convergence and converge faster than the standard genetic algo rithms concludes from simulation results that the method is effective for robot path planning.
限定搜索区域的分层遗传算法无人机路径规划%Restricted Searching Area Hierarchical Genetic Algorithm for UAV Path Planning
Institute of Scientific and Technical Information of China (English)
王景; 李京华; 倪宁; 武琳静
2011-01-01
为克服简单遗传算法易陷入局部最优解的缺点,减小路径搜索范围,提出了限定搜索区域的分层遗传算法无人机路径规划方法,该方法将分层遗传算法引入无人机路径规划的优化搜索问题中,将路径节点的二维坐标作为基因进行编码,根据威胁的分布情况缩小路径规划算法的搜索范围,使子种群可以获得包含不同优良模式的新个体,为子种群提供更加平等的竞争生存机会,使优化搜索有较为明确的搜索方向.仿真结果表明:与基于分层遗传算法的路径规划方法相比,该方法提高了路径寻优算法的性能,减少了绕行路径的出现几率,缩短了最优路径的长度.%In order to overcome the shortcoming of simple genetic algorithm (SGA) that it is to fall into the local optimal solution and reduce the path search range, a restricted-searching-area HGA path planning approach was proposed. In this approach,the Hierarchy Genetic Algorithm (HGA) was introduced into the optimization problem of the UAV path planning, 2D coordinates of path nodes were coded as genes, searching area of path planning algorithm was reduced according to the distribution of threats,subpopulation could obtain individuals of different optimal patterns, and provided the subpopulation more equal an opportunity to compete with each to survival,thus the searching process became more directional. The simulation results showed that,comparing with HGA based path planning approaches, the proposed approach enhanced the performance optimal path planning and reduced the incidence of by-pass paths, thus the length of optimal path was shortened.
Path Planning Control for Mobile Robot
Directory of Open Access Journals (Sweden)
Amenah A.H. Salih
2011-01-01
Full Text Available Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process. This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and points of intersection with the straight path to find the nearly optimal path which connects the start and the goal point.This work has theoretical part and experimental part. The theoretical part includes building a MATLAB program which is applied to environment image to find the nearly optimal path .MATLAB - C++.NET interface is accomplished then to supply the path information for C++.NET program which is done for programming the pioneer mobile robot to achieve the desired path. The experimental part includes using wireless camera that takes an image for the environment and send it to the computer which processes this image and sends ( by wireless connection the resulted path information to robot which programmed in C++.NET program to walk according to this path.So, the overall system can be represented by:Wireless camera computer wireless connection for the mobile robot .The experimental work including some experiments shows that the developed mobile robot (pioneer p3-dx travels successfully from the start point and reach the goal point across the optimal path (according to time and power which is obtained as result of the proposed path planning algorithm introduced in this paper.
Wiener, J M; Ehbauer, N N; Mallot, H A
2009-09-01
For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.
Hierarchical Planning Methodology for a Supply Chain Management
National Research Council Canada - National Science Library
Virna Ortiz-Araya; Víctor M Albornoz
2012-01-01
Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision-making levels of the planning...
Feasible Path Planning for Autonomous Vehicles
Directory of Open Access Journals (Sweden)
Vu Trieu Minh
2014-01-01
Full Text Available The objective of this paper is to find feasible path planning algorithms for nonholonomic vehicles including flatness, polynomial, and symmetric polynomial trajectories subject to the real vehicle dynamical constraints. Performances of these path planning methods are simulated and compared to evaluate the more realistic and smoother generated trajectories. Results show that the symmetric polynomial algorithm provides the smoothest trajectory. Therefore, this algorithm is recommended for the development of an automatic control for autonomous vehicles.
Parallel path planning in unknown terrains
Prassler, Erwin A.; Milios, Evangelos E.
1991-03-01
We present a parallel processing approach to path planning in unknown terrains which combines map-based and sensor-based techniques into a real-time capable navigation system. The method is based on massively parallel computations in a grid of simple processing elements denoted as cells. In the course of a relaxation process a potential distribution is created in the grid which exhibits a monotonous slope from a start cell to the cell corresponding to the robot''s goal position. A shortest path is determined by means of a gradient descent criterion which settles on the steepest descent in the potential distribution. Like high-level path planning algorithms our approach is capable of planning shortest paths through an arbitrarily cluttered large-scale terrain on the basis of its current internal map. Sequentially implemented its complexity is in the order of efficient classical path planning algorithms. Unlike these algorithms however the method is also highly responsive to new obstacles encountered in the terrain. By continuing the planning process during the robot''s locomotion information about previously unknown obstacles immediately affects further path planning without a need to interrupt the ongoing planning process. New obstacles cause distortions of the potential distribution which let the robot find proper detours. By ensuring a monotonous slope in the overall distribution we avoid local minimum effects which may trap a robot in the proximity of an obstacle configuration before it has reached its goal. 1 Until the recent past research on path planning in the presence of obstacles can be assigned to two major categories: map-based high-level planning approaches and sensor-based low-level conLrol approaches. In work such as 12 path planning is treated as a high-level planning task. Assuming that an (accnrae) precompiled map of the terrain is available high-level path planners provide paths which guarantee a collision-free locomotion through an arbitrary
Institute of Scientific and Technical Information of China (English)
祁悦; 赵洋; 杨帆
2014-01-01
This paper focuses on how to generate a 3D navmesh and implement high-speed path-finding for autonomous characters in 3D games. We proposed a hierarchical solution to meet the requirement. Firstly, a navmesh is used to divide the state space. Then we used the A* algorithm to find the path of the navmesh with making use of binary heaps to optimize the OPEN table. We also proposed a method of corner points to find the final path. At last, we used ray transmission to detect the dynamic obstacles. The initial experimentation shows that our solution is able to be used in some 3D games.%以3D游戏中智能体的路径规划为研究背景，对于如何生成3D游戏的地形网格以及如何进行高速、准确的路径规划进行了研究。提出了一种分层的解决方案，首先通过建立导航网格划分状态空间；接着使用引入地形估价因子的算法进行网格寻路，并通过拐角点法生成路径，同时对算法的OPEN表进行了二叉堆的优化；最后介绍了基于射线透射的局部算法对动态障碍物的处理。实验分析表明该算法的有效性。
Aircraft Path Planning under Adverse Weather Conditions
Directory of Open Access Journals (Sweden)
Xie Z.
2016-01-01
Full Text Available In recent years, flight safety is still one of the main issues for all airlines. En route civil airplanes may encounter adverse weather conditions. Some fatal airplane accidents happened because of the weather disturbance. Moreover, we should also design path to avoid the prohibited area. Therefore a good path planning algorithm plays an increasingly important role in air traffic management. An efficient path planning algorithm can help the plane to avoid severe weather conditions, restricted areas and moving obstacles to ensure the safety of the cabin crews and passengers. Here, we build our algorithm based on the A* search algorithm. Moreover, our algorithm can also find the path with least energy costs. As a result, our algorithm can improve the safety operation of the airplanes and reduce the workload of pilots and air traffic controllers.
A novel method for robot path planning
Institute of Scientific and Technical Information of China (English)
CAI Qiang; LI Hai-sheng; YANG Qin; LI Ji-gang
2009-01-01
Path planning is one of the most important problems in the design of a mobile robot. A novel approach called generalized Voronoi diagrams (GVD) may deal with this matter. First, a method was introduced to normalize the obstacles and present efficient techniques for generating GVDs. Then a best path searching algorithm was presented. Examples implemented were given to indicate the availability of the mentioned algorithms. The approaches in this paper can also be used in applications including visualization, spatial data manipulation, etc.
Robot path planning using a genetic algorithm
Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu
1988-01-01
Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
Collaborative path planning for a robotic wheelchair.
Zeng, Qiang; Teo, Chee Leong; Rebsamen, Brice; Burdet, Etienne
2008-11-01
Generating a path to guide a wheelchair's motion faces two challenges. First, the path is located in the human environment and that is usually unstructured and dynamic. Thus, it is difficult to generate a reliable map and plan paths on it by artificial intelligence. Second, the wheelchair, whose task is to carry a human user, should move on a smooth and comfortable path adapted to the user's intentions. To meet these challenges, we propose that the human operator and the robot interact to create and gradually improve a guide path. This paper introduces design tools to enable an intuitive interaction, and reports experiments performed with healthy subjects in order to investigate this collaborative path learning strategy. We analyzed features of the optimal paths and user evaluation in representative conditions. This was complemented by a questionnaire filled out by the subjects after the experiments. The results demonstrate the effectiveness of this approach, and show the utility and complementarity of the tools to design ergonomic guide paths.
Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network.
Balaguer, Jan; Spiers, Hugo; Hassabis, Demis; Summerfield, Christopher
2016-05-18
Planning allows actions to be structured in pursuit of a future goal. However, in natural environments, planning over multiple possible future states incurs prohibitive computational costs. To represent plans efficiently, states can be clustered hierarchically into "contexts". For example, representing a journey through a subway network as a succession of individual states (stations) is more costly than encoding a sequence of contexts (lines) and context switches (line changes). Here, using functional brain imaging, we asked humans to perform a planning task in a virtual subway network. Behavioral analyses revealed that humans executed a hierarchically organized plan. Brain activity in the dorsomedial prefrontal cortex and premotor cortex scaled with the cost of hierarchical plan representation and unique neural signals in these regions signaled contexts and context switches. These results suggest that humans represent hierarchical plans using a network of caudal prefrontal structures. VIDEO ABSTRACT.
Planning paths through a spatial hierarchy - Eliminating stair-stepping effects
Slack, Marc G.
1989-01-01
Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.
Learning to improve path planning performance
Energy Technology Data Exchange (ETDEWEB)
Chen, Pang C.
1995-04-01
In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To remedy this situation, we present and analyze a learning algorithm that uses past experience to increase future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful.
Ways of looking ahead: hierarchical planning in language production.
Lee, Eun-Kyung; Brown-Schmidt, Sarah; Watson, Duane G
2013-12-01
It is generally assumed that language production proceeds incrementally, with chunks of linguistic structure planned ahead of speech. Extensive research has examined the scope of language production and suggests that the size of planned chunks varies across contexts (Ferreira & Swets, 2002; Wagner & Jescheniak, 2010). By contrast, relatively little is known about the structure of advance planning, specifically whether planning proceeds incrementally according to the surface structure of the utterance, or whether speakers plan according to the hierarchical relationships between utterance elements. In two experiments, we examine the structure and scope of lexical planning in language production using a picture description task. Analyses of speech onset times and word durations show that speakers engage in hierarchical planning such that structurally dependent lexical items are planned together and that hierarchical planning occurs for both direct and indirect dependencies. Copyright © 2013 Elsevier B.V. All rights reserved.
Stochastic Evolutionary Algorithms for Planning Robot Paths
Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard
2006-01-01
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
Li, Qingquan; Zeng, Zhe; Zhang, Tong; Li, Jonathan; Wu, Zhongheng
2011-02-01
Optimal paths computed by conventional path-planning algorithms are usually not "optimal" since realistic traffic information and local road network characteristics are not considered. We present a new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories. The approach consists of three steps. First, routes are recovered from original taxi trajectories. Second, an experiential road hierarchy is constructed using travel frequency and speed information for road segments. Third, experiential optimal paths are planned based on the experiential road hierarchy. Compared with conventional path-planning methods, the proposed method provides better experiential optimal path identification. Experiments demonstrate that the travel time is less for these experiential paths than for paths planned by conventional methods. Results obtained for a case study in the city of Wuhan, China, demonstrate that experiential optimal paths can be flexibly obtained in different time intervals, particularly during peak hours.
Sub-optimality analysis of mobile robot rolling path planning
Institute of Scientific and Technical Information of China (English)
张纯刚; 席裕庚
2003-01-01
Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.
Adaptive path planning: Algorithm and analysis
Energy Technology Data Exchange (ETDEWEB)
Chen, Pang C.
1993-03-01
Path planning has to be fast to support real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To alleviate this problem, we present a learning algorithm that uses past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful subgoals is learned to support faster planning. The algorithm is suitable for both stationary and incrementally-changing environments. To analyze our algorithm, we use a previously developed stochastic model that quantifies experience utility. Using this model, we characterize the situations in which the adaptive planner is useful, and provide quantitative bounds to predict its behavior. The results are demonstrated with problems in manipulator planning. Our algorithm and analysis are sufficiently general that they may also be applied to task planning or other planning domains in which experience is useful.
Survey of Robot 3D Path Planning Algorithms
Liang Yang; Juntong Qi; Dalei Song; Jizhong Xiao; Jianda Han; Yong Xia
2016-01-01
Robot 3D (three-dimension) path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints). The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path...
Path Planning in a Dynamic Environment
Directory of Open Access Journals (Sweden)
Mohamed EL KHAILI
2014-08-01
Full Text Available Path planning is an important area in the control of autonomous mobile robots. Recent work has focused on aspects reductions in processing time than the memory requirements. A dynamic environment uses a lot of memory and hence the processing time increases too. Our approach is to reduce the processing time by the use of a pictorial approach to reduce the number of data used. In this paper, we present a path planning approach that operates in three steps. First, a construction of the visibility tree is performed. The following treatments are not performed on the original image but on the result tree whose elements are specific points of the environment linked by the relationship of visibility. We construct thereafter a visibility graph which one seeks the shortest path. This approach has a great interest because of its fast execution speed. The path search is extended also for the case where obstacles can move. The moving obstacles may be other mobile robots whose trajectories and speeds are known initially. At the end, some applications are provided on solving similar problem such civil aviation in order to guide plane avoiding collisions.
Cutting Path Planning for Ruled Surface Impellers
Institute of Scientific and Technical Information of China (English)
Liang Quan; Wang Yongzhang; Fu Hongya; Han Zhenyu
2008-01-01
At present, most commercial computer-aided manufacturing (CAM) systems are deficient in efficiency and performances on generating tool path during machining impellers. To solve the problem, this article develops a special software to plan cutting path for ruled surface impellers. An approximation algorithm to generate cutting path for machining integral ruled surface impellers is proposed. By fitting sampling data points of an impeller blade into a curve, a model of ruled surface blade of an impeller is built up. Furthermore, by calculating the points where the cutter axis vector intersects the flee-form hub surface of an impeller, problems about, for instance, the ambiguity in calculation and machining the wide blade surface with a short flute cutter are solved. Finally, an integral impeller cutting path is planned by way of an integrated cutter location control algorithm. Simulation and machining tests with an impeller are performed on a 5-axis computer numerically controlled (CNC) mill machine, which shows the feasibility of the proposed algorithm.
Study on Hierarchical Structure of Detailed Control Planning
Institute of Scientific and Technical Information of China (English)
2010-01-01
Using case studies,this paper analyzes the characteristics of detailed control planning and its hierarchical controls,the form and composition of plan content,and methodological innovations.It then suggests improvements to the planning structure that are oriented at adaptability,fairness,centrality,and scientific principles with regard to the content,methods,and results of the planning.Regarding the hierarchical control system,the paper suggests that the detailed control plan should be composed of "block planning" and "plot planning".It is believed that through a combination of block and plot planning,the problem of joining long-term and short-term planning will be solved and it will be possible to address the need for adjustment and revision of detailed control plan.
Hierarchical Planning Methodology for a Supply Chain Management
Directory of Open Access Journals (Sweden)
Virna ORTIZ-ARAYA
2012-01-01
Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.
Adaptive robot path planning in changing environments
Energy Technology Data Exchange (ETDEWEB)
Chen, P.C.
1994-08-01
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for incrementally-changing environments such as those encountered in manufacturing of evolving products and waste-site remediation. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
Path planning algorithms for assembly sequence planning. [in robot kinematics
Krishnan, S. S.; Sanderson, Arthur C.
1991-01-01
Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.
Adaptive path planning: Algorithm and analysis
Energy Technology Data Exchange (ETDEWEB)
Chen, Pang C.
1995-03-01
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions difficult tasks. From these solutions, an evolving sparse work of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a framework in which a slow but effective planner may be improved both cost-wise and capability-wise by a faster but less effective planner coupled with experience. We analyze algorithm by formalizing the concept of improvability and deriving conditions under which a planner can be improved within the framework. The analysis is based on two stochastic models, one pessimistic (on task complexity), the other randomized (on experience utility). Using these models, we derive quantitative bounds to predict the learning behavior. We use these estimation tools to characterize the situations in which the algorithm is useful and to provide bounds on the training time. In particular, we show how to predict the maximum achievable speedup. Additionally, our analysis techniques are elementary and should be useful for studying other types of probabilistic learning as well.
Replanning Using Hierarchical Task Network and Operator-Based Planning
Wang, X.; Chien, S.
1997-01-01
In order to scale-up to real-world problems, planning systems must be able to replan in order to deal with changes in problem context. In this paper we describe hierarchical task network and operatorbased re-planning techniques which allow adaptation of a previous plan to account for problems associated with executing plans in real-world domains with uncertainty, concurrency, changing objectives.
UAV Path Planning using MILP with Experiments
Directory of Open Access Journals (Sweden)
Anders Albert
2017-01-01
Full Text Available In this paper, we look at the problem of tracking icebergs using multiple Unmanned Aerial Vehicles (UAVs. Our solutions use combinatorial optimization for UAV path planning by formulating a mixed integer linear programing (MILP optimization problem. To demonstrate the approach, we present both a simulation and a practical experiment. The simulation demonstrates the possibilities of the MILP algorithm by constructing a case where three UAVs help a boat make a safe passage through an area with icebergs. Furthermore, we compare the performance of three against a single UAV. In the practical experiment, we take the first step towards full-scale experiments. We run the algorithm on a ground station and use it to set the path for a UAV tracking five simulated icebergs.
Stealth-Based Path Planning using Corridor Maps
Geraerts, R.J.|info:eu-repo/dai/nl/304830291; Schager, E.
2010-01-01
A relatively new area within the field of path planning deals with computing a stealthy path for a character moving in a virtual environment. Besides efficiently obtaining a path that is collision-free, short and smooth, the added difficulty is that the path must have little or no exposure to observ
An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles
Energy Technology Data Exchange (ETDEWEB)
Cunningham, C.T.; Roberts, R.S.
2000-09-12
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
Path planning on satellite images for unmanned surface vehicles
Directory of Open Access Journals (Sweden)
Joe-Ming Yang
2015-01-01
Full Text Available In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A * algorithm (FAA *, an advanced A * algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV
Robot path planning in dynamic environment based on reinforcement learning
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Proposes an adaptive learning method based on reinforcement learning for robot path planning prob lem, which enables the robot to adaptively learn and perform effective path planning, to avoid the moving obsta cles and reach the target. Thereby achieving automatic construction of path planning strategy and making the system adaptive to multi-robots system dynamic environments, and concludes from computer simulation experi ment that the method is powerful to solve the problem of multi-robot path planning, and it is a meaningful try to apply reinforcement learning techniques in multi-robot systems to develop the system's intelligence degree.
Global path planning of mobile robots using a memetic algorithm
Zhu, Zexuan; Wang, Fangxiao; He, Shan; Sun, Yiwen
2015-08-01
In this paper, a memetic algorithm for global path planning (MAGPP) of mobile robots is proposed. MAGPP is a synergy of genetic algorithm (GA) based global path planning and a local path refinement. Particularly, candidate path solutions are represented as GA individuals and evolved with evolutionary operators. In each GA generation, the local path refinement is applied to the GA individuals to rectify and improve the paths encoded. MAGPP is characterised by a flexible path encoding scheme, which is introduced to encode the obstacles bypassed by a path. Both path length and smoothness are considered as fitness evaluation criteria. MAGPP is tested on simulated maps and compared with other counterpart algorithms. The experimental results demonstrate the efficiency of MAGPP and it is shown to obtain better solutions than the other compared algorithms.
AN OPTIMUM VEHICULAR PATH ALGORITHM FOR TRAFFIC NETWORK BASED ON HIERARCHICAL SPATIAL REASONING
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.
Needle Path Planning for Autonomous Robotic Surgical Suturing.
Jackson, Russell C; Cavuşoğlu, M Cenk
2013-12-31
This paper develops a path plan for suture needles used with solid tissue volumes in endoscopic surgery. The path trajectory is based on the best practices that are used by surgeons. The path attempts to minimize the interaction forces between the tissue and the needle. Using surgical guides as a basis, two different techniques for driving a suture needle are developed. The two techniques are compared in hardware experiments by robotically driving the suture needle using both of the motion plans.
A New Method of Global Path Planning for AGV
Institute of Scientific and Technical Information of China (English)
SHI En-xiu; HUANG Yu-mei
2006-01-01
Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle(AGV), which is a kind of MR, is used in a flexible manufacturing system(FMS). Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine (APMM) and Relative Pos Matrix of Machines (RPMM), which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result: simplicity, saving time and reliability.
Tool path planning based on conformal parameterization for meshes
Institute of Scientific and Technical Information of China (English)
Zhao Jibin; Zou Qiang; Li Lun; Zhou Bo
2015-01-01
The similarity property of conformal parameterization makes it able to locally preserve the shapes between a surface and its parameter domain, as opposed to common parameterization methods. A parametric tool path planning method is proposed in this paper through such parameterization of triangular meshes which is furthermore based on the geodesic on meshes. The parameterization has the properties of local similarity and free boundary which are exploited to simplify the formulas for computing path parameters, which play a fundamentally important role in tool path planning, and keep the path boundary-conformed and smooth. Experimental results are given to illustrate the effectiveness of the proposed methods, as well as the error analysis.
Analysis of construction dynamic plan using fuzzy critical path method
Directory of Open Access Journals (Sweden)
Kurij Kazimir V.
2014-01-01
Full Text Available Critical Path Method (CPM technique has become widely recognized as valuable tool for the planning and scheduling large construction projects. The aim of this paper is to present an analytical method for finding the Critical Path in the precedence network diagram where the duration of each activity is represented by a trapezoidal fuzzy number. This Fuzzy Critical Path Method (FCPM uses a defuzzification formula for trapezoidal fuzzy number and applies it on the total float (slack time for each activity in the fuzzy precedence network to find the critical path. The method presented in this paper is very effective in determining the critical activities and finding the critical paths.
Mobile robot dynamic path planning based on improved genetic algorithm
Wang, Yong; Zhou, Heng; Wang, Ying
2017-08-01
In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.
A* Path Planning for Line Segmentation of Handwritten Documents
Surinta, Olarik; Karaaba, Mahir; van Oosten, Jean-Paul; Schomaker, Lambertus; Wiering, Marco
2014-01-01
This paper describes the use of a novel A∗ path-planning algorithm for performing line segmentation of handwritten documents. The novelty of the proposed approach lies in the use of a smart combination of simple soft cost functions that allows an artificial agent to compute paths separating the uppe
A Hybrid 3D Path Planning Method for UAVs
DEFF Research Database (Denmark)
Ortiz-Arroyo, Daniel
2015-01-01
This paper presents a hybrid method for path planning in 3D spaces. We propose an improvement to a near-optimal 2D off-line algorithm and a ﬂexible normalized on-line fuzzy controller to ﬁnd shortest paths. Our method, targeted to low altitude domains, is simple and efﬁcient. Our preliminary resu...
Path Planning with a Lazy Significant Edge Algorithm (LSEA
Directory of Open Access Journals (Sweden)
Joseph Polden
2013-04-01
Full Text Available Probabilistic methods have been proven to be effective for robotic path planning in a geometrically complex environment. In this paper, we propose a novel approach, which utilizes a specialized roadmap expansion phase, to improve lazy probabilistic path planning. This expansion phase analyses roadmap connectivity information to bias sampling towards objects in the workspace that have not yet been navigated by the robot. A new method to reduce the number of samples required to navigate narrow passages is also proposed and tested. Experimental results show that the new algorithm is more efficient than the traditional path planning methodologies. It was able to generate solutions for a variety of path planning problems faster, using fewer samples to arrive at a valid solution.
Trajectory Generation and Path Planning for Autonomous Aerobots
Sharma, Shivanjli; Kulczycki, Eric A.; Elfes, Alberto
2007-01-01
This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.
A bi-criteria path planning algorithm for robotics applications
Clawson, Zachary; Ding, Xuchu; Englot, Brendan; Frewen, Thomas A.; Sisson, William M.; Vladimirsky, Alexander
2015-01-01
Realistic path planning applications often require optimizing with respect to several criteria simultaneously. Here we introduce an efficient algorithm for bi-criteria path planning on graphs. Our approach is based on augmenting the state space to keep track of the "budget" remaining to satisfy the constraints on secondary cost. The resulting augmented graph is acyclic and the primary cost can be then minimized by a simple upward sweep through budget levels. The efficiency and accuracy of our...
Path planning for everday robotics with SANDROS
Energy Technology Data Exchange (ETDEWEB)
Watterberg, P.; Xavier, P. [Sandia National Labs., Albuquerque, NM (United States); Hwang, Y. [Korea Inst. of Science and Technology, Seoul (Korea, Republic of)
1997-02-01
We discuss the integration of the SANDROS path planner into a general robot simulation and control package with the inclusion of a fast geometry engine for distance calculations. This creates a single system that allows the path to be computed, simulated, and then executed on the physical robot. The architecture and usage procedures are presented. Also, we present examples of its usage in typical environments found in our organization. The resulting system is as easy to use as the general simulation system (which is in common use here) and is fast enough (example problems are solved in seconds) to be used interactively on an everyday basis.
DEFF Research Database (Denmark)
Kallestrup, Kasper Bislev; Lynge, Lasse Hadberg; Akkerman, Renzo;
2014-01-01
In this paper, we discuss the development of decision support systems for hierarchically structured planning approaches, such as commercially available advanced planning systems. We develop a framework to show how such a decision support system can be designed with the existing organization in mind......, and how a decision process and corresponding software can be developed from this basis. Building on well-known hierarchical planning concepts, we include the typical anticipation mechanisms used in such systems to be able to decompose planning problems, both from the perspective of the planning problem...... and from the perspective of the organizational aspects involved. To exemplify and develop our framework, we use a case study of crude oil procurement planning in the refining industry. The results of the case study indicate an improved organizational embedding of the DSS, leading to significant savings...
Optimal Path Planning for Mobile Robot Using Tailored Genetic Algorithm
Directory of Open Access Journals (Sweden)
Dong Xiao Xian
2013-07-01
Full Text Available During routine inspecting, mobile robot may be requested to visit multiple locations to execute special tasks occasionally. This study aims at optimal path planning for multiple goals visiting task based on tailored genetic algorithm. The proposed algorithm will generate an optimal path that has the least idle time, which is proven to be more effective on evaluating a path in our previous work. In proposed algorithm, customized chromosome representing a path and genetic operators including repair and cut are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.
Development of Flight Path Planning for Multirotor Aerial Vehicles
Directory of Open Access Journals (Sweden)
Yi-Ju Tsai
2015-04-01
Full Text Available This study addresses the flight-path planning problem for multirotor aerial vehicles (AVs. We consider the specific features and requirements of real-time flight-path planning and develop a rapidly-exploring random tree (RRT algorithm to determine a preliminary flight path in three-dimensional space. Since the path obtained by the RRT may not be optimal due to the existence of redundant waypoints. To reduce the cost of energy during AV’s flight, the excessive waypoints need to be refined. We revise the A-star algorithm by adopting the heading of the AV as the key indices while calculating the cost. Bezier curves are finally proposed to smooth the flight path, making it applicable for real-world flight.
Points-Based Safe Path Planning of Continuum Robots
Directory of Open Access Journals (Sweden)
Khuram Shahzad
2015-07-01
Full Text Available Continuum robots exhibit great potential in a number of challenging applications where traditional rigid link robots pose certain limitations, e.g., working in unstructured environments. In order to enable the usage of continuum robots in safety-critical applications, such as surgery and nuclear decontamination, it is extremely important to ensure a safe path for the robot's movement. Existing algorithms for continuum robot path planning have certain limitations that need to be addressed. These include the fact that none of the algorithms provide safety assurance parameters and control for path planning. They are computationally expensive, applicable to a specific type of continuum robots, and mostly they do not incorporate design and kinematics constraints. In this paper, we propose a points-based path planning (PoPP algorithm for continuum robots that computes the path by imposing safety constraints and improves upon the limitations of existing approaches. In the algorithm, we exploit the constant curvature-bending property of continuum robots in their path planning process. The algorithm is computationally efficient and provides a good tradeoff between accuracy and efficiency that can be implemented to enable the safety-critical application of continuum robots. This algorithm also provides information regarding path volume and flexibility in movement. Simulation results confirm that the algorithm possesses promising potential for all types of continuum robots (following the constant curvature-bending property. We believe that this effectively balances the desired safety and efficiency requirements.
Points-based Safe Path Planning of Continuum Robots
Directory of Open Access Journals (Sweden)
Khuram Shahzad
2015-07-01
Full Text Available Continuum robots exhibit great potential in a number of challenging applications where traditional rigid link robots pose certain limitations, e.g.,working in unstructured environments. In order to enable the usage of continuum robots in safety-critical applications, such as surgery and nuclear decontamination, it is extremely important to ensure a safe path for the robot’s movement. Existing algorithms for continuum robot path planning have certain limitations that need to be addressed. These include the fact that none of the algorithms provide safety assurance parameters and control for path planning. They are computationally expensive, applicable to a specific type of continuum robots, and mostly they do not incorporate design and kinematics constraints. In this paper, we propose a points-based path planning (PoPP algorithm for continuum robots that computes the path by imposing safety constraints and improves upon the limitations of existing approaches. In the algorithm, we exploit the constant curvature-bending property of continuum robots in their path planning process. The algorithm is computationally efficient and provides a good tradeoff between accuracy and efficiency that can be implemented to enable the safety-critical application of continuum robots. This algorithm also provides information regarding path volume and flexibility in movement. Simulation results confirm that the algorithm possesses promising potential for all types of continuum robots (following the constant curvature-bending property. We believe that this effectively balances the desired safety and efficiency requirements.
Global path planning methods of UUV in coastal environment
Institute of Scientific and Technical Information of China (English)
ZHANG Honghan; LIU Xiaofu; YAN Zheping; ZHOU Jiajia
2014-01-01
In coastal environment,the motion of unmanned underwater vehicle (UUV) is influenced signiifcantly by complex current. The operational performance of UUV can be greatly improved when the impact of ocean current is con-sidered. A global path planning method of the static obstacle environmental space is addressed in the paper. Firstly,accord-ing to the typically coastal vortex,a model of ocean current is proposed and the influence to the motion of UUV is analyzed. Secondly,to satisfy the rapid requirement in path planning,a heuristic A*algorithm is used to design global planning path with multiple constraints. Besides,to meet the UUV’s smooth path requirement,Bezier curve theory is applied. Simula-tion experiments are performed to illustrate the feasibility of the algorithm in the steady current and vortex environment.
AUV Local Path Planning Based on Acoustic Image Processing
Institute of Scientific and Technical Information of China (English)
LI Ye; CHANG Wen-tian; JIANG Da-peng; ZHANG Tie-dong; SU Yu-min
2006-01-01
The forward-looking image sonar is a necessary vision device for Autonomous Underwater Vehicles (AUV). Based on the acoustic image received from forward-looking image sonar, AUV local path is planned. When the environment model is made to adapt to local path planning, an iterative algorithm of binary conversion is used for image segmentation. Raw data of the acoustic image, which were received from serial port, are processed. By the use of "Mathematic Morphology" to filter noise, a mathematic model of environment for local path planning is established after coordinate transformation. The optimal path is searched by the distant transmission (Dt) algorithm. Simulation is conducted for the analysis of the algorithm. Experiment on the sea proves it reliable.
SHP: Smooth Hypocycloidal Paths with Collision-Free and Decoupled Multi-Robot Path Planning
Directory of Open Access Journals (Sweden)
Abhijeet Ravankar
2016-06-01
Full Text Available Generating smooth and continuous paths for robots with collision avoidance, which avoid sharp turns, is an important problem in the context of autonomous robot navigation. This paper presents novel smooth hypocycloidal paths (SHP for robot motion. It is integrated with collision-free and decoupled multi-robot path planning. An SHP diffuses (i.e., moves points along segments the points of sharp turns in the global path of the map into nodes, which are used to generate smooth hypocycloidal curves that maintain a safe clearance in relation to the obstacles. These nodes are also used as safe points of retreat to avoid collision with other robots. The novel contributions of this work are as follows: (1 The proposed work is the first use of hypocycloid geometry to produce smooth and continuous paths for robot motion. A mathematical analysis of SHP generation in various scenarios is discussed. (2 The proposed work is also the first to consider the case of smooth and collision-free path generation for a load carrying robot. (3 Traditionally, path smoothing and collision avoidance have been addressed as separate problems. This work proposes integrated and decoupled collision-free multi-robot path planning. ‵Node caching‵ is proposed to improve efficiency. A decoupled approach with local communication enables the paths of robots to be dynamically changed. (4 A novel ‵multi-robot map update‵ in case of dynamic obstacles in the map is proposed, such that robots update other robots about the positions of dynamic obstacles in the map. A timestamp feature ensures that all the robots have the most updated map. Comparison between SHP and other path smoothing techniques and experimental results in real environments confirm that SHP can generate smooth paths for robots and avoid collision with other robots through local communication.
A Global Path Planning Algorithm Based on Bidirectional SVGA
Directory of Open Access Journals (Sweden)
Taizhi Lv
2017-01-01
Full Text Available For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by A⁎. This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning.
ROBIL: Robot Path Planning Based on PBIL Algorithm
Directory of Open Access Journals (Sweden)
Bo-Yeong Kang
2014-09-01
Full Text Available Genetic algorithm (GAs have attracted considerable interest for their usefulness in solving complex robot path planning problems. Specifically, researchers have combined conventional GAs with problem-specific operators and initialization techniques to find the shortest paths in a variety of robotic environments. Unfortunately, these approaches have exhibited inherently unstable performance, and they have tended to make other aspects of the problem-solving process (e.g., adjusting parameter sensitivities and creating high-quality initial populations unmanageable. As an alternative to conventional GAs, we propose a new population-based incremental learning (PBIL algorithm for robot path planning, a probabilistic model of nodes, and an edge bank for generating promising paths. Experimental results demonstrate the computational superiority of the proposed method over conventional GA approaches.
Singularity-free path planning for parallel manipulator
Institute of Scientific and Technical Information of China (English)
陈峰; 赵锡芳; 费燕琼; 殷跃红
2004-01-01
Given a start pose and a goal pose, a large number of singularity-free poses are created randomly in the 6 dimensional task space, a short line segment is used to create a feasible path between two singularity-free poses. A well connected roadmap can be obtained and stored in the 6 dimension task space for a specific 6 DOF parallel manipulator in this way and a singularity-free path is queried to connect the start pose and the goalpose. So the singularity-free path planning between any two given poses for this parallel manipulator can be per-formed very efficiently. This singularity-free path planning method can be used with any type of parallel manipu-lator only if the matrix used can be given to define singularities.
Research on the ant colony algorithm in robot path planning
Wang, Yong; Ma, Jianming; Wang, Ying
2017-05-01
Using the A* algorithm principle proposed adaptive adjustment heuristic function, to reduce the degree of divergence algorithm; The state transition of the next ant improvement strategies, to improve the diversity of path planning solution; Control the change of the pheromone, to avoid algorithm trapped in local optimal solution; The improved ant colony algorithm makes the robot along an optimal or suboptimal path to arrive at the target.
Path planning of the robot assembly based on Voronoi diagram
Institute of Scientific and Technical Information of China (English)
FU Zhuang; ZHAO Yan-zheng
2008-01-01
Based on the concepts of Voronoi diagram that describes geometry information of the robot assembly in C space, the position vector path parameter equation of the assembly movement between the step shaft and two-sided beating bracket was given. And the path planning strategy of the component initiative assembly was put forward as well. Theoretical analysis proves that using the Voronoi diagram to do the geometry reasoning on the assembly space can evaluate the feasibility of the component assembly, and can present the reference posi-tion vector path of the component movement from the initial configuration to the objective configuration, there-fore improves the flexibility of the robot initiative assembly.
Aircraft path planning for optimal imaging using dynamic cost functions
Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin
2015-05-01
Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
Life Extending Minimum-Time Path Planning for Hexapod Robot
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Xin Wu
2011-06-01
Full Text Available This paper presents a minimum‐time path planning scheme for life‐extending operation of legged robots, illustrated with a six‐legged walking robot (hexapod. The focus of this study is on extending the bearing fatigue life for leg joints. As a typical treatment, the minimum‐time path planning is performed through a bisecting‐plane (BP algorithm with the constraints of maximum joint angular velocity and acceleration. Based on bearing fatigue life theory, its fatigue life increases while the dynamic radial force on the bearing decreases. By imposing more rigorous constraint on the dynamic radial force, the minimum‐time path planning algorithm is thus revised by reinforcing the constraint of maximum radial force based on the expectation of life extension. A symmetric hexapod with 18 degree‐of‐freedom (DOF is adopted as the illustrative example for simulation study. The simulation results validate the effectiveness of possible life extending with moderate compromise in transient performance.
Collision-free path planning in multi-dimensional environments
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Edwin Francis Cárdenas
2011-05-01
Full Text Available Reliable path-planning and generation of collision-free trajectories has become an area of active research over the past decade where the field robotics has probably been the most active area. This paper's main objective is to analyse the advantages and disadvantages of two of the most popular techniques used in collision-free trajectory generation in n-dimensional spaces. The importance of analysing such techniques within a generalised framework is evident as path-planning is used in a variety of fields such as designing medical drugs, computer animation and artificial intelligence and, of course, robotics. The review provided in this paper starts by drawing a historical map of path-planning and the techniques used in its early stages. The main concepts involved in artificial potential fields and probabilistic roadmaps will be addressed as these are the most influential methods and have been widely used in specialised literature.
Survey of Robot 3D Path Planning Algorithms
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Liang Yang
2016-01-01
Full Text Available Robot 3D (three-dimension path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints. The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path planning algorithms which have been developed in recent years and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots, and underwater robots. This paper classifies all the methods into five categories based on their exploring mechanisms and proposes a category, called multifusion based algorithms. For all these algorithms, they are analyzed from a time efficiency and implementable area perspective. Furthermore a comprehensive applicable analysis for each kind of method is presented after considering their merits and weaknesses.
A Bat Algorithm with Mutation for UCAV Path Planning
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Gaige Wang
2012-01-01
Full Text Available Path planning for uninhabited combat air vehicle (UCAV is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.
Hierarchical planning for a surface mounting machine placement
Institute of Scientific and Technical Information of China (English)
曾又姣; 马登哲; 金烨; 严隽琪
2004-01-01
For a surface mounting machine (SMM) in printed circuit board (PCB) assembly line, there are four problems, e.g. CAD data conversion, nozzle selection, feeder assignment and placement sequence determination. A hierarchical planning for them to maximize the throughput rate of an SMM is presented here. To minimize set-up time, a CAD data conversion system was first applied that could automatically generate the data for machine placement from CAD design data files. Then an effective nozzle selection approach was implemented to minimize the time of nozzle changing. And then, to minimize picking time, an algorithm for feeder assignment was used to make picking multiple components simultaneously as much as possible. Finally, in order to shorten pick-and-place time, a heuristic algorithm was used to determine optimal component placement sequence according to the decided feeder positions. Experiments were conducted on a four head SMM. The experimental results were used to analyse the assembly line performance.
Hierarchical resource analysis for land use planning through remote sensing
Byrnes, B. H.; Frazee, C. J.; Cox, T. L.
1976-01-01
A hierarchical resource analysis was applied to remote sensing data to provide maps at Planning Levels I and III (Anderson et al., U.S. Geological Survey Circular 671) for Meade County, S. Dak. Level I land use and general soil maps were prepared by visual interpretation of imagery from a false color composite of Landsat MSS bands 4, 5, and 7 and single bands (5 and 7). A modified Level III land use map was prepared for the Black Hills area from RB-57 photography enlarged to a scale of 1:24,000. Level III land use data were used together with computer-generated interpretive soil maps to analyze relationships between developed and developing areas and soil criteria.
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J
2010-12-01
Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies
Access Path Planning of Mobile Agent in Wireless Sensor Networks
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Chaoyu Yang
2014-02-01
Full Text Available Adopting the two-stage optimization model and hybrid optimized algorithm based on evolutionary computation, a new two-stage optimization model that more conforms to the actual demand is proposed on the basis of formal description of Mobile Agent access path planning. This new model divides the access path planning problem into two sub problems of integer linear programming --data integration sub paths and return sub paths, which can reduce search space and improve the efficiency of algorithm. Then a hybrid optimized method named GAPSO, combined with GA (Genetic Algorithm and PSO (Particle Swarm Optimization, is advanced to solve this model, which integrates discrete PSO into the interlace operation of GA to avoid infeasible solution and improve search quality. Meanwhile convergence can be accelerated by optimizing the GA population with PSO in search of return sub paths. By means of virtual connected topology graph, the high-quality to-be-accessed candidate node set is acquired, the number of to-be-selected nodes is reduced，and the complexity of solution space is decreased, making planning algorithm performance not rely on network scale directly any more. Simulation results show that the advantages of the optimization model is obvious as the node number increases, and GASPO has a better performance than GA and BPSO in the same model
Mobile Robot Path Planning by RRT* in Dynamic Environments
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Roudabe Seif
2015-05-01
Full Text Available Robot navigation is challenging for mobile robots technology in environments with maps. Since finding an optimal path for the agent is complicated and time consuming, path planning in robot navigation is an axial issue. The objective of this paper is to find a reasonable relation between parameters used in the path planning algorithm in a platform which a robot will be able to move from the start point in a dynamic environment with map and plan an optimal path to specified goal without any collision with moving and static obstacles. For this purpose, an asymptotically optimal version of Rapidly-exploring Random Tree RRT algorithm, named RRT* is used. The algorithm is based on an incremental sampling which covers the whole space and acts fast. Moreover this algorithm is computationally efficient, therefore it can be used in multidimensional environments. The obtained results indicate that a feasible path for mobile holomonic robot may be found in a short time by using this algorithm. Also different standard distances measurements like (Chebyshev, Euclidean, and City Block are examined, and coordinated with sampling node number in order to reach the suitable result based on environment circumstances.
Safe Maritime Autonomous Path Planning in a High Sea State
Ono, Masahiro; Quadrelli, Marco; Huntsberger, Terrance L.
2014-01-01
This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.
Mobile Robot Path Planning with Randomly Moving Obstacles and Goal
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Vanitha Aenugu
2012-03-01
Full Text Available This article presents the dynamic path planning for a mobile robot to track a randomly moving goal with avoidance of multiple randomly moving obstacles. The main feature of the developed scheme is its capability of dealing with the situation that the paths of both the goal and the obstacles are unknown a priori to the mobile robot. A new mathematical approach that is based on the concepts of 3-D geometry is proposed to generate the path of the mobile robot. The mobile robot decides its path in real time to avoid the randomly moving obstacles and to track the randomly moving goal. The developed scheme results in faster decision-making for successful goal tracking. 3-D simulations using MATLAB validate the developed scheme.
Obstacle avoidance and path planning for carrier aircraft launching
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Wu Yu
2015-06-01
Full Text Available Launching safety and efficiency are important indexes to measure the fighting capacity of carrier. The study on path planning for taxi of carrier aircraft launching under actual deck environment is of great significance. In actual deck scheduling, manual command is applied to taxi of carrier aircraft, which has negative effects on the safety of staff and carrier aircraft launching. In consideration of both the safety and efficiency of carrier aircraft launching, the key elements of the problem are abstracted based on the analysis of deck environment, carrier aircraft maneuver performance and task requirements. According to the problem description, the mathematical model is established including various constraints. The carrier aircraft and the obstacles are reasonably simplified as circle and polygons respectively. What’s more, the proposed collision detection model reduces the calculations. Aimed at the features of model, the theory of model predictive control (MPC is applied to the path search. Then a dynamic weight heuristic function is designed and a dynamic multistep optimization algorithm is proposed. Taking the Nimitz-class aircraft carrier as an example, the paths from parking place to catapult are planned, which indicate the rationality of the model and the effectiveness of the algorithm by comparing the planning results under different simulation environments. The main contribution of research is the establishment of obstacle avoidance and path planning model. In addition, it provides the solution of model and technological foundations for comprehensive command and real-time decision-making of the carrier aircraft.
Realistic Crowd Simulation with Density-Based Path Planning
van Toll, W.G.; Cook IV, A.F.; Geraerts, R.J.
2012-01-01
Virtual characters in games and simulations often need to plan visually convincing paths through a crowded environment. This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid
Path planning for steerable needles using duty-cycled spinning
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Borges G.A.
2011-12-01
Full Text Available This paper presents an adaptive approach for 2D path planning of steerable needles. It combines dutycycled rotation of the needle with the classic RapidlyExploring Random Tree (RRT algorithm and it is used intraoperatively to compensate for system uncertainties and perturbations. Simulation results demonstrate the performance of the proposed motion planner on a workspace based in ultrasound images.
Realistic Crowd Simulation with Density-Based Path Planning
van Toll, W.G.; Cook IV, A.F.; Geraerts, R.J.
2012-01-01
Virtual characters in games and simulations often need to plan visually convincing paths through a crowded environment. This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid
Aircraft path planning with the use of smooth trajectories
Belokon', S. A.; Zolotukhin, Yu. N.; Nesterov, A. A.
2017-01-01
A simplified method of plane trajectory calculation is proposed for solving the problem of planning a path defined by a sequence of waypoints. The trajectory consists of oriented segments of straight lines joined by clothoids (Cornu spirals). The efficiency of the method is validated by means of numerical simulations in the MATLAB/Simulink environment.
Robust Path Planning and Feedback Design Under Stochastic Uncertainty
Blackmore, Lars
2008-01-01
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
Study of Multi-objective Fuzzy Optimization for Path Planning
Institute of Scientific and Technical Information of China (English)
WANG Yanyang; WEI Tietao; QU Xiangju
2012-01-01
During path planning,it is necessary to satisfy the requirements of multiple objectives.Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker.The decision-maker,however,has illegibility for understanding the requirements of multiple objectives and the subjectivity inclination.It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning.Based on Voronoi diagram method for the path planning,this paper studies the synthesis method of the multi-objective cost performance index.According to the application of the cost performance index to the path planning based on Voronoi diagram method,this paper analyzes the cost performance index which has been referred to at present.The analysis shows the insufficiency of the cost performance index at present,i.e.,it is difficult to synthesize sub-objective functions because of the great disparity of the sub-objective functions.Thus,a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy,and an improved performance index is established,which could coordinate the weight conflict of the sub-objective functions.Finally,the experimental result shows the effectiveness of the proposed approach.
Robust Path Planning and Feedback Design Under Stochastic Uncertainty
Blackmore, Lars
2008-01-01
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
MRPPSim: A Multi-Robot Path Planning Simulation
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Ebtehal Turki Saho Alotaibi
2016-08-01
Full Text Available Multi-robot path planning problem is an interesting problem of research having great potential for several optimization problems in the world. In multi-robot path planning problem domain (MRPP, robots must move from their start locations to their goal locations avoiding collisions with each other. MRPP is a relevant problem in several domains, including; automatic packages inside a warehouse, automated guided vehicles, planetary exploration, robotics mining, and video games. This work introduces MRPPSim; a new modeling, evaluation and simulation tool for multi-robot path planning algorithms and its applications. In doing so, it handles all the aspects related to the multi-robot path planning algorithms. Through its working, MRPPSim unifies the representation for the input. This algorithm provides researchers with a set of evaluation models with each of them serving a set of objectives. It provides a comprehensive method to evaluate and compare the algorithm’s performance to the ones that solve public benchmark problems inas shown in literature. The work presented in this paper also provides a complete tool to reformat and control user input, critical small benchmark, biconnected, random and grid problems. Once all of this is performed, it calculates the common performance measurements of multi-robot path planning algorithms in a unified way. The work presented in this paper animates the results so the researchers can follow their algorithms’ executions. In addition, MRPPSim is designed as set of models, each is dedicated to a specific function, this allows new algorithm, evaluation model, or performance measurements to be easily plugged into the simulator.
Mobile transporter path planning using a genetic algorithm approach
Baffes, Paul; Wang, Lui
1988-01-01
The use of an optimization technique known as a genetic algorithm for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the Space Station which must be able to reach any point of the structure autonomously. Specific elements of the genetic algorithm are explored in both a theoretical and experimental sense. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research. However, trajectory planning problems are common in space systems and the genetic algorithm provides an attractive alternative to the classical techniques used to solve these problems.
Optimal Path Planning for Minimizing Base Disturbance of Space Robot
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Xiao-Peng Wei
2016-03-01
Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.
An optimal antenna motion generation using shortest path planning
Jeon, Moon-Jin; Kwon, Dong-Soo
2017-03-01
This paper considers an angular velocity minimization method for a satellite antenna. For high speed transmission of science data, a directional antenna with a two-axis gimbal is generally used. When a satellite passes over a ground station while pointing directly at it, the angular velocity of the satellite antenna can increase rapidly due to the gimbal kinematics. The high angular velocity could exceed the dynamic constraint of the antenna. Furthermore, micro vibration induced by high speed antenna rotation during an imaging operation might cause jitter, which can degrade the satellite image quality. To solve this problem, a minimum-velocity antenna motion generation method is proposed. Boundaries of the azimuth and elevation angles of the antenna within an effective beam width are derived using antenna geometry. A minimum-velocity azimuth profile and elevation profile within the boundaries are generated sequentially using a shortest path planning method. For fast and correct generation of the shortest path, a new algorithm called a string nailing algorithm is proposed. A numerical simulation shows that the antenna profile generated by the shortest path planning has a much lower angular velocity than the profiles generated by previous methods. The proposed string nailing algorithm also spends much less computation time than a search-based shortest path planning algorithm to generate almost the same antenna profiles.
Optimal Path Planning for Minimizing Base Disturbance of Space Robot
Directory of Open Access Journals (Sweden)
Xiao-Peng Wei
2016-03-01
Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.
Path planning for complex terrain navigation via dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Kwok, K.S.; Driessen, B.J.
1998-12-31
This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains.
Robot collision-free path planning utilizing gauge function
Institute of Scientific and Technical Information of China (English)
朱向阳; 朱利民; 钟秉林
1997-01-01
Based on the generalized gauge function, a numerical criterion which specifies the topological rela-tionship between convex polyhedra is presented. It can be applied to detecting the overlap, just contact or separation between two sets of convex polyhedra. As the solution of a linear programming problem, the value of this criterion can be calculated easily. The presented criterion is available to provide heuristic information for generating intermediate configuration point as well as checking the hypothesized path for admissibility in flexible-trajectory path planning ap-proach.
Ronay, R.D.; Greenaway, K; Anicich, E.M; Galinsky, A.D.
2012-01-01
Two experiments examined the psychological and biological antecedents of hierarchical differentiation and the resulting consequences for productivity and conflict within small groups. In Experiment 1, which used a priming manipulation, hierarchically differentiated groups (i.e., groups comprising 1
Ronay, R.D.; Greenaway, K; Anicich, E.M; Galinsky, A.D.
2012-01-01
Two experiments examined the psychological and biological antecedents of hierarchical differentiation and the resulting consequences for productivity and conflict within small groups. In Experiment 1, which used a priming manipulation, hierarchically differentiated groups (i.e., groups comprising 1
BIM-BASED INDOOR PATH PLANNING CONSIDERING OBSTACLES
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M. Xu
2017-09-01
Full Text Available At present, 87 % of people’s activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people’s daily life are more and more complex, many obstacles influence humans’ moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.
Path Planning Algorithms for the Adaptive Sensor Fleet
Stoneking, Eric; Hosler, Jeff
2005-01-01
The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.
Hierarchical planning for a surface mounting machine placement
Institute of Scientific and Technical Information of China (English)
曾又姣; 马登哲; 金烨; 严隽琪
2004-01-01
For a surface mounting machine(SMM)in printed circuit board(PCB)assembly line,there are four problems,e.g. CAD data conversion,nozzle selection,feeder assignment and placement sequence determination. A hierarchical planning for them to maximize the throughput rate of an SMM is presented here. To minimize set-up time,a CAD data conversion system was first applied that could automatically generate the data for machine placement from CAD design data files. Then an effective nozzle selection approach was implemented to minimize the time of nozzle changing. And then,to minimize picking time,an algorithm for feeder assignment was used to make picking multiple components simultaneously as much as possible. Finally,in order to shorten pick-and-place time,a heuristic algorithm was used to determine optimal component placement sequence according to the decided feeder positions. Experiments were conducted on a four head SMM.The experimental results were used to analyse the assembly line performance.
Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization
Directory of Open Access Journals (Sweden)
Lianbo Ma
2014-01-01
Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.
TOOL PATH PLANNING USING VORONOI DIAGRAM AND THREE STACKS
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Based on the object-oriented data structure of Vor onoi diagram, the algorithm of the trimmed offset generating and the optimal too l path planning of the pocket machining for multiply connected polygonal domains are studied. The intersection state transition rule is improved in this algorit hm. The intersection is between the trimmed offsets and Voronoi polygon. On this basis, the trimmed offset generating and the optimal tool path planning are mad e with three stacks(I-stack, C-stack and P-stack)in different monotonous pouc hes of Voronoi diagram. At the same time, a merging method of Voronoi diagram an d offsets generating for multiply connected polygonal domains is also presented. The above algorithms have been implemented in NC machining successfully, and th e efficiency is fully verified.
Path Planning for Search and Rescue Mission using Multicopters
Andersen, Håvard Lægreid
2014-01-01
This thesis considers path planning for a low-cost multicopter used in the searchpart of a search and rescue mission. Search patterns or trajectories are consideredand evaluated through simulations in MATLAB. How to place the onboard camerain order to cover as much area as possible and which altitude that gives the mostarea coverage without making the subjects too small to detect is discussed.The proposed search patterns are implemented in the existing software structureused in this project. ...
Chattopadhyay, Ishanu; Ray, Asok
2010-01-01
We report a globally-optimal approach to robotic path planning under uncertainty, based on the theory of quantitative measures of formal languages. A significant generalization to the language-measure-theoretic path planning algorithm $\
A Path Planning Method for Robotic Belt Surface Grinding
Institute of Scientific and Technical Information of China (English)
WANG Wei; YUN Chao
2011-01-01
The flexible contact and machining with wide strip are two prominent advantages for the robotic belt grinding system,which can be widely used to improve the surface quality and machining efficiency while finishing the workpieces with sculptured surfaces.There lacks research on grinding path planning with the constraint of curvature.With complicated contact between the contact wheel and the workpiece,the grinding paths for robot can be obtained by the theory of contact kinematics.The grinding process must satisfy the universal demands of the belt grinding technologies,and the most important thing is to make the contact wheel conform to the local geometrical features on the contact area.For the local surfaces with small curvature,the curve length between the neighboring cutting locations becomes longer to ensure processing efficiency.Otherwise,for the local areas with large curvature,the curve length becomes shorter to ensure machining accuracy.A series of planes are created to intersect with the target surface to be ground,and the corresponding sectional profile curves are obtained.For each curve,the curve length between the neighboring cutting points is optimized by inserting a cutter location at the local area with large curvatures.A method of generating the grinding paths including curve length spacing optimization is set up.The validity is completely approved by the off-line simulation,and during the grinding experiments with the method,the quality of surface is improved.The path planning method provides a theoretical support for the smooth and accuracy path of robotic surface grinding.
Cooperative Path-Planning for Multi-Vehicle Systems
Directory of Open Access Journals (Sweden)
Qichen Wang
2014-11-01
Full Text Available In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently.
Path planning in uncertain flow fields using ensemble method
Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.
2016-10-01
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-08-20
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Path planning in uncertain flow fields using ensemble method
Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.
2016-08-01
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Human-machine teaming for effective estimation and path planning
McCourt, Michael J.; Mehta, Siddhartha S.; Doucette, Emily A.; Curtis, J. Willard
2016-05-01
While traditional sensors provide accurate measurements of quantifiable information, humans provide better qualitative information and holistic assessments. Sensor fusion approaches that team humans and machines can take advantage of the benefits provided by each while mitigating the shortcomings. These two sensor sources can be fused together using Bayesian fusion, which assumes that there is a method of generating a probabilistic representation of the sensor measurement. This general framework of fusing estimates can also be applied to joint human-machine decision making. In the simple case, binary decisions can be fused by using a probability of taking an action versus inaction from each decision-making source. These are fused together to arrive at a final probability of taking an action, which would be taken if above a specified threshold. In the case of path planning, rather than binary decisions being fused, complex decisions can be fused by allowing the human and machine to interact with each other. For example, the human can draw a suggested path while the machine planning algorithm can refine it to avoid obstacles and remain dynamically feasible. Similarly, the human can revise a suggested path to achieve secondary goals not encoded in the algorithm such as avoiding dangerous areas in the environment.
Ant Colony Based Path Planning Algorithm for Autonomous Robotic Vehicles
Directory of Open Access Journals (Sweden)
Yogita Gigras
2012-11-01
Full Text Available The requirement of an autonomous robotic vehicles demand highly efficient algorithm as well as software. Today’s advanced computer hardware technology does not provide these types of extensive processing capabilities, so there is still a major space and time limitation for the technologies that are available for autonomous robotic applications. Now days, small to miniature mobile robots are required for investigation, surveillance and hazardous material detection for military and industrial applications. But these small sized robots have limited power capacity as well as memory and processing resources. A number of algorithms exist for producing optimal path for dynamically cost. This paper presents a new ant colony based approach which is helpful in solving path planning problem for autonomous robotic application. The experiment of simulation verified its validity of algorithm in terms of time.
A Rough Set GA-based Hybrid Method for Robot Path Planning
Institute of Scientific and Technical Information of China (English)
Cheng-Dong Wu; Ying Zhang; Meng-Xin Li; Yong Yue
2006-01-01
In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations are optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed.
A feature information based VPH for local path planning with obstacle avoidance of the mobile robot
Oh, Tae-Seok; Shin, Yun-Su; Yun, Sung-Yong; Lee, Wang-Heon; Kim, Il-Hwan
2007-12-01
This study shows how a mobile service robot can avoid obstacles, and presents a VPH method using feature information for Local Path Planning. It is not easy to make a mobile service robot automatically move towards the goal. Path Planning lays out the path through which a robot follows to reach the goal. It can be divided into two folds: Global Path Planning (GPP) and Local Path Planning (LPP). Local path planning sets a path in a changing environment with moving obstacles such as in a museum and exhibition hall so that the robot reaches the goal without any collision. This study evaluates the Fusion Map-VPH (FM-VPH) Local path planning method with improved VPH by making use of the combined data drawn up through the ultrasonic sensor and laser sensor and by means of feature information. The results of the simulations and experiments have verified the validity of the methods described.
Path Planning Optimization for Teaching and Playback Welding Robot
Directory of Open Access Journals (Sweden)
Yuehai Wang
2013-02-01
Full Text Available Path planning for the industrial robot plays an important role in the intelligent control of robot. Tradition strategies, including model-based methods and human taught based methods, find it is difficult to control manipulator intelligently and optically. Thus, it is hard to ensure the better performance and lower energy consumption even if the same welding task was executed repeatedly. A path planning optimization method was proposed to add learning ability to teaching and playback welding robot. The optimization was divided into the welding points sequence improvement and trajectory improvement, which was done both on-line and off-line. Points sequence optimization was modeled as TSP and was continuously improved by genetic algorithm based strategy, while the trajectory between two welding points was on-line improved by an try-and-error strategy where the robot try different trajectory from time to time so as to search a better plan. Simulation results verified that this control strategy reduced the time and energy cost as compared with the man-made fix-order sequence. Our method prevents the robot from the computation-intensive model-based control, and offers a convenient way for self-improvement on the basis of human teaching.
Multilevel hierarchical production planning architecture for engineer-to-order enterprises
Institute of Scientific and Technical Information of China (English)
李小平; 徐晓飞; 战德臣
2002-01-01
The critical materials and critical parts are keys to the production at Engineer-to-Order (ETO) enter-prises implies that the control of plans for critical materials and critical parts is essential to the control of allplans at ETO enterprises. A mixed mode of hierarchical network planning/MRP (NP/MRP) is proposed to gen-erate network plans for critical materials or critical parts from project networks and the plans for non-criticalparts produced by MRP are constrained by the related project networks. The multilevel hierarchical networkplanning/MRP mixed planning (MHNM) architecture proposed is the extension of the hierarchical NP/MRP tothe supply chain based on the temporal constraints of multilevel project networks for critical materials or criticalparts. A general model is formulated for scheduling tasks on machines at work centers as well.
General Path Planning Methodology for Leader-Follower Robot Formations
Directory of Open Access Journals (Sweden)
Santiago Garrido
2013-01-01
Full Text Available This paper describes a robust algorithm for mobile robot formations based on the Voronoi Fast Marching path planning method. This is based on the propagation of a wave throughout the model of the environment, the wave expanding faster as the wave's distance from obstacles increases. This method provides smooth and safe trajectories and its computational efficiency allows us to maintain a good response time. The proposed method is based on a local-minima-free planner; it is complete and has an O(n complexity order where n is the number of cells of the map. Simulation results show that the proposed algorithm generates good trajectories.
Intelligent Online Path Planning for UAVs in Adversarial Environments
Directory of Open Access Journals (Sweden)
Xingguang Peng
2012-03-01
Full Text Available Online path planning (OPP for unmanned aerial vehicles (UAVs is a basic issue of intelligent flight and is indeed a dynamic multi‐objective optimization problem (DMOP. In this paper, an OPP framework is proposed in the sense of model predictive control (MPC to continuously update the environmental information for the planner. For solving the DMOP involved in the MPC we propose a dynamic multi‐objective evolutionary algorithm based on linkage and prediction (LP‐DMOEA. Within this algorithm, the historical Pareto sets are collected and analysed to enhance the performance. For intelligently selecting the best path from the output of the OPP, the Bayesian network and fuzzy logic are used to quantify the bias to each optimization objective. The DMOEA is validated on three benchmark problems characterized by different changing types in decision and objective spaces. Moreover, the simulation results show that the LP‐DMOEA overcomes the restart method for OPP. The decision‐making method for solution selection can assess the situation in an adversarial environment and accordingly adapt the path planner.
Multi-path planning algorithm based on fitness sharing and species evolution
Institute of Scientific and Technical Information of China (English)
ZHANG Jing-juan; LI Xue-lian; HAO Yan-ling
2003-01-01
A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.
Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng
2016-02-01
Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.
Making planned paths look more human-like in humanoid robot manipulation planning
DEFF Research Database (Denmark)
Zacharias, F.; Schlette, C.; Schmidt, F.
2011-01-01
It contradicts the human's expectations when humanoid robots move awkwardly during manipulation tasks. The unnatural motion may be caused by awkward start or goal configurations or by probabilistic path planning processes that are often used. This paper shows that the choice of an arm's target...... for the robot arm....
Directory of Open Access Journals (Sweden)
Srinivas Bulusu
2016-06-01
Full Text Available An operational consistency model for real-time dynamic traffic assignment (DTA applications seeks to correct the time-dependent path assignment within a rolling horizon scheme. This study extends an existing consistency framework to develop a hierarchy for the time-dependent path set based upon their relative importance to ensuring consistency. Using the analytic hierarchy process, the eigenvalue associated with a path is identified as the parameter which enables the rank ordering of paths. The ability to identify a subset of dominant paths relative to enhancing consistency enhances the computational viability of the consistency framework for real-time implementation and has significant practical implications. Additionally, it provides insights on the complex dynamics that are inherent to the operational consistency problem.
The path planning of UAV based on orthogonal particle swarm optimization
Liu, Xin; Wei, Haiguang; Zhou, Chengping; Li, Shujing
2013-10-01
To ensure the attack mission success rate, a trajectory with high survivability and accepted path length and multiple paths with different attack angles must be planned. This paper proposes a novel path planning algorithm based on orthogonal particle swarm optimization, which divides population individual and speed vector into independent orthogonal parts, velocity and individual part update independently, this improvement advances optimization effect of traditional particle swarm optimization in the field of path planning, multiple paths are produced by setting different attacking angles, this method is simulated on electronic chart, the simulation result shows the effect of this method.
Autonomous guided vehicles methods and models for optimal path planning
Fazlollahtabar, Hamed
2015-01-01
This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...
Singularities of robot mechanisms numerical computation and avoidance path planning
Bohigas, Oriol; Ros, Lluís
2017-01-01
This book presents the singular configurations associated with a robot mechanism, together with robust methods for their computation, interpretation, and avoidance path planning. Having such methods is essential as singularities generally pose problems to the normal operation of a robot, but also determine the workspaces and motion impediments of its underlying mechanical structure. A distinctive feature of this volume is that the methods are applicable to nonredundant mechanisms of general architecture, defined by planar or spatial kinematic chains interconnected in an arbitrary way. Moreover, singularities are interpreted as silhouettes of the configuration space when seen from the input or output spaces. This leads to a powerful image that explains the consequences of traversing singular configurations, and all the rich information that can be extracted from them. The problems are solved by means of effective branch-and-prune and numerical continuation methods that are of independent interest in themselves...
Visibility-based optimal path and motion planning
Wang, Paul Keng-Chieh
2015-01-01
This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...
Algorithm Plans Collision-Free Path for Robotic Manipulator
Backes, Paul; Diaz-Calderon, Antonio
2007-01-01
An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps
Directory of Open Access Journals (Sweden)
Harri Antikainen
2013-10-01
Full Text Available A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS, the latter is usually associated with the cost surface method, which allows optimum paths to be calculated through rasters in which the value of each cell depicts the cost of traversal through that cell. One of the problems with this method is computational expense, which may be very high with large rasters. In this study, a pathfinding method called Hierarchical Pathfinding A* (HPA*, based on an abstraction strategy, is investigated as an alternative to the traditional approach. The aim of this study is to enhance the method to make it more suitable for calculating paths over cost rasters with nonuniform traversal cost. The method is implemented in GIS and tested with actual data. The results indicate that by taking into account the information embedded in the cost raster, paths of relatively good quality can be calculated while effecting significant savings in computational effort compared to the traditional, nonhierarchical approach.
Global path planning approach based on ant colony optimization algorithm
Institute of Scientific and Technical Information of China (English)
WEN Zhi-qiang; CAI Zi-xing
2006-01-01
Ant colony optimization (ACO) algorithm was modified to optimize the global path. In order to simulate the real ant colonies, according to the foraging behavior of ant colonies and the characteristic of food, conceptions of neighboring area and smell area were presented. The former can ensure the diversity of paths and the latter ensures that each ant can reach the goal. Then the whole path was divided into three parts and ACO was used to search the second part path. When the three parts pathes were adjusted,the final path was found. The valid path and invalid path were defined to ensure the path valid. Finally, the strategies of the pheromone search were applied to search the optimum path. However, when only the pheromone was used to search the optimum path, ACO converges easily. In order to avoid this premature convergence, combining pheromone search and random search, a hybrid ant colony algorithm(HACO) was used to find the optimum path. The comparison between ACO and HACO shows that HACO can be used to find the shortest path.
A morphological adaptation approach to path planning inspired by slime mould
Jones, Jeff
2015-04-01
Path planning is a classic problem in computer science and robotics which has recently been implemented in unconventional computing substrates such as chemical reaction-diffusion computers. These novel computing schemes utilise the parallel spatial propagation of information and often use a two-stage method involving diffusive propagation to discover all paths and a second stage to highlight or visualise the path between two particular points in the arena. The true slime mould Physarum polycephalum is known to construct efficient transport networks between nutrients in its environment. These networks are continuously remodelled as the organism adapts its body plan to changing spatial stimuli. It can be guided towards attractant stimuli (nutrients, warm regions) and it avoids locations containing hazardous stimuli (light irradiation, repellents, or regions occupied by predatory threats). Using a particle model of slime mould we demonstrate scoping experiments which explore how path planning may be performed by morphological adaptation. We initially demonstrate simple path planning by a shrinking blob of virtual plasmodium between two attractant sources within a polygonal arena. We examine the case where multiple paths are required and the subsequent selection of a single path from multiple options. Collision-free paths are implemented via repulsion from the borders of the arena. Finally, obstacle avoidance is implemented by repulsion from obstacles as they are uncovered by the shrinking blob. These examples show proof-of-concept results of path planning by morphological adaptation which complement existing research on path planning in novel computing substrates.
Neural network and genetic algorithm based global path planning in a static environment
Institute of Scientific and Technical Information of China (English)
DU Xin; CHEN Hua-hua; GU Wei-kang
2005-01-01
Mobile robot global path planning in a static environment is an important problem. The paper proposes a method of global path planning based on neural network and genetic algorithm. We constructed the neural network model of environmental information in the workspace for a robot and used this model to establish the relationship between a collision avoidance path and the output of the model. Then the two-dimensional coding for the path via-points was converted to one-dimensional one and the fitness of both the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results showed that the proposed method is correct and effective.
Improved Path Planning Onboard the Mars Exploration Rovers
Stentz, Anthony; Ferguson, David; Carsten, Joseph; Rankin, Arturo
2007-01-01
A revised version of the AutoNav (autonomous navigation with hazard avoidance) software running onboard each Mars Exploration Rover (MER) affords better obstacle avoidance than does the previous version. Both versions include GESTALT (Grid-based Estimation of Surface Traversability Applied to Local Terrain), a navigation program that generates local-terrain models from stereoscopic image pairs captured by onboard rover cameras; uses this information to evaluate candidate arcs that extend across the terrain from the current rover location; ranks the arcs with respect to hazard avoidance, minimization of steering time, and the direction towards the goal; and combines the rankings in a weighted vote to select an arc, along which the rover is then driven. GESTALT works well in navigating around small isolated obstacles, but tends to fail when the goal is on the other side of a large obstacle or multiple closely spaced small obstacles. When that occurs, the goal seeking votes and hazard avoidance votes conflict severely. The hazard avoidance votes will not allow the rover to drive through the unsafe area, and the waypoint votes will not allow enough deviation from the straight-line path for the rover to get around the hazard. The rover becomes stuck and is unable to reach the goal. The revised version of AutoNav utilizes a global path-planning program, Field D*, to evaluate the cost of traveling from the end of each GESTALT arc to the goal. In the voting process, Field D* arc votes supplant GESTALT goal-seeking arc votes. Hazard avoidance, steering bias, and Field D* votes are merged and the rover is driven a preset distance along the arc with the highest vote. Then new images are acquired and the process as described is repeated until the goal is reached. This new technology allows the rovers to autonomously navigate around much more complex obstacle arrangements than was previously possible. In addition, this improved autonomy enables longer traverses per Sol (a day
Directory of Open Access Journals (Sweden)
Kaijun Zhou
2017-09-01
Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.
A path planning algorithm based on Bezier curves for underwater vehicles
Institute of Scientific and Technical Information of China (English)
Shang Liuji; Wang Shuo
2010-01-01
An on-line path planning algorithm based on Bezier curves is presented for underwater vehicles.Aiming at the special requirements of underwater vehicles and 3D environment,the algorithm consists of two steps: the generation of spatial path and the processing of some constraints.A path for underwater vehicles is planned,which satisfies the velocity constraint and the centripetal acceleration constraint of underwater vehicles.The proposed path planning method can be used for the vehicle's locomotion and navigation control.
Research on stereo vision path-planning algorithms for mobile robots autonomous navigation
Institute of Scientific and Technical Information of China (English)
ZHANG Guo-wei; LU Qiu-hong
2009-01-01
Using stereo vision for autonomous mobile robot path-planning is a hot technology. The environment mapping and path-planning algorithms were introduced, and they were applied in the autonomous mobile robot experiment platform. Through experiments in the robot platform, the effectiveness of these algorithms was verified.
Maslow and Motherboards: Taking a Hierarchical View of Technology Planning.
Johnson, Doug
2003-01-01
Presents a planning model for educational uses of technology that is based on Maslow's hierarchy of needs. Topics include established infrastructure; effective administration; extensive resources; enhanced teaching, including creating distance learning opportunities; empowered students, including evaluation methods and information literacy skills;…
Maslow and Motherboards: Taking a Hierarchical View of Technology Planning.
Johnson, Doug
2003-01-01
Presents a planning model for educational uses of technology that is based on Maslow's hierarchy of needs. Topics include established infrastructure; effective administration; extensive resources; enhanced teaching, including creating distance learning opportunities; empowered students, including evaluation methods and information literacy skills;…
A hierarchical approach to multi-project planning under uncertainty
Hans, Elias W.; Herroelen, W.; Wullink, Gerhard; Leus, R.
2007-01-01
We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. Based on these viewpoints we propose a positioning framework to distinguish between different types of project-driven organisations. This framework is meant to aid project
Hierarchical Production Planning and multi-echelon inventory management
Zijm, Willem H.M.
1992-01-01
In this paper we present a framework for the planning and control of the materials flow in a multi-item production system. Our prime objective is to meet a prespecified customer service level at minimum overall costs. In order to motivate our study we first outline the basic architecture of a
Improved ant colony algorithm for global path planning
Li, Pengfei; Wang, Hongbo; Li, Xiaogang
2017-03-01
The ant colony algorithm has many advantages compared with other algorithms in path planning, but its shortcomings still cannot be ignored. For example, the convergence speed is very low at initial stage, it is easy to fall into the local optimal solution, and the solution speed is slow and so on. In order to solve these problems and reduce the search time, this paper firstly makes the assignment of the main parameters of α, β, M and ρ in the ant colony algorithm through a large number of experimental data analysis. Then an improved ant colony algorithm based on dynamic parameters and new pheromone updating mechanism is proposed in this paper. Simulation results show that the improved ant colony algorithm can not only greatly shorten the algorithm running time, but also has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm. It is very advantageous for solving large-scale optimization problems.
Robot path planning in globally unknown environments based on rolling windows
Institute of Scientific and Technical Information of China (English)
张纯刚; 席裕庚
2001-01-01
In this paper, robot path planning in globally unknown environments is studied. Using the rolling optimization concept in predictive control for reference, a new strategy of path planning for a mobile robot, based on rolling windows, is proposed. The method makes full use of the real-time local environmental information detected by the robot and the on-line path planning is carried on in a rolling style. Optimization and feedback are combined in a reasonable way. The convergence of the planning algorithm is also discussed.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Directory of Open Access Journals (Sweden)
Kai Yit Kok
Full Text Available The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
Institute of Scientific and Technical Information of China (English)
Liu Wei; Zheng Zheng; Cai Kaiyuan
2013-01-01
This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs' relevant performances,with respect to sensory capability,maneuverability,and flight velocity limit.On the basis of a novel adaptability-involved problem statement,bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization.Additionally,both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability.A discrete-search-based path planning solution,embedded with four optimization strategies,is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces,within which different surface-to-air missiles (SAMs) are deployed.Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner,and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.
Research and application of genetic algorithm in path planning of logistics distribution vehicle
Wang, Yong; Zhou, Heng; Wang, Ying
2017-08-01
The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.
A Multi-pipe Path Planning by Modified Ant Colony Optimization
Institute of Scientific and Technical Information of China (English)
QU Yan-feng; JIANG Dan; LIU Bin
2011-01-01
Path planning in 3D geometry space is used to find an optimal path in the restricted environment, according to a certain evaluation criteria. To solve the problem of long searching time and slow solving speed in 3D path planning, a modified ant colony optimization is proposed in this paper. Firstly, the grid method for environment modeling is adopted. Heuristic information is connected with the planning space. A semi-iterative global pheromone update mechanism is proposed. Secondly, the optimal ants mutate the paths to improve the diversity of the algorithm after a defined iterative number. Thirdly, co-evolutionary algorithm is used. Finally, the simulation result shows the effectiveness of the proposed algorithm in solving the problem of 3D pipe path planning.
基于EMRP算法的多UAV协同航迹规划%Cooperative Path Planning Based on EMRP Algorithm for Multi-UAVs
Institute of Scientific and Technical Information of China (English)
张亮; 鲁艺; 徐安; 胡智先; 周帅; 何海波
2011-01-01
A path planning method based on the hierarchical decomposition strategy was proposed for multi-UAV cooperative path planning in the battle field. First, the planning space was obtained by means of skeletonization algorithm, and K backup paths were generated for each UAV based on Evolutionary Multiple Route Planner (EMRP) algorithm. The EMRP algorithm was used together with mathematical morphology for solving the problem of multi-UAV cooperative path planning. The initial paths generated were smoothed,and the feasible paths that satisfied the maneuvering requirement of the UAV was obtained. Then a cooperative planning model was established, which could plan a feasible path for each UAV, which meeted both the requirements of time-coordination and the minimum cost. The simulation shows that this method is viable.%为解决作战环境中的多无人机协同航迹规划问题,提出一种基于层次分解策略的航迹规划方法.通过骨架化算法生成规划空间,利用基于进化计算的多航迹规划(EMRP)算法为各UAV找到K条备用航迹,实现了利用EMRP算法与数学形态学相结合解决多UAV协同航迹规划问题,并对生成的初始航迹进行平滑处理,得到满足UAV机动要求的可行航迹.然后建立协同模型,为各无人机规划出既能满足时间协同要求,又能满足整体代价最优的可行航迹.仿真袁明了该种方法的可行性.
An adaptive dual-optimal path-planning technique for unmanned air vehicles
Directory of Open Access Journals (Sweden)
Whitfield Clifford A.
2016-01-01
Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.
Curvature-continuous 3D Path-planning Using QPMI Method
Directory of Open Access Journals (Sweden)
Seong-Ryong Chang
2015-06-01
Full Text Available It is impossible to achieve vertex movement and rapid velocity control in aerial robots and aerial vehicles because of momentum from the air. A continuous-curvature path ensures such robots and vehicles can fly with stable and continuous movements. General continuous path-planning methods use spline interpolation, for example B-spline and Bézier curves. However, these methods cannot be directly applied to continuous path planning in a 3D space. These methods use a subset of the waypoints to decide curvature and some waypoints are not included in the planned path. This paper proposes a method for constructing a curvature-continuous path in 3D space that includes every waypoint. The movements in each axis, x, y and z, are separated by the parameter u. Waypoint groups are formed, each with its own continuous path derived using quadratic polynomial interpolation. The membership function then combines each continuous path into one continuous path. The continuity of the path is verified and the curvature-continuous path is produced using the proposed method.
Cooperative co-evolution based distributed path planning of multiple mobile robots
Institute of Scientific and Technical Information of China (English)
WANG Mei; WU Tie-jun
2005-01-01
This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution,which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2Dpath planning problems.
On-line real-time path planning of mobile robots in dynamic uncertain environment
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A new path planning method for mobile robots in globally unknown environment with moving obstacles is presented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predicted position taken as the next position of moving obstacles, a motion path in dynamic uncertain environment is planned by means of an on-line real-time path planning technique based on polar coordinates in which the desirable direction angle is taken into consideration as an optimization index. The effectiveness, feasibility, high stability, perfect performance of obstacle avoidance, real-time and optimization capability are demonstrated by simulation examples.
Interactive multi-objective path planning through a palette-based user interface
Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph
2016-05-01
n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a
Path planning for mobile robots based on visibility graphs and A* algorithm
Contreras, Juan D.; Martínez S., Fernando; Martínez S., Fredy H.
2015-07-01
One of most worked issues in the last years in robotics has been the study of strategies to path planning for mobile robots in static and observable conditions. This is an open problem without pre-defined rules (non-heuristic), which needs to measure the state of the environment, finds useful information, and uses an algorithm to select the best path. This paper proposes a simple and efficient geometric path planning strategy supported in digital image processing. The image of the environment is processed in order to identify obstacles, and thus the free space for navigation. Then, using visibility graphs, the possible navigation paths guided by the vertices of obstacles are produced. Finally the A* algorithm is used to find a best possible path. The alternative proposed is evaluated by simulation on a large set of test environments, showing in all cases its ability to find a free collision plausible path.
A New Real-Time Path Planning Method Based on the Belief Space
Directory of Open Access Journals (Sweden)
Yu-xin Zhao
2013-01-01
Full Text Available A new approach of real-time path planning based on belief space is proposed, which solves the problems of modeling the real-time detecting environment and optimizing in local path planning with the fusing factors. Initially, a double-safe-edges free space is defined for describing the sensor detecting characters, so as to transform the complex environment into some free areas, which can help the robots to reach any positions effectively and safely. Then, based on the uncertainty functions and the transferable belief model (TBM, the basic belief assignment (BBA spaces of each factor are presented and fused in the path optimizing process. So an innovative approach for getting the optimized path has been realized with the fusing the BBA and the decision making by the probability distributing. Simulation results indicate that the new method is beneficial in terms of real-time local path planning.
Directory of Open Access Journals (Sweden)
L.Yang
2015-12-01
Full Text Available Three-dimensional path planning for underwater vehicles is an important problem that focuses on optimizing the route with consideration of various constraints in a complex underwater environment. In this paper, an improved ant colony optimization (IACO algorithm based on pheromone exclusion is proposed to solve the underwater vehicle 3D path planning problem. The IACO algorithm can balance the tasks of exploration and development in the ant search path, and enable the ants in the search process to explore initially and develop subsequently. Then, the underwater vehicle can find the safe path by connecting the chosen nodes of the 3D mesh while avoiding the threat area. This new approach can overcome common disadvantages of the basic ant colony algorithm, such as falling into local extremum, poor quality, and low accuracy. Experimental comparative results demonstrate that this proposed IACO method is more effective and feasible in underwater vehicle 3D path planning than the basic ACO model.
Challenging of path planning algorithms for autonomous robot in known environment
Farah, R. N.; Irwan, N.; Zuraida, Raja Lailatul; Shaharum, Umairah; Hanafi@Omar, Hafiz Mohd
2014-06-01
Most of the mobile robot path planning is estimated to reach its predetermined aim through the shortest path and avoiding the obstacles. This paper is a survey on path planning algorithms of various current research and existing system of Unmanned Ground Vehicles (UGV) where their challenging issues to be intelligent autonomous robot. The focuses are some short reviews on individual papers for UGV in the known environment. Methods and algorithms in path planning for the autonomous robot had been discussed. From the reviews, we obtained that the algorithms proposed are appropriate for some cases such as single or multiple obstacles, static or movement obstacle and optimal shortest path. This paper also describes some pros and cons for every reviewed paper toward algorithms improvement for further work.
Development of an interaction and visualisation approach for egress path planning
Hoffmann Eilenberger, Peter
2014-01-01
[ANGLÈS] Many disasters during the past decades, such as natural disasters or terrorist attacks showed that building evacuation is an important issue that has to be analysed thoroughly. Nowadays, static evacuation plans are still used where evacuees have to follow a predefined path to reach the exit of a building. But what happens if this path is blocked due to agglomeration of people, fire or smoke spreading? The escape paths need to be dynamic and building planners require efficient tools t...
Cooperative Path Planning and Constraints Analysis for Master-Slave Industrial Robots
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Yahui Gan
2012-09-01
Full Text Available A strategy of cooperative path planning for a master-slave multiple robot system is presented in this paper. The path planning method is based on motion constraints between the end-effectors of cooperative robots. Cooperation motions have been classified into three types by relative motions between end-effectors of master and slave robots, which is concurrent cooperation, coupled synchronous cooperation and combined synchronous cooperation. Based on this classification, position /orientation constraints and joint velocity constraints are explored in-depth here. In order to validate the path planning method and the theoretical developments in motion constraints analysis, representative experiments based on two industrial robots, Motoman VA1400 and HP20, are provided at the end of the paper. The experimental results have proved both the effectiveness of the path planning method and the correctness of the constraints analysis.
Path planning based on sliding window and variant A*algorithm for quadruped robot
Institute of Scientific and Technical Information of China (English)
张慧
2016-01-01
In order to improve the adaptability of the quadruped robot in complex environments , a path planning method based on sliding window and variant A * algorithm for quadruped robot is presen-ted .To improve the path planning efficiency and robot security , an incremental A*search algorithm ( IA*) and the A*algorithm having obstacle grids extending ( EA*) are proposed respectively .The IA* algorithm firstly searches an optimal path based on A * algorithm, then a new route from the current path to the new goal projection is added to generate a suboptimum route incrementally .In comparison with traditional method solving path planning problem from scratch , the IA* enables the robot to plan path more efficiently .EA* extends the obstacle by means of increasing grid g-value, which makes the route far away from the obstacle and avoids blocking the narrow passage .To navi-gate the robot running smoothly , a quadratic B-spline interpolation is applied to smooth the path . Simulation results illustrate that the IA* algorithm can increase the re-planning efficiency more than 5 times and demonstrate the effectiveness of the EA * algorithm.
Robot Path Planning in Uncertain Environments: A Language-Measure-Theoretic Approach
2015-03-01
especially to ensure collision-free naviga- tion. In this case, Markov decision process (MDP) tools may not be suitable because of the requirement...of robot path planning (see Assumption (4) at the beginning of this section). Therefore, probabilistic decisions of path planning need Journal of...Autonomous Underwater Vehicles,” IEEE Conference on Decision and Con- trol (CDC), Atlanta, GA, Dec. 15–17, pp. 5828–5834. [4] Lolla, T., Ueckermann, P
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Gaige Wang; Lihong Guo; Hong Duan; Heqi Wang; Luo Liu; Mingzhen Shao
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of th...
UAV path planning using artificial potential field method updated by optimal control theory
Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long
2016-04-01
The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.
Application of ant colony algorithm in path planning of the data center room robot
Wang, Yong; Ma, Jianming; Wang, Ying
2017-05-01
According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.
Intelligent learning technique based-on fuzzy logic for multi-robot path planning
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Soccer robot system is a tremendously challenging intelligent system developed to mimic human soc cer competition based on the multi-discipline research: robotics, intelligent control, computer vision, etc. robot path planning strategy is a very important subject concerning to the performance and intelligence degree of the multi-robot system. Therefore, this paper studies the path planning strategy of soccer system by using fuzzy log ic. After setting up two fuzziers and two sorts of fuzzy rules for soccer system, fuzzy logic is applied to work space partition and path revision. The experiment results show that this technique can well enhance the perform ance and intelligence degree of the system.
MOD* Lite: An Incremental Path Planning Algorithm Taking Care of Multiple Objectives.
Oral, Tugcem; Polat, Faruk
2016-01-01
The need for determining a path from an initial location to a target one is a crucial task in many applications, such as virtual simulations, robotics, and computer games. Almost all of the existing algorithms are designed to find optimal or suboptimal solutions considering only a single objective, namely path length. However, in many real life application path length is not the sole criteria for optimization, there are more than one criteria to be optimized that cannot be transformed to each other. In this paper, we introduce a novel multiobjective incremental algorithm, multiobjective D* lite (MOD* lite) built upon a well-known path planning algorithm, D* lite. A number of experiments are designed to compare the solution quality and execution time requirements of MOD* lite with the multiobjective A* algorithm, an alternative genetic algorithm we developed multiobjective genetic path planning and the strength Pareto evolutionary algorithm.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
Dynamic path planning for mobile robot based on particle swarm optimization
Wang, Yong; Cai, Feng; Wang, Ying
2017-08-01
In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.
Directory of Open Access Journals (Sweden)
Biwei Tang
2016-05-01
Full Text Available Global path planning is a challenging issue in the filed of mobile robotics due to its complexity and the nature of nondeterministic polynomial-time hard (NP-hard. Particle swarm optimization (PSO has gained increasing popularity in global path planning due to its simplicity and high convergence speed. However, since the basic PSO has difficulties balancing exploration and exploitation, and suffers from stagnation, its efficiency in solving global path planning may be restricted. Aiming at overcoming these drawbacks and solving the global path planning problem efficiently, this paper proposes a hybrid PSO algorithm that hybridizes PSO and differential evolution (DE algorithms. To dynamically adjust the exploration and exploitation abilities of the hybrid PSO, a novel PSO, the nonlinear time-varying PSO (NTVPSO, is proposed for updating the velocities and positions of particles in the hybrid PSO. In an attempt to avoid stagnation, a modified DE, the ranking-based self adaptive DE (RBSADE, is developed to evolve the personal best experience of particles in the hybrid PSO. The proposed algorithm is compared with four state-of-the-art evolutionary algorithms. Simulation results show that the proposed algorithm is highly competitive in terms of path optimality and can be considered as a vital alternative for solving global path planning.
Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅱ)
Institute of Scientific and Technical Information of China (English)
谭冠政; 胡生员
2002-01-01
Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the segments of the path. But, this method resulted in the heavier on-line computational burden for the robot controller. In this paper, aiming at this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method for robots. Through selecting some extra knots on the specified hand path by a certain rule, which enables the number of knots on each segment to increase from two to four, and through introducing a sinusoidal function and a cosinoidal function to the joint displacement equation of each segment, this method can raise the path tracking accuracy of robot′s hand greatly but does not increase the computational burden of robot controller markedly.
Sampling-based Motion Planning: Analysis and Path Quality
Geraerts, R.J.
2006-01-01
One of the fundamental tasks robots have to perform is planning their motions while avoiding collisions with obstacles in the environment. This is the central topic of the thesis. We restrict ourselves to motion planning for two- and three-dimensional rigid bodies and articulated robots moving in st
Missile trajectory shaping using sampling-based path planning
Pharpatara, Pawit; Pepy, Romain; Hérissé, Bruno; Bestaoui, Yasmina
2013-01-01
International audience; This paper presents missile guidance as a complex robotic problem: a hybrid non-linear system moving in a heterogeneous environment. The proposed solution to this problem combines a sampling-based path planner, Dubins' curves and a locally-optimal guidance law. This algorithm aims to find feasible trajectories that anticipate future flight conditions, especially the loss of manoeuverability at high altitude. Simulated results demonstrate the substantial performance imp...
Kenneth J. Ruzicka; Deanna H. Olson; Klaus J. Puettmann
2013-01-01
Initiated simultaneously, the Density Management and Riparian Buff er Study of western Oregon and the Northwest Forest Plan have had intertwining paths related to federal forest management and policy changes in the Pacifi c Northwest over the last 15 to 20 years. We briefl y discuss the development of the Northwest Forest Plan and how it changed the way forest policy...
Directory of Open Access Journals (Sweden)
A. A. Heidari
Full Text Available An essential task of UAV autonomy is automatic path planning. There are many evolutionary planners for Unmanned Aerial Vehicles (UAVs that have been developed UAV community. In this paper a comparative study about performance of effective trajectory plan ...
A Variational Approach to Path Planning in Three Dimensions Using Level Set Methods
2004-12-08
planning. IEEE Transactions on Robotics and Automa- tion, 14(1), 1998. [15] L. Kavraki, P. Svestka, J. Latombe, and M. Overmars. Probabilistic roadmaps...for path planning in high dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4), 1996. [16] Ron Kimmel and James A
Path planning for MIG surfacing of robot-based remanufacturing system
Institute of Scientific and Technical Information of China (English)
Zhu Sheng; Liang Yuanyuan
2006-01-01
Robot-based remanufacturing system can scan the worn parts and develop the corresponding models, compare them with the standard model, calculate the weld deposit, implement welding path planning, and repair the worn parts with MIG surfacing automatically. This paper investigates the welding path planning after calibrating, scanning and model rebuilding.The following aspects are contained: introducing the planning principle, selecting the suitable welding process based on welding parameters ( current and speed), calculating welding overlap quantity by the superposition method. Also, it has been verified that good weld profile can be obtained with the optimized parameters.
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Directory of Open Access Journals (Sweden)
Gaige Wang
2012-01-01
Full Text Available Three-dimension path planning for uninhabited combat air vehicle (UCAV is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE and cuckoo search (CS algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.
A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.
Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.
Energy Technology Data Exchange (ETDEWEB)
Tsauo, Jiaywei, E-mail: 80732059@qq.com; Luo, Xuefeng, E-mail: luobo-913@126.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China); Ye, Linchao, E-mail: linchao.ye@siemens.com [Siemens Ltd, Healthcare Sector (China); Li, Xiao, E-mail: simonlixiao@gmail.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China)
2015-06-15
PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.
Research on Path Planning Method of Coal Mine Robot to Avoid Obstacle in Gas Distribution Area
Directory of Open Access Journals (Sweden)
Ruiqing Mao
2016-01-01
Full Text Available As the explosion-proof safety level of a coal mine robot has not yet reached the level of intrinsic safety “ia” and it cannot work in a dangerous gas distribution area, therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. In this paper, to avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed with consideration of gas concentration distributions. First, with consideration of gas distribution area and obstacles, MAKLINK method is adopted to describe the working environment network diagram of the coal mine robot. Second, the initial working paths for the coal mine robot are obtained based on Dijkstra algorithm, and then the global optimal working path for the coal mine robot is obtained based on ant colony algorithm. Lastly, experiments are conducted in a roadway after an accident, and results by different path planning methods are compared, which verified the effectiveness of the proposed path planning method.
Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm
Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.
This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).
Production paths – an innovative concept for heavy machinery production planning and control
R. Lenort; R. Klepek; A. Samolejová; Besta, P.
2013-01-01
The paper introduces a new concept for planning and control of complicated heavy machinery production which is based on the principle of „production paths“ – production paths planning and control concept. The concept refl ects the limited applicability of traditional concepts and systems for production planning and control in conditions of heavy machinery industry that is specifi c by the limited repeatability of product structures and volumes, by complicated and variant material ...
Alomari, Abdullah; Phillips, William; Aslam, Nauman; Comeau, Frank
2017-08-18
Mobile anchor path planning techniques have provided as an alternative option for node localization in wireless sensor networks (WSNs). In such context, path planning is a movement pattern where a mobile anchor node's movement is designed in order to achieve a maximum localization ratio possible with a minimum error rate. Typically, the mobility path planning is designed in advance, which is applicable when the mobile anchor has sufficient sources of energy and time. However, when the mobility movement is restricted or limited, a dynamic path planning design is needed. This paper proposes a novel distributed range-free movement mechanism for mobility-assisted localization in WSNs when the mobile anchor's movement is limited. The designed movement is formed in real-time pattern using a fuzzy-logic approach based on the information received from the network and the nodes' deployment. Our proposed model, Fuzzy-Logic based Path Planning for mobile anchor-assisted Localization in WSNs (FLPPL), offers superior results in several metrics including both localization accuracy and localization ratio in comparison to other similar works.
Strategic Path Planning by Sequential Parametric Bayesian Decisions
Directory of Open Access Journals (Sweden)
Baro Hyun
2013-11-01
Full Text Available The objective of this research is to generate a path for a mobile agent that carries sensors used for classification, where the path is to optimize strategic objectives that account for misclassification and the consequences of misclassification, and where the weights assigned to these consequences are chosen by a strategist. We propose a model that accounts for the interaction between the agent kinematics (i.e., the ability to move, informatics (i.e., the ability to process data to information, classification (i.e., the ability to classify objects based on the information, and strategy (i.e., the mission objective. Within this model, we pose and solve a sequential decision problem that accounts for strategist preferences and the solution to the problem yields a sequence of kinematic decisions of a moving agent. The solution of the sequential decision problem yields the following flying tactics: “approach only objects whose suspected identity matters to the strategy”. These tactics are numerically illustrated in several scenarios.
Strategic Path Planning by Sequential Parametric Bayesian Decisions
Directory of Open Access Journals (Sweden)
Baro Hyun
2013-11-01
Full Text Available The objective of this research is to generate a path for a mobile agent that carries sensors used for classification, where the path is to optimize strategic objectives that account for misclassification and the consequences of misclassification, and where the weights assigned to these consequences are chosen by a strategist. We propose a model that accounts for the interaction between the agent kinematics (i.e., the ability to move, informatics (i.e., the ability to process data to information, classification (i.e., the ability to classify objects based on the information, and strategy (i.e., the mission objective. Within this model, we pose and solve a sequential decision problem that accounts for strategist preferences and the solution to the problem yields a sequence of kinematic decisions of a moving agent. The solution of the sequential decision problem yields the following flying tactics: “approach only objects whose suspected identity matters to the strategy". These tactics are numerically illustrated in several scenarios.
Real—Time Collision—Free Path Planning for Robots in Configuration Space
Institute of Scientific and Technical Information of China (English)
李伟; HilmarJaschek; 等
1994-01-01
Collision-free path planning for an industrial robot in configuration space requires mapping obstacles from robot's workspace into its configuration space.In this paper,an approach to real-time collision-free path planning for robots in configuration space is presented.Obstacle mapping is carried out by fundamental obstacles defined in the workspace and their images in the configuration space.In order to avoid dealing with unimportant parts of the configuration space that do not affect searching a collision-free path between starting and goal configurations,we construct a free subspace by slice configuration obstacles.In this free subspace,the collision-free path is determined by the A* algorithm.Finally,graphical simulations show the effectiveness of the proposed approach.
Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang
2016-08-01
Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.
Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination
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Yong Ma
2014-01-01
Full Text Available This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach.
Institute of Scientific and Technical Information of China (English)
季学武; 王健; 赵又群; 刘亚辉; 臧利国; 李波
2015-01-01
In order to diminish the impacts of external disturbance such as parking speed fluctuation and model un-certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre-view back propagation (BP) neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po-sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.
Path planning using a tangent graph for mobile robots among polygonal and curved obstacles
Energy Technology Data Exchange (ETDEWEB)
Liu, Yun-Hui; Arimoto, Suguru (Univ. of Tokyo (Japan))
1992-08-01
This article proposes a tangent graph for path planning of mobile robots among obstacles with a general boundary. The tangent graph is defined on the basis of the locally shortest path. It has the same data structure as the visibility graph, but its nodes represent common tangent points on obstacle boundaries, and its edges correspond to collision-free common tangents between the boundaries and convex boundary segments between the tangent points. The tangent graph requires O(K[sup 2]) memory, where K denotes the total number of convex segments of the obstacle boundaries. The tangent graph includes all locally shortest paths and is capable of coping with path planning not only among polygonal obstacles but also among curved obstacles.
Path Planning Using Concatenated Analytically-Defined Trajectories for Quadrotor UAVs
Directory of Open Access Journals (Sweden)
Jonathan Jamieson
2015-04-01
Full Text Available This paper presents a semi-analytical trajectory planning method for quadrotor UAVs. These trajectories are analytically defined, are constant in speed and sub-optimal with respect to a weighted quadratic cost function of the translational and angular velocities. A technique for concatenating the trajectories into multi-segment paths is demonstrated. These paths are smooth to the first derivative of the translational position and pass through defined waypoints. A method for detecting potential collisions by discretizing the path into a coarse mesh before using a numerical optimiser to determine the point of the path closest to the obstacle is presented. This hybrid method reduces the computation time when compared to discretizing the trajectory into a fine mesh and calculating the minimum distance. A tracking controller is defined and used to show that the paths are dynamically feasible and the typical magnitudes of the controller inputs required to fly them.
Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅰ)
Institute of Scientific and Technical Information of China (English)
谭冠政; 梁丰; 王越超
2002-01-01
Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Car-tesian space mainly through increasing the number of knots on the path and the number of the path′s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot′s hand and does not change the number of the path′s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots.
Chen, Jun; Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Tang, Yipeng
2010-01-01
An enhanced dynamic Delaunay Triangulation-based (DT) path planning approach is proposed for mobile robots to plan and navigate a path successfully in the context of the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The Autonomous Challenge course requires the application of vision techniques since it involves path-based navigation in the presence of a tightly clustered obstacle field. Course artifacts such as switchbacks, ramps, dashed lane lines, trap etc. are present which could turn the robot around or cause it to exit the lane. The main contribution of this work is a navigation scheme based on dynamic Delaunay Triangulation (DDT) that is heuristically enhanced on the basis of a sense of general lane direction. The latter is computed through a "GPS (Global Positioning System) tail" vector obtained from the immediate path history of the robot. Using processed data from a LADAR, camera, compass and GPS unit, a composite local map containing both obstacles and lane line segments is built up and Delaunay Triangulation is continuously run to plan a path. This path is heuristically corrected, when necessary, by taking into account the "GPS tail" . With the enhancement of the Delaunay Triangulation by using the "GPS tail", goal selection is successfully achieved in a majority of situations. The robot appears to follow a very stable path while navigating through switchbacks and dashed lane line situations. The proposed enhanced path planning and GPS tail technique has been successfully demonstrated in a Player/Stage simulation environment. In addition, tests on an actual course are very promising and reveal the potential for stable forward navigation.
Heuristic methods for shared backup path protection planning
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2012-01-01
present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5% was achieved for more than half of the benchmark instances (and a gap of less...
Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning
Fu, QiMing
2016-01-01
To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704
A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning
Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei
2013-03-01
In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.
Application of particle swarm optimization in path planning of mobile robot
Wang, Yong; Cai, Feng; Wang, Ying
2017-08-01
In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.
Minimum Time Path Planning for Robotic Manipulator in Drilling/ Spot Welding Tasks
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Qiang Zhang
2016-04-01
Full Text Available In this paper, a minimum time path planning strategy is proposed for multi points manufacturing problems in drilling/spot welding tasks. By optimizing the travelling schedule of the set points and the detailed transfer path between points, the minimum time manufacturing task is realized under fully utilizing the dynamic performance of robotic manipulator. According to the start-stop movement in drilling/spot welding task, the path planning problem can be converted into a traveling salesman problem (TSP and a series of point to point minimum time transfer path planning problems. Cubic Hermite interpolation polynomial is used to parameterize the transfer path and then the path parameters are optimized to obtain minimum point to point transfer time. A new TSP with minimum time index is constructed by using point-point transfer time as the TSP parameter. The classical genetic algorithm (GA is applied to obtain the optimal travelling schedule. Several minimum time drilling tasks of a 3-DOF robotic manipulator are used as examples to demonstrate the effectiveness of the proposed approach.
UAV feasible path planning based on disturbed fluid and trajectory propagation
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Yao Peng
2015-08-01
Full Text Available In this paper, a novel algorithm based on disturbed fluid and trajectory propagation is developed to solve the three-dimensional (3-D path planning problem of unmanned aerial vehicle (UAV in static environment. Firstly, inspired by the phenomenon of streamlines avoiding obstacles, the algorithm based on disturbed fluid is developed and broadened. The effect of obstacles on original fluid field is quantified by the perturbation matrix, where the tangential matrix is first introduced. By modifying the original flow field, the modified one is then obtained, where the streamlines can be regarded as planned paths. And the path proves to avoid all obstacles smoothly and swiftly, follow the shape of obstacles effectively and reach the destination eventually. Then, by considering the kinematics and dynamics equations of UAV, the method called trajectory propagation is adopted to judge the feasibility of the path. If the planned path is unfeasible, repulsive and tangential parameters in the perturbation matrix will be adjusted adaptively based on the resolved state variables of UAV. In most cases, a flyable path can be obtained eventually. Simulation results demonstrate the effectiveness of this method.
An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective.
Faigl, Jan
2016-01-01
In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to "see" the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning.
An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective
Directory of Open Access Journals (Sweden)
Jan Faigl
2016-01-01
Full Text Available In this paper, Self-Organizing Map (SOM for the Multiple Traveling Salesman Problem (MTSP with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots’ workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning.
Continuous Genetic Algorithms for Collision-Free Cartesian Path Planning of Robot Manipulators
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Za'er S. Abo-Hammour
2011-12-01
Full Text Available A novel continuous genetic algorithm (CGA along with distance algorithm for solving collisions‐free path planning problem for robot manipulators is presented in this paper. Given the desired Cartesian path to be followed by the manipulator, the robot configuration as described by the D‐H parameters, and the available stationary obstacles in the workspace of the manipulator, the proposed approach will autonomously select a collision free path for the manipulator that minimizes the deviation between the generated and the desired Cartesian path, satisfy the joints limits of the manipulator, and maximize the minimum distance between the manipulator links and the obstacles. One of the main features of the algorithm is that it avoids the manipulator kinematic singularities due to the inclusion of forward kinematics model in the calculations instead of the inverse kinematics. The new robot path planning approach has been applied to two different robot configurations; 2R and PUMA 560, as non‐ redundant manipulators. Simulation results show that the proposed CGA will always select the safest path avoiding obstacles within the manipulator workspace regardless of whether there is a unique feasible solution, in terms of joint limits, or there are multiple feasible solutions. In addition to that, the generated path in Cartesian space will be of very minimal deviation from the desired one.
Complete coverage path planning of a random polygon - A FroboMind component
DEFF Research Database (Denmark)
Aslund, Sebastian; Jensen, Kjeld; Jørgensen, Rasmus Nyholm
solution where all the steps in the process is included: Segmentation of a data set, creation of a configuration space, decomposition of a polygon, global and local path planning. To achieve this, a series of known algorithms are used including some tweaks and improvements to create a solid foundation...... for the FroboMind architecture and the agricultural community to explore and develop new algorithms for coverage path planning. Furthermore will the project be tested and verified by implementing it on a vehicle based on the FroboMind architecture.......The aim of this work is to have an universal solution for complete coverage which will be a component in the FroboMind architecture suggested by Kjeld Jensen in [9]. ... Compared to previously work done within the field of coverage path planning this work presents a complete, universal and generic...
An Improved VFF Approach for Robot Path Planning in Unknown and Dynamic Environments
Directory of Open Access Journals (Sweden)
Jianjun Ni
2014-01-01
Full Text Available Robot path planning in unknown and dynamic environments is one of the hot topics in the field of robot control. The virtual force field (VFF is an efficient path planning method for robot. However, there are some shortcomings of the traditional VFF based methods, such as the local minimum problem and the higher computational complexity, in dealing with the dynamic obstacle avoidance. In this paper, an improved VFF approach is proposed for the real-time robot path planning, where the environment is unknown and changing. An area ratio parameter is introduced into the proposed VFF based approach, where the size of the robot and obstacles are considered. Furthermore, a fuzzy control module is added, to deal with the problem of obstacle avoidance in dynamic environments, by adjusting the rotation angle of the robot. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach.
Institute of Scientific and Technical Information of China (English)
WANG Weizhong; ZHAO Jie; GAO Yongsheng; CAI Hegao
2006-01-01
A novel approach for collision-free path planning of a multiple degree-of-freedom (DOF)articulated robot in a complex environment is proposed. Firstly, based on visual neighbor point (VNP), a numerical artificial potential field is constructed in Cartesian space, which provides the heuristic information, effective distance to the goal and the motion direction for the motion of the robot joints. Secondly, a genetic algorithm, combined with the heuristic rules, is used in joint space to determine a series of contiguous configurations piecewise fiom initial configuration until the goal configuration is attained. A simulation shows that the method can not only handle issues on path planning of the articulated robots in environment with complex obstacles, but also improve the efficiency and quality of path planning.
Path Planning of Planar Kinked Line Seam by Visual Servoing for Robotic Welding
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Welding path planning can substitute for the manual teaching process of the robot and can promote the autonomous level of the robotic welding. A path planning method by visual servoing was presented, in which the optimal angle of charge-coupled device (CCD) camera was also planned. Aiming at planning two forms of kinked line seams, obtuse angle seam and right angle seam, a practicable solution was put forward. In this solution, the intersection of two adjacent straight segments is detected in each local seam image, and if intersection is found, theseam errors are calculated using the next straight segment. The experimental results show that kinked line seam can be well planned using this solution.
Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X
2017-01-01
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.
Directory of Open Access Journals (Sweden)
Jianjun Ni
2017-01-01
Full Text Available Real-time path planning for autonomous underwater vehicle (AUV is a very difficult and challenging task. Bioinspired neural network (BINN has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.
Research on Navigation Path Planning for An Underground Load Haul Dump
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Qi Yulong
2015-11-01
Full Text Available The improved A * algorithm is a method of navigation path planning for articulated underground scrapers. Firstly, an environment model based on a mining Geographic Information System (GIS map is established, and then combined with improved A * algorithm, the underground global path planning problem of the intelligent Load Haul Dump (LHD is solved. In this paper, for the articulated structure, the method of expanding nodes by articulation angle is adopted to make expanded nodes meet the trajectory characteristics. In addition, collision threat cost is introduced in the evaluation function to avoid collisions between the LHD and the tunnel walls. As peran analysis of the simulation test to verify the effectiveness of the improved A * algorithm and a comparison with the traditional A * algorithm, the improved A * algorithm can enhance search efficiency. Acontrast of multiple sets of test parameters suggests that when the price weighted coefficient of collision is 0.2, the shortest path can be derived to avoid impact. Finally, tracking results indicate that the proposed algorithm for navigation path planning can maintain the tracking error to within 0.2 m in line with the structural characteristics of the scraper in the laboratory environment to realize the path planning of unmanned scrapers and trajectory tracking. Moreover, the algorithm can enhance the safety of scrapers and prevent roadway collisions. The feasibility and practicality of the proposed method is verified in this work.
Adaptive and less-complex path-planning behavior for mobile robots
Mantegh, Iraj; Jenkin, Michael R. M.; Goldenberg, Andrew A.
1998-01-01
The objective of path planing is to find a sequence of states that a system has to visit in order to attain the goal state. Because of their real-time efficiency, potential field methods present a powerful heuristic to guide this search. However, potential field approaches can not guarantee goal attainability. They are often referred to as 'local methods' and are used in conjunction with a global path planning method to ensure completeness of the path planning algorithm. The present work introduces a novel methodology for path planing which combines the real- time efficiency of potential field methods with goal-attainability characteristics of global methods. The algorithm of this work is: 1) free from local minima, ii) capable of considering arbitrary-shaped obstacles, iii) computationally less complex than previous search methods; and iv) able to handle obstacle avoidance and goal attainability at the same time. At the first step a new probabilistic scheme, based on absorbing Markov chains, is presented for global planning inside structured environments, such as office, etc. The potential field method is then reformulated for adaptive path planning among modeled and new obstacles.
Directory of Open Access Journals (Sweden)
Chang Liu
2015-01-01
Full Text Available Path planning is a classic optimization problem which can be solved by many optimization algorithms. The complexity of three-dimensional (3D path planning for autonomous underwater vehicles (AUVs requires the optimization algorithm to have a quick convergence speed. This work provides a new 3D path planning method for AUV using a modified firefly algorithm. In order to solve the problem of slow convergence of the basic firefly algorithm, an improved method was proposed. In the modified firefly algorithm, the parameters of the algorithm and the random movement steps can be adjusted according to the operating process. At the same time, an autonomous flight strategy is introduced to avoid instances of invalid flight. An excluding operator was used to improve the effect of obstacle avoidance, and a contracting operator was used to enhance the convergence speed and the smoothness of the path. The performance of the modified firefly algorithm and the effectiveness of the 3D path planning method were proved through a varied set of experiments.
2017-01-01
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297
An Analysis of the Assembly Path Planning of Decelerator Based on Virtual Technology
Jin, Xiangyang; Zhang, Tiefeng; Yang, Hanlin
According to structural features of different components of decelerator, the general rule of three-dimensional solid modeling of components is summarized, the three-dimensional model of gear stand is built, all components are organized into groups to form a whole partial assembly, and various kinds of assembly relations are added among components, as well as hierarchical relations. Then the assembly path of decelerator is programmed, the sequence of assembling components is decided, and finally the assembly simulation is completed, laying the foundation for component disassembly. Virtual assembly technology helps to introduce advanced design approaches, improve the quality of products, reduce development cost and shorten development cycle.
Robot path Planning Using SIFT and Sonar Sensor Fusion
DEFF Research Database (Denmark)
Plascencia, Alfredo; Raposo, Hector
2007-01-01
This paper presents a novel map building approach for path planning purposes, which takes into account the uncertainty inherent in sensor measurements. To this end, Bayesian estimation and Dempster-Shafer evidential theory are used to fuse the sensory information and to update the occupancy...... and evidential grid maps, respectively. The approach is illustrated using actual measurements from a laboratory robot. The sensory information is obtained from a sonar array and the Scale Invariant Feature Transform (SIFT) algorithm. Finally, the resulting two evidential maps based on Bayes and Dempster theories...... are used for path planning using the potential field method. Both yield satisfying results...
Kinematic modeling and path planning for MIRADAS arms
Sabater, Josep; Gómez, José María.; López, Manuel; Torra, Jordi; Raines, Steven N.; Eikenberry, Stephen S.
2014-07-01
The Mid-resolution InfRAreD Astronomical Spectrograph (MIRADAS) is a near-infrared (NIR) multi-object spectrograph for the Gran Telescopio Canarias (GTC). It can simultaneously observe multiple targets selected by 20 identical deployable probe arms with pickoff mirror optics. The bases of the arms are fixed to the multiplexing system (MXS) plate, a circular platform, and arranged in a circular layout with minimum separation between elements of the arms. This document presents the MXS prototype P2a, a full-scale, fully operational prototype of a MIRADAS probe arm. This planar closed-loop mechanism compared to other previous designs offers some advantages specially in terms of stability and from the point of view of optics. Unfortunately, these benefits come at the expense of a more complicated kinematics and an unintuitive arm motion. Furthermore, the cryogenic motor controllers used in prototyping impose severe restrictions in path planing. They negatively impact in the slice of pie approach, a collision-avoidance patrolling strategy that can gives good results in other scenarios. This study is a starting point to define collision-free trajectory algorithms for the 20 probe arms of MIRADAS.
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Imen Châari
2014-07-01
Full Text Available Path planning is a fundamental optimization problem that is crucial for the navigation of a mobile robot. Among the vast array of optimization approaches, we focus in this paper on Ant Colony Optimization (ACO and Genetic Algorithms (GA for solving the global path planning problem in a static environment, considering their effectiveness in solving such a problem. Our objective is to design an efficient hybrid algorithm that takes profit of the advantages of both ACO and GA approaches for the sake of maximizing the chance to find the optimal path even under real-time constraints. In this paper, we present smartPATH, a new hybrid ACO-GA algorithm that relies on the combination of an improved ACO algorithm (IACO for efficient and fast path selection, and a modified crossover operator to reduce the risk of falling into a local minimum. We demonstrate through extensive simulations that smartPATH outperforms classical ACO (CACO, GA algorithms. It also outperforms the Dijkstra exact method in solving the path planning problem for large graph environments. It improves the solution quality up to 57% in comparison with CACO and reduces the execution time up to 83% as compared to Dijkstra for large and dense graphs. In addition, the experimental results on a real robot shows that smartPATH finds the optimal path with a probability up to 80% with a small gap not exceeding 1m in 98%.
Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.
van de Wetering, Rogier; Batenburg, Ronald; Lederman, Reeva
2010-07-01
While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the scientific literature. Consequently, in this paper we propose a strategic planning method for PACS deployment. This method builds upon a PACS maturity model (PMM), based on the elaboration of the strategic alignment concept and the maturity growth path concept previously developed in the PACS domain. First, we review the literature on strategic planning for information systems and information technology and PACS maturity. Secondly, the PMM is extended by applying four different strategic perspectives of the Strategic Alignment Framework whereupon two types of growth paths (evolutionistic and revolutionary) are applied that focus on a roadmap for PMM. This roadmap builds a path to get from one level of maturity and evolve to the next. An extended method for PACS strategic planning is developed. This method defines eight distinctive strategies for PACS strategic situational planning that allow decision-makers in hospitals to decide which approach best suits their hospitals' current situation and future ambition and what in principle is needed to evolve through the different maturity levels. The proposed method allows hospitals to strategically plan for PACS maturation. It is situational in that the required investments and activities depend on the alignment between the hospital strategy and the selected growth path. The inclusion of both strategic alignment and maturity growth path concepts make the planning method rigorous, and provide a framework for further empirical research and clinical practice.
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Juan Carlos Osorio Gómez
2010-04-01
Full Text Available Production planning and control are complex problems for manufacturing organisations. Hierarchical production planning and control is one way to address the problem as it can reduce its complexity and reach good solutions in reasonable computational time. This paper presents a hierarchical approach to resolving production programming in a flexible job shop configuration; this problem includes pre-emption and sequence-dependent setup times. Al-though non-optimal (as expected, good solutions were obtained as shown in the validation of the method.
Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm
Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam
2017-04-01
The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.
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Imen Chaari
2017-03-01
Full Text Available This article presents the results of the 2-year iroboapp research project that aims at devising path planning algorithms for large grid maps with much faster execution times while tolerating very small slacks with respect to the optimal path. We investigated both exact and heuristic methods. We contributed with the design, analysis, evaluation, implementation and experimentation of several algorithms for grid map path planning for both exact and heuristic methods. We also designed an innovative algorithm called relaxed A-star that has linear complexity with relaxed constraints, which provides near-optimal solutions with an extremely reduced execution time as compared to A-star. We evaluated the performance of the different algorithms and concluded that relaxed A-star is the best path planner as it provides a good trade-off among all the metrics, but we noticed that heuristic methods have good features that can be exploited to improve the solution of the relaxed exact method. This led us to design new hybrid algorithms that combine our relaxed A-star with heuristic methods which improve the solution quality of relaxed A-star at the cost of slightly higher execution time, while remaining much faster than A* for large-scale problems. Finally, we demonstrate how to integrate the relaxed A-star algorithm in the robot operating system as a global path planner and show that it outperforms its default path planner with an execution time 38% faster on average.
A Novel Global Path Planning Method for Mobile Robots Based on Teaching-Learning-Based Optimization
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Zongsheng Wu
2016-07-01
Full Text Available The Teaching-Learning-Based Optimization (TLBO algorithm has been proposed in recent years. It is a new swarm intelligence optimization algorithm simulating the teaching-learning phenomenon of a classroom. In this paper, a novel global path planning method for mobile robots is presented, which is based on an improved TLBO algorithm called Nonlinear Inertia Weighted Teaching-Learning-Based Optimization (NIWTLBO algorithm in our previous work. Firstly, the NIWTLBO algorithm is introduced. Then, a new map model of the path between start-point and goal-point is built by coordinate system transformation. Lastly, utilizing the NIWTLBO algorithm, the objective function of the path is optimized; thus, a global optimal path is obtained. The simulation experiment results show that the proposed method has a faster convergence rate and higher accuracy in searching for the path than the basic TLBO and some other algorithms as well, and it can effectively solve the optimization problem for mobile robot global path planning.
PSO-Based Robot Path Planning for Multisurvivor Rescue in Limited Survival Time
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N. Geng
2014-01-01
Full Text Available Since the strength of a trapped person often declines with time in urgent and dangerous circumstances, adopting a robot to rescue as many survivors as possible in limited time is of considerable significance. However, as one key issue in robot navigation, how to plan an optimal rescue path of a robot has not yet been fully solved. This paper studies robot path planning for multisurvivor rescue in limited survival time using a representative heuristic, particle swarm optimization (PSO. First, the robot path planning problem including multiple survivors is formulated as a discrete optimization one with high constraint, where the number of rescued persons is taken as the unique objective function, and the strength of a trapped person is used to constrain the feasibility of a path. Then, a new integer PSO algorithm is presented to solve the mathematical model, and several new operations, such as the update of a particle, the insertion and inversion operators, and the rapidly local search method, are incorporated into the proposed algorithm to improve its effectiveness. Finally, the simulation results demonstrate the capacity of our method in generating optimal paths with high quality.
Gorbenko, Anna; Popov, Vladimir
2017-07-01
Different planning problems for robotic remote laser welding are of considerable interest. In this paper, we consider the problem of integrated task sequencing and path planning for robotic remote laser welding. We propose an efficient approach to solve the problem. In particular, we consider an explicit reduction from the decision version of the problem to the satisfiability problem. We present the results of computational experiments for different satisfiability algorithms.
Efficient UAV Path Planning with Multiconstraints in a 3D Large Battlefield Environment
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Weiwei Zhan
2014-01-01
Full Text Available This study introduces an improved A* algorithm for the real-time path planning of Unmanned Air Vehicles (UAVs in a 3D large-scale battlefield environment to solve the problem that UAVs require high survival rates and low fuel consumption. The algorithm is able to find the optimal path between two waypoints in the target space and comprehensively takes factors such as altitude, detection probability, and path length into account. It considers the maneuverability constraints of the UAV, including the safety altitude, climb rate, and turning radius, to obtain the final flyable path. Finally, the authors test the algorithm in an approximately 2,500,000 square meter area containing radars, no-fly zones, and extreme weather conditions to measure its feasibility, stability, and efficiency.
Shortest Path Planning for a Tethered Robot or an Anchored Cable
Energy Technology Data Exchange (ETDEWEB)
Xavier, P.G.
1999-02-22
We consider the problem of planning shortest paths for a tethered robot with a finite length tether in a 2D environment with polygonal obstacles. We present an algorithm that runs in time O((k{sub 1} + 1){sup 2}n{sup 4}) and finds the shortest path or correctly determines that none exists that obeys the constraints; here n is the number obstacle vertices, and k{sub 1} is the number loops in the initial configuration of the tether. The robot may cross its tether but nothing can cross obstacles, which cause the tether to bend. The algorithm applies as well for planning a shortest path for the free end of an anchored cable.
HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments
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Javier Garrido
2013-08-01
Full Text Available Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were not developed considering computational limitations (i.e., processing and memory capacity. This paper presents the HCTNav path-planning algorithm (HCTLab research group’s navigation algorithm. This algorithm was designed to be run in low-cost robots for indoor navigation. The results of the comparison between HCTNav and the Dijkstra’s algorithms show that HCTNav’s memory peak is nine times lower than Dijkstra’s in maps with more than 150,000 cells.
Multi-robot path planning in a dynamic environment using improved gravitational search algorithm
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P.K. Das
2016-09-01
Full Text Available This paper proposes a new methodology to optimize trajectory of the path for multi-robots using improved gravitational search algorithm (IGSA in a dynamic environment. GSA is improved based on memory information, social, cognitive factor of PSO (particle swarm optimization and then, population for next generation is decided by the greedy strategy. A path planning scheme has been developed using IGSA to optimally obtain the succeeding positions of the robots from the existing position. Finally, the analytical and experimental results of the multi-robot path planning have been compared with those obtained by IGSA, GSA and PSO in a similar environment. The simulation and the Khepera environmental results outperform IGSA as compared to GSA and PSO with respect to performance matrix.
Path Planning for Mobile Robots using Iterative Artificial Potential Field Method
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Hossein Adeli
2011-07-01
Full Text Available In this paper, a new algorithm is proposed for solving the path planning problem of mobile robots. The algorithm is based on Artificial Potential Field (APF methods that have been widely used for path planning related problems for more than two decades. While keeping the simplicity of traditional APF methods, our algorithm is built upon new potential functions based on the distances from obstacles, destination point and start point. The algorithm uses the potential field values iteratively to find the optimum points in the workspace in order to form the path from start to destination. The number of iterations depends on the size and shape of the workspace. The performance of the proposed algorithm is tested by conducting simulation experiments.
3D Path Planning for Autonomous Aerial Vehicles in Constrained Spaces
DEFF Research Database (Denmark)
Schøler, Flemming
Determining how an autonomous Unmanned Aircraft System (UAS) should reach a goal position amidst obstacles is a challenging and difficult problem. This thesis treats the subject of path planning and trajectory generation for UAS, while utilizing the ability to move in all three spatial dimensions...
Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning
Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao
2015-01-01
This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…
Solving the empty space problem in robot path planning by mathematical morphology
Roerdink, J.B.T.M.
1993-01-01
In this paper we formulate a morphological approach to path planning problems, in particular with respect to the empty-space problem, that is, the question of finding the allowed states for an object, moving in a space with obstacles. Our approach is based upon a recent generalization of mathematic
The force control and path planning of electromagnetic induction-based massage robot.
Wang, Wendong; Zhang, Lei; Li, Jinzhe; Yuan, Xiaoqing; Shi, Yikai; Jiang, Qinqin; He, Lijing
2017-07-20
Massage robot is considered as an effective physiological treatment to relieve fatigue, improve blood circulation, relax muscle tone, etc. The simple massage equipment quickly spread into market due to low cost, but they are not widely accepted due to restricted massage function. Complicated structure and high cost caused difficulties for developing multi-function massage equipment. This paper presents a novel massage robot which can achieve tapping, rolling, kneading and other massage operations, and proposes an improved reciprocating path planning algorithm to improve massage effect. The number of coil turns, the coil current and the distance between massage head and yoke were chosen to investigate the influence on massage force by finite element method. The control system model of the wheeled massage robot was established, including control subsystem of the motor, path algorithm control subsystem, parameter module of the massage robot and virtual reality interface module. The improved reciprocating path planning algorithm was proposed to improve regional coverage rate and massage effect. The influence caused by coil current, the number of coil turns and the distance between massage head and yoke were simulated in Maxwell. It indicated that coil current has more important influence compared to the other two factors. The path planning simulation of the massage robot was completed in Matlab, and the results show that the improved reciprocating path planning algorithm achieved higher coverage rate than the traditional algorithm. With the analysis of simulation results, it can be concluded that the number of coil turns and the distance between the moving iron core and the yoke could be determined prior to coil current, and the force can be controllable by optimizing structure parameters of massage head and adjusting coil current. Meanwhile, it demonstrates that the proposed algorithm could effectively improve path coverage rate during massage operations, therefore
A Hybrid System of Hierarchical Planning of Behaviour Selection Networks for Mobile Robot Control
Directory of Open Access Journals (Sweden)
Young-Seol Lee
2014-04-01
Full Text Available An office delivery robot receives a large amount of sensory data and there is uncertainty in its action outcomes. The robot should not only accomplish its goals using environmental information, but also consider various exceptions simultaneously. In this paper, we propose a hybrid system using hierarchical planning of modular behaviour selection networks to generate autonomous behaviour in the office delivery robot. Behaviour selection networks, one of the well-known behaviour-based methods suitable for goal-oriented tasks, are made up of several smaller behaviour modules. Planning is attached to the construct and adjust sequences of the modules by considering the sub-goals, the priority in each task and the user feedback. This helps the robot to quickly react in dynamic situations as well as achieve global goals efficiently. The proposed system is verified with both the Webot simulator and a Khepera II robot that runs in a real office environment carrying out delivery tasks. Experimental results have shown that a robot can achieve goals and generate module sequences successfully even in unpredictable situations. Additionally, the proposed planning method reduced the elapsed time during tasks by 17.5% since it adjusts the behaviour module sequences more effectively.
基于分级规划策略的 A*算法多航迹规划%Multiple routes planning for A* algorithm based on hierarchical planning
Institute of Scientific and Technical Information of China (English)
李枭扬; 周德云; 冯琦
2015-01-01
In order to avoid setting operating parameters and generate multiple routes steadily,a multiple routes planning for the A* algorithm based on hierarchical planning is proposed.The hierarchical planning is in-troduced to divide the planning process into two parts,the initial route planning and the fine route planning.In the initial route planning,many feasible routes are obtained by setting the middle route point and the A* algo-rithm,then the hierarchical clustering method is presented to obtain the initial reference route so as to avoid the weakness of K-means clustering sensitive to the initial clustering center.In the fine route planning,a variable width path planning channel is designed,and the final multiple routes are obtained by planning in the channel. Simulation results prove the feasibility of the algorithm.%为了避免设置运行参数，稳定地生成多条航迹，提出一种基于分级规划策略的 A*算法多航迹规划技术。采用分级规划策略将规划过程分成初始航迹规划和精细航迹规划两部分。在初始航迹规划中，通过设置中间航迹点并利用 A*算法得到多条初始可行航迹，然后为了避免 K 均值算法对初始聚类中心敏感的问题，提出采用层次聚类法对所得到的初始可行航迹进行聚类，得到初始参考航迹。在精细航迹规划中，设计了一种变宽度的航迹规划通道，并在通道内进行航迹规划以得到最终的多条航迹。仿真实验证明了算法的可行性。
CA Based Path Planning Method for Mobile Robots Enhanced by ant Colony Inspired Mechanis
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Adel Akbarimajd
2011-05-01
Full Text Available In path planning of mobile robots dealing with concave obstacles is a major challenge. More specifically in real-time planning where there is no complete representation of the environment, this challenge would be much more problematic. In such cases local minimums and high computations cost are the most important problems. In this paper, in order to reduce computational cost, cellular automata as a distributed computational method with parallel processing properties is employed as tool for path planning purposes. The environment of the robot is modeled as a two dimensional cellular automata with four states. Evolutionary rules of the automata are proposed to perform the planning task. The proposed method is appropriate for single robot systems as well as multi robot systems. The proposed method is afterwards extended to be employed for concave obstacles using a ant colony inspired technique. The most superior advantage of the proposed method is its capability of real-time path planning of mobile robots with no need to prior representation of the environment.
Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators
Institute of Scientific and Technical Information of China (English)
高胜; 赵杰; 蔡鹤皋
2003-01-01
Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASA GA and the strategy of decoupled planning.
Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing
Low, Kian Hsiang; Khosla, Pradeep
2011-01-01
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing information-theoretic exploration strategies for learning GP-based environmental field maps adopt the non-Markovian problem structure and consequently scale poorly with the length of history of observations. Hence, it becomes computationally impractical to use these strategies for in situ, real-time active sampling. To ease this computational burden, this paper presents a Markov-based approach to efficient information-theoretic path planning for active sampling of GP-based fields. We analyze the time complexity of solving the Markov-based path planning problem, and demonstrate analytically that it scales better than that of deriving the non-Markovian strategies with increasing length of planning horizon. For a class of exploration tasks called the transect sampling task, we provide theoretical guarantees on the active sampling performance of...
Path planning for UAV based on quantum-behaved particle swarm optimization
Fu, Yangguang; Ding, Mingyue; Zhou, Chengping; Cai, Chao; Sun, Yangguang
2009-10-01
Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach.
Multi-Robot Path-Planning Problem for a Heavy Traffic Control Application: A Survey
Directory of Open Access Journals (Sweden)
Ebtehal Turki Saho Alotaibi
2016-06-01
Full Text Available This survey looked at the methods used to solve multi-autonomous vehicle path-planning for an application of heavy traffic control in cities. Formally, the problem consisted of a graph and a set of robots. Each robot has to reach its destination in the minimum time and number of movements, considering the obstacles and other robots’ paths, hence, the problem is NP-hard. The study found that decoupled centralised approaches are the most relevant approaches for an autonomous vehicle path-planning problem for three reasons: (1 a city is a large environment and coupled centralised approaches scale weakly, (2 the overhead of a coupled decentralised approach to achieve the global optimal will affect the time and memory of the other robots, which is not important in a city configuration and (3 the coupled approaches suppose that the number of robots is defined before they start to find the paths and resolve collisions, while in a city, any car can start at any time and hence, each car should work individually and resolve collisions as they arise. In addition, the study reviewed four decoupled centralised techniques to solve the problem: multi-robot path-planning rapidly exploring random tree (MRRRT, push and swap (PAS, push and rotate (PAR and the Bibox algorithm. The experiments showed that MRRRT is the best for exploring any search space and optimizing the solution. On the other hand, PAS, PAR and Bibox are better in terms of providing a complete solution for the problem and resolving collisions in significantly much less time, the analysis, however, shows that a wider class of solvable instances are excluded from PAS and PAR domain. In addition, Bibox solves a smaller class than the class solved by PAS and PAR in less time, in the worst case, and with a shorter path than PAS and PAR.
Real-Time Path Planning for Multi-DoF Manipulators in Dynamic Environment
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Lotfi Romdhane
2008-11-01
Full Text Available An efficient path planning algorithm, for multi degrees of freedom manipulator robots in dynamic environments, is presented in this paper. The proposed method is based on a local planner and a boundary following method for rapid solution finding. The local planner is replaced by the boundary following method whenever the robot gets stuck in a local minimum. This method was limited to 2-DoF mobile robots and in this work we showed how it can be applicable for a robot with n degrees of freedom in a dynamic environment. The path planning task is performed in the configuration space and we used a hyperplane in the n dimensional space to find the way out of the deadlock situation when it occurs. This method is, therefore, able to find a path, when it exists, no matter how cluttered is the environment, and it avoids deadlocking inherent to the use of the local method. Moreover, this method is fast, which makes it suitable for on-line path planning in dynamic environment. The algorithm has been implemented into a robotic CAD system for testing. Some examples are presented to demonstrate the ability of this algorithm to find a path no matter how complex is the environment. These examples involve a 5-DoF robot in a cluttered environment, then two 5-DoF robots, and finally three 5-DoF robots. In all cases, the proposed method was able to find a path to reach the goal and to avoid the dynamic obstacles.
Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa
2017-07-11
This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.
Path Planning Method for UUV Homing and Docking in Movement Disorders Environment
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Zheping Yan
2014-01-01
Full Text Available Path planning method for unmanned underwater vehicles (UUV homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO, inertia weight particle swarm optimization (LWPSO, EPSO, and time-varying acceleration coefficient (TVAC. It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path.
TP-Space RRT – Kinematic Path Planning of Non-Holonomic Any-Shape Vehicles
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Jose Luis Blanco
2015-05-01
Full Text Available The autonomous navigation of vehicles typically combines two kinds of methods: a path is first planned, and then the robot is driven by a local obstacle-avoidance controller. The present work, which focuses on path planning, proposes an extension to the well-known rapidly-exploring random tree (RRT algorithm to allow its integration with a trajectory parameter-space (TP-space as an efficient method to detect collision-free, kinematically-feasible paths for arbitrarily-shaped vehicles. In contrast to original RRT, this proposal generates navigation trees, with poses as nodes, whose edges are all kinematically-feasible paths, suitable to being accurately followed by vehicles driven by pure reactive algorithms. Initial experiments demonstrate the suitability of the method with an Ackermann-steering vehicle model whose severe kinematic constraints cannot be obviated. An important result that sets this work apart from previous research is the finding that employing several families of potential trajectories to expand the tree, which can be done efficiently under the TP-space formalism, improves the optimality of the planned trajectories. A reference C++ implementation has been released as open-source.
Directory of Open Access Journals (Sweden)
Wenyu Cai
2017-07-01
Full Text Available This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP problem and the Genetic Algorithm (GA is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB or Tour Length Balance (TLB constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X − Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.
Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment
Directory of Open Access Journals (Sweden)
Yong-feng Dong
2016-01-01
Full Text Available In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time.
A Heuristic and Dynamic Method for Task Scheduling and Path Planning%启发式动态任务调度与航路规划方法
Institute of Scientific and Technical Information of China (English)
沈淑梅; 姚臣
2012-01-01
A hierarchical structure of mission planning system was proposed for task scheduling and path planning. The multi-task priority and conflict resolution were implemented in the upper layer of the mission planning system, and path planning and real-time re-planning were implemented in the lower layer. The algorithms of heuristic and dynamic task scheduling and path planning were proposed, which can improve the situation adaptability and conflict resolution ability to various emergencies, and the capability to attack time-critical target, and thus can increase the autonomy level of UAV under dynamic and uncertain environment.%针对任务、资源、航路的调度与规划需要,建立了一种分层递阶的任务规划系统结构,上层主要解决任务优先级和冲突消解问题；下层主要解决满足各种要求的航路规划与实时重规划问题.提出了启发式动态任务调度与航路实时规划算法,可以有效提高对各种突发事件的态势自适应和冲突消解能力以及对时敏目标的打击能力,进而提高无人机在动态不确定环境下的自主性.
Ancient village fire escape path planning based on improved ant colony algorithm
Xia, Wei; Cao, Kang; Hu, QianChuan
2017-06-01
The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.
3D Environment Mapping Using the Kinect V2 and Path Planning Based on RRT Algorithms
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Wilbert G. Aguilar
2016-10-01
Full Text Available This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees variant (RRT*, for a safe and optimal navigation of robots in 3D spaces. Results on RGB-D segmentation and recognition, point cloud processing, and comparisons between different RRT* algorithms, are presented.
Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics
Directory of Open Access Journals (Sweden)
Wenfu Xu
2008-11-01
Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of freefloating robot. In order to avoid its effect, the direct kinematic equations are used for path planning in the paper. Here, the joint position, rate and acceleration are bounded. Firstly, the joint trajectories are parameterized by polynomial or sinusoidal functions. And the two parametric functions are compared in details. It is the first contribution of the paper that polynomial functions can be used when the joint angles are limited(In the similar work of other researchers, only sinusoidla functions could be used. Secondly, the joint functions are normalized and the system of equations about the parameters is established by integrating the differential kinematics equations. Normalization is another contribution of the paper. After normalization, the boundary of the parameters is determined beforehand, and the general criterion to assign the initial guess of the unknown parameters is supplied. The criterion is independent on the planning conditions such as the total time tf. Finally, the parametes are solved by the iterative Newtonian method. Modification of tf may not result in the recalculation of the parameters. Simulation results verify the path planning method.
Directory of Open Access Journals (Sweden)
Trevor Davies
2008-08-01
Full Text Available This paper presents the development and implementation a hybrid control architecture to direct a collective of three X80 mobile robots to multiple user-defined waypoints. The Genetic Algorithm Path Planner created an optimized, reduction in the time to complete the task, path plan for each robot in the collective such that each waypoint was visited once without colliding with a priori obstacles. The deliberative Genetic Algorithm Path Planner was then coupled with a reactive Potential Field Trajectory Planner and kinematic based controller to create a hybrid control architecture allowing the mobile robot to navigate between multiple user-defined waypoints, while avoiding a priori obstacles and obstacles detected using the robots' range sensors. The success of this hybrid control architecture was proven through simulation and experimentation using three of Dr. Robot's ™ wireless X80 mobile robots.
Curiac, Daniel-Ioan; Volosencu, Constantin
2014-10-01
The path-planning algorithm represents a crucial issue for every autonomous mobile robot. In normal circumstances a patrol robot will compute an optimal path to ensure its task accomplishment, but in adversarial conditions the problem is getting more complicated. Here, the robot’s trajectory needs to be altered into a misleading and unpredictable path to cope with potential opponents. Chaotic systems provide the needed framework for obtaining unpredictable motion in all of the three basic robot surveillance missions: area, points of interests and boundary monitoring. Proficient approaches have been provided for the first two surveillance tasks, but for boundary patrol missions no method has been reported yet. This paper addresses the mentioned research gap by proposing an efficient method, based on chaotic dynamic of the Hénon system, to ensure unpredictable boundary patrol on any shape of chosen closed contour.
Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua
2015-11-01
Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.
Robotic path planning for non-destructive testing of complex shaped surfaces
Mineo, Carmelo; Pierce, Stephen Gareth; Wright, Ben; Nicholson, Pascual Ian; Cooper, Ian
2015-03-01
The requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides significant motivation for the use of 6 axis robots for deployment of NDT probes in these inspections. A new system for robot deployed ultrasonic inspection of composite aerospace components is presented. The key novelty of the approach is through the accommodation of flexible robotic trajectory planning, coordinated with the NDT data acquisition. Using a flexible approach in MATLAB, the authors have developed a high level custom toolbox that utilizes external control of an industrial 6 axis manipulator to achieve complex path planning and provide synchronization of the employed ultrasonic phase array inspection system. The developed software maintains a high level approach to the robot programming, in order to ease the programming complexity for an NDT inspection operator. Crucially the approach provides a pathway for a conditional programming approach and the capability for multiple robot control (a significant limitation in many current off-line programming applications). Ultrasonic and experimental data has been collected for the validation of the inspection technique. The path trajectory generation for a large, curved carbon-fiber-reinforced polymer (CFRP) aerofoil component has been proven and is presented. The path error relative to a raster-scan tool-path, suitable for ultrasonic phased array inspection, has been measured to be within + 2mm over the 1.6 m2 area of the component surface.
Rapid, parallel path planning by propagating wavefronts of spiking neural activity
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Filip Jan Ponulak
2013-07-01
Full Text Available Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware.
A robust online path planning approach in cluttered environments for micro rotorcraft drones
Institute of Scientific and Technical Information of China (English)
Shupeng LAI; Kangli WANG; Hailong QIN; Jin Q CUI; Ben M CHEN
2016-01-01
We present in this paper a robust online path planning method, which allows a micro rotorcraft drone to fly safely in GPS-denied and obstacle-strewn environments with limited onboard computational power. The approach is based on an effi-ciently managed grid map and a closed-form solution to the two point boundary value problem (TPBVP). The grid map assists trajectory evaluation whereas the solution to the TPBVP generates smooth trajectories. Finally, a top-level trajectory switching algorithm is utilized to minimize the computational cost. Advantages of the proposed approach include its conservation of com-putational resource, robustness of trajectory generation and agility of reaction to unknown environment. The result has been realized on actual drones platforms and successfully demonstrated in real flight tests. The video of flight tests can be found at:http://uav.ece.nus.edu.sg/robust-online-path-planning-Lai2015.html.
Adaptive Gait Control for a Quadruped Robot on 3D Path Planning
Igarashi, Hiroshi; Kakikura, Masayoshi
A legged walking robot is able to not only move on irregular terrain but also change its posture. For example, the robot can pass under overhead obstacles by crouching. The purpose of our research is to realize efficient path planning with a quadruped robot. Therefore, the path planning is expected to extended in three dimensions because of the mobility. However, some issues of the quadruped robot, which are instability, workspace limitation, deadlock and slippage, complicate realizing such application. In order to improve these issues and reinforce the mobility, a new static gait pattern for a quadruped robot, called TFG: Trajectory Following Gait, is proposed. The TFG intends to obtain high controllability like a wheel robot. Additionally, the TFG allows to change it posture during the walk. In this paper, some experimental results show that the TFG improves the issues and it is available for efficient locomotion in three dimensional environment.
Minimum-time trajectory planning based on the shortest path for the wheeled mobile robot
Institute of Scientific and Technical Information of China (English)
LIN Feng-yun; LV Tian-sheng
2006-01-01
The time-optimal trajectory planning is proposed under kinematic and dynamic constraints for a 2-DOF wheeled robot. In order to make full use of the motor' s capacity, we calculate the maximum torque and the minimum torque by considering the maximum heat-converted power generated by the DC motor. The shortest path is planned by using the geometric method under kinematic constraints. Under the bound torques, the velocity limits and the maximum acceleration (deceleration) are obtained by combining with the dynamics. We utilize the phase-plane analysis technique to generate the time optimal trajectory based on the shortest path. At last, the computer simulations for our laboratory mobile robot were performed. The simulation results prove the proposed method is simple and effective for practical use.
Directory of Open Access Journals (Sweden)
Zhou Feng
2013-09-01
Full Text Available A based on Rapidly-exploring Random Tree(RRT and Particle Swarm Optimizer (PSO for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.
Non-smooth environment modeling and global path planning for mobile robots
Institute of Scientific and Technical Information of China (English)
邹小兵; 蔡自兴; 孙国荣
2003-01-01
An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.
IMMUNE GENETIC ALGORITHM FOR THE PATH PLANNING OF TIGHTLY COORDINATED TWO-ROBOT MANIPULATORS
Institute of Scientific and Technical Information of China (English)
Gao Sheng; Zhao Jie; Cai Hegao
2004-01-01
A novel algorithm, the immune genetic algorithm based on multi-agent, is proposed for the path planning of tightly coordinated two-robot manipulators, which constructs mainly immune operators accomplished by three steps: defining strategies and methods of multi-agent, calculating virtual forces acting on an agent, and constructing immune operators and performing immunization during the evolutionary process. It is illustrated to be able to restrain the degenerate phenomenon effectively and improve the searching ability with high converging speed.
Adaptive PSO using random inertia weight and its application in UAV path planning
Zhu, Hongguo; Zheng, Changwen; Hu, Xiaohui; Li, Xiang
2008-10-01
A novel particle swarm optimization algorithm, called APSO_RW is presented. Random inertia weight improves its global optimization performance and an adaptive reinitialize mechanism is used when the global best particle is detected to be trapped. The new algorithm is tested on a set of benchmark functions and experimental results show its efficiency. APSO_RW is later applied in UAV (Unmanned Aerial Vehicle) path planning.
Path planning algorithms for a multi-robot framework on an agricultural environment
DEFF Research Database (Denmark)
Hameed, Ibrahim
2016-01-01
the fertility of the soil. This is a significant threat to soil in Europe. Compacted soils require more than a decade of expensive treatment to recover its fertility. The problem can be solved by replacing heavy tractors with a number of smaller vehicles which can treat crop fields just as well and without...... Control Center and Intelligent Coverage Path Planning algorithms to enable team members to communicate and cooperate, and solve a range of agricultural tasks in a safe and efficient way....
Fuzzy logic path planning system for collision avoidance by an autonomous rover vehicle
Murphy, Michael G.
1993-01-01
The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.
Directory of Open Access Journals (Sweden)
Yueyue Deng
2013-01-01
Full Text Available Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. This paper presents a solution for the task allocation and path planning for multiple AUVs under marginal acoustic communication conditions: a location-aided task allocation framework (LAAF algorithm for multitarget task assignment and the grid-based multiobjective optimal programming (GMOOP mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Both the LAAF and GMOOP algorithms are well suited in poor acoustic network condition and dynamic environment. Our research is based on an existing mobile ad hoc network underwater acoustic simulator and blind flooding routing protocol. Simulation results demonstrate that the location-aided auction strategy performs significantly better than the well-accepted auction algorithm developed by Bertsekas in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path-planning technique provides an efficient method for executing multiobjective tasks by cooperative agents with limited communication capabilities. This is in contrast to existing multiobjective action selection methods that are limited to networks where constant, reliable communication is assumed to be available.
Energy Technology Data Exchange (ETDEWEB)
Fukuda, Toshio (Nagoya Univ. (Japan). Faculty of Engineering); Hosokai, Hidemi; Uemura, Masahiro
1990-01-01
This paper deals with inspection path planning for in-pipe inspection mobile robots which have the capability of moving through complicated pipeline networks. It is imperative that the robot systems have an inspection path planning system for such networks for their reasonable and rational operation, controlled by themselves or by the operators. The planning mainly requires two projects: the selection of the place to put the robot in or out, and the generation of the paths in the networks. This system provides the for complicated problems with plural inspection points using a basic strategy of systematically producing patterns and dividing partial problems of simple searches based on rules. (author).
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Wang Honglun
2015-02-01
Full Text Available This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle (UAV in complex terrain based on interfered fluid dynamical system (IFDS and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles’ overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm (GA is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles.
Institute of Scientific and Technical Information of China (English)
Wang Honglun; Lyu Wentao; Yao Peng; Liang Xiao; Liu Chang
2015-01-01
This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle (UAV) in complex terrain based on interfered fluid dynamical system (IFDS) and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles’ overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm (GA) is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles.
Song, Linze; Shi, Qiang
2015-11-21
Based on recent findings in the hierarchical equations of motion (HEOM) for correlated initial state [Y. Tanimura, J. Chem. Phys. 141, 044114 (2014)], we propose a new stochastic method to obtain the initial conditions for the real time HEOM propagation, which can be used further to calculate the equilibrium correlation functions and symmetrized correlation functions. The new method is derived through stochastic unraveling of the imaginary time influence functional, where a set of stochastic imaginary time HEOM are obtained. The validity of the new method is demonstrated using numerical examples including the spin-Boson model, and the Holstein model with undamped harmonic oscillator modes.
Planning Curvature-Constrained Paths to Multiple Goals Using Circle Sampling.
Lobaton, Edgar; Zhang, Jinghe; Patil, Sachin; Alterovitz, Ron
2011-01-01
We present a new sampling-based method for planning optimal, collision-free, curvature-constrained paths for nonholonomic robots to visit multiple goals in any order. Rather than sampling configurations as in standard sampling-based planners, we construct a roadmap by sampling circles of constant curvature and then generating feasible transitions between the sampled circles. We provide a closed-form formula for connecting the sampled circles in 2D and generalize the approach to 3D workspaces. We then formulate the multi-goal planning problem as finding a minimum directed Steiner tree over the roadmap. Since optimally solving the multi-goal planning problem requires exponential time, we propose greedy heuristics to efficiently compute a path that visits multiple goals. We apply the planner in the context of medical needle steering where the needle tip must reach multiple goals in soft tissue, a common requirement for clinical procedures such as biopsies, drug delivery, and brachytherapy cancer treatment. We demonstrate that our multi-goal planner significantly decreases tissue that must be cut when compared to sequential execution of single-goal plans.
A Virus-Evolutionary Genetic Algorithm-Based Fast Air Vehicle Path Planning%基于病毒遗传算法的快速航迹规划方法
Institute of Scientific and Technical Information of China (English)
俞琪; 刘新; 周成平; 蔡超
2011-01-01
To enhance the real time planning ability of existing system , a fast path planning method based on virus-evolutionary genetic algorithm is proposed, the proposed method is aimed at improving the global step of a path planning method based on hierarchical strategy. The hierarchical planning method is used to efficiently handle path constraints by dividing the whole planning process into two steps : global planing and local planning. Employing a hierarchical strategy, this method may reduce the computation complexity. However it is well known that problems of premature and weakness in local searching exist in the genetic algorithm used in glohal planning. To overcome problems, the theory of virus-evolution is introduced into the global planning step. By designing a problem-specific representation of virus solutions and its virus infection operators ,the convergence performance and search efficiency are improved. Simulation results show that given the same path constraints our method can fast generate a satisfactory path.%为了提高现有航迹规划系统的实时规划能力,对基于分层策略的航迹规划方法中全局规划部分进行改进,提出了基于病毒遗传算法的快速规划方法.分层策略的航迹规划包括全局规划和局部规划,由于对不同性质的约束条件分阶段进行处理,该方法降低了航迹规划的计算复杂度.但全局规划采用的标准遗传算法仍存在早熟和局部收敛慢的问题.针对这些缺陷,采用病毒遗传算法进行改进.结合航迹规划的领域知识,给出了病毒种群的编码方法并设计了特定的病毒感染算子,使航迹寻优效率得以提高.仿真实验表明,在相同约束条件下,该方法能更快生成满足战术要求的航迹.
Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters
Directory of Open Access Journals (Sweden)
Yu-Hsiang Lin
2011-07-01
Full Text Available This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS and the Flight Control System (FCS. The FPPS finds the shortest flight path by the A-Star (A* algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM.
An optimal path planning problem for heterogeneous multi-vehicle systems
Directory of Open Access Journals (Sweden)
Klaučo Martin
2016-06-01
Full Text Available A path planning problem for a heterogeneous vehicle is considered. Such a vehicle consists of two parts which have the ability to move individually, but one of them has a shorter range and is therefore required to keep in a close distance to the main vehicle. The objective is to devise an optimal path of minimal length under the condition that at least one part of the heterogeneous system visits all desired waypoints exactly once. Two versions of the problem are considered. One assumes that the order in which the waypoints are visited is known a priori. In such a case we show that the optimal path can be found by solving a mixed-integer second-order cone problem. The second version assumes that the order in which the waypoints are visited is not known a priori, but can be optimized so as to shorten the length of the path. Two approaches to solve this problem are presented and evaluated with respect to computational complexity.
Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig
2012-01-01
In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.
The Exact Euclidean Distance Transform: A New Algorithm for Universal Path Planning
Directory of Open Access Journals (Sweden)
Juan Carlos Elizondo-Leal
2013-06-01
Full Text Available The Path‐Planning problem is a basic issue in mobile robotics, in order to allow the robots to solve more complex tasks, for example, an exploration assignment in which the distance given by the planner is taken as a utility measure. Among the different proposed approaches, algorithms based on an exact cell decomposition of the environment are very popular. In this paper, we present a new algorithm for universal path planning in cell decomposition, using a raster scan method for computing the Exact Euclidean Distance Transform (EEDT for each cell in the map. Our algorithm computes, for every cell in the map, the point sequence to the goal. For each sequence, the sub‐goals are selected near to the vertices of the obstacles, reducing the total distance to the goal without post processing. At the end, we obtain a smooth path up to the goal without the need for post‐processing. The paths are computed by visibility verification among the cells, exploiting the processing performed in the neighbouring cells.
Directory of Open Access Journals (Sweden)
Yang Liu
2016-01-01
Full Text Available This paper proposes a potential odor intensity grid based optimization approach for unmanned aerial vehicle (UAV path planning with particle swarm optimization (PSO technique. Odor intensity is created to color the area in the searching space with highest probability where candidate particles may locate. A potential grid construction operator is designed for standard PSO based on different levels of odor intensity. The potential grid construction operator generates two potential location grids with highest odor intensity. Then the middle point will be seen as the final position in current particle dimension. The global optimum solution will be solved as the average. In addition, solution boundaries of searching space in each particle dimension are restricted based on properties of threats in the flying field to avoid prematurity. Objective function is redesigned by taking minimum direction angle to destination into account and a sampling method is introduced. A paired samples t-test is made and an index called straight line rate (SLR is used to evaluate the length of planned path. Experiments are made with other three heuristic evolutionary algorithms. The results demonstrate that the proposed method is capable of generating higher quality paths efficiently for UAV than any other tested optimization techniques.
Directory of Open Access Journals (Sweden)
Vahid Behravesh
2012-08-01
Full Text Available Presented article is studying the issue of path navigating for numerous robots. Our presented approach is based on both priority and the robust method for path finding in repetitive dynamic. Presented model can be generally implementable and useable: We do not assume any restriction regarding the quantity of levels of freedom for robots, and robots of diverse kinds can be applied at the same time. We proposed a random method and hill-climbing technique in the area based on precedence plans, which is used to determine a solution to a given trajectory planning problem and to make less the extent of total track. Our method plans trajectories for particular robots in the setting-time scope. Therefore, in order to specifying the interval of constant objects similar to other robots and the extent of the tracks which is traversed. For measuring the hazard for robots to conflict with each other it applied a method based on probability of the movements of robots. This algorithm applied to real robots with successful results. The proposed method performed and judged on both real robots and in simulation. We performed sequence of100tests with 8 robots for comparing with coordination method and current performances are effective. However, maximizing the performance is still possible. These performances estimations performed on Windows operating system and 3GHz Intel Pentium IV with and compiles with GCC 3.4. We used our PCGA robot for all experiments. For a large environment of 19×15m2where we accomplished 40tests, our model is competent to plan high-quality paths in a severely short time (less than a second. Moreover, this article utilized lookup tables to keep expenses the formerly navigated robots made, increasing the number of robots don’t expand computation time.
Neural Network Model for Path-Planning of Robotic Rover Systems
Bassil, Youssef
2012-01-01
Today, robotics is an auspicious and fast-growing branch of technology that involves the manufacturing, design, and maintenance of robot machines that can operate in an autonomous fashion and can be used in a wide variety of applications including space exploration, weaponry, household, and transportation. More particularly, in space applications, a common type of robots has been of widespread use in the recent years. It is called planetary rover which is a robot vehicle that moves across the surface of a planet and conducts detailed geological studies pertaining to the properties of the landing cosmic environment. However, rovers are always impeded by obstacles along the traveling path which can destabilize the rover's body and prevent it from reaching its goal destination. This paper proposes an ANN model that allows rover systems to carry out autonomous path-planning to successfully navigate through challenging planetary terrains and follow their goal location while avoiding dangerous obstacles. The propos...
Time-optimal path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-01-06
An ensemble-based approach is developed to conduct time-optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where a set deterministic predictions is used to model and quantify uncertainty in the predictions. In the operational setting, much about dynamics, topography and forcing of the ocean environment is uncertain, and as a result a single path produced by a model simulation has limited utility. To overcome this limitation, we rely on a finitesize ensemble of deterministic forecasts to quantify the impact of variability in the dynamics. The uncertainty of flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each the resulting realizations of the uncertain current field, we predict the optimal path by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Pedestrian flow-path modeling to support tsunami-evacuation planning
Wood, N. J.; Jones, J. M.; Schmidtlein, M.
2015-12-01
Near-field tsunami hazards are credible threats to many coastal communities throughout the world. Along the U.S. Pacific Northwest coast, low-lying areas could be inundated by a series of catastrophic tsunamis potentially arriving in a matter of minutes following a Cascadia subduction zone (CSZ) earthquake. We developed a geospatial-modeling method for characterizing pedestrian-evacuation flow paths and evacuation basins to support evacuation and relief planning efforts for coastal communities in this region. We demonstrate this approach using the coastal communities of Aberdeen, Hoquiam, and Cosmopolis in southwestern Grays Harbor County, Washington (USA), where previous research suggests approximately 20,500 people (99% of the residents in tsunami-hazard zones) will likely have enough time to evacuate before tsunami-wave arrival. Geospatial, anisotropic, path distance models were developed to map the most efficient pedestrian paths to higher ground from locations within the tsunami-hazard zone. This information was then used to identify evacuation basins, outlining neighborhoods sharing a common evacuation pathway to safety. We then estimated the number of people traveling along designated evacuation pathways and arriving at pre-determined safe assembly areas, helping determine shelter demand and relief support (e.g., for elderly individuals or tourists). Finally, we assessed which paths may become inaccessible due to earthquake-induced ground failures, a factor which may impact an individual's success in reaching safe ground. The presentation will include a discussion of the implications of our analysis for developing more comprehensive coastal community tsunami-evacuation planning strategies worldwide.
Uncalibrated Path Planning in the Image Space for the Fixed Camera Configuration
Institute of Scientific and Technical Information of China (English)
LIANG Xin-Wu; HUANG Xin-Han; WANG Min
2013-01-01
Image-based visual servoing can be used to efficiently control the motion of robot manipulators.When the initial and the desired configurations are distant,however,as pointed out by many researchers,such a control approach can suffer from the convergence and stability problems due to its local properties.By specifying adequate image feature trajectories to be followed in the image,we can take advantage of the local convergence and stability of image-based visual servoing to avoid these problems.Hence,path planning in the image space has been an active research topic in robotics in recent years.However,almost all of the related results are established for the case of camera-in-hand configuration.In this paper,we propose an uncalibrated visual path planning algorithm for the case of fixed-camera configuration.This algorithm computes the trajectories of image features directly in the projective space such that they are compatible with rigid body motion.By decomposing the projective representations of the rotation and the translation into their respective canonical forms,we can easily interpolate their paths in the projective space.Then,the trajectories of image features in the image plane can be generated via projective paths.In this way,the knowledge of feature point structures and camera intrinsic parameters are not required.To validate the feasibility and performance of the proposed algorithm,simulation results based on the puma560 robot manipulator are given in this paper.
zePPeLIN: Distributed Path Planning Using an Overhead Camera Network
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Andreagiovanni Reina
2014-08-01
Full Text Available We introduce zePPeLIN, a distributed system designed to address the challenges of path planning in large, cluttered, dynamic environments. The objective is to define a sequence of instructions to precisely move a ground object (e.g., a mobile robot from an initial to a final configuration in an environment. zePPeLIN is based on a set of wirelessly networked overhead cameras. While each camera only covers a limited environment portion, the camera set fully covers the environment through the union of its fields of view. Path planning is performed in a fully distributed and cooperative way, based on potential diffusion over local Voronoi skeletons and local message exchanging. Additionally, the control of the moving object is fully distributed: it receives movement instructions from each camera when it enters that camera’s field of view. The overall task is made particularly challenging by intrinsic errors in the overlap in cameras’ fields of view. We study the performance of the system as a function of these errors, as well as its scalability for the size and density of the camera network. We also propose a few heuristics to improve performance and computational and communication efficiency. The reported results include both extensive simulation experiments and validation using a real camera network planning for a two-robot system.
Dollé, Laurent; Sheynikhovich, Denis; Girard, Benoît; Chavarriaga, Ricardo; Guillot, Agnès
2010-10-01
In this article, we describe a new computational model of switching between path-planning and cue-guided navigation strategies. It is based on three main assumptions: (i) the strategies are mediated by separate memory systems that learn independently and in parallel; (ii) the learning algorithms are different in the two memory systems-the cue-guided strategy uses a temporal-difference (TD) learning rule to approach a visible goal, whereas the path-planning strategy relies on a place-cell-based graph-search algorithm to learn the location of a hidden goal; (iii) a strategy selection mechanism uses TD-learning rule to choose the most successful strategy based on past experience. We propose a novel criterion for strategy selection based on the directions of goal-oriented movements suggested by the different strategies. We show that the selection criterion based on this "common currency" is capable of choosing the best among TD-learning and planning strategies and can be used to solve navigational tasks in continuous state and action spaces. The model has been successfully applied to reproduce rat behavior in two water-maze tasks in which the two strategies were shown to interact. The model was used to analyze competitive and cooperative interactions between different strategies during these tasks as well as relative influence of different types of sensory cues.
Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan
This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.
Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach
2014-01-01
approximation of chance-constrained stochastic predic- tive control. IEEE Transactions on Robotics . 2010;26(3):502–517. [7] Chakravorty S, Kumar S... Transactions on Robotics and Automation. 2007;23(2):331–341. [3] Rhoads B, Mezić I, Poje A. Minimum Time feedback control of autonomous underwater vehicles...2005. p. 194–198. [2] Pêtrès C, Pailhas Y, Patrón P, Petillot Y, Evans J, Lane D. Path Planning for autonomous underwater vehicles. IEEE
Tool-path planning for free-form surface high-speed high-resolution machining using torus cutter
Institute of Scientific and Technical Information of China (English)
WANG Yu-han; LI Ru-qiong; WU Zu-yu; CHEN Zhao-neng
2006-01-01
In CNC machining, two essential components decide the accuracy and machining time for a sculptured surface: one is the step-size interval, the other is the tool-path interval. Due to the limitation of the conventional method for calculating the tool-path interval, it cannot satisfy the machining requirement for highspeed and high-resolution machining. Accordingly, for high-speed and high-resolution machining, the current study proposes a new tool-path interval algorithm, plus a variable step-size algorithm for NURBS. Furthermore,a new type cutter, which can improve the cutting efficiency, is investigated in the paper. The transversal equation of the torus cutter onto the flat plan is given in this paper. The tool-path interval is calculated with the transversal equation and the proposed algorithm. The illustrated example shows that the redundant tool paths can be reduced because an accurate tool-path interval could be calculated.
基于路径预测的机器人足球路径规划%Robot soccer path planning based on path prediction
Institute of Scientific and Technical Information of China (English)
刘付民
2012-01-01
针对常用的机器人路径规划算法过于复杂并且在每个运动周期都计算路径的问题,提出了一种结合路径预测的路径最优算法.充分利用预测结果减少每周期的路径规划时间；用微量调整动态控制机器人左右轮速度,并充分利用折线路径的短距离优势,为避障机器人创建一条最短路径；以基于周期性预测在同个时间轴上的相交作为碰撞信号,来减少每个周期的重复性计算时间.实验结果表明,该方法能大大提高机器人路径规划的速度,降低不同周期上路径规划结果不一致导致的运动震荡.%The commonly used intelligent methods are artificial potential field method, visual vertex graph method and genetic method. However, these methods are more complex and need calculation for each movement cycle path in the robot. An optimal path algorithm that combines the path planning is presented, which takes full use of the path planning to reduce the cycle time and increase the stability of the robot movement It is able to create the shortest path for the obstacle-avoidance robot with micro-adjustment to control the speed of two wheels dynamically and make fully use of the advantage of the short distance of the broken line. Based on periodic forecast, the intersection on a timeline as a collision signal can reduce time-computing repeatability of each cycle, thus, the speed of the robot path planning is enhanced greatly and the sports concussion resulted by different path plan-ning results on different cycles is reduced.
Time-optimal path planning in dynamic flows using level set equations: theory and schemes
Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.
2014-10-01
We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.
Optimization of beamforming and path planning for UAV-assisted wireless relay networks
Directory of Open Access Journals (Sweden)
Ouyang Jian
2014-04-01
Full Text Available Recently, unmanned aerial vehicles (UAVs acting as relay platforms have attracted considerable attention due to the advantages of extending coverage and improving connectivity for long-range communications. Specifically, in the scenario where the access point (AP is mobile, a UAV needs to find an efficient path to guarantee the connectivity of the relay link. Motivated by this fact, this paper proposes an optimal design for beamforming (BF and UAV path planning. First of all, we study a dual-hop amplify-and-forward (AF wireless relay network, in which a UAV is used as relay between a mobile AP and a fixed base station (BS. In the network, both of the AP and the BS are equipped with multiple antennas, whereas the UAV has a single antenna. Then, we obtain the output signal-to-noise ratio (SNR of the dual-hop relay network. Based on the criterion of maximizing the output SNR, we develop an optimal design to obtain the solution of the optimal BF weight vector and the UAV heading angle. Next, we derive the closed-form outage probability (OP expression to investigate the performance of the dual-hop relay network conveniently. Finally, computer simulations show that the proposed approach can obtain nearly optimal flying path and OP performance, indicating the effectiveness of the proposed algorithm. Furthermore, we find that increasing the antenna number at the BS or the maximal heading angle can significantly improve the performance of the considered relay network.
APF-guided adaptive immune network algorithm for robot path planning
Institute of Scientific and Technical Information of China (English)
Mingxin YUAN; Sunan WANG; Canyang WU; Kunpeng LI
2009-01-01
Inspired by the mechanism of Jerne's idiotypic network hypothesis, a new adaptive immune network algorithm (AINA) is presented through the stimulation and suppression between the antigen and antibody by taking the environment and robot behavior as antigen and antibody respectively. A guiding weight is defined based on the artificial potential field (APF) method, and the guiding weight is combined with antibody vitality to construct a new antibody selection operator, which improves the searching efficiency. In addition, an updating operator of antibody vi-tality is provided based on the Baldwin effect, which results in a positive feedback mechanism of search and accelerates the convergence of the immune network. The simulation and experimental results show that the proposed algorithm is characterized by high searching speed, good convergence performance and strong planning ability, which solves the path planning well in complicated environments.
Virtual Velocity Vector-based Offline Collision-free Path Planning of Industrial Robotic Manipulator
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Fan Ouyang
2015-09-01
Full Text Available Currently, industrial robotic manipulators are applied in many manufacturing applications. In most cases, an industrial environment is a cluttered and complex one where moving obstacles may exist and hinder the movement of robotic manipulators. Therefore, a robotic manipulator not only has to avoid moving obstacles, but also needs to fulfill the manufacturing requirements of smooth movement in fixed tact time. Thus, this paper proposes a virtual velocity vector-based algorithm of offline collision-free path planning for manipulator arms in a controlled industrial environment. The minimum distance between a manipulator and a moving obstacle can be maintained at an expected value by utilizing our proposed algorithm with established offline collision-free path-planning and trajectory generating systems. Furthermore, both joint space velocity and Cartesian space velocity of generated time-efficient trajectory are continuous and smooth. In addition, the vector of detour velocity in a 3D environment is determined and depicted. Simulation results indicate that detour velocity can shorten the total task time as well as escaping the local minimal effectively. In summary, our approach can fulfill both safety requirements of collision avoidance of moving obstacles and manufacturing requirements of smooth movement within fixed tact time in an industrial environment.
Stereo camera-based intelligent UGV system for path planning and navigation
Lee, Jung-Suk; Ko, Jung-Hwan; Chungb, Dal-Do
2006-08-01
In this paper, a new real-time and intelligent mobile robot system for path planning and navigation using stereo camera embedded on the pan/tilt system is proposed. In the proposed system, face area of a moving person is detected from a sequence of the stereo image pairs by using the YCbCr color model and using the disparity map obtained from the left and right images captured by the pan/tilt-controlled stereo camera system and depth information can be detected. And then, the distance between the mobile robot system and the face of the moving person can be calculated from the detected depth information. Accordingly, based-on the analysis of these data, three-dimensional objects can be detected. Finally, by using these detected data, 2-D spatial map for a visually guided robot that can plan paths, navigate surrounding objects and explore an indoor environment is constructed. From some experiments on target tracking with 480 frames of the sequential stereo images, it is analyzed that error ratio between the calculated and measured values of the relative position is found to be very low value of 1.4 % on average. Also, the proposed target tracking system has achieved a high speed of 0.04 sec/frame for target detection and 0.06 sec/frame for target tracking.
Energy Technology Data Exchange (ETDEWEB)
Lin, C.C.; Huang, S.J. [National Cheng Kung Univ., Tainan, Taiwan (China). Dept. of Electrical Engineering
2007-07-01
This paper proposed an algorithm to improve the power transmission network in Taiwan which has experienced increased competition since the addition of competitive local exchange carriers (CLEC) into the telecommunication market. Recently, the CLECs requested to rent pipelines from the original incumbent local exchange carriers (ILECs) and from the Taiwan Power Company. The Taiwan Power Company not only builds transmission lines, but also telecommunication networks using different kinds of fiber optic cables, including Optical Power Ground Wire (OPGW), All-Dielectric Self-Supporting (ADSS), and Wrapped types (WOC). This paper also discussed the integration of pipeline rent-out work with AM/FM/geographic information system software. The Java-based software determines a shortest path-planning method for the piping layout to help improve the pipeline system and the construction of an electricity network. The method is expected to increase the use of existing pipelines by improving the efficiency of network planning and maintenance. The method also reduces the potential for design faults and is easy to apply in the field due to the clear criteria. This paper described the proposed system architecture in detail and presented test results. It was shown that the use of a shortest path for the piping layout can reduce the distance between manholes in the huge network. According to test results, the proposed method is considered to be feasible. 11 refs., 2 tabs., 10 figs.
无人机航路规划算法研究%Path Planning Algorithm for UAV
Institute of Scientific and Technical Information of China (English)
叶文; 廉华耕; 漆云海; 陈海生; 赵方义
2011-01-01
It was proposed to use cellular ant algorithm in path planning of Unmanned Aerial Vehicle (UAV). A series of improvements were made in cellular ant algorithm on the basis of the basic ant colony algorithm. Then the improved ant colony algorithm was used together with evolutionary rule of cellular in cellular space. The simulation results showed that the cellular ant algorithm could help the solutions to escape from their local optimum and could find a better path at higher convergence speed and with a higher precision. Therefore, the cellular ant algorithm is an effective method for such kind of multi-objective optimization problems with multiple constraints as UAV path planning under complex environment.%针对无人机航路规划问题,研究了一种基于元胞蚂蚁算法的无人机航路规划方法.元胞蚂蚁算法对基本蚁群算法进行了系列改进,并将元胞邻居演化和改进后的蚂蚁寻优相结合,有效地克服了基本蚁群算法的收敛速度慢、易于过早陷入局部最优的缺点,提高了算法的运算精度,从而为解决复杂战场环境下无人机航路规划这一多约束多目标优化问题提供了一条可行的途径.
Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.
Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando
2017-08-15
This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.
Directory of Open Access Journals (Sweden)
Lavrenov Roman
2017-01-01
Full Text Available Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment.
Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields
Wolf, Michael; Blackmore, James C.; Kuwata, Yoshiaki
2011-01-01
Lighter-than-air vehicles such as hot-air balloons have been proposed for exploring Saturn s moon Titan, as well as other bodies with significant atmospheres. For these vehicles to navigate effectively, it is critical to incorporate the effects of surrounding wind fields, especially as these winds will likely be strong relative to the control authority of the vehicle. Predictive models of these wind fields are available, and previous research has considered problems of planning paths subject to these predicted forces. However, such previous work has considered the wind fields as known a priori, whereas in practical applications, the actual wind vector field is not known exactly and may deviate significantly from the wind velocities estimated by the model. A probabilistic 3D path-planning algorithm was developed for balloons to use uncertain wind models to generate time-efficient paths. The nominal goal of the algorithm is to determine what altitude and what horizontal actuation, if any is available on the vehicle, to use to reach a particular goal location in the least expected time, utilizing advantageous winds. The solution also enables one to quickly evaluate the expected time-to-goal from any other location and to avoid regions of large uncertainty. This method is designed for balloons in wind fields but may be generalized for any buoyant vehicle operating in a vector field. To prepare the planning problem, the uncertainty in the wind field is modeled. Then, the problem of reaching a particular goal location is formulated as a Markov decision process (MDP) using a discretized space approach. Solving the MDP provides a policy of what actuation option (how much buoyancy change and, if applicable, horizontal actuation) should be selected at any given location to minimize the expected time-to-goal. The results provide expected time-to-goal values from any given location on the globe in addition to the action policy. This stochastic approach can also provide
Robot path planning in globally unknown environments based on rolling windows
Institute of Scientific and Technical Information of China (English)
ZHANG; Chungang; (
2001-01-01
［1］Schwartz, J. T., Sharir, M., On the “Piano Movers” problem: I. The case of a two-dimensional rigid polygonal body moving amidst polygonal barriers, Comm. Pure Appl. Math., 1983, 36: 345-398.［2］Lozano-Perez, T., Spatial planning: a configuration space approach, IEEE Trans. on Computers, 1983, 32(2): 108-120.［3］Crowley, J. L., Navigation for an intelligent mobile robot, IEEE Trans. on Robotics and Automation, 1985, 1(1): 31-41.［4］Brooks, R. A., Solving the find-path problem by good representation of free space, IEEE Trans. on Systems, Man and Cybernetics, 1983, 13(3): 190-197.［5］Takahashi, O., Schilling, R. J., Motion planning in a plane using generalized Voronoi diagrams, IEEE Trans. on Robotics and Automation, 1989, 5(2): 142-150.［6］Sankaranarayanan, A., Vidyasagar, M., A new path planning algorithm for moving a point object amidst unknown obstacles in a plane, in Proc. IEEE Conf. on Robotics and Automation, Nice, France, 1990, 1930-1936.［7］Borenstein, J., Koren, Y., Real time obstacle avoidance for fast mobile robots, IEEE Trans. on Systems, Man and Cybernetics, 1989, 19 (5): 1179-1187.［8］Tilove, R. B., Local obstacle avoidance for mobile robots based on the method of artificial potentials, in Proc. IEEE Conf. on Robotics and Automation, Nice, France, 1990, 566-571.［9］Lumelsky, V. J., Algorithm and complexity issues of robot motion in an uncertain environment, Journal of Complexity, 1987, 3: 146-182.［10］Iyengar, S. S., Jorgensen, C. C., Rao, S. V. N. et al., Learned navigation paths for a robot in unexplored terrain, in Proc. 2nd Conf. on Artificial Intelligence Applications and Engineering of Knowledge Based Systems, Miami Beach, Florida, 1985, 11-13.［11］Xi Yugeng, Predictive Control (in Chinese), Beijing: National Defense Industry Press, 1993.［12］Xi Yugeng, Predictive control of generalized control problem in dynamic uncertain environment, Control Theory and Applications (in Chinese), 2000, (1): 5.
Institute of Scientific and Technical Information of China (English)
ZHU; Xiangyang; DING; Han; XIONG; Youlun
2001-01-01
By using the pseudo minimum translational distance between convex objects, this paper presents two algorithms for robot path planning. First, an analytically tractable potential field is defined in the robot configuration space, and the concept of virtual obstacles is introduced and incorporated in the path planner to handle the local minima of the potential function. Second, based on the Lipschitz continuity and differentiability of the pseudo minimum translational distance, the flexible-trajectory approach is implemented. Simulation examples are given to show the effectiveness and efficiency of the path planners for both mobile robots and manipulators.
Planning of circle locus for multi-path/multi-layer welding robot with automatical error-correction
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
In this paper, a planning algorithm for multi-path/multi-layer circular locus is poposed. The algorithm is applied to weld the nipples on the header of boiler. Multi-path/multi-layer circular locus is planned according to three teaching points, which is lapped head-on-end to satisfy the requirement of technology. For the nipples wherever they are arranged radially or axially, even if there are errors caused by positioning and thermal deformations, providing that nipple's position and orientation relative to the teaching one can be measured, the multi-path/multi-layer circular locus can be planned without teaching any more. The algorithm has been applied in welding robot for manufacturing power station' boiler.
Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs
Directory of Open Access Journals (Sweden)
Daniel-Ioan Curiac
2015-11-01
Full Text Available During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter.
Directory of Open Access Journals (Sweden)
Syed Bilal Hussain Shah
2017-01-01
Full Text Available In Wireless Sensors Networks (WSNs, researcher’s main focus is on energy preservation and prolonging network lifetime. More energy resources are required in case of remote applications of WSNs, where some of the nodes die early that shorten the lifetime and decrease the stability of the network. It is mainly caused due to the non-optimal Cluster Heads (CHs selection based on single criterion and uneven distribution of energy. We propose a new clustering protocol for both homogeneous and heterogeneous environments, named as Optimized Path planning algorithm with Energy efficiency and Extending Network lifetime in WSN (OPEN. In the proposed protocol, timer value concept is used for CH selection based on multiple criteria. Simulation results prove that OPEN performs better than the existing protocols in terms of the network lifetime, throughput and stability. The results explicitly explain the cluster head selection of OPEN protocol and efficient solution of uneven energy distribution problem.
New Design of Mobile Robot Path Planning with Randomly Moving Obstacles
Directory of Open Access Journals (Sweden)
T. A. Salih
2013-05-01
Full Text Available The navigation of a mobile robot in an unknown environment has always been a very challenging task. In order to achieve safe and autonomous navigation, the mobile robot needs to sense the surrounding environment and plans a collision-free path. This paper focuses on designing and implementing a mobile robot which has the ability of navigating smoothly in an unknown environment, avoiding collisions, without having to stop in front of obstacles, detecting leakage of combustible gases and transmitting a message of detection results to the civil defense unit automatically through the Internet to the E-mail. This design uses the implementation of artificial neural network (ANN on a new technology represented by Field Programmable Analog Array (FPAA for controlling the motion of the robot. The robot with the proposed controller is tested and has completed the required objective successfully.
Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.
Lin, Lanny; Goodrich, Michael A
2014-12-01
During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.
National Research Council Canada - National Science Library
Rafael Piatti Oiticica de Paiva; Reinaldo Morabito
2013-01-01
... álcool.This work studies the hierarchical production planning of sugarcane milling companies and proposes a robust optimization model that considers several uncertainties in the problem parameters...
Employing Multiple Unmanned Aerial Vehicles for Co-Operative Path Planning
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Durdana Habib
2013-05-01
Full Text Available In this paper, we work to develop a path planning solution for a group of Unmanned Aerial Vehicles (UAVs using a Mixed Integer Linear Programming (MILP approach. Co‐operation among team members not only helps reduce mission time, it makes the execution more robust in dynamic environments. However, the problem becomes more challenging as it requires optimal resource allocation and is NP‐hard. Since UAVs may be lost or may suffer significant damage during the course of the mission, plans may need to be modified in real‐time as the mission proceeds. Therefore, multiple UAVs have a better chance of completing a mission in the face of failures. Such military operations can be treated as a variant of the Multiple Depot Vehicle Routing Problem (MDVRP. The proposed solution must be such that m UAVs start from multiple source locations to visit n targets and return to a set of destination locations such that (1 each target is visited exactly by one of the chosen UAVs (2 the total distance travelled by the group is minimized and (3 the number of targets that each UAV visits may not be less than K or greater than L.
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks
Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok
2016-05-01
This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.
3D digitizing path planning for part inspection with laser scanning
Mahmud, Mussa; Joannic, David; Fontaine, Jean-François
2007-01-01
If the first work relating to the automation of the digitalization of machine elements goes back to approximately 25 years, the process of digitalization of parts with non-contact sensor remains nevertheless complex. It is not completely solved today, in particular from a metrological point of view. In this article, we consider the determination of the trajectory planning within the framework of the control of dimensional and geometrical specifications. The sensor used in this application is a laser planner scanner with CCD camera oriented and moved by a CMM. For this purpose, we have focused on the methodology used to determine the best possible viewpoints which will satisfy the digitizing of a mechanical part. The developed method is based on the concept of visibility: for each facet of a part CAD Model (STL) a set of orientations, called real visibility chart, is calculated under condition of measurement uncertainties. By application of several optimisation criteria, the real visibility chart is reduced to create a viewpoint set from which the path planning is built.
Institute of Scientific and Technical Information of China (English)
Xiang Gao; Yangwang Fang; Youli Wu
2013-01-01
The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dual-aircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithm for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar’s radiation area. The problem is formulated as a Markov decision process (MDP) by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu-vering target.
Croteau, Jon Derek; Wolk, Holly Gordon
2010-01-01
There are many factors that can influence whether a highly talented staff member will build a career within an institution or use it as a stepping stone. This article defines and explores the notions of developing career paths and succession planning and why they are critical human capital investment strategies in retaining the highest performers…
Croteau, Jon Derek; Wolk, Holly Gordon
2010-01-01
There are many factors that can influence whether a highly talented staff member will build a career within an institution or use it as a stepping stone. This article defines and explores the notions of developing career paths and succession planning and why they are critical human capital investment strategies in retaining the highest performers…
Path planning in multi-scale ocean flows: Coordination and dynamic obstacles
Lolla, T.; Haley, P. J., Jr.; Lermusiaux, P. F. J.
2015-10-01
As the concurrent use of multiple autonomous vehicles in ocean missions grows, systematic control for their coordinated operation is becoming a necessity. Many ocean vehicles, especially those used in longer-range missions, possess limited operating speeds and are thus sensitive to ocean currents. Yet, the effect of currents on their trajectories is ignored by many coordination techniques. To address this issue, we first derive a rigorous level-set methodology for distance-based coordination of vehicles operating in minimum time within strong and dynamic ocean currents. The new methodology integrates ocean modeling, time-optimal level-sets and optimization schemes to predict the ocean currents, the short-term reachability sets, and the optimal headings for the desired coordination. Schemes are developed for dynamic formation control, where multiple vehicles achieve and maintain a given geometric pattern as they carry out their missions. To do so, a new score function that is suitable for regular polygon formations is obtained. Secondly, we obtain an efficient, non-intrusive technique for level-set-based time-optimal path planning in the presence of moving obstacles. The results are time-optimal path forecasts that rigorously avoid moving obstacles and sustain the desired coordination. They are exemplified and investigated for a variety of simulated ocean flows. A wind-driven double-gyre flow is used to study time-optimal dynamic formation control. Currents exiting an idealized strait or estuary are employed to explore dynamic obstacle avoidance. Finally, results are analyzed for the complex geometry and multi-scale ocean flows of the Philippine Archipelago.
Directory of Open Access Journals (Sweden)
Etsuji Okamoto
2011-09-01
Full Text Available Introduction: In April 2008, Japan launched a radical reform in regional health planning that emphasized the development of disease-oriented clinical care pathways. These 'inter-provider critical paths' have sought to ensure effective integration of various providers ranging among primary care practitioners, acute care hospitals, rehabilitation hospitals, long-term care facilities and home care. Description of policy practice: All 47 prefectures in Japan developed their Regional Health Plans pursuant to the guideline requiring that these should include at least four diseases: diabetes, acute myocardial infarction, cerebrovascular accident and cancer. To illustrate the care pathways developed, this paper describes the guideline referring to strokes and provides examples of the new Regional Health Plans as well as examples of disease-oriented inter-provider clinical paths. In particular, the paper examines the development of information sharing through electronic health records (EHR to enhance effective integration among providers is discussed.Discussion and conclusion: Japan's reform in 2008 is unique in that the concept of "disease-oriented regional inter-provider critical paths" was adopted as a national policy and all 47 prefectures developed their Regional Health Plans simultaneously. How much the new regional health planning policy has improved the quality and outcome of care remains to be seen and will be evaluated in 2013 after the five year planned period of implementation has concluded. Whilst electronic health records appear to be a useful tool in supporting care integration they do not guarantee success in the application of an inter-provider critical path.
Directory of Open Access Journals (Sweden)
Etsuji Okamoto
2011-09-01
Full Text Available Introduction: In April 2008, Japan launched a radical reform in regional health planning that emphasized the development of disease-oriented clinical care pathways. These 'inter-provider critical paths' have sought to ensure effective integration of various providers ranging among primary care practitioners, acute care hospitals, rehabilitation hospitals, long-term care facilities and home care. Description of policy practice: All 47 prefectures in Japan developed their Regional Health Plans pursuant to the guideline requiring that these should include at least four diseases: diabetes, acute myocardial infarction, cerebrovascular accident and cancer. To illustrate the care pathways developed, this paper describes the guideline referring to strokes and provides examples of the new Regional Health Plans as well as examples of disease-oriented inter-provider clinical paths. In particular, the paper examines the development of information sharing through electronic health records (EHR to enhance effective integration among providers is discussed. Discussion and conclusion: Japan's reform in 2008 is unique in that the concept of "disease-oriented regional inter-provider critical paths" was adopted as a national policy and all 47 prefectures developed their Regional Health Plans simultaneously. How much the new regional health planning policy has improved the quality and outcome of care remains to be seen and will be evaluated in 2013 after the five year planned period of implementation has concluded. Whilst electronic health records appear to be a useful tool in supporting care integration they do not guarantee success in the application of an inter-provider critical path.
Path planning of mobile robot by mixing experience with modified artificial potential field method
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Huasong Min
2015-12-01
Full Text Available In this article, a new method is proposed to help the mobile robot to avoid many kinds of collisions effectively, which combined past experience with modified artificial potential field method. In the process of the actual global obstacle avoidance, system will invoke case-based reasoning algorithm using its past experience to achieve obstacle avoidance when obstacles are recognized as known type; otherwise, it will invoke the modified artificial potential field method to solve the current problem and the new case will also be retained into the case base. In case-based reasoning, we innovatively consider that all the complex obstacles are retrieved by two kinds of basic build-in obstacle models (linear obstacle and angle-type obstacle. Our proposed experience mixing with modified artificial potential field method algorithm has been simulated in MATLAB and implemented on actual mobile robot platform successfully. The result shows that the proposed method is applicable to the dynamic real-time obstacle avoidance under unknown and unstructured environment and greatly improved the performances of robot path planning not only to reduce the time consumption but also to shorten the moving distance.
Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers
Trease, Brian; Arvidson, Raymond; Lindemann, Randel; Bennett, Keith; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine; Van Dyke, Lauren
2011-01-01
To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.
Path planning for first responders in the presence of moving obstacles
Directory of Open Access Journals (Sweden)
Zhiyong Wang
2015-06-01
Full Text Available Navigation services have gained much importance for all kinds of human activities ranging from tourist navigation to support of rescue teams in disaster management. However, despite the considerable amount of route guidance research that has been performed, many issues that are related to navigation for first responders still need to be addressed.During disasters, emergencies can result in different types of moving obstacles (e.g., fires, plumes, floods, which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently.During the past decades, more and more hazard simulations, which can modify the models with incorporation of dynamic data from the field, have been developed. These hazard simulations use methods such as data assimilation, stochastic estimation, and adaptive measurement techniques, and are able to generate more reliable results of hazards. This would allow the hazard simulation models to provide valuable information regarding the state of road networks affected by hazards, which supports path planning for first responders among the moving obstacles.The objective of this research is to develop an integrated navigation system for first responders in the presence of moving obstacles. Such system should be able to navigate one or more responders to one or multiple destinations avoiding the moving obstacles, using the predicted information of the moving obstacles generated from by hazard simulations. In this dissertation, the objective we have is expressed as the following research question:How do we safely and efficiently navigate one or more first responders to one or more destinations avoiding moving obstacles?To address the
Embedding Agile Practices within a Plan-Driven Hierarchical Project Life Cycle
Energy Technology Data Exchange (ETDEWEB)
Millard, W. David; Johnson, Daniel M.; Henderson, John M.; Lombardo, Nicholas J.; Bass, Robert B.; Smith, Jason E.
2014-07-28
Organizations use structured, plan-driven approaches to provide continuity, direction, and control to large, multi-year programs. Projects within these programs vary greatly in size, complexity, level of maturity, technical risk, and clarity of the development objectives. Organizations that perform exploratory research, evolutionary development, and other R&D activities can obtain the benefits of Agile practices without losing the benefits of their program’s overarching plan-driven structure. This paper describes application of Agile development methods on a large plan-driven sensor integration program. While the client employed plan-driven, requirements flow-down methodologies, tight project schedules and complex interfaces called for frequent end-to-end demonstrations to provide feedback during system development. The development process maintained the many benefits of plan-driven project execution with the rapid prototyping, integration, demonstration, and client feedback possible through Agile development methods. This paper also describes some of the tools and implementing mechanisms used to transition between and take advantage of each methodology, and presents lessons learned from the project management, system engineering, and developer’s perspectives.
A dynamical model of hierarchical selection and coordination in speech planning.
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Sam Tilsen
Full Text Available studies of the control of complex sequential movements have dissociated two aspects of movement planning: control over the sequential selection of movement plans, and control over the precise timing of movement execution. This distinction is particularly relevant in the production of speech: utterances contain sequentially ordered words and syllables, but articulatory movements are often executed in a non-sequential, overlapping manner with precisely coordinated relative timing. This study presents a hybrid dynamical model in which competitive activation controls selection of movement plans and coupled oscillatory systems govern coordination. The model departs from previous approaches by ascribing an important role to competitive selection of articulatory plans within a syllable. Numerical simulations show that the model reproduces a variety of speech production phenomena, such as effects of preparation and utterance composition on reaction time, and asymmetries in patterns of articulatory timing associated with onsets and codas. The model furthermore provides a unified understanding of a diverse group of phonetic and phonological phenomena which have not previously been related.
A dynamical model of hierarchical selection and coordination in speech planning.
Tilsen, Sam
2013-01-01
studies of the control of complex sequential movements have dissociated two aspects of movement planning: control over the sequential selection of movement plans, and control over the precise timing of movement execution. This distinction is particularly relevant in the production of speech: utterances contain sequentially ordered words and syllables, but articulatory movements are often executed in a non-sequential, overlapping manner with precisely coordinated relative timing. This study presents a hybrid dynamical model in which competitive activation controls selection of movement plans and coupled oscillatory systems govern coordination. The model departs from previous approaches by ascribing an important role to competitive selection of articulatory plans within a syllable. Numerical simulations show that the model reproduces a variety of speech production phenomena, such as effects of preparation and utterance composition on reaction time, and asymmetries in patterns of articulatory timing associated with onsets and codas. The model furthermore provides a unified understanding of a diverse group of phonetic and phonological phenomena which have not previously been related.
Directory of Open Access Journals (Sweden)
A. A. Heidari
2013-09-01
Full Text Available This paper addresses an innovative evolutionary computation approach to 3D path planning of autonomous UAVs in real environment. To solve this Np-hard problem, Newtonian imperialist competitive algorithm (NICA was developed and extended for path planning problem. This paper is related to optimal trajectory-designing before UAV missions. NICA planner provides 3D optimal paths for UAV planning in real topography of north Tehran environment. To simulate UAV path planning, a real DTM is used to algorithm. For real-world applications, final generated paths should be smooth and also physical flyable that made the path planning problems complex and more constrained. The planner progressively presents a smooth 3D path from first position to mission target location. The objective function contains distinctive measures of the problem. Our main goal is minimization of the total mission time. For evaluating of NICA efficiency, it is compared with other three well-known methods, i.e. ICA, GA, and PSO. Then path planning of UAV will done. Finally simulations proved the high capabilities of proposed methodology.
Heidari, A. A.; Afghan-Toloee, A.; Abbaspour, R. A.
2013-09-01
This paper addresses an innovative evolutionary computation approach to 3D path planning of autonomous UAVs in real environment. To solve this Np-hard problem, Newtonian imperialist competitive algorithm (NICA) was developed and extended for path planning problem. This paper is related to optimal trajectory-designing before UAV missions. NICA planner provides 3D optimal paths for UAV planning in real topography of north Tehran environment. To simulate UAV path planning, a real DTM is used to algorithm. For real-world applications, final generated paths should be smooth and also physical flyable that made the path planning problems complex and more constrained. The planner progressively presents a smooth 3D path from first position to mission target location. The objective function contains distinctive measures of the problem. Our main goal is minimization of the total mission time. For evaluating of NICA efficiency, it is compared with other three well-known methods, i.e. ICA, GA, and PSO. Then path planning of UAV will done. Finally simulations proved the high capabilities of proposed methodology.
Directory of Open Access Journals (Sweden)
Peiling Cui
2012-01-01
Full Text Available In view of the issue of rapid attitude maneuver control of agile satellite, this paper presents an attitude-tracking control algorithm with path planning based on the improved genetic algorithm, adaptive backstepping control as well as sliding mode control. The satellite applies double gimbal control moment gyro as actuator and is subjected to the external disturbance and uncertain inertia properties. Firstly, considering the comprehensive mathematical model of the agile satellite and the double gimbal control moment gyro, an improved genetic algorithm is proposed to solve the attitude path-planning problem. The goal is to find an energy optimal path which satisfies certain maneuverability under the constraints of the input saturation, actuator saturation, slew rate limit and singularity measurement limit. Then, the adaptive backstepping control and sliding mode control are adopted in the design of the attitude-tracking controller to track accurately the desired path comprised of the satellite attitude quaternion and velocity. Finally, simulation results indicate the robustness and good tracking performance of the derived controller as well as its ability to avert the singularity of double gimbal control moment gyro.
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Kun-Lin Wu
2016-01-01
Full Text Available In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.
Directory of Open Access Journals (Sweden)
Bai Li
2014-01-01
Full Text Available Unmanned combat aerial vehicles (UCAVs have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC algorithm improved by a balance-evolution strategy (BES is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Li, Bai; Gong, Li-gang; Yang, Wen-lun
2014-01-01
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Directory of Open Access Journals (Sweden)
Zhu Qi-dan
2013-04-01
Full Text Available The path planning and obstacle avoidance are the most important tasks for an autonomous mobile robot moving in an unknown environment. This paper presents a simple fuzzy logic controller which involves searching target and path planning with obstacle avoidance. In this contest, fuzzy logic controllers are constructed for target searching behavior and obstacle avoidance behavior based on the distance and angle between the robot and the target as inputs for the first behavior and the distance between the robot and the nearest obstacle for the second behavior; then a third fusion behavior is developed to combine the outputs of the two behaviors to compute the speed of the mobile robot in order to fulfill its task properly. Simulation results show that the proposed approach is efficient and can be applied to the mobile robots moving in unknown environments.
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Utkarsh Gautam
2015-05-01
Full Text Available Addressing the need for exploration of benthic zones utilising autonomous underwater vehicles, this paper presents a simulation for an optimised path planning from the source node to the destination node of the autonomous underwater vehicle SLOCUM Glider in near-bottom ocean environment. Near-bottom ocean current data from the Bedford Institute of Oceanography, Canada, have been used for this simulation. A cost function is formulated to describe the dynamics of the autonomous underwater vehicle in near-bottom ocean currents. This cost function is then optimised using various biologically-inspired algorithms such as genetic algorithm, Ant Colony optimisation algorithm and particle swarm optimisation algorithm. The simulation of path planning is also performed using Q-learning technique and the results are compared with the biologically-inspired algorithms. The results clearly show that the Q-learning algorithm is better in computational complexity than the biologically-inspired algorithms. The ease of simulating the environment is also more in the case of Q-learning techniques. Hence this paper presents an effective path planning technique, which has been tested for the SLOCUM glider and it may be extended for use in any standard autonomous underwater vehicle.Defence Science Journal, Vol. 65, No. 3, May 2015, pp.220-225, DOI: http://dx.doi.org/10.14429/dsj.65.7855
UAV Path Planning in Static Threats%静态威胁下的无人机航迹规划
Institute of Scientific and Technical Information of China (English)
刘洲洲; 潘鲁宁
2014-01-01
TheUAV(UninhabitedAirVehicle),duingtoitsadvantages,hasbeenwidelyusedin military and civilian fields.The essential of the UAV path planning is optimization for multi -objective and multi-constraint.This article introduces the crucial theory of the UAV path planning.The neural network algorithm is used to set models for the fired and non-fired threats in a static environment and the genetic algorithm is used for UAV path planning.The superiority of the algorithm is verified by simulation of different environment models.%无人机（Uninhabited Air Vehicle，UAV）由于其自身优点，已经在军事以及民用领域取得广泛使用。无人机的航迹规划本质可归结为一个多目标多约束条件的最优化问题。简单介绍无人机航迹规划的基本理论。运用神经网络算法针对静态环境下的火力威胁和非火力分别建模。运用遗传算法对无人机进行航迹规划。通过建立不同环境的模型仿真验证算法的优越性。
Path Planning Algorithm for Autonomous Vehicle%自主车辆路径规划算法研究
Institute of Scientific and Technical Information of China (English)
张艳溶; 马戎; 吕文杰
2011-01-01
ath planning of autonomous vehicles through a specific point of whether the actual situation of two, which proposed the respective solution: a certain point without the need for global planning, conditions of heuristic, compared with traditional A * algorithm, is equaled with euclidean distance, and add a weight which reducing the importance of heuristic relatively. In the other opposite planning , the hopfiled neural network is adopted in order to achieve the desired path planning. The simulations show that the improved algorithm enhances the performance of path planning, and proved the validity of the algorithm.%在自主车辆的路径规划是否经过特定点的两种实际情况下,提出了不同的解决方案.当车辆不需要经过特定点时,引入A*算法,较传统算法将启发函数改为欧几里得函数(Euclidean Distance),并引入一个权值以降低启发函数的权重.当车辆需要经过特定点时,应用Hopfield神经网络思想优化算法,以达到理想的路径规划.仿真实验表明,改进后的算法使得路径规划寻优得到明显提高,并验证了算法的有效性.
A new iso-scallop height tool path planning method in three-dimensional space
Institute of Scientific and Technical Information of China (English)
MIN Cheng
2012-01-01
This paper presents a new approach for designing the tool paths in the machining of sculptured surfaces for computer nu- merical controlled end milling. In the proposed method, the tool paths are determined so that the scallop height formed by two adja- cent machining paths is maintained constant across the machined surface. Unlike previous work on iso-scallop height milling, the present work considers the true 3D configuration of the milling procedure and can be used to generate better results, which is shown by examoles.
Optimal paths planning in dynamic transportation networks with random link travel times
Institute of Scientific and Technical Information of China (English)
孙世超; 段征宇; 杨东援
2014-01-01
A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent (STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers’ robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.
Buschbaum, Jan; Fremd, Rainer; Pohlemann, Tim; Kristen, Alexander
2017-08-01
Reduction is a crucial step in the surgical treatment of bone fractures. Finding an optimal path for restoring anatomical alignment is considered technically demanding because collisions as well as high forces caused by surrounding soft tissues can avoid desired reduction movements. The repetition of reduction movements leads to a trial-and-error process which causes a prolonged duration of surgery. By planning an appropriate reduction path-an optimal sequence of target-directed movements-these problems should be overcome. For this purpose, a computer-based method has been developed. Using the example of simple femoral shaft fractures, 3D models are generated out of CT images. A reposition algorithm aligns both fragments by reconstructing their broken edges. According to the criteria of a deduced planning strategy, a modified A*-algorithm searches collision-free route of minimal force from the dislocated into the computed target position. Muscular forces are considered using a musculoskeletal reduction model (OpenSim model), and bone collisions are detected by an appropriate method. Five femoral SYNBONE models were broken into different fracture classification types and were automatically reduced from ten randomly selected displaced positions. Highest mean translational and rotational error for achieving target alignment is [Formula: see text] and [Formula: see text]. Mean value and standard deviation of occurring forces are [Formula: see text] for M. tensor fasciae latae and [Formula: see text] for M. semitendinosus over all trials. These pathways are precise, collision-free, required forces are minimized, and thus regarded as optimal paths. A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.
一种快速3维无人机航迹规划方法%A Fast 3D Path Planning Method for UAVs
Institute of Scientific and Technical Information of China (English)
李时东; 艾青; 刘嵩
2012-01-01
无人机三维航迹规划由于规划约束众多，同时面临在巨大的搜索空间中寻优，往往规划速度慢，规划效率低．结合二维规划和高度规划实现三维规划是一种有效提升规划速度的解决方案，在利用Fast M arching Method（FMM）进行二维规划的基础上，采用SparseA—star（SAS）搜索算法进行高度规划，分阶段考虑航迹规划的各种环境约束和机动约束，从而压缩规划空间．实验表明，该方法航迹规划速度快，所得到的三维航迹具有良好的地形跟随能力和避障能力．%3D path planning is always slow and in efficient for there are many constraints to be considered while planning, meanwhile, the path is produced by searching in huge space. It is an efficient scheme to improve path planning speed by combining 2D path planning and height planning. We proposed a fast 3D path planning method＇ by planning 2D path with Fast Marching Method （FMM） and making height plan- ning using Sparse A-Star （SAS） searching method, where the environment and maneuverability constraints are processed by stages, thereby, the planning space is reduced. Experiments showed that the proposed method generates path quickly, and the obtained path follows terrain and avoids obstacle well.
基于区域分割的无人机路径规划%Region Segmentation of UAV Path Planning
Institute of Scientific and Technical Information of China (English)
刘山; 曹盛文; 刘轩
2012-01-01
研究无人机路径规划优化问题,针对在城市环境下执行飞行任务前,需要根据所经城市内已知的建筑物信息以及飞机本身性能的限制计算出飞行轨迹,并根据规划出的路径完成飞行任务.在给定起始点和目标点上,提出了一种城市建筑物遮挡模型的无人机路径规划方法.主要包含两方面的内容:一是利用圆柱虚拟城市建筑物环境使建筑物对无人机的遮挡面积可计算；二是在计算出无人机飞行的水平平面上(x,y)点遮挡值的基础上,给出了无人机搜索区域等分的沿对角线折线走法的优化路径规划,得到一条遮挡面积最小的路径并进行仿真.仿真结果表明,规划方法能够快速有效地完成规划任务,获得满意的航迹,为无人机优化路径提供了依据.%The path of unmanned aerial vehicles should be calculated according to the building known by the city itself as well as flight capability of itself before executing mission and accomplish the mission by tracking the path. This paper represented a method of path planning of UAV based on Block model of urban buildings at the given starting point and destination point. The proposed algorithm mainly contains two parts, first the algorithm simulated the buildings in urban environment with cylinders, and second, after calculating the curved surface of UAV's flight plane, this algorithm proposed an optimal path planning method of UAV. The path is a polygonal line along the equant diagonal line on the searching area of UAV, getting the smallest shading area of this path and simulated. The experiment results demonstrate that this method can complete planning mission efficiently, obtain a desirable route, and have important practical significance.
Calibration of neural networks using genetic algorithms, with application to optimal path planning
Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel
1987-01-01
Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.
Cooperative Path Planning for Multiple UAVs%多无人机协同航迹规划技术研究
Institute of Scientific and Technical Information of China (English)
程晓明; 曹东; 李春涛
2014-01-01
Cooperative path planning is an important part of cooperative control for multiple unmanned aerial vehicles ( UAVs) .To get optimal flight path which can satisfy constraints such as security perform-ance ,cooperative performance and mission requests ,cooperative path planning is important for enhancing system efficiency of UAVs.Problem description and solution frameworks are introduced respectively ,and constraints and path coordination approaches are summarized .Several control methods commonly used in formation of multiple UAVs are explained particularly .Base on the analysis ,possible research directions in the future time are put forward .%多无人机协同航迹规划是多无人机协同控制的重要组成部分。多无人机协同航迹规划能得到满足安全性、协同性和任务要求的较优航迹，这对提高无人机系统性能有重要的意义。介绍了多无人机协同航迹规划的问题描述和求解结构，总结了在协同规划问题中的约束条件和航迹协调方法，着重阐述了几种在多无人机编队中常用的控制方法。在此基础上，对未来可能的研究方向进行了展望。
Sakieh, Yousef; Salmanmahiny, Abdolrassoul; Mirkarimi, Seyed Hamed
2017-02-01
This study attempts to develop a non-path-dependent model for environmental risk management and polycentric urban land-use planning in Gorgan Township area, Iran. Applying three suitability layers of environmental risk (soil erosion, flood risk, fire risk, and land susceptibility), urbanization potential, and integrated surface (environmental risk plus urbanization potential layers), a non-path-dependent Cellular Automata-Markov Chain (CA-MC) model was configured to execute three scenarios of polycentric urban growth allocation. Specifically, the modeling approach improved the traditional functionality of the CA-MC model from a prediction algorithm into an innovative land allocation tool. Besides, due to its flexibility, the non-path-dependent model was able to explicitly include different characteristics of the landscape structure ranging from physical land attributes to landscape functions and processes (natural hazards). Accordingly, three polycentric urban growth allocation efforts were undertaken and compared in terms of connectivity and compactness of the resultant patterns and consumption of other land resources. Based on results, the polycentric allocation procedure based on integrated suitability layer produced a more manageable pattern of urban landscape, while the growth option based on environmental risk layer was more successful for protecting farmlands against excessive urbanization. This study suggests that polycentric urban land-use planning under the strategy of rural land development programs is an available option for designing an urban landscape with lower exposure to natural hazards and more economic benefits to rural residents. Finally, the non-path-dependent modeling is a recommended approach, when highly flexible and interactive decision-support systems as well as trend-breaking scenarios are desired.
Calculation on the pitch angle of rocker of a rocker lunar rover on uneven terrain and path planning
Institute of Scientific and Technical Information of China (English)
DENG Zong-quan; HOU Xu-yan; GAO Hai-bo; HU Ming
2008-01-01
Forthe concertedmotion of rockerlunar rover,the pitch angle of rocker of a rocker lunar rover in uneven terrain must be calculated.According to the character of passive shape-shifting adaptive suspension of rocker lunar rover,the model of rocker lunar rover and the model of terrain were both simplified.The pitch angle of rocker was calculated using forward solving,reverse solving and the method of offsetting the curve of terrain respectively.Because of the banishment of the nonlinearity of equation sets of calculation by reverse solving,the calculation of the pitch angle based on reverse solving was programmed by means of MATLAB.Simulations were carried out by means of ADAMS.The result verified the validity of the calculation based on reverse solving.It provides the theoretical foundation for motion planning and path planning of rocker lunar rover.As applications of the calculation of pitch angle of rocker,the multi-attribute decision making of path based on the concerted motion planning and the predictive control on lunar rover based on the Markov prediction model were introduced.
RSMDP-based Robust Q-learning for Optimal Path Planning in a Dynamic Environment
Directory of Open Access Journals (Sweden)
Yunfei Zhang
2014-07-01
Full Text Available This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP is formed to present the dynamic environment; second a probabilistic roadmap (PRM is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative. The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.
Path Planning, Dynamic Trajectory Generation and Control Analysis for Industrial Manipulators
2011-01-01
Many unsolved problems exists in the field of robot control.This text investigates state of the art methods for path finding, trajectory generation and control in order to identify their properties, which problems they are applicable to, and their weaknesses.This is done by applying them to problems with actual real-world relevance.
Optimal Path Planning for Agricultural Machinery%田作业机械路径优化方法
Institute of Scientific and Technical Information of China (English)
孟志军; 刘卉; 王华; 付卫强
2012-01-01
提出了一种面向农田作业机械的地块全区域覆盖路径优化方法.基于农田地块几何形状、作业机具参数、地头转弯模式等先验信息,将田间作业划分为不同区域,根据选择不同的路径优化目标:转弯数最少、作业消耗最小、总作业路径最短或有效作业路径比最大,计算出最优作业方向,生成最优作业路径.基于地块全区域覆盖路径优化算法,设计开发了农田作业机械的路径规划软件,并选取了4块典型的凸四边形农田地块进行作业路径规划测试.测试结果表明,最优作业方向上的路径优化目标量比其他作业方向上有显著减少;对于上述4个地块,按照不同优化目标计算所得的最优作业方向均与地块某个边的方向角相同,对于长宽比较大的地块,最长边方向通常为最优作业方向.%A kind of optimal path planning method for complete field coverage in agricultural machinery farming was described. The given convex field was decomposed into sub regions according to typical faming pattern of complete field coverage. Optimal path planning should minimize agricultural machines turns, farming time, route distance or other optimization object. According to the different purpose of path planning above, optimal travel direction could be determined based on topological features of arable lands, turns pattern in the headland and other useful information. Fanning path planning software was developed by using this algorithm. The test results from four actual quadrangular fields showed that the optimization object for field operation in optimal travel direction decreased obviously compared with other directions. Each optimal travel direction in those quadrangular fields above was along any edge-Especially for a quadrangle having a larger edge ratio, the optimal travel direction was almost the longest edge.
Energy Technology Data Exchange (ETDEWEB)
Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)
2015-06-15
In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.
Practical Research on Robot Path Planning Algorithm%机器人室内路径规划算法的实用性研究
Institute of Scientific and Technical Information of China (English)
周嵘; 张志翔; 翟晓晖; 闵慧芹; 孔庆杰
2016-01-01
Path planning is an important branch in the field of robot research,and its research has been a hot topic.In this paper,based on the experimental platform for robot P3 DX,the indoor environment is divided into blocks using the grid modeling method.The feasibility of the four path planning back path planning,alternate path planning,heuristic path planning and bounding path planning,has been veri-fied.In order to verify the practicability of the four path planning,the four path planning algorithms are studied in the real environment.According to the data returned by the robot after walking,we plot a road-map through software.At the same time,according to the path planning algorithm of the roadmap for the different repetition rates and coverage rates,we find out the efficient path planning algorithm.%机器人研究领域中的一个关键分支即路径规划技术，本课题在机器人P3 DX实验平台的基础上，通过栅格化建模对室内的环境实现分块。4种路径规划回字形路径规划、迂回式路径规划、启发式路径规划与包围式路径规划的可行性已经得到验证，为验证4种路径规划的实用性，在真实环境中将这4种路径规划算法进行了实验研究，通过软件将机器人行走后返回的数据绘制出相应的路线图，同时，根据各路径规划算法的路线图的不同重复率与覆盖率，找出效率较高的路径规划算法。
Expanding the mission plan for large scale telescope systems via skew path optical conditioners
Savastinuk, John; Palmer, Troy A.; Alexay, Christopher
2017-05-01
We describe a case study in which a telescope system, originally designed for a large format, visible camera, needed MWIR imaging capabilities while maintaining its original setup. The dedicated telescope system was adapted to share its existing optics with a new imaging module via a skew path concept. The challenges of non-rotationally symmetric design are explored along with an explanation of the methodology used to analyze and address the unique configuration.
Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment
Arman Nedjati; Gokhan Izbirak; Bela Vizvari; Jamal Arkat
2016-01-01
This paper presents a post-earthquake response system for a rapid damage assessment. In this system, multiple Unmanned Aerial Vehicles (UAVs) are deployed to collect the images from the earthquake site and create a response map for extracting useful information. It is an extension of well-known coverage path problem (CPP) that is based on the grid pattern map decomposition. In addition to some linear strengthening techniques, two mathematic formulations, 4-index and 5-index models, are propos...
Gholamnia Shirvani, Zeinab; Ghofranipour, Fazlollah; Gharakhanlou, Reza; Kazemnejad, Anoshirvan
2014-11-30
Level of physical activity as a key determinant of healthy lifestyle less than is required in individuals particularly women. Applying theories of behavioral change about complex behaviors such as physical activity leads to identify effective factors and their relations. The aim of this study was to determine predictors of physical activity behavior based on the Theory of Planned Behavior in military staff's wives in Tehran. This cross-sectional study was performed in 180 military personnel's spouses residing in organizational houses, in Tehran, Iran in 2014. The participants were randomly selected with multi-stage cluster sampling. The validity and reliability of the theory based scale evaluated before conducting the path analysis. Statistical analysis was carried out using SPSS16 and LISREL8.8. The results indicated the model explained 77% and 17% of intention and behavior variance. Subjective norms (Beta=0.83) and intention (Beta=0.37) were the strongest predictors of intention and behavior, respectively. The instrumental and affective attitude had no significant path to intention and behavior. The direct relation of perceived behavioral control to behavior was non-significant. This research demonstrated relative importance and relationships of Theory of Planned Behavior constructs in physical activity behavior of military personnel's spouses in Tehran. It is essential to consider these determinants in designing of educational interventions for promoting and maintaining physical activity behavior in this target group.
Institute of Scientific and Technical Information of China (English)
刘群芳; 李军华
2016-01-01
In order to solve the problem of unmanned aerial vehicle (UAV) dynamic target path planning, this paper uses the two-level hierarchical planning structure and the hybrid evolutionary algorithm of the sparse A* algorithm and the cultural algorithm (CA) to realize the dynamic UAV path real-time planning under the dynamic target, solves the dynamic path planning problem of avoiding threats and following the target, improves the planning speed and reliability of the track, strengthens the flight safety of UAV.%针对移动目标的无人机航迹规划问题，结合文化算法改进稀疏A*算法解决静态航迹的绕径问题，然后进一步使用混合算法解决目标跟随过程中动态航迹的规划速度和最优路径的平衡选择问题，最终实现不确定环境下跟随目标和威胁躲避的动态航迹实时规划。通过采用静态和动态两级分层规划结构，使用基于稀疏A*算法与文化算法的混合算法实现了动态目标和动态威胁的无人机航迹规划。
Path Planning Method for Car-like Mobile Robot%一种车型机器人路径规划方法
Institute of Scientific and Technical Information of China (English)
张金学; 李媛媛; 掌明
2012-01-01
在自主移动机器人的许多应用中,路径规划技术顺序地设置一套分散的路径点来引导机器人以最短的时间从起始位置到达目标点.针对移动机器人路径规划问题,提出了一种非完整型机器人路径规划技术,该技术采用基本原子操纵方法来解决车型机器人路径规划问题,并采用平滑路径规划方法来产生更多的连续路径用以解决基本原子操纵技术在做路径规划时具有很不连续的缺点从而为机器人获得最优路径.仿真结果证明了该方法的有效性和实用性.%In many applications of autonomous mobile robots, path planning technique determines a sequential discrete path points leading robat to the goal from the start position in the shorteds time. As to mobile robot path plan ning, a robot path planning technique was proposed in the paper, which utilized basic atomic maneuvers for solving the path planning for car-like mobile robot. Atomic maneuvers technique has the drawback of being very discontinu ous. To solve this problem, another technique, smooth path planning was used to geneerate much more continuous paths and therefore an optimal path was obtained for the robot. The simulation results demonstrate the effectiveness and practicality of the proposed approach.
Soft energy paths in Japan: The backcasting approach to energy planning
Suwa, Aki
Climate change is increasingly recognised as a serious threat to the global ecosystem. The international framework, such as the United Nations Framework Convention for Climate Change provides a main mechanism to harness world-wide commitment for greenhouse gas (GHG) emission reduction, to cope with the climate change. Japan is one of the countries which are required to reduce significant amounts of GHG emissions, including C02. The Japanese energy policy is rather fragmented and ineffective in coping with the global climate challenge, and often highly controversial options have been included. Nuclear is, for example, considered by the Japanese government as one of the most important elements to meet its obligation, although there are many doubts over the legitimacy of the option in the light of sustainable development. Against this background, it is critical to review the current energy policy and policy making processes in Japan. This study takes the challenge to propose alternative future visions and to examine their implications in the real policy context. Backcasting methodology, that creates a normative vision and identifies policy path to reach the vision, is identified as a highly relevant conceptual framework to this study. A strategic perspective is applied to the analysis, and the core research quest includes whether the strategic level of discussion between different parties could reduce the policy conflicts and divisions. The study offered four visions and the subsequent policy packages. The detailed policy paths are created to achieve the visions. Two tier evaluation stages are set to validate the policy packages and paths, through communication with selected Japanese energy experts. The study provides an insight as to the effectiveness of the methodology, and the legitimacy of the proposed visions and policy packages. Series of recommendation are made in terms of methodological and policy perspective. In particular, a "policy road map" is proposed as
Plans to Observe the 2017 Total Solar Eclipse from near the Path Edges
Waring Dunham, David; Nugent, Richard; Guhl, Konrad; Bode, Hans-Joachim
2015-08-01
The August 21st, 2017 solar eclipse provides a good opportunity, to time the totality contacts, other Baily’s bead phenomena, and observe other dynamic edge phenomena, from locations near the edges of the path of totality. A good network of roads and generally favorable weather prospects means that more observers will likely be able to deploy more equipment than during most previous eclipses. The value of contact and Baily’s bead timings of total solar eclipses, for determining solar diameter and intensity variations, was described in an earlier presentation in Focus Meeting 13. This presentation will concentrate on how observations of different types that have been used during past eclipses can be made by different observers, to obtain better information about the accuracy of the different types of observations for determining the mean solar diameter, and the systematic differences between them. A problem has been that the few observers who have attempted recording Baily’s beads from path edge locations have wanted to use the latest technology, to try to record the observations better, rather than try to make the observations in the same ways that were used for many past eclipses. Several observers trying different techniques at the same location, and doing that at several locations at different places along the path, is needed. Past techniques that we would like to compare include direct visual observation (but keeping eye safety in mind); visual observation of telescopically projected images; direct filtered video telescopic observations; and recording the flash spectrum. There are several towns that straddle the path edges. The International Occultation Timing Association would like to mobilize people in those towns to observe the eclipse from many places, to say whether or not the eclipse happened, and if it did, time it. A suitable cell phone app could be designed to report observations, including the observer’s location, as was attempted for an
Risk-Aware Planetary Rover Operation: Autonomous Terrain Classification and Path Planning
Ono, Masahiro; Fuchs, Thoams J.; Steffy, Amanda; Maimone, Mark; Yen, Jeng
2015-01-01
Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed groundbased Mars rover operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers.
自主移动机器人局部路径规划综述%Survey of local path planning of autonomous mobile robot
Institute of Scientific and Technical Information of China (English)
鲍庆勇; 李舜酩; 沈峘; 门秀花
2009-01-01
Autonomous mobile robot investigate is an active research society recently. However,mobile robot path planning technology is one of the most important issues in autonomous mobile robot research. The classification of mobile robot path planning method and the importance of local path planning are summarized; the state of the art relative mobile robot local path planning approaches are presented. The advantages and disadvantages of these algorithms are discussed. A conclusion and perspectives of autonomous mobile robot local path planning is addressed.%自主移动机器人技术是近年来的研究热点,而路径规划技术是自主移动机器人技术研究中的一个重要内容.讨论了自主移动机器人路径规划技术的分类和研究局部路径规划的重要性;分析了局部路径规划技术的发展现状;指出了局部路径规划各种方法的优点与不足;对局部路径规划技术今后的发展方向做出了展望.
Lagrange relaxation for UAV path planning%拉格朗日松弛的无人机路径规划
Institute of Scientific and Technical Information of China (English)
刘山; 顾晔倩; 李雨石; 曹盛文; 刘轩
2012-01-01
提出了基于城市建筑物遮挡模型的无人驾驶飞行器(简称无人机)路径规划方法,主要包含两方面的内容:一是利用圆柱体虚拟城市的建筑物环境,使建筑物对无人机的遮挡面积可计算,另外,由于建筑物的相对位置会相互遮挡,不可以进行简单的面积加法.采用程序实现了无人机的遮挡总和的计算,即每个建筑物遮挡面积的并集.二是在计算出无人机飞行的水平平面上(x,y)点的遮挡曲面值的基础上,给出了无人机基于拉格朗日松弛算法的优化路径规划,即走一条遮挡面积最小的路径的方法.给出matlab仿真结果,实验结果表明该方法是十分有效的.%It proposes a path planning algorithm based on an urban building block model for Unmanned Air Vehicle (UAV for short).The proposed algorithm mainly contains two aspects. First the algorithm simulates the buildings in urban environment with cylinders, so it' s able to calculate the block area of the relative position between the buildings and UAV. In addition, the total shading area isn' t the addition of each shading area, instead it' s a union set. The algorithm calculates the union set by using a program. Second, after calculating the curved surface of UAV' s flight plane, this algorithm proposes an optimal path planning method based on Lagrange relaxation of UAV. The path is a polygonal line along the equant diagonal line on the searching area of UAV. The shading area of this path is minimal. The Matlab simulation result suggests this algorithm is efficient.
An algorithm for Path planning with polygon obstacles avoidance based on the virtual circle tangents
Directory of Open Access Journals (Sweden)
Zahraa Y. Ibrahim
2016-12-01
Full Text Available In this paper, a new algorithm called the virtual circle tangents is introduced for mobile robot navigation in an environment with polygonal shape obstacles. The algorithm relies on representing the polygonal shape obstacles by virtual circles, and then all the possible trajectories from source to target is constructed by computing the visible tangents between the robot and the virtual circle obstacles. A new method for searching the shortest path from source to target is suggested. Two states of the simulation are suggested, the first one is the off-line state and the other is the on-line state. The introduced method is compared with two other algorithms to study its performance.
Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment
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Arman Nedjati
2016-12-01
Full Text Available This paper presents a post-earthquake response system for a rapid damage assessment. In this system, multiple Unmanned Aerial Vehicles (UAVs are deployed to collect the images from the earthquake site and create a response map for extracting useful information. It is an extension of well-known coverage path problem (CPP that is based on the grid pattern map decomposition. In addition to some linear strengthening techniques, two mathematic formulations, 4-index and 5-index models, are proposed in the approach and coded in GAMS (Cplex solver. They are tested on a number of problems and the results show that the 5-index model outperforms the 4-index model. Moreover, the proposed system could be significantly improved by the solver-generated cuts, additional constraints, and the variable branching priority extensions.
Career Paths of Professional Leaders in Counseling: Plans, Opportunities, and Happenstance.
Magnuson, Sandy; Wilcoxon, S. Allen; Norem, Ken
2003-01-01
The authors conducted qualitative analyses of 10 counseling leaders' accounts of turning points in their professional development, turning points that led them to become leaders. The participants' explanations provided support for applying the planned happenstance theory of career development to leadership development. (Contains 11 references and…
Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.
Wetering, R. van de; Batenburg, R.; Lederman, R.
2010-01-01
PURPOSE: While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the
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Chao Zhang
2016-06-01
Full Text Available An improved ant colony optimization (ACO combined with immunosuppression and parameters switching strategy is proposed in this paper. In this algorithm, a novel judgment criterion for immunosuppression is introduced, that is, if the optimum solution has not changed for default iteration number, the immunosuppressive strategy is carried out. Moreover, two groups of parameters in ACO are switched back and forth according to the change of optimum solution as well. Therefore, the search space is expanded greatly and the problem of the traditional ACO such as falling into local minima easily is avoided effectively. The comparative simulation studies for path planning of landfill inspection robots in Asahikawa, Japan are executed, and the results show that the proposed algorithm has better performance characterized by higher search quality and faster search speed.
Yang, Yi; Pang, Yongjie; Li, Hongwei; Zhang, Rubo
2014-09-01
Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model's collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.
Institute of Scientific and Technical Information of China (English)
Yi Yang; Yongjie Pang; Hongwei Li; Rubo Zhang
2014-01-01
Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model’s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.
Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications
Abdelkader, Mohamed
2014-05-01
Floods are the most common natural disasters, causing thousands of casualties every year in the world. In particular, flash flood events are particularly deadly because of the short timescales on which they occur. Unmanned air vehicles equipped with mobile microsensors could be capable of sensing flash floods in real time, saving lives and greatly improving the efficiency of the emergency response. However, of the main issues arising with sensing floods is the difficulty of planning the path of the sensing agents in advance so as to obtain meaningful data as fast as possible. In this particle, we present a fast numerical scheme to quickly compute the trajectories of a set of UAVs in order to maximize the accuracy of model parameter estimation over a time horizon. Simulation results are presented, a preliminary testbed is briefly described, and future research directions and problems are discussed. © 2014 IEEE.
无人机三维航迹规划方法研究%Study on three-dimension path planning for unmanned aircraft vehicle
Institute of Scientific and Technical Information of China (English)
康乐
2009-01-01
Path planning is essential for both UAVs and mission planning system.This paper proposes a three-dimension path Planning algorithm based on a hybrid of an improved voronoi diagram algorithm and a dynamic A~* algorithm for a fixed-point.The proposed algorithm plans a two-dimension path by the improved voronoi diagram method,and then presents a three-dimen-sion path coinciding with the flight constraints of UAVs by referring to the former two-dimension path.Experiments highlight the efficiency of the path planning method.%航迹规划算法是无人机关键技术之一,同时也是任务规划系统(Mission Planning System)心之一.针对固定目标规划问题,提出一种voronoi图改进算法和动态稀疏A~*算法融合的三维航迹规划方法.该方法针对固定威胁目标,通过改进voronoi图规划算法快速求解二维航迹路径,然后在该路径参考下,用动态稀疏A~*算法求解符合无人机飞行动力学约束的三维航迹.试验表明,该算法比动态稀疏A~*算法规划速度快,并保证了航迹最优性.
Wood, Nathan J.; Jones, Jeanne M.; Schmidtlein, Mathew; Schelling, John; Frazier, T.
2016-01-01
Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience.
Directory of Open Access Journals (Sweden)
Jung A Lee
2014-10-01
Full Text Available Ecosystem service values have rarely been incorporated in the process of planning ecological infrastructure for urban areas. Urban ecological infrastructure is a network system of natural lands and waters that provides ecosystem services. The purpose of this study was to design landscape corridors that maximize the value of ecosystem services in ecological infrastructure planning. We explored the optimal corridors to enhance the connectivity among landscape elements to design an ecological infrastructure for the city of Gwacheon, South Korea, as an example of a small urban area. We calculated the value of ecosystem services using standardized estimation indices based on an intensive review of the relevant literature and employed the least-cost path method to optimize the connectivity of landscape structural elements. The land use type in the city with the highest estimated value of ecosystem services was the riparian zone (i.e., 2011 US$7,312.16/ha. Given areal coverage of all land use types, the estimated value of developed area open spaces was 2011 US$899,803.25, corresponding to the highest contribution to the total value of ecosystem services. Therefore, the optimal configured dispersal corridors for wildlife were found from the riparian zones (source area to the developed area open spaces (destination area in the city. Several challenges remain for improving the estimation of the value of ecosystem services and incorporating these ecosystems in ecological infrastructure planning. Nonetheless, the approaches taken to estimate the value of ecosystem services and design landscape corridors in this study may be of value to future efforts in urban ecological infrastructure planning.
Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles
Institute of Scientific and Technical Information of China (English)
Mohammad Pourmahmood Aghababa; Mohammad Hossein Amrollahi; Mehdi Borjkhani
2012-01-01
In this paper,an underwater vehicle was modeled with six dimensional nonlinear equations of motion,controlled by DC motors in all degrees of freedom.Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP).An energy performance index as a cost function,which should be minimized,was defined.The resulting problem was a two-point boundary value problem (TPBVP).A genetic algorithm (GA),particle swarm optimization (PSO),and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP.Applying an Euler-Lagrange equation to the NOCE a conjugate gradient penalty method was also adopted to solve the TPBVP.The problem of energetic environments,involving some energy sources,was discussed.Some near-optimal paths were found using a GA,PSO,and ACO algorithms.Finally,the problem of collision avoidance in an energetic environment was also taken into account.
Path Planning of Mobile Elastic Robotic Arms by Indirect Approach of Optimal Control
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Moharam Habibnejad Korayem
2011-03-01
Full Text Available Finding optimal trajectory is critical in several applications of robot manipulators. This paper is applied the open-loop optimal control approach for generating the optimal trajectory of the flexible mobile manipulators in point-to-point motion. This method is based on the Pontryagin-s minimum principle that by providing a two-point boundary value problem is solved the problem. This problem is known to be complex in particular when combined motion of the base and manipulator, non-holonomic constraint of the base and highly non-linear and complicated dynamic equations as a result of flexible nature of links are taken into account. The study emphasizes on modeling of the complete optimal control problem by remaining all nonlinear state and costate variables as well as control constraints. In this method, designer can compromise between different objectives by considering the proper penalty matrices and it yields to choose the proper trajectory among the various paths. The effectiveness and capability of the proposed approach are demonstrated through simulation studies. Finally, to verify the proposed method, the simulation results obtained from the model are compared with the results of those available in the literature.
The Path to Far-IR Interferometry in Space: Recent Developments, Plans, and Prospects
Leisawitz, David T.; Rinehart, Stephen A.
2012-01-01
The far-IR astrophysics community is eager to follow up Spitzer and Herschel observations with sensitive, highresolution imaging and spectroscopy, for such measurements are needed to understand merger-driven star formation and chemical enrichment in galaxies, star and planetary system formation, and the development and prevalence of waterbearing planets. The community is united in its support for a space-based interferometry mission. Through concerted efforts worldwide, the key enabling technologies are maturing. Two balloon-borne far-IR interferometers are presently under development. This paper reviews recent technological and programmatic developments, summarizes plans, and offers a vision for space-based far-IR interferometry involving international collaboration.
Research on Auto Flight Path Planning Algorithm of Multiple Unmanned Air Vehicles%多无人机飞行路径自动规划算法研究
Institute of Scientific and Technical Information of China (English)
马传焱
2015-01-01
The path planning plays an important role in the reconnaissance task of unmanned air vehicle(UAV).Aiming at auto flight path planning algorithm of multi⁃UAV,this paper analyzes the key technologies of modeling and algorithm design.The algorithm uses Voronoi diagram for path planning. Based on the constructed battlefield environment V diagram, the Dijkstra algorithm in graph theory is used for initial path search and optimization.The simulation results show that this algorithm can be used to plan flight path for a typical multi⁃UAV flight task,and adapt to multiple constraint conditions.At last,it is shown that reasonable results of path planning are obtained.%路径规划对无人机完成其侦察作战任务具有重要意义。针对多无人机飞行路径自动规划算法，从模型建立和算法设计2个方面对规划过程中的关键技术进行了详细分析。算法采用构造Voronoi多边形图的方法来进行路径规划。基于构建的战场环境V图，采用图论中的Dijkstra 算法，对V图进行搜索得到初始航路并进行优化。经过分析仿真结果证明，该算法能对典型的多无人机飞行任务进行路径规划，并能满足多种约束条件，获取合理的规划结果。
移动机器人全局路径规划算法的研究%Research on Global Path Planning Algorithm of Mobile Robot
Institute of Scientific and Technical Information of China (English)
黄静; 陈汉伟
2014-01-01
Path planning is an important problem of mobile robots,and a better path planning algorithm can search the effec-tive paths quickly, enhance the intelligence of mobile robot and enhance interaction experience of users.This paper studied the A* algorithm and genetic algorithm and applied these algorithms in path planning of mobile robot based on Unity engine.Path plan-ning module for virtual mobile robot was implemented using the A*algorithm.The path search efficiency is increased and the mo-bile robots are more intelligent and authentic.%全局路径规划是移动机器人要解决的重要问题，较好的路径搜索算法可以迅速搜索有效路径，提升移动机器人的智能性，提升用户体验。针对目前移动机器人行为决策能力较弱的问题，着重研究移动机器人的全局路径规划问题，通过研究盲目式搜索算法、A*算法和遗传算法，分析了3种算法在解决路径规划问题中的优劣，使用A*算法在Unity平台上虚拟移动机器人的全局路径规划模块，并且使用贪婪平滑算法优化A*算法产生的多余路径，路径搜索的效率较高，移动机器人的智能性和真实感较好。
A Neural Network based Path Planning Algorithm for Extinguishing Forest Fires
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M.P.Sivaram Kumar
2012-03-01
Full Text Available In this work an algorithm for automatic detection and suppression of Forest fires is proposed. The algorithm is implemented using parallel distributed model of neural network with three activation functions to determine the next consecutive moves to the cells for the actor. The algorithm uses reinforcement learning with weights determined dynamically in each iteration. The Entire forest is decomposed into grid of square cells with initial position of the Actor is assumed to be the cell 1 and the goal cell is the cell where the fire has occurred. The neural network model uses starting cell, goal cell and number of cells in each row or column and three activation functions to determine the next consecutive cells in which the robot has to travel. It uses only three movements LEFT, DIAGONAL and UP to reach the target cell. After calculating next cell, the check will be made for presence of obstacles in that cell. If there is any obstacle in that cell, then one cell from other two cells obtained using other two movements, which is free from obstacle will be chosen for next move. Then the cell number is stored in memory. This process is repeated till the next cell computed is same as the goal cell. The Actor will begin to move from start cell and reach the goal cell using the cell numbers available in the memory to extinguish Forest fire. This algorithm is designed keeping in mind only static obstacles and hence it works well for Forest environment with static obstacles. Computer simulation results show that path has been found successfully without collision with obstacles.
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Manuel Hung Varela
2010-09-01
Full Text Available Present work was making at Teaching Paediatrics Hospital “José Martí” in Sancti Spíritus province, Sancti Spíritus city. Its main purpose is apply a control and planning system to a strategic planning project at mentioned entity, getting by this way to contribute to efficacy and efficient of planning process, through Critical Path Method. To it, was use tools like classic strategic planning procedure and software like WINQSB. As result, is obtaining the project estimate duration, the necessary information for its control and execution, including critical path, and resources assignment mainly. The project is finishing and has been useful the used method for its execution.
Dynamic Adaptive RRT Path Planning Algorithm%动态自适应快速扩展树航迹规划算法研究
Institute of Scientific and Technical Information of China (English)
潘广贞; 秦帆; 张文斌
2013-01-01
快速扩展随机树(RRT)是航迹规划的重要算法,针对其难以直接应用于无人机航迹规划的问题,提出了动态自适应RRT算法.动态自适应RRT算法在随机点产生过程中加入无人机转弯角约束,使航迹更适合无人机直接跟踪；同时引入动态调节因子,根据环境中障碍密集程度调整规划步长,有效避免各类障碍.计算机实验结果表明动态自适应RRT算法在单航迹规划和多航迹规划中明显优于基本RRT算法和其它改进RRT算法,更适用于无人机航迹规划.%RRT is the important path planning algorithm. In view of its difficult to directly apply in UAVS path planning, this paper puts forwards the dynamic adaptive RRT algorithm. Adding turn corner constraints in the process of random point produce in order to make track for UAVS tracking more directly. At the same time, introduce dynamic adjustment factor, according to the environment of intensive degree to adjust the planning step length and avoid all kinds of barriers effectively. The computer experimental results show that the dynamic adaptive RRT algorithm in single path planning and more significantly than the basic path planning algorithm and other improvements RRT RRT algorithm, more applicable for UAVS path planning.
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Daqi Zhu
2014-03-01
Full Text Available In this paper a biologically inspired neural dynamics and map planning based approach are simultaneously proposed for AUV (Autonomous Underwater Vehicle path planning and obstacle avoidance in an unknown dynamic environment. Firstly the readings of an ultrasonic sensor are fused into the map using the D-S (Dempster-Shafer inference rule and a two-dimensional occupancy grid map is built. Secondly the dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation. The AUV path is autonomously generated from the dynamic activity landscape of the neural network and previous AUV location. Finally, simulation results show high quality path optimization and obstacle avoidance behaviour for the AUV.
Directory of Open Access Journals (Sweden)
Daqi Zhu
2014-03-01
Full Text Available In this paper a biologically inspired neural dynamics and map planning based approach are simultaneously proposed for AUV (Autonomous Underwater Vehicle path planning and obstacle avoidance in an unknown dynamic environment. Firstly the readings of an ultrasonic sensor are fused into the map using the D-S (Dempster-Shafer inference rule and a two-dimensional occupancy grid map is built. Secondly the dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation. The AUV path is autonomously generated from the dynamic activity landscape of the neural network and previous AUV location. Finally, simulation results show high quality path optimization and obstacle avoidance behaviour for the AUV.
RISK ASSESSMENT IN PROJECT PLANNING USING FMEA AND CRITICAL PATH METHOD
Directory of Open Access Journals (Sweden)
Sandra Milena CHOLES ARVILLA
2014-10-01
Full Text Available This paper is based upon the research undertaken for the development of the doctoral thesis “Management of software projects based on object-oriented technology”. The study examines the existing risk management practices commonly used for classic software development. The goal is to integrate the elements of the traditional risk management methodologies to create a new agile risk management methodology. The thesis focuses on techniques that can be easily implemented in extreme programming (XP and SCRUM. This study is motivated by the following research questions: What are the elements of existing quality assurance tools that could meet the principles of agile development? And is it possible to use risk estimation for improving quality in agile projects? The thesis presents a synthesis of the most common risk management techniques, as well as an introduction to agile methods XP and SCRUM. The proposal integrates the concepts of Failure Mode and Effect Analysis into the iterative life cycle of an agile software project. The thesis presents a metamodel which integrates the concepts of agile development methodologies: SCRUM and XP with the FMEA concepts for risk quantification. The model was partly implemented into a real development project. Partial results show the improvement in early identification of failures and allowed to reconsider the Sprint plan.
多雷达威胁环境下的无人机路径规划%Unmanned Aerial Vehicle Path Planning Under Multi-radar Threatening Environment
Institute of Scientific and Technical Information of China (English)
章国林; 李平; 韩波; 郑巍
2011-01-01
According to the radar for unmanned aerial vehicle instantaneous detection probability model and motion characteristics of unmanned aerial vehicle, this paper presents an unmanned aerial vehicle path planning method based on improved Ant Colony Algorithrn(ACA) and Voronoi diagram in order to minimize the path cost when unmanned aerial vehicle breaks through the threaten field with multiple radars. Compared with other three kinds of path planning methods in income fuel costs, threat path cost, total costs and computing time, this method has lower path cost and less computing time.%根据雷达对无人机的瞬时探测概率模型以及无人机的运动特性,提出一种基于改进蚁群算法与Voronoi图相结合的无人机路径规划方法,使无人机突破雷达威胁环境的路径成本最低.将该方法与其他路径规划方法在所得路径燃油成本、威胁成本、总成本以及计算时间方面进行对比,表明该方法具有更低的路径成本和更少的计算时间.
A Method for Path Planning of UAVs Based on Improved Genetic Algorithm%基于改进遗传算法的UAV航迹规划
Institute of Scientific and Technical Information of China (English)
鲁艺; 吕跃; 罗燕; 张亮; 赵志强; 唐隆
2012-01-01
An improved genetic algorithm was proposed to solve the problem of UAV's path planning in actual battle field. First,the planned search space was generated by means of skeleton algorithm,the information of the search space was extracted, and the kill probability of path points in the search space was calculated out. Then,with the information of the planned search space and by using a special gene coding mode,K possible paths were obtained by using genetic algorithm. According to the rules of path selection, the optimal path was obtained, and was smoothed by using different step lengths. Eventually the optimal path was acquired, which can meet the safety and maneuverability requirement of UAV.%针对实际作战环境中的UAV航迹规划,提出一种基于改进遗传算法的UAV航迹规划方法；通过骨架化算法生成规划搜索空间,对规划搜索空间中的信息进行提取,求解出规划搜索空间中航迹点的杀伤概率；根据规划搜索空间中的信息,采用特殊的基因编码方式,使用遗传算法为UAV找到K条备选航迹,提高了航迹规划效率；根据设定的航迹选取原则,求出最优航迹并对其按不同步长进行平滑处理,最终得到满足UAV机动性要求的可飞航迹.
复杂环境下无人机快速航迹规划研究%Research on fast path planning for UAV in complex circumstance
Institute of Scientific and Technical Information of China (English)
杨俊; 朱凡; 张健; 郝震
2012-01-01
For some deficiency of general path planning methods such as weak applicability, long time-cost and easily planning-fail, a new fast path planning method is proposed. A new method of multi-danger-value matrix is used as the modeling carrier. The ameliorative PSO method is used for seeking the cursory path, after that some optimization is needed to be made respectively for the cursory path. The path will become the global-best path. The simulation result indicates that the method plays well in complex circumstance. The method is universally available, fast and precise.%针对一般航迹规划算法在复杂环境下适用性差、耗时长、容易失效的问题,提出了一种复合快速航迹生成算法.该算法采用新型的多逻辑威胁值网点法为环境建模形式,在此基础上将加以改进后的粒子群算法引入到航迹近似最优解的快速求取过程中,对所得的航迹近似解进行分段局部优化以及可飞性修正处理,将近似解变为最优解.仿真结果显示该复合算法通用性好、速度快、精度高,能较好地应用于复杂环境下无人机航迹的快速求解.
Application of Genetic Algorithm in Mobile Robot Path Planning%遗传算法在移动机器人路径规划中的应用
Institute of Scientific and Technical Information of China (English)
徐丁; 朱擎飞; 叶晓东
2013-01-01
移动机器人的路径规划是机器人研究的重要领域。文中旨在研究遗传算法对于机器人路径规划问题的适用性。对于路径规划的目标，提出了基于路径长度、路径平滑度和路径安全度等因素综合衡量的方法，并在传统的遗传算法的交叉、变异操作的基础上，针对路径规划问题的特点，增加了捷径寻找、障碍避让、平滑优化等方法。实验表明，此算法在存在形状复杂的障碍物的静态环境中表现良好，其效率与准确性皆满足机器人路径规划的要求。%Path planning is an important subject in mobile robot research area. It aims to verify the feasibility of genetic algorithm towards mobile robot path planning problem. The goal of path planning is measured by the combination of path length,path smoothness and path safety. Besides traditional operators of crossover and mutation in genetic algorithm,there are additional methods such as shortcut seeking, obstacle avoidance and smoothness optimization. Through experiments,the algorithm performs well in static environment with obstacles in complex shapes and its efficiency and accuracy satisfies the requirements of the problem.
Path Planning for UAV Based on Mixed Ant Colony Algorithm%基于混合蚁群算法的无人机航路规划
Institute of Scientific and Technical Information of China (English)
税薇; 葛艳; 韩玉; 魏振钢; 孟友新
2011-01-01
The key and difficult problem of UAV path planning is how to satisfy safety and real-time environment,meanwhile, a global path-planning and a local path-planning are considered to improve operational efficiency and survival probability. For this question, according to the existing research of UAV path planning, the method of synthesizing Ant Colony Algorithm (ACA) and Artificial Potential Field (APF) was drscussed. ACA was used as a global route-planning algorithm,and APF was used as a local route-planning algorithm. Simulation results verify that the efficiency of the algorithm can provide some reference value to related researchers.%无人机(UAV)航路规划的热点和难点在于如何满足安全性和实时性的同时,兼顾全局路径规划和局部路径重规划,以提高无人机的作战效率和生存概率.针对这一问题,在现有无人机航路规划研究基础之上,提出采用蚁群算法与人工势场法相结合的方法.蚁群算法用于全局航路规划,人工势场法用于局部路径重规划.仿真结果表明,两种算法结合所得优化航路较好反映了算法的有效性,可以为航路规划辅助决策研究提供借鉴和参考.
基于图论的WSN节点定位路径规划%WSN Node Localization Path Planning Based on Graph Theory
Institute of Scientific and Technical Information of China (English)
党小超; 李小艳
2012-01-01
The mobile anchor node planning path exists the node access repetition, and can not improve the localization accuracy. In order to solve this problem, this paper puts forward Mobile Anchor node Path Planning(MAPP) algorithm, quotes the graph theory knowledge, translates sensor nodes into figure vertices, and combines with the ant colony algorithm, uses graph traversal to solve the problem of path planning, looks for a path. Experimental results show that the algorithm can locate the whole sensor nodes, meanwhile avoid the repetition of access, and reduce nodes localization error.%移动锚节点规划路径存在节点重复访问的问题,会影响定位精度的提高.为此,提出一种移动锚节点路径规划算法,引用图论知识,将传感器节点转化为图的顶点,并结合蚁群算法,利用图的遍历解决路径规划问题,寻找出一条路径.实验结果表明,该算法能够定位传感器节点,避免节点的重复访问,降低节点定位的误差.
booc.io: An Education System with Hierarchical Concept Maps and Dynamic Non-linear Learning Plans.
Schwab, Michail; Strobelt, Hendrik; Tompkin, James; Fredericks, Colin; Huff, Connor; Higgins, Dana; Strezhnev, Anton; Komisarchik, Mayya; King, Gary; Pfister, Hanspeter
2017-01-01
Information hierarchies are difficult to express when real-world space or time constraints force traversing the hierarchy in linear presentations, such as in educational books and classroom courses. We present booc.io, which allows linear and non-linear presentation and navigation of educational concepts and material. To support a breadth of material for each concept, booc.io is Web based, which allows adding material such as lecture slides, book chapters, videos, and LTIs. A visual interface assists the creation of the needed hierarchical structures. The goals of our system were formed in expert interviews, and we explain how our design meets these goals. We adapt a real-world course into booc.io, and perform introductory qualitative evaluation with students.
基于蚁群优化的AUV全局路径规划研究%Research on global path planning based on ant colony optimization for AUV
Institute of Scientific and Technical Information of China (English)
王宏健; 熊伟
2009-01-01
路径规划是自主式水下潜器(AUV)导航研究的重要课题,AUV可用于未知环境如海洋空间探测.在大范围海洋环境中,应用蚁群优化原理对自主式水下潜器的全局路径规划问题进行了研究.引入栅格建模方法建立了蚁群可视图模型,设计了蚁群信息素更新规则;给出了蚁群全局路径规划的操作步骤;针对蚁群规划路径不平滑问题,设计了切割算予和插点算子.仿真实验结果表明,蚁群全局规划算法非常适合于求解复杂环境中的规划问题,规划时间短、路径平滑,其原型系统可应用于非结构化无人环境监测.%Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.
Path planning of multi head drilling machine and simulation software development%多头钻床轨迹规划和仿真软件的开发
Institute of Scientific and Technical Information of China (English)
梁全
2011-01-01
针对多主轴头的数控钻床钻孔路径规划问题进行了分析,在充分考虑机床的机械结构和加工效率要求的前提下,提出了多头数控钻床的钻孔路径规划算法.首先分析了DXF文件的结构,接下来将二维空间中的孔群分解成一维空间中的孔群进行钻孔路径的规划.为了验证算法和真实加工的可行性,还开发了仿真软件,针对某工程中的某管板类零件规划了钻孔路径,并进行了仿真加工.仿真加工结果证明,开发的算法正确可靠,可以用来进行多头钻的钻孔路径规划.%This paper analyzed the problem of drilling path planning about CNC drill machine. Under the premise of taking account of the mechanical structure and processing machine efficiency requirements, promoting path planning algorithm about multi spindles CNC drilling machine. First, this paper analyzed the structure of DXF file, then dividing the two dimensional space hole-group into one dimensional hole-group to plan. In order to verify the feasibility of processing algorithms and real application, this paper also developed simulation software, planned drilling path for a tube plate in actual application and made simulation machining. Simulation results show that the algorithm is accurate and can be used in drilling path planning in multi spindle CNC drilling machine.
Hoebel, Louis J.
1993-01-01
The problem of plan generation (PG) and the problem of plan execution monitoring (PEM), including updating, queries, and resource-bounded replanning, have different reasoning and representation requirements. PEM requires the integration of qualitative and quantitative information. PEM is the receiving of data about the world in which a plan or agent is executing. The problem is to quickly determine the relevance of the data, the consistency of the data with respect to the expected effects, and if execution should continue. Only spatial and temporal aspects of the plan are addressed for relevance in this work. Current temporal reasoning systems are deficient in computational aspects or expressiveness. This work presents a hybrid qualitative and quantitative system that is fully expressive in its assertion language while offering certain computational efficiencies. In order to proceed, methods incorporating approximate reasoning using hierarchies, notions of locality, constraint expansion, and absolute parameters need be used and are shown to be useful for the anytime nature of PEM.
Institute of Scientific and Technical Information of China (English)
谭冠政; 贺欢; SLOMAN Aaron
2007-01-01
A novel method for the real-time globally optimal path planning of mobile robots is proposed based on the ant colony system (ACS) algorithm. This method includes three steps: the first step is utilizing the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is utilizing the Dijkstra algorithm to find a sub-optimal collision-free path,and the third step is utilizing the ACS algorithm to optimize the location of the sub-optimal path so as to generate the globally optimal path. The result of computer simulation experiment shows that the proposed method is effective and can be used in the real-time path planning of mobile robots. It has been verified that the proposed method has better performance in convergence speed, solution variation, dynamic convergence behavior, and computational efficiency than the path planning method based on the genetic algorithm with elitist model.
2007-11-02
me a much needed creative outlet. Thanks also to Maj Jon Anderson, Maj Jim Rogers, Capt John Erickson , Capt Dave Laird, Capt Kevin LaRochelle, Capt...Mathematical Functions with Formulas, Graphs, and Mathematical Tables, (Ninth Edition) edited by Milton Abramowitz and Irene A. Stegun, Washington DC: U.S...Handbook of Mathematical Func- tions with Formulas, Graphs, and Mathematical Tables, (Ninth Edition) edited by BIB-2 Milton Abramowitz and Irene A. Stegun
基于虚拟障碍物的移动机器人路径规划方法%Virtual Obstacles Based Path Planning for Mobile Robots
Institute of Scientific and Technical Information of China (English)
叶炜垚; 王春香; 杨明; 王冰
2011-01-01
针对城市道路环境,将全局路径规划方法和局部路径规划方法相结合,提出了基于虚拟障碍物的路径规划方法.该方法首先采用A*算法得到一条全局最优的车道路径,然后根据全局最优的路径生成虚拟障碍物,最后将虚拟障碍物与传感器探知的实际障碍物融合,采用改进的向量直方图方法进行局部路径规划.该方法不仅能够充分利用已知环境信息生成全局最优路径,而且能够实时处理随机动态障碍物,真实环境下的实验结果表明本文方法的有效性和可靠性.%A virtual obstacles based path planning method for mobile robot in urban road environment is presented.It's based on both the benefits of global and local path planners.Firstly, it uses A* algorithm to produce a global optimal path.Secondly, virtual obstacles are generated according to the global path.Finally, by fusing virtual and actual detected obstacles, the local path is planned based on the improved vector field histogram method.This method can not only fully utilize environment information to get the global optimal path, but also avoid the stochastic obstacles on the road in real-time.Practical experiments illustrate the effectiveness and robustness of this method.
UAV 3D Path Planning Based on IHDR Autonomous-Learning-Framework%基于IHDR自主学习框架的无人机3维路径规划
Institute of Scientific and Technical Information of China (English)
陈洋; 张道辉; 赵新刚; 韩建达
2012-01-01
提出一种基于自主学习框架的无人机3维路径规划方法.该自主学习框架由知识学习、知识检索和在线更新三部分组成.在该框架中,无人机在线路径规划时首先从过去的规划经验中提取控制量直接用于指导当前机器人的行动,另一方面,如果检索结果对于当前无人机的状态是无效的,可以在线启动常规3维路径规划算法,实时计算机器人的控制量,在控制机器人运动的同时将当前状态下的新决策量添加到知识库中从而对其进行更新.此外,分别采用增量分层判别回归算法(IHDR)和k-D树方法建立了路径规划知识库.其中,IHDR方法通过增量方式,可将以往的路径样本建立为一棵分层树.大量的仿真结果对比表明,在本文提出的框架下,基于IHDR的方法比传统的k-D树方法具有更好的实时性.%An autonomous learning framework for UAV (unmanned aerial vehicle) 3D path planning is proposed. This framework consists of three parts, I.e. Knowledge learning, knowledge retrieving and updating online. In this framework, the control value will be retrieved firstly from the existed knowledge when UAV runs online, so as the current action of the robot can be guided by the results. If the decisions retrieved from the knowledge base are invalid for the current UAV states, the custom algorithm for UAV path planning will be launched online and it generates the decisions for UAV's movement in real time. In the meanwhile, the knowledge library is updated by adding the new decisions for the current states. Additionally, the knowledge library is constructed by the algorithm of incremental hierarchical discriminant regression (IHDR) and k-D tree, respectively. Among these methods, IHDR can construct a hierarchical tree by using the past path planning samples. By several simulations, IHDR method demonstrates better real time performance than the traditional k-D tree method under the proposed framework.
视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach
Institute of Scientific and Technical Information of China (English)
张一巍; 黄源清
2002-01-01
The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.
Research of Path Planning of Autonomous Robot in Dynamic Environment%一种移动机器人动态环境下的路径规划
Institute of Scientific and Technical Information of China (English)
唐建平; 宋红生; 王东署
2012-01-01
一种动态环境下自主机器人路径规划的方法由趋于目标的全局运动规划和躲避障碍物的局部运动规划两部分组成.首先通过栅格法建立机器人的工作环境,利用蚁群算法初步规划出机器人的全局优化路径；在此基础上,采用滚动窗口的方法进行局部环境探测和碰撞预测,对动态障碍物实行局部避碰,使机器人安全顺利地到达目的地.该方法适用于环境中同时存在静止和动态障碍物的情况.仿真结果证明该方法有效.%A method of path planning for autonomous robot was proposed. The method had two parts including global path planning towards target and local path planning for obstacles avoidance. First, the work environment for the robot was established with grid method. Then a global path was planned using ant colony algorithm, and rolling windows which predicted collision in dynamic environment was adopted to avoid the robot obstacles. The method applied to the circumstances existing static and dynamic obstacles. Finally, the simulation results showed the effectiveness of the method.
Institute of Scientific and Technical Information of China (English)
殷洁琰
2013-01-01
This paper condects a deep investigation about the road classification system and hierarchical planning management mode of China. It uses the characteristic of road classification system and hierarchical planning management mode for reference to analyzing the planning of information network. Based on the similarity between information network and road network, suggestions on the classification system and hierarchical planning management mode for information network are put forword.% 从信息网络与道路网络内涵的相关性、结构的相似性、建设的关联性出发，分析借鉴目前成熟的道路分级体系和分层规划管理模式，提出对信息管网在合理的等级体系和分层管理模式下进行统一规划建设的建议。
多无人机交会过程的协同航迹规划方法%Cooperative Path Planning for Rendezvous of Unmanned Aerial Vehicles
Institute of Scientific and Technical Information of China (English)
孙小雷; 孟宇麟; 齐乃明; 姚蔚然
2015-01-01
交会过程是多无人机(UAV)协同控制的重要组成部分,为此提出一种无人机恒速飞行交会过程的协同航迹规划方法.为兼顾航迹较短的迂回机动和航迹较长的盘旋机动方式,无人机实时计算至目标的最小机动距离,生成最短Dubins路径作为航迹参考.近程无人机在其基础上重新规划生成等待机动航迹,补偿与远程无人机的航程差.远程无人机同样根据该过程调整航迹,实现同时到达对目标的可攻击范围.无人机在该范围内沿Dubins路径飞行,以最小化执行时间,降低风险.仿真结果表明,所规划的协同航迹可实现无人机在目标可攻击范围的交会,同时控制规律容易实现,验证了算法的可行性和有效性.%Rendezvous is an important process of cooperative control for unmanned aerial vehicles (UAVs). Thus this paper investigates a cooperative path planning for rendezvous of UAVs with constant speed. To achieve both wandering maneuver with shorter range-to-go and circle maneuver with longer range-to-go, UAVs calculate the minimum maneuver distance to target in real time in order to plan a Dubins path as a reference. Based on this path, the UAV with shorter range-to-go re-plans the waiting maneuver to extend the path length. In addition, as the UAV with longer range-to-go also follows this manner, the UAVs will arrive at the boundary of the target execution range at the same time. To reduce the risk of collision in this range, the UAVs fly along the Dubins path to minimize the execution time. The simulation results show that the UAVs can perform cooperative path planning for rendezvous in target execution range by using the proposed method, and it is easy to implement the corresponding control law, which demonstrates the feasibility and effectiveness of the method.
Li, Xin; Yu, Jiaguo; Jaroniec, Mietek
2016-05-01
As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.
1989-06-01
must be permissible in region R&.1 and path segement P-S must be permissible in region Rk. Since all path segments are non-braking episodes, distance...34Defense Mapping Agency Digital Data Policy," in Geographic Information Systems in Government, ed. B. K. Opitz, v. 2 , A. Deepak Publishing, Hampton, VA...and Automation, 1985. 20. Antony, R. and Emmerman, P. J., "Spatial Reasoning and Knowledge Representation," in Geographic Information Systems in
Path Planning Research Based on GIS for Helicopter%基于GIS的直升机辅助航迹规划探讨
Institute of Scientific and Technical Information of China (English)
赵磊; 杨磊; 闫鹤; 乔健
2012-01-01
GIS在各行业中正发挥着愈来愈重要的作用。在航迹规划中,利用GIS提供的时空基准以及分析、量算、统计等功能,使得航迹规划更具科学性和实用性,提高了规划的精度和速度。本文利用GIS平台研究面向直升机的辅助航迹规划问题,解决了飞行参数解算、航迹显示、编辑和预警以及航线评估等。%GIS in all walks of life is playing an increasingly important role. In path planning, the use of GIS to provide spatial and temporal reference and analysis, the amount of calculation, statistical and other functions, making the track more scientific and practical plan to improve the planning accuracy and speed. This paper studies the use of GIS platform for supporting the helicopter flight path planning problem, solver to solve the flight parameters, track display, edit, and route assessment and early warning.
Efficient Path Planning Algorithm in Three Dimensions for UAV%无人机快速三维航迹规划算法
Institute of Scientific and Technical Information of China (English)
尹高扬; 周绍磊; 吴青坡
2016-01-01
To satisfy the real⁃time requirement of path planning in three dimensions for unmanned aerial vehicle, a path planning algorithm based on rapidly⁃exploring random tree is proposed. By random sampling point in configura⁃tion space, the search will be guided to empty area, thus the algorithm can search the high⁃dimension space quickly and efficiently according to the current environment, which can be used in real⁃time path planner. By introducing the path length constraint, the search tree will explore along the direction of the near optimal path. The proposed al⁃gorithm overcomes the disadvantage of basic RRT algorithm that only to quickly get feasible path, unable to obtain near optimal path. During the search process, the path constraints of UAV and the terrain information are fully uti⁃lized, so that the path generated by the algorithm can avoid terrain and threat automatically, and meet the dynamic constraints of UAV. Simulations for the algorithm are made on a generated virtual digital map. Simulation results demonstrated that this proposed method can complete path planning mission in three dimensions quickly and effec⁃tively.%针对无人机三维航迹规划的实时性问题，提出了基于快速扩展随机树的三维航迹规划方法。该算法能够根据当前环境快速有效搜索规划空间，通过随机采样点将搜索导向空白区域，使三维航迹规划能够用于实时航迹规划。通过引入航迹距离约束，搜索树将沿着路径距离最短的近似最优航迹的方向进行扩展，克服了基本快速扩展随机树方法随机性强，只能快速获得可行航迹，无法获得较优航迹的缺点。在搜索过程中无人机的航迹约束条件和地形信息得到了充分利用，使算法生成的航迹能够自动回避地形和威胁，同时满足无人机的动力学约束。通过生成的虚拟数字地图对算法进行了仿真验证，仿真结果表明该方法能够快速有效
Path planning for autonomous underwater vehicles by using QPSO%采用量子粒子群算法的潜器路径规划
Institute of Scientific and Technical Information of China (English)
2013-01-01
针对复杂海底环境中的潜器路径规划问题，提出了一种采用量子粒子群算法的潜器路径规划方法。该方法首先从海图中提取水深数据，基于自然邻点插值和随机中点位移插值得到密集规格水深数据。然后由此数据建立海底三维模型，确定一个路径安全性检测方案及避碰原则，将海流大小方向对潜器航行的影响和路径点的转弯角度对航行的影响转化为相应的路径长度。最后将总长度作为适应度函数，利用量子粒子群算法迭代来求取最优路径。仿真结果得到了一条安全、简洁的路径，验证了该方法的有效性和可行性。%In efforts to address the submersible path planning problem in complex undersea environment , a path planning method for autonomous underwater vehicles was put forward , which is based on quantum-behaved particle swarm optimization (PSO).First, the bathymetric data was extracted from a nautical chart , and the intensive-spec-ification depth data was acquired by dealing with the natural neighbor interpolation and the random midpoint dis -placement interpolation.Next, we were able to establish the undersea 3D model and determine a path security tes-ting program, along with the principle to prevent collisions .The influence of the ocean current size , and direction on autonomous underwater vehicle navigation and the influence of the turning angle of the path points on navigation were transformed into corresponding path lengths .At last, the total length was used as the fitness function and the optimal path was obtained by iteration of quantum-behaved particle swarm optimization (QPSO).A safe and simple path was achieved as the result of the simulation , verifying effectiveness and feasibility of the method .
航迹预测的多无人机任务规划方法%Mission planning based on path prediction for multiple UAVs
Institute of Scientific and Technical Information of China (English)
齐乃明; 孙小雷; 董程; 姚蔚然
2016-01-01
为提高无人机自主控制性能，实现任务分配与航迹规划整体架构，提出一种基于航迹预测的多无人机任务规划方法。首先，将禁飞区考虑为更接近真实场景的多边形模型；然后，使用改进A∗航迹预测算法生成任意两个航迹点间障碍规避后的最短路径，利用该路径近似航迹航程作为任务分配过程的输入信息，建立目标函数，采用改进PSO算法求取最优结果；最后，使用B样条曲线平滑分配后的路径组合，生成无人机可飞行航迹。仿真结果表明，该方法能够以较高的计算速度和精度生成近似最优的任务分配结果和满足飞行约束的平滑航迹。%In order to improve the autonomous ability of unmanned aerial vehicles ( UAVs) and achieve the integral framework of task assignment and path planning, a mission planning system based on path prediction algorithm for multiple UAVs is presented. To model obstacles more accurately, the forbidden areas are defined as polygons. Then, the optimal path segment avoiding all obstacles between two waypoints is computed by using improved A∗path prediction algorithm. According to this path segment, the task assignment is determined by improved particle swarm optimization ( PSO) algorithm. Finally, the B⁃spline method is adopted to smooth the flight path, which consists of the sequential path segments. Numerical results demonstrate that the proposed method can achieve the near⁃optimal task assignment and best flight routes with effectiveness of computation speed and precision.
基于进化算法的多无人机协同航路规划%Cooperative Path Planning of Multi-UAV Based on Evolutionary Algorithm
Institute of Scientific and Technical Information of China (English)
李子杰; 刘湘伟
2015-01-01
以突防航路时域协同指数、空域协同指数、突防时长指数和受威胁指数为规划目标，以最小直线航路段长度、可飞空域、续航能力和进入任务航路方向为约束，构建了多无人机协同突防航路规划模型。结合模型特点，利用合作型协同进化遗传算法对该模型进行求解。%Aiming at maximizing penetration path time synergy index and penetration path airspace synergy index, minimizing penetration time length index and intimidate index, restricted by the minimum length of straight path, flyable space, endurance and intro-mission route direction, the penetration path planning model of Multiple Unmanned Serial Vehicle (Multi-UAV)is constructed. Combining its characteristic, the model is solved by use of Cooperative Co-evolutionary Genetic Algorithms(CCGA).
基于改进RRT算法的无人机航迹规划%Path planning of UAV based on the improved rapidly-exploring random tree algorithm
Institute of Scientific and Technical Information of China (English)
崔挺; 李俨; 张明庄
2013-01-01
为了提高无人机的作战效率,航迹规划系统必须为无人机设计出安全系数高,能量消耗少,处理时间短,同时还必须满足飞行器自身物理特性的威胁回避轨迹.基于上述研究目的,本文选择快速随机搜索树算法(RRT)作为迹规划航算法主体,结合Dijkstra算法改进了RRT算法,完成最小航迹代价飞行轨迹的设计.%In order to improve the operational efficiency of the uav,path planning for uav system must design a high safety coefficient,less energy consumption,the short processing time,but also must satisfy the physical characteristics of the vehicle itself threat avoidance path.Based on the above research purpose,this article chooses fast rando.m-exploring search tree algorithm (RRT) as a trace planning navigation algorithm,combined with the main Dijkstra algorithm improved the RRT algorithm,complete the minimum path cost trajectory design.
Research on automated path planning in crowd animation%群体动画中路径自动规划方法研究
Institute of Scientific and Technical Information of China (English)
魏丽
2012-01-01
为了在制作群体动画时产生逼真的运动路径,在群体运动的模拟中设计了碰撞检测和碰撞避免的方法,并基于微粒群算法和人工蜂群算法提出了群体动画路径自动规划方法.仿真实验表明；该方法能够实现群体动画运动路径的自动设计,提高了群体动画的制作效率.%To produce the realistic movement path in crowd animation, this paper presents a method of collision detection and collision avoidance in the crowd movement. Based on Particle Swarm Optimization algorithm and Artificial Bee Colony Algorithm, it provides an automated path planning method for crowd animation. Simulation results show that this method can realize the automated design of path planning in crowd animation and improve the efficiency of producing crowd animation.
Path Planning Algorithm for Smart Wheelchair Indoor Navigation%智能轮椅室内导航路径规划算法
Institute of Scientific and Technical Information of China (English)
徐彪; 蒋朝阳; 朱健铭; 陈真诚
2015-01-01
The smart wheelchair improve the quality of life and give more freedom for people who lose the ability to walk. Path planning for smart wheelchair technology is one of an important Technology. Research method The degree of difficulty walking in the actual environment is difference. A new path planning algorithm for a kind of navigation methods to find the optimal path has been proved. Firstly the grid modeling has been established for indoor environment, and the adjacent relation with the improved A* algorithm has been used to optimal planning of global path between the two positions, then the virtual force field algorithm can be implemented for the local path planning on the way. Results and Conclusions This algorithm just needs to gather the information where you want to reach, then the smart wheelchair can automatically navigate to the destination. The experiments show that the algorithm is applied to the smart wheelchair indoor navigation system to reach the expectations and has the advantages of quick response, stable performance, easy to use and strong extensibility.%智能轮椅为丧失行走能力的人提高生活质量和生活自由度. 适用于智能轮椅的路径规划问题是其重要的技术之一. 实际环境中行走的难易程度是有区别的, 对此提出一种新的路径规划算法, 即寻找最优路径的导航方法, 对室内环境进行栅格模型建模, 并利用最邻近关系结合改进的 A*算法来规划两个位置之间的最优全局路径, 采用虚拟力场算法实现途中的局部路径规划. 此算法只需要采集用户需要到达目的地的信息, 智能轮椅能自动导航到达目的地, 经实验验证, 该算法运用到智能轮椅室内导航系统中路径得到较好的改善并具有反应快、工作稳定可靠、使用灵活方便和扩展性强等优点.
Directory of Open Access Journals (Sweden)
Yong Ma
2013-01-01
Full Text Available We present one algorithm based on particle swarm optimization (PSO with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP. With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP. Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.
A Control Algorithm for UAV Path Planning%无人机路径规划的控制算法
Institute of Scientific and Technical Information of China (English)
柳传武; 张奇
2016-01-01
Real time control is almost impossible for traditional unmanned aircraft continuous path algo-rithm due to the deferred response because of the time spent on flight path calculation.Using the Bessel curve to calculate flight path can simplify the process,but it is still very difficult to generate the desired flight path. In this paper,the linear and circular interpolation technology of numerical control system is applied to control the turning path of aircraft,which can achieve real time response to system and accurate control of the flight path,thus a turning path control algorithm is designed by relating to UAV flight altitude,speed and angle of attack.The results show that the algorithm is simple with accurate path control,and its rationality is verified through flight test.%传统的无人机连续路径算法，因计算飞行路径需要一定的时间而延迟响应，很难实时控制。采用贝塞尔曲线来计算飞行路径，过程会简化很多，但要产生预期的飞行路径仍然很难实现。现将数值控制系统的直线和圆弧插补技术用于飞机转弯路径控制算法，实现实时响应，精确控制飞行路径，再结合无人机飞行高度、速度和迎角，设计了一种实现转弯路径控制算法。研究结果表明该算法简单，路径控制准确，并通过飞行测试验证了设计的合理性。
预约机制下的共乘路径规划策略%Carpool path planning strategy under reservation mechanism
Institute of Scientific and Technical Information of China (English)
刘潇; 李德敏; 张光林; 汤海涅
2016-01-01
For the reason that existing carpooling path algorithms focus only on the minimum of the total weight of path rather than the accuracy of arrival time, it proposes an optimal algorithm of carpooling path under the mechanism of appoint-ment. It collects the information of appointment ride, introduces the concept of classification to classify the passenger information in group. Then it utilizes the Bellman-Ford algorithm intragroup, and arriving time path algorithm intergroup, so that it comes up with Carpooling Path Planning Algorithm in Order(CPPAO), which takes into account both the accuracy of arriving time and consumption of travel cost.%现有的共乘路径算法只专注优化路径总权值而很少考虑到达时间准确性，针对这一现状提出一种预约机制下的共乘路径最优算法。采集乘客的预约搭乘信息，引入分类的概念对乘客信息进行团体分类，对团体内使用Bellman-Ford算法，团体间使用到达时间路径算法，得出了预约机制下的共乘路径最优算法CPPAO，使得该算法兼顾到达时间的准确和行驶代价的消耗。
Design of Intelligent Monitoring and Path Planning in Picking Robot%采摘机器人智能监控和路径规划设计研究
Institute of Scientific and Technical Information of China (English)
吴芳; 汪小志
2016-01-01
In order to improve the picking robot autonomous navigation and automatic positioning capability and improve the accuracy of path planning for the machine vision, based on MSP430F149 of TI company,it designs a function auto-matic picking robot with the monitoring terminal and GPS navigation, the robot path planning in real-time processing, communication, location and alarm integration and automation control function.Through the test, the MSP430 F149 micro controller has the advantages of low power consumption, small size, simple operation, and easy to maintain the system management and maintenance.5 robot path planning for the overall running accuracy and path planning of mobile time u-tilization, path planning leakage recovery rate were tested, it was found by test that five kinds of path planning method for various index to test the effect best, combined with MSP430F149 MCU and PID algorithm, to realize picking robot, auto-matic picking function, which can improve the robot's picking accuracy and provides a valuable reference for the picking robot intelligent design.%为了提高采摘机器人自主导航和自动化定位能力,提升机器视觉的路径规划精度,基于 TI 公司的MSP430 F149 单片机,设计了一款具有监控终端和GPS导航功能的自动采摘机器人,实现了机器人路径规划实时处理、通讯、定位、报警一体化和自动化控制功能. 通过测试发现,MSP430F149 单片机具有功耗低、体积小、操作简单,便于系统管理维护等优点. 对机器人5 种路径规划的总体行驶精度路、径规划的移动时间利用率、路径规划的漏采率进行了测试,通过测试发现:5 种路径规划中套行法的各种指标测试效果最好. 同时,结合MSP430 F149 单片机和PID算法,实现了采摘机器人高效自动化采摘功能,提高了机器人的采摘精度,为采摘机器人的智能化设计提供了较有价值的参考 .
Institute of Scientific and Technical Information of China (English)
王宏伦; 姚鹏; 梁宵; 吕文涛
2015-01-01
This paper introduces a novel path planning algorithm for Unmanned Aerial Vehicle ( UAV ) based on theory of fluid avoiding obstacles. To the problem of path planning which aims at the global optimum, not only the influence of terrain constraints on path safety but also the performance constraints of UAV should be taken into con-sideration, thus a feasible and smooth path will be planned in the three-dimensional space. The computation com-plexity and the path quality by traditional algorithms are usually unsatisfactory, hence we propose the method in-spired by the phenomenon that water can avoid rocks and reach the destination. The common features between this phenomenon and the path planning problem are extracted and analyzed, and then the mathematical model generali-zing the phenomenon is constructed on the basis of theory of fluid mechanics. By selecting the optimal streamline from the fluid field under the evaluation index, the three-dimensional optimal path under flight and environment con-straints is obtained eventually.
反舰导弹航路规划图形化快速逆推方法%Fast Graphic Converse Method for Path Planning of Anti-ship Missile
Institute of Scientific and Technical Information of China (English)
刘钢; 老松杨; 谭东风; 周智超
2011-01-01
为提高反舰导弹航路规划的决策效率,基于几何学原理提出了航路规划功能区域的概念,发掘出了航路规划的几何学本质.将功能区域概念融入逆向航路规划过程中,发现了功能区域的几何学渐变规律,据此提出了一种航路规划图形化快速逆推方法.开发并实现了反舰导弹航路规划图形化辅助决策系统,应用实例表明,该方法可定量描述航路规划决策空间,消除决策"盲目性",符合人的认知习惯;该方法可有效提高航路规划效率,缩小其他航路规划算法的搜索空间,加速算法收敛.%To improve the decision efficiency of path planning of anti-ship missile,the concept of operational area of path planning was proposed based on geometric principle and the geometrical essence of path planning was obtained. Fusing the concept of operational area into the process of converse path planning, the geometric gradual transformation rule of operational area was revealed;thereby, a fast graphic converse method of path planning was proposed. The graphic decision support system for path planning of anti-ship missile was developed and realized. Application instance indicates that by the method, the decision space of path planning can be described quantificationally. The"blindness"of decision can be eliminated,and the method of path planning accords with human's cognitive habit. The method can improve the efficiency of path planning effectively, and can be applied to reduce the search space of other algorithm of path planning to increase the convergence speed.
Energy Technology Data Exchange (ETDEWEB)
None, None
2003-03-05
This report presents a plan for the deployment of a fusion demonstration power plant within 35 years, leading to commercial application of fusion energy by mid-century. The plan is derived from the necessary features of a demonstration fusion power plant and from the time scale defined by President Bush. It identifies critical milestones, key decision points, needed major facilities and required budgets.
Institute of Scientific and Technical Information of China (English)
洪晔; 房建成
2009-01-01
路径规划是UAV(Unmanned Aerial Vehicle)自主飞行的重要保障.初步建立了基于MDP(Markov Decision Processes)的全局路径规划模型,把UAV的路径规划看作是给定环境模型和奖惩原则的情况下,寻求最优策略的问题;为解决算法时空开销大、UAV航向改变频繁的缺点,提出一种基于状态聚类方法的HMDP(Hierarchical Markov Decision Processes)模型,并将其拓展到三维规划中.仿真实验证明:这种简单的规划模型可以有效解决UAV的三维全局路径规划问题,为其在实际飞行中的局部规划奠定了基础.
基于网格模型的无人机航路规划仿真%Path Planning Simulation for Unmanned Air Vehicles Based on Mesh Model Method
Institute of Scientific and Technical Information of China (English)
任博; 吕雪燕; 董彦斌
2011-01-01
In order to research on autonomous path planning for unmanned air vehicles searching uncertain environment with prior information, a mesh model method was proposed for path planning. Firstly, mission area was divided into weighted meshes considering the existence probability of targets. Secondly, a control model was built according to a path decision set and sensor sweep model was proposed to describe coverage area of a prospecting apparatus carried by unmanned air vehicles. Thirdly, control model and sensor sweep model were applied to calculate the path value of next limited steps. Then an optimum path decision was carried out through solving a dynamic programming. Lastly, a simulation testing for unmanned air vehicles searching uncertain environment was designed, and the simulation results proved the effectiveness of the method.%关于优化无人机覆盖路径规划,应便于实时调整航路.实施战场游弋侦察的无人机要搜索含有先验信息的任务区域,并且没有确定的目标点.针对战场环境瞬息万变,提出了网格模型的航路规划方法.首先,将无人机的任务环境区域划分为若干网格单元,并根据存在目标的概率赋予网格单元权值.接着,依据航路决策集合建立了控制模型,根据探测区域对环境网格的覆盖情况建立了探测模型,采用控制和探测模型计算有限步长内的航路价值,通过求解一个动态规划得到当前状态下的最优航路决策.最后通过对一架和多架无人机侦察给定区域的仿真,验证了方法的有效性,为设计航路提供了科学参考.
有限干预下的 UAV 低空突防航迹规划%Human intervention flight path planning for UAV low-altitude penetration
Institute of Scientific and Technical Information of China (English)
任鹏; 高晓光
2014-01-01
低空突防航迹规划是实现有人机和无人机（unmanned aerial vehicle，UAV）编队协同作战的关键技术，针对目前智能算法在求解低空突防航迹规划问题中存在的不足，充分发挥人脑这个超级智能系统来引导飞行航迹求解过程，将基于角度量编码的小生境伪并行自适应遗传算法（niche adaptive pseudo parallel genetic algo-rithm，NAPPGA）和人有限干预情况下的智能决策结合起来，提出 UAV 低空突防航迹规划技术。通过大量仿真计算，结果表明，应用该技术预规划和重规划的三维航迹能够有效实现威胁回避、地形回避和地形跟随，满足UAV 低空突防要求，具有一定的实用性。%The flight path planning for unmanned aerial vehicle (UAV)low-altitude penetration is a key technology for achieving manned and unmanned aerial vehicles cooperative combat.The technique of human in-tervention flight path planning for UAV low-altitude penetration against several limitations of the existing intel-ligent algorithms is proposed.It makes full use of the human brain to guide the solution procedures of the flight path planning,combining the niche adaptive pseudo parallel genetic algorithm (NAPPGA)based on angle codes and the intelligent decision with human intervention.A lot of simulation studies show that the solving off-line and on-line three-dimensional flight paths by this technique can meet the requirements for UAV low-altitude penetration to realize efficient implementation of threat avoidance,terrain avoidance and terrain following.This method has a certain practicality.
改进免疫算法在无人机航线规划中的应用%Application of Improved Immune Algorithm in UAV Path Planning
Institute of Scientific and Technical Information of China (English)
缪永飞; 钟珞; 陈艳恩; 夏罗生
2015-01-01
Unmanned aerial vehicle ( UAV) path planning method was discussed.It's designed to establish a much more ob-jective and reasonable planned path which could blend with real digital terrain.On account of the slow convergence rate, and that immune algorithm is easily to fall into local optimum, an improved immune algorithm based on tabu criterion was proposed, and it was used to solve the UAV path planning problem.It aimed at determining the individual evaluation criteria through gene enco-ding and a series of genetic manipulation such as crossover and hyper-mutation.Through the optimization of initial track of UAV on a digital elevation map which was proposed on real geographical information.The flight path could meet various constraints. The comparative analysis with ant colony algorithm shows that the algorithm is faster and more effective to get convergent process and good solutions.%针对无人机的航线规划方法展开研究，旨在建立能够融合真实数字地形的，更为客观、合理的航迹规划方法。由于免疫算法易陷入局部最优点及收敛速度过慢等问题，提出了一种基于禁忌准则的改进免疫算法，并应用于无人机航迹规划，其通过基因编码确定个体评价准则、交叉和高频变异等操作，通过在真实的地理环境信息所建立的数字高程地图上进行无人机的初始航迹优化，使航迹能够满足各种约束条件。与蚁群算法对比分析的结果表明，该算法加快了收敛进程，并可求得较优解。
the application of graph planning in path plannng%图规划在路径规划中的应用
Institute of Scientific and Technical Information of China (English)
林尔敏; 张逢春; 蔡莉莎
2016-01-01
随着科学技术的不断发展，机器人研究成为当今的热门话题，人们趋向于用机器人替代人类去完成一些危险的工作。而路径规划是机器人研究的难点之一。本文以机器人的运输问题为例，介绍了图规划的算法，以及如何利用图规划技术对路径规划问题进行求解。%With thedevelopment of science and technology,Robotics research is a hot topic,people tend to use robots to do some dangerous work instead of people.The path planning is one of the difficulties of robotics research,in this paper,by the example of the robot's transportation problem,introduced the algorithm of Graphplan,and how to use the technology of Graphplan to solve the problem of Path planning.
基于模糊算法的移动机器人路径规划%Mobile Robot Path Planning Based on Fuzzy Algorithms
Institute of Scientific and Technical Information of China (English)
陈卫东; 朱奇光
2011-01-01
为了解决移动机器人最优路径规划问题,提出一种基于模糊算法的移动机器人路径规划策略.利用超声波传感器对环境进行探测,得到关于障碍物和目标的信息.运用模糊推理将障碍位置信息与目标位置信息模糊化,建立模糊规则并解模糊最终使机器人可以很好的避障,从而实现了移动机器人的路径规划.仿真实验结果表明了模糊算法优于势场法和A*算法,具有较高的有效性和可行性.%To solve the optimal path planning problem of mobile robots,a novel mobile robot path planning strategy based on fuzzy algorithm has been proposed. The environment situation has been detected using ultrasonic sensors to obtain the information about obstacles and goals. Fuzzy the position informations about obstacles and goals through fuzzy reasoning and establish the fuzzy rules. By defuzzification could make the mobile robot avoid obstacles successfully and find the optimal path. The simulation experiment results have shown that the fuzzy algorithm mentioned above is superior to potential field method and the A * algorithm with more effectiveness and feasibility.
RGBD-based Indoor Robot SLAM and Path Planning System%基于RGBD的机器人室内SLAM与路径规划系统
Institute of Scientific and Technical Information of China (English)
李卫成; 汪地; 宗殿栋; 姜海龙
2016-01-01
By use RGB-D sensor mounted on NAO robot,this paper captures sensor data for feature extraction and matching,then integrate the RGB and depth data and establish an environmental map.On the environment map,this paper uses the Path Search Algorithm of D* for the robot to plan its path.This paper constructs a simultaneous localization and mapping system (SLAM) for NAO robot in indoor environment,in the generated map,the NAO robot can plan its path and control its motion correctly.%移动机器人路径规划通常需要搭载多种传感器来建立环境模型和对自身进行定位，导致系统过于复杂。通过NAO机器人搭载的RGB－D传感器，在ROS环境下，对传感器数据进行特征提取和匹配，融合RGB和深度数据，建立环境地图并对机器人进行定位；在环境地图上，利用D*路径搜索算法，对机器人路径进行规划。实现了室内环境下移动机器人的同时定位与建图系统（SLAM），并在生成的环境地图中进行路径规划与控制。
Mark Setterfield
2015-01-01
Path dependency is defined, and three different specific concepts of path dependency – cumulative causation, lock in, and hysteresis – are analyzed. The relationships between path dependency and equilibrium, and path dependency and fundamental uncertainty are also discussed. Finally, a typology of dynamical systems is developed to clarify these relationships.
Institute of Scientific and Technical Information of China (English)
孔令富; 高胜男; 吴培良
2012-01-01
针对机器人行走路径规划与机械手操作路径规划之间缺乏同步陛，提出了一种机器人与机械手同步路径规划方法，使机器人在路径规划时不仅可以实现行走路径规划，还实现了对操作路径的规划。首先，借鉴人对空间规划的思想，设计了实现机器人与机械手同步规划的总体思路，并且给出了其涉及的两个新概念，分别为物品点和二维物品操作点；其次，设定了同步规戈旷摸型，利用转换矩阵将其同化为机器人路径点模型；最后，将机器人路径点模型分裂为二维行走路径规划模型和三维珞径规划模型，并据此同步的规划行走路径和操作路径。在家庭环境下，家庭服务机器人基于全息地图利用该方法实现了机器人行走与机械手操作之间的同步性，同时也可以生成合理的行走路径和操作路径。%According for lack of synchronicities between robots walk path planning and manipulator operation path planning, a synchronous path planning method between robot and manipulator was put forward, that made the robot path planning could not only realize when walking path planning, but also realize the operation path planning. First of all, taking from the thought of people in space planning, general idea of synchronous planning for robot was designed, and two new concepts were given： items point and 2-Ditems operation point. Secondly, a synchronous Path Planning Model for robot, and assimilates it into a Robot Path Point Model depends on transformational relation of robot was designed. Finally, 2-D and 3-D path planning model from Robot Path Point Model were split up, on these grounds, robot plans walk path and operation path synchronously. In the family environment, family service robot based on holographic map with this method brings about the integration of robot walking and manipulator operating, at the same time it also can generate reasonable walk path and
Institute of Scientific and Technical Information of China (English)
Zhang Xing; Chen Jie; Xin Bin; Peng Zhihong
2014-01-01
The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs’ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
Directory of Open Access Journals (Sweden)
Zhang Xing
2014-06-01
Full Text Available The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs’ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
UAV Path Planning Across Weather Threat%穿越恶劣天气区域的无人机航迹规划
Institute of Scientific and Technical Information of China (English)
罗冠辰; 于剑桥; 张思宇; 井文明; 赵俊锋
2014-01-01
To solve the problem of UAV path planning across weather threat,the harsh weather zone occurring during UAV's trip was discussed adequately and abstracted into mathematical model.An additional control force was introduced into artificial potential field method as the optimization variable for path planning.The artificial potential fields were built up in terms of a generalized form describing spatial constraints,i.e.,the probability of accomplishment of the task,which could release the rigorous requirements on field's foundation.Simulation results verified that the proposed method benefits to UAV path planning across weather threat.At the same time,the proposed method inherits the advantages of traditional artificial potential field method,and improves the disadvantages that the trajectory is apt to sink into local minimum and the foundation of potential fields lacks of actual significance.%研究无人机穿越恶劣天气区域的航迹规划问题.充分考虑无人机飞行过程中可能遭遇的恶劣天气,并建立数学模型.以人工势场法为基础引入附加控制力,航迹规划任务通过优化附加控制力实现.采用任务完成概率这一关于空间的客观物理量刻画势场,从而解除了过去建立势场的苛刻要求.仿真结果表明所提出的方法能有效完成恶劣天气条件下的无人机航迹规划任务,同时,继承了传统人工势场法的优点,改善其容易陷入局部极值、势场的建立缺乏实际意义的固有缺陷.
基于几何相交测试的机器人路径规划算法%Geometry intersection testing based robot path planning algorithm
Institute of Scientific and Technical Information of China (English)
周之平; 黎明; 华路
2011-01-01
针对机器人路径规划问题,提出一种基于几何相交测试的路径规划方法.该方法首先搜索位于当前路径点到目标点连线上的首障碍栅格;然后结合贪婪法、回溯法和邻域搜索策略从障碍栅格邻域搜索下一个路径栅格;接着从新的路径点出发迭代搜索后续的路径点,从而确定从起点到目标点的路径;最后对得到的最好路径进行路径点合并以提高路线的连贯性.实验结果表明,新方法规划的路径性能优于其他同类算法,路径呈现出更好的连续性,规划时间能满足实际应用的要求.%For the problem of robot path planning,a geometry intersection testing based path planning algorithm is presented.Firstly,the first obstacle grid is searched in the configuration space which lies on the oriented segment from start to target.By combining the greedy method and backward strategy,the grid where next way point lies is determined from the neighbors of the first obstacle grid by local searching.Then subsequent way points are obtained iteratively scratching from the last obtained way point in order to get some routes from start to target as possible.Finally,the best route is refined by incorporating subroutes to maintain the consistency of trajectory.The experimental results show that,the presented method can plan a shorter and more reasonable path than other algorithms,which represents higher consistency of trajectory,and the computing time can meet the requirement of practical application.
水切割机器人路径规划方法%Path planning method of water-jet cutting robot
Institute of Scientific and Technical Information of China (English)
王玫; 孟正大
2012-01-01
以汽车内饰件切割路径优化为研究对象,提出了一种改进禁忌表蚁群算法,实现优化排序.根据水切割过程特点和工艺要求,进行了水切割路径规划问题分析与建模,设计了改进的禁忌表,利用分层思想将禁忌表划分为3段:内部小环段、内部大环段和外部轮廓段,各段的优先级依次降低,并确定了与此相应的禁忌表的更新规则.在此基础上,给出了基于改进禁忌表蚁群算法的水切割路径优化排序方法,对轮廓切割顺序和各轮廓起始点选择同时进行优化.仿真与实验结果表明,改进禁忌表蚁群算法是可行、有效的,可大大缩短水切割机器人的示教编程时间,显著提高水切割作业的效率和质量.%Taking the optimization of path planning of cutting automotive interior ornament as the research object, an improved tabu list based ant colony algorithm is presented to achieve cutting sequence optimization. According to the characteristics and technology demands of the water-jet cutting process, water-jet cutting path planning problem was analyzed and modeled. Taking advantage of the hierarchy principle, an improved tabu list was designed, which was divided into three sections : interior small loop, interior large loop, exterior outline section, and their priority reduces successively. Corresponding updating rules of the tabu list were proposed. The water-jet cutting path planning method based on the improved ant colony algorithm was proposed with which the cutting sequence of outlines and selection of starting point for cutting every outline are optimized simultaneously. Simulation and experimental results show that the improved tabu list based ant colony algorithm is feasible and effective. The teaching programming time of water-jet cutting robots can be shorten greatly, efficiency and quality of water-jet cutting jobs can be raised evidently.
Institute of Scientific and Technical Information of China (English)
戈新生; 陈凯捷
2016-01-01
基于Legendre伪谱法研究自由漂浮空间机器人非完整路径规划的最优控制问题。自由漂浮是空间机器人执行任务常用的工作模式，其路径优化是空间机器人完成复杂空间任务的基础。由于空间机器人不具有固定基座，机械臂和载体之间存在非完整约束，使得自由漂浮空间机器人路径规划完全不同于地面机器人而变得具有挑战性。本文提出自由漂浮空间机器人路径规划的最优控制伪谱方法。首先，利用多体动力学理论建立自由漂浮空间机器人动力学模型，给定系统的初始和目标位形，选取机械臂关节耗散能最小为性能指标，并考虑实际控制输入受限，建立其路径规划的 Bolza 问题。然后，应用 Legendre 伪谱法，将状态和控制变量在Legendre-Gauss-Lobatto (LGL)点上离散，并构造 Lagrange 插值多项式逼近系统状态和控制变量，将连续路径优化问题离散化为非线性规划问题求解。最后通过数值仿真表明，应用Legendre伪谱法求解自由漂浮空间机器人非完整路径规划问题，得到的机械臂和载体最优运动轨迹，较好地满足各种约束条件，且计算精度高、速度快，并具有良好的实时性。%Based on the Legendre pseudospectral method, the optimal control of free floating space robots path planning problems are studied. Free floating is the working status for the space robots in task and path planning is the foundation for them to fulfil a complex space task. Because the space robots have no fixed pedestal and there are nonholonomic constraints between the manipulator and the carrier, and it makes the path planning for free floating space robots different from those on the ground. In this paper, the Legendre pseudospectral method which can realize the optimal control of free floating space robots path planning problem is presented. Firstly, a dynamic model of free floating space robots is estab
Intelligent scheduling and path planning of warehouse mobile robots%仓储物流机器人集群的智能调度和路径规划
Institute of Scientific and Technical Information of China (English)
沈博闻; 于宁波; 刘景泰
2014-01-01
电子商务迅猛发展，为仓储物流带来了新的需求和挑战。其发货单位小型化，品种多、批量小、批次多、周期短，传统的仓储物流难以适应新的需求，基于移动机器人的自动化仓储技术正在兴起。首先基于电子商务仓储物流的任务特点，建立了一个灵活可重构的仓储空间模型，制订了适于仓储物流的机器人运行规则。随后，将物流任务分解，给出了综合考虑曼哈顿路径代价和等待时间代价的机器人调度方法，修正A∗算法实现了在特殊道路规则约束下的路径规划，进而加入时序建立了时间空间运行地图进行三维路径规划。通过仿真，比较了路径规划方法和机器人数量对任务完成时间、运行总里程、道路冲突协调的影响，验证了智能调度和路径规划方法的有效性。%The rapid increase of E⁃commerce brings new challenges for warehouse logistics. The shipments are char⁃acterized as big variety, small volume, large number of small batches and short cycle, and thus are difficult to han⁃dle. Emerging logistic technology based on mobile robots is the promising solution. In this work, firstly a warehouse model with flexible re⁃configurability was set up and a set of rules to govern warehouse logistics and robot movement were defined. After that, the logistic task was decomposed and a robot scheduling method taking into account the Manhattan path cost and the waiting time cost was proposed. Next, the A∗ algorithm was adapted for robot path planning under the special constraint rules. Finally, timing information was included for consideration and a time⁃space map was established to carry out three⁃dimensional path planning. The intelligent scheduling and path plan⁃ning methods were validated by simulation experiments. The path planning methods and number of robots were com⁃pared in relation to total time cost, total mileage and number of conflicts.
Institute of Scientific and Technical Information of China (English)
吴宪祥; 郭宝龙; 王娟
2009-01-01
针对移动机器人路径规划问题,提出了一种基于粒了群三次样条优化的路径规划方法.借助三次样条连接描述路径,这样将路径规划问题转化为三次样条曲线的参数优化问题.借助粒了群优化算法快速收敛和全局寻优特性实现最优路径规划.实验结果表明:所提算法町以快速有效地实现障碍环境下机器人的无碰撞路径规划,规划路径平滑,利于机器人的运动控制.%A novel algorithm based on particle swarm optimization (PSO) of cubic splines is proposed for mobile robot path planning. The path is described by string of cubic splines, thus the path planning is equivalent to parameter optimization of particular cubic splines. PSO is introduced to get the optimal path for its fast convergence and global search character. Ex-perimental results show that a collision-avoidance path can be found fleetly and effectively among obstacles by the proposed algorithm. The planned path is smooth which is useful for robot motion control.
A Path Planning Algorithm for UAV Based on Skeleton Algorithm%一种骨架提取的无人机航迹规划法
Institute of Scientific and Technical Information of China (English)
袁操; 周德云; 张堃
2012-01-01
The Unmanned Aerial Vehicle(UAV) will play a more and more important role in the future, and how to improve its survival-rate and operational effectiveness has become focus of the path-planning. The threat-circles were simplified from threats of radar, antiaircraft missile, landform, no-fly areas and so on, and a skeleton diagram was constructed based on the distribution of the threat-circles. The skeleton graph yielded the feasible paths for travel between a set of threat-circles to avoid the threats. The vector graphics were consisted of the lines whose cost was calculated out according to the specific information of threats. The initial optimal path was obtained, which was shortened according to the need of the threat avoiding. Simulation was made with Matlab platform and the simulation result is presented in the paper.%未来战争中无人机的应用地位将大大提高,如何提高无人机的生存率、作战效率成为航路规划研究的主要方向.将敌方雷达、对空导弹、地形等威胁简化构建成威胁圆,根据威胁圆的分布情况,构造基于威胁圆的规避威胁的骨架化图；结合各具体威胁信息,计算各路径段的代价值,形成有赋值的有向图,计算初始最优航路；利用实际飞行中无人机对威胁规避的要求,对初始航路做缩短处理.运用Matlab编制图形化界面,得到仿真结果的图形显示.
基于典型事例推理的路径规划方法研究%A Path Planning Algorithm Based on Typical Case Reasoning
Institute of Scientific and Technical Information of China (English)
翁敏; 魏秀琴; 瞿嵘; 蔡忠亮
2009-01-01
Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people's preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be? How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them? All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and com-pletely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.
Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D
2016-08-01
Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.
Collision-Free Path Planning for Manipulator Based on the Grid%基于网格法的机械臂无碰撞轨迹规划
Institute of Scientific and Technical Information of China (English)
鲁守银; 韩佳林
2014-01-01
This article describes a method of high voltage operation mechanical arm trajectory planning of collision-free in three-dimensional space. By mesh partition the whole workspace, a complete description of the free space and the obstructions space is made. And each grid is corresponding to an index. Then in the search path which used A*algorithm can be quickly and accurately get the best collision-free path and reduced the running time of the system.%介绍了高压带电作业机械臂在三维空间中进行无碰撞轨迹规划的一种方法，通过对整个作业空间进行网格化划分，完整的描述出自由空间与障碍物空间，并对每一个网格进行索引对应，使其在利用 A*算法搜索路径是可以迅速准确的得到最优的无碰撞路径，减少系统的运行时间。
面齿轮齿面检测路径规划方法研究%Research on Measuring Path Planning of Face Gear Tooth Surface
Institute of Scientific and Technical Information of China (English)
丁志耀; 张俐; 李东升; 王延忠
2011-01-01
Based on the theory of path planning in the measuring process, three different methods, namely routine method, longitudinal method, transverse method, were presented for the measurement of face gear tooth surface. The total journeys of three paths were calculated, and the gear was measured on CMM. According to the comparison between theoretical calculation and experiment, it is proved that the routine method and transverse method are both feasible in the practical measurement, but the latter is better in both speed and efficiency.%针对面齿轮齿面检测,根据检测过程中路径规划的原理,提出采用3种不同方法(常规方法、纵向法、横向法)规划路径,分别计算其相对应的测头测量总行程,并在三坐标测量机上进行齿面检测试验.比较理论计算的结果及试验结果,表明常规方法和横向法在实际检测试验中都是可行的,但后者更为快速、高效.
Indoor path planning for seeing eyes robot based on RFID%基于RFID技术导盲机器人室内路径规划的研究
Institute of Scientific and Technical Information of China (English)
陈超; 唐坚; 靳祖光
2013-01-01
为了辅助视力障碍者在室内行走及寻物,以自主设计的导盲机器人为实际应用背景,提出一种适用于室内导航的算法.该路径规划算法利用射频识别(radio frequency identification,RFID)系统,将基于RFID系统的三角定位思想与A*搜索算法相结合,在提高搜索效率的同时保证了规划路径的可行性.通过在平面障碍物环境下实验,验证了该算法的可行性.%In this paper, we presents a new indoor path planning algorithm for seeing eyes robot using the RFID system. The algorithm combines the idea of triangle positioning with A * algorithm, which not only improves the efficiency of searching but also guarantees the feasibility of the path at the same time. The simulation outcomes and field tests verify the effectiveness and feasibility of the method.
基于A*算法的智能轮椅的路径规划%The Path Planning for an Intelligent Wheelchair Based on A*Algorithom
Institute of Scientific and Technical Information of China (English)
周晶; 曹国华; 翟娟
2014-01-01
文章研究提取智能轮椅所处位置的环境信息，并对其进行可视图化。基于Matlab平台，利用A*算法对可视图进行分析，建立合理的估价函数，进而对智能轮椅进行路径规划，实现智能轮椅避障的最优路径设计。%The paper studies the extraction of the environment information about the position the intelligent wheelchair is located and makes a diagram about it. Based on the Matlab platform and using the A*algorithm the diagram is analyzed, and a reasonable evaluation function is established, in order to achieve a good path planning and obstacles avoidance for the intelligent wheelchair.
DEFF Research Database (Denmark)
Hameed, Ibrahim; la Cour-Harbo, Anders; Osen, O. L.
2016-01-01
Automated path planning is important for the automation and optimization of field operations. It can provide the waypoints required for guidance, navigation and control of agricultural robots and autonomous tractors throughout the execution of these field operations. In agriculture, field...... the machine rolls on slopes the effective width of the implement decreases by a similar amount to double this error and complicates the problem. In this paper, a numerical approach to estimate the total skip and/or overlap areas is developed and applied to determine the optimum driving angle which minimizes...... experimental fields of uneven terrain nature. The proposed approaches illustrated that a significant percentage of uncovered area could be saved and used if appropriate driving angle is chosen and if a side-to-side 3D coverage is used....
Search path planning of unmanned aerial vehicles based on game theory%基于博弈论的无人机搜索路径规划
Institute of Scientific and Technical Information of China (English)
杨少环; 高晓光; 符小卫
2011-01-01
现阶段的无人机搜索路径规划主要以区域覆盖率以及搜索时间为指标,缺乏对目标运动行为的综合利用.本文以敌我双方为局中人,把敌我双方可能的行为作为策略集,建立博弈论模型,通过求解Nash均衡改进扫描式搜索路径规划算法.仿真表明,基于博弈模型的规划算法较改进前不仅能够满足对待搜索区域的完全覆盖,而且提高了无人机的任务完成率,说明了该算法的有效性.%The regional coverage and the search time are used as the evaluation index for search path planning of unmanned aerial vehicles (UAV) at present, which leads to the lack of utilization of the target behaviors. A game theory model, which takes both parties in the struggle as the players and uses the behavior of both parties as the strategy set, is established. By solving the Nash equilibrium of the model, the scanning algorithm for the search path planning is improved. Simulation results, which demonstrate that the improved algorithm can not only match the needs to completely cover the search area, but also improve the completion rates of UAV task, illustrate the effectiveness of the algorithm.
Path planning of UAV in water environmental monitoring%无人机在水环境监测中的航迹规划
Institute of Scientific and Technical Information of China (English)
孟庆志; 李平
2012-01-01
无人机在水环境监测中,受其物理性能和风险因素影响无法一次性的对所有区域进行监测,充分发挥无人机的使用效率变得极为重要.提出了无人机在水环境监测中的最优航迹规划问题,建立了该问题的数学模型,在此基础上提出了一种基于遗传-模拟退火优化算法,采用网格空间表示与方向编码相结合的方法减小了计算量.仿真实验结果表明:该方法能够得到比遗传算法更优的解,可以有效解决无人机在水环境监测中的航迹规划问题.%In water environmental monitoring, unmanned aerial vehicle ( UAV ) can not monitor all the areas at a time due to the influence of its physical properties and risk factor. So it' s extremely important to bring the service efficiency of the UAV into full play. The optimal path planning problem of the UAV for water environmental monitoring is presented and a mathematic model of the problem is built up. On the basis of this, a genetic-simulation annealing algorithm is presented. The computational amount is decreased, a method combined of both grid space indication and directional code is adopted. The simulation test result indicates that this method can get a better solution than genetic algorithm and it can resolve the path planning problem of the UAV for water environmental monitoring effectively.
挠性航天器大角度姿态机动路径规划%Path planning for large angle attitude maneuver of flexible spacecraft
Institute of Scientific and Technical Information of China (English)
郑立君; 郭毓; 赖爱芳; 周端
2011-01-01
针对挠性航天器大角度姿态快速机动快速稳定的控制要求,通过分析挠性航天器姿态动力学特性,提出了一种基于抛物线型角加速度曲线的三段式机动路径规划算法.该算法考虑了机动过程中对最大角加速度与最大角速度限制,充分发挥执行机构的功能来提高系统的快速性,并使角加速度平滑变化以减小帆板的振动.该路径规划方法简单,适于在轨实现.仿真结果表明该路径规划算法能够明显提高机动快速性和姿态的稳定度.%In order to meet the control requirement of rapid maneuvering and rapid stable for flexible spacecraft with large angle attitude maneuver, a kind of there-segment slew path planning algorithm based on a parabolic angle acceleration curve was proposed by analyzing its dynamic characteristics. This algorithm considers the process of flexible spacecraft large angle attitude maneuver limited to maximal acceleration and maximal angular velocity, makes the most of actuator ability to improve the criterions of rapidly, and lets the acceleration variate smoothly to decrease the vibration of solar panel. The algorithm is simple and easy to be realized, suitable for implementation on orbit. Simulation results indicate that this path planning algorithm can significantly improve the criterions of rapidly, highstability degree of attitude and decrease the vibration of flexible panel.
模糊控制在移动机器人路径规划中的应用%Application of fuzzy control in mobile robot path planning
Institute of Scientific and Technical Information of China (English)
陈卫东; 李宝霞; 朱奇光
2009-01-01
针对移动机器人最优路径规划问题,设计了一种模糊智能控制方法.利用超声波传感器对机器人周围环境进行探测,得到关于障碍物和目标的信息.通过设计模糊控制器,把得到的障碍与目标位置信息模糊化,建立模糊规则并解模糊最终使机器人可以很好地避障,并且解决了模糊算法存在的死锁问题,从而实现了移动机器人的路径规划.仿真实验结果表明了模糊算法优于人工势场法,具有有效性和可行性.%For optimal design of mobile robot path planning problem,a fuzzy control method is designed.Using ultrasonic sensors to detect the surrounding environment will get the information of obstacles and goals.Through the design of fuzzy controller,fuzzy the obstacle and target location information,the establishment of fuzzy rules and fuzzy solution can make the robot obstacle avoidance in the end,and fuzzy algorithm solve the existence of deadlock problem,to achieve mobile robot path planning.The simulation results show that the fuzzy algorithm is superior to the artificial potential field method,with the effectiveness and feasibility.
Path Planning for Multi-robot Rescue System under Coal Mine%矿井中多机器人搜救系统路径规划
Institute of Scientific and Technical Information of China (English)
金纯; 王升刚; 尹远阳
2014-01-01
矿难发生后，井下通信设施可能已有一定的损害、无法正常使用，因而无法知道被困人员的确切位置并且井下环境复杂危险，可能对营救人员造成伤害发生二次事故。为了快速地搜索到被困人员，结合井下无线传播环境的特点，提出井下多机器人组网搜救系统，其中包括机器人自由空间环境模型的创建、机器人搜索的局部和全局路径的规划。利用MAKLINK图论理论对井下环境进行建模，并且采用Dijkstra算法规划出避障初始路径，最后依据距离改进蚁群算法节点选择得出优化的最终路径，完成搜索路径的规划。MATLAB仿真结果表明，优化的路径总长度明显优于初始路径并且改进的蚁群算法有着较好的收敛速度，可以满足多机器人搜救系统的要求。%Because communication facilities from underground are damaged and may not work normally after mine disaster,accu-rate position about trapped workers cannot be known.The dangerous environment may cause second accident and hurt rescue workers. To find out trapped workers quickly,the multi-robot rescue system was proposed combined with the characteristics of under coal mine wireless environment,including creation of a free space model for robot,global and local path plan for multi-robot rescue system.The MAKLINK graph theory was used to establish the free space model of the mobile robot,and then Dijkstra algorithm was utilized to find a sub-optimal collision-free path.Lastly,the improved algorithm based on distance to optimize the location of sub-optimal path was a-dopted to generate the optimal path of the mobile robot.The result of MATLAB simulation experiment shows that the proposed algorithm has a better performance in convergence speed and matches to the multi-robot rescue system.
Study on Battlefield and Threat Modeling for UAV Path Planning%无人机路径规划中的环境和威胁模型研究
Institute of Scientific and Technical Information of China (English)
高晓静; 陈晓峰; 智勇
2013-01-01
In order to improve the penetration ability of UAV,it needs to estimate threat environment in battle environment,which is associated with the risk of aircraft detection by radars or similar sensors in path planning,and utilizes more'knowledge include the location and strength of threats within the UAV's sensory range.To solve the problem of unmanned aircraft vehicle flight path and waypoint generation is crucially depended upon modeling ways of airspace,include environment and threat modeling.Unfortunately,the methods of modeling is lack of systemic arguments.First of all,it analyzes the ways of battlefield environment modeling in this paper,mainly aimed at the discrete models.Additionally,according to different types of threat that UAV maybe encounter in flying process,it establishes the threat risk model.That's all to prepare for development of algorithm for real-time path planning of UAVs on parameter-level.%为了提高无人机执行任务时的突防能力,在进行飞行路径规划时必须对战场环境中的威胁环境进行评估,而威胁环境中的威胁估计与飞机被雷达或类似的传感器探测出的风险度有关,需要考虑的信息包括无人机传感器范围内的威胁位置和强度.路径规划算法依赖于路径规划空间的建模方式,包括环境建模和威胁源建模.目前针对规划空间环境和威胁模型的建模方法缺乏系统分类和论述.分析了战场环境的建模方法,研究了规划空间的离散建模方式,根据无人机飞行过程中可能遭遇的威胁类型进行威胁源类型的划分,并针对三种威胁类型分别建立威胁风险模型,为无人机在复杂环境下的路径规划实现做了参数准备.
个体机器人局部路径规划的人工力矩方法%Artificial moment method for local path planning of single robot
Institute of Scientific and Technical Information of China (English)
徐望宝; 陈雪波; 赵杰
2012-01-01
For the local path planning of single robot,two new concepts,optimal way representative point and dangerous wall representative point,are defined for path optimization and obstacle-avoidance.A new attraction moment function to make robot′s principal motion direction line（PMDline） face to the present optimal way representative point in general and a new repulsion moment function to make robot′s PMDline away to the corresponding dangerous wall representative point are designed.Then,a motion controller is designed based on the two artificial moments.As the controller will make robot move along its PMDline with its longest step length when the line segment between robot and target is blocked by obstacles,robot will not be trapped even in complicated environments.The algorithm for optimal way representative points,the general steps for the path planning and a simulation are also given.The simulation results indicate that the proposed method is of feasibility and validity.%针对个体机器人的局部路径规划问题,定义了最优路径代表点、危墙代表点等概念,以优化路径和避障.设计了吸引矩、排斥矩两种人工力矩函数,其中吸引矩常使机器人的基本运动方向线（PMDline）指向最优路径代表点而排斥矩则总使机器人的PMDline背向相应的危墙代表点.基于两种人工力矩,设计了机器人运动控制器.在机器人通向目标的路径被障碍阻断时,该控制器总使机器人沿其PMDline以最大步幅运动,所以无论环境多复杂,机器人也不会停止运动,即不会被陷住.还给出了最优路径代表点的求解算法、局部路径规划的一般步骤及一个仿真.仿真结果表明,给出的方法是可行且有效的.
Vrooijink, Gustaaf J.; Abayazid, Momen; Patil, Sachin; Alterovitz, Ron; Misra, Sarthak
2015-01-01
Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle). PMID:26279600
Using Hierarchical Folders and Tags for File Management
Ma, Shanshan
2010-01-01
Hierarchical folders have been widely used for managing digital files. A well constructed hierarchical structure can keep files organized. A parent folder can have several subfolders and one subfolder can only reside in one parent folder. Files are stored in folders or subfolders. Files can be found by traversing a given path, going through…
Converse path planning for anti-ship missiles based on operational area%基于功能区域的反舰导弹逆向航路规划
Institute of Scientific and Technical Information of China (English)
刘钢; 老松杨; 谭东风
2011-01-01
In order to describe the planning space of path planning quantitatively, the concept of operational area of anti-ship missiles path planning is put forward based on geometric principle, and the geometrical essence of path planning is unearthed. Then the tactical significance of operational areas is deeply analyzed, and based on this concept, the method of converse path planning is put forward. The process of converse path planning reveals the geometric gradual transformation rule of operational areas, and increases the efficiency for the extension of path points. Barriers are evaded by polar extending, which can build a better path tree. Finally the required path is searched by the method of multi-attribute fuzzy optimization. Simulation results indicate that the proposed algorithm has fewer computation load, higher computing rate, and the calculated path accords with the flight characteristics of anti-ship missiles, which is close to practice of project application.%为了定量描述航路规划的规划空间,基于几何学原理提出了反舰导弹航路规划功能区城的概念,发掘出了航路规划的几何学本质.深入分析了航路规划功能区域的战术意义,并基于此概念进一步提出了一种逆向航路规划方法.逆向航路规划过程揭示出了航路规划功能区域的几何学渐变规律,为航路点的扩展提高效率.通过极线扩展进行障碍规避,得到较优航路树.最后使用多属性模糊优化方法搜索到所需航路.仿真结果表明,该方法信息处理量小,运算速度快,所得航路符合反舰导弹的航路特征,十分贴近工程应用实际.
Morris, J. F.; Merrill, O. S.; Reddy, H. K.
1981-01-01
Thermionic energy conversion (TEC) is discussed. In recent TEC-topping analyses, overall plant efficiency (OPE) and cost of electricity (COE) improved slightly with current capabilities and substantially with fully matured technologies. Enhanced credibility derives from proven hot-corrosion protection for TEC by silicon-carbide clads in fossil fuel combustion products. Combustion augmentation with TEC (CATEC) affords minimal cost and plant perturbation, but with smaller OPE and COE improvements than more conventional topping applications. Risk minimization as well as comparative simplicity and convenience, favor CATEC for early market penetration. A program-management plan is proposed. Inputs, characteristics, outputs and capabilities are discussed.
Morris, J. F.; Merrill, O. S.; Reddy, H. K.
Thermionic energy conversion (TEC) is discussed. In recent TEC-topping analyses, overall plant efficiency (OPE) and cost of electricity (COE) improved slightly with current capabilities and substantially with fully matured technologies. Enhanced credibility derives from proven hot-corrosion protection for TEC by silicon-carbide clads in fossil fuel combustion products. Combustion augmentation with TEC (CATEC) affords minimal cost and plant perturbation, but with smaller OPE and COE improvements than more conventional topping applications. Risk minimization as well as comparative simplicity and convenience, favor CATEC for early market penetration. A program-management plan is proposed. Inputs, characteristics, outputs and capabilities are discussed.
Path Planning for Mobile Robot and Simulation%移动机器人的路径规划与仿真
Institute of Scientific and Technical Information of China (English)
高晓巍
2013-01-01
During the process of applying particle swarm optimization in mobile robot' s path programming,we found some problems,such as the weakening ability of whole searching,the easily occurring phenomenon of earlymature.Then this paper put forward a better algorithm based on QPSO.The advantages of the QPSO algorithm based on 8potential model are simple model,less control parameters,stronger ability of whole searching.But at the same time,there is the disadvantage of early-maturing convergence.The paper took the perspective of diversity of population to analyze how to introduce diversity function in the iteration process of the algorithm.When the diversity of population is less than dlow,we made adaptive adjustment by diversified manipulating to sustain individual difference.In this way we can avoid the algorithm falling into local optimum and then leading to the premature phenomenon.After making simulation experiment wirh MATLAB,the findings show that this algorithm can effectively solve the programming problem of the whole static path.Compared with the QPSO algorithm,the convergence speed and searching quality have been obviously improved.%在机器人路径优化设计的研究中,由于应用环境存在障碍物,要求寻找最优无碰路径.针对于粒子群优化算法应用于移动机器人路径规划计算中,存在全局搜索能力弱,易出现早熟现象等问题,提出了一种QPSO算法的改进算法.采用8势阱模型的QPSO算法模型简单,控制参数少,全局搜索能力强,但存在早熟收敛的缺陷,从种群的多样性角度分析,在算法的迭代过程中,引入多样性函数,在种群的多样性小于dl.时,由多样性变异操作进行自适应调整,保持了种群中个体的差异性,避免算法陷入局部最优而出现早熟现象.在MATLAB平台上进行仿真,结果表明,改进算法能够有效地解决全局静态无碰路径优化问题,收敛速度、搜索质量与QPSO算法相比明显提高.
The Shortest Path with Intelligent Algorithm
Directory of Open Access Journals (Sweden)
Surachai Panich
2010-01-01
Full Text Available Problem statement: Path planning algorithms need to be developed and implemented in a suitable manner to give better understanding about the intelligent system and also stimulates technological supply to enormous demands in an intelligent vehicle industry. Approach: This study concerned with intelligent path planning using A* search algorithm. Results: This study introduced intelligent path planning with A* search algorithm, which use to generate the most efficient path to goal. The algorithm was tested on simulator. Conclusion: This study is an implementation of a path planning for an intelligent path planning. The implementations are tested and verified with the simulation software. The path planning algorithms were selected for the implementation and to verify them.
A Plan Recognition Technique Based On Critical Path Method%基于统筹法的规划识别技术
Institute of Scientific and Technical Information of China (English)
钱月梅
2012-01-01
To identify a agent’s plan swiftly is a tough work. Each different kinds of relation between the actions which happened or happening wil lead to another conclusion and, it is keep changing from the begging to the end. Here is a new approach to recognize this changing plan which based on the thinking of the Critical path method and, the introduction of temporal relation is the key to this solution. The optimal arranging of job in the real word is a basic rule of Critical path method, with this ideal we can proposed this method into the Keyhole plan recognition, continuing optimize the solution space, then we can obtain a instant answer swiftly. At the end, we use ontology technology constructed a model which can represent the temporal relations between the actions and prescribed the process procedure in an algorithm.% 通常快速地确定一个Agent的规划是很困难的,Agent的不同行为之间由于时态关系的不同而将导致的结果也是复杂多变的。这里提出一种新的基于统筹法的规划识别方法,引入时态关系,结合统筹法思想中对事件发生次序的优化安排原则,对锁眼型规划识别中的目标Agent的行为进行规划预测,并及时对预测空间状态进行调整,从而达到快速规划的目的。在这种识别方法的实现过程中给合本体技术,构建了一种关系模型,将时态与事件相结合,最后通过算法对其识别过程进行描述。
基于 Fast Marching 方法的多目标点路径规划的研究%Research on Multi-target Path Planning Based on Fast Marching Method
Institute of Scientific and Technical Information of China (English)
于晖; 王永骥
2015-01-01
This paper proposed a new path planning method by combining Multi-Direction Fast Marching (MDFM) method and genetic algorithm (GA)to resolve the multi-targets path planning for autonumous underwater robotic fish to mo-nitor the water quality.First,MDFM method was used to plan the point-to-point path among multiple targets;second the final optimal path to travel all the targets was planned by GA;at last,the simulation experiment shows that our method is feasible.%目前，水下自主机器鱼已经被应用于对水域多个目标点依次进行水质监测，因此有必要研究多个目标点的路径规划。针对遍历多个目标点的路径规划问题，提出一种 Multi-Direction Fast Marching (MDFM)方法和遗传算法相结合的路径规划方法。该方法首先使用 MDFM 方法对工作站和多个目标点两两之间进行路径规划，然后使用遗传算法规划出遍历所有点的最短路径，最后通过仿真实验验证算法的可行性。
Robot path planning in environment of many terrains%多地貌环境下的移动机器人路径规划研究
Institute of Scientific and Technical Information of China (English)
巩敦卫; 耿娜; 张勇
2012-01-01
针对多地貌环境下的移动机器人路径规划问题,建立多目标优化模型,并采用微粒群算法解决该问题.首先,采用区域权值表示机器人在各种地形下的通行困难度;然后,结合局部优化准则计算机器人的通行时间,通过计算机器人与危险源之间覆盖的面积来衡量路径的危险程度,并将上述问题转化为两目标优化问题;最后,采用多目标微粒群优化算法优化上述问题.仿真结果表明了所提出方法的有效性.%For the problem of robot path planning in an environment of many terrains,mathematical model of multi-objective is established.Particle swarm optimization algorithm is used to solve the problem.Firstly,region weight is used to represent the difficulty when the robot passes through the terrain.Then passage time is calculated by utilizing local optimal criterion,and the danger degree is calculated according to the area between the danger sources and the robot＇s path.Thus the problem can be converted into a bi-objective problem.Finally,particle swarm optimization algorithm is used to optimize the problem above,and the simulation results show the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Amol M. Dalavi
2016-07-01
Full Text Available Optimization of hole-making operations in manufacturing industry plays a vital role. Tool travel and tool switch planning are the two major issues in hole-making operations. Many industrial applications such as moulds, dies, engine block, automotive parts etc. requires machining of large number of holes. Large number of machining operations like drilling, enlargement or tapping/reaming are required to achieve the final size of individual hole, which gives rise to number of possible sequences to complete hole-making operations on the part depending upon the location of hole and tool sequence to be followed. It is necessary to find the optimal sequence of operations which minimizes the total processing cost of hole-making operations. In this work, therefore an attempt is made to reduce the total processing cost of hole-making operations by applying relatively new optimization algorithms known as shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm for the determination of optimal sequence of hole-making operations. An industrial application example of ejector plate of injection mould is considered in this work to demonstrate the proposed approach. The obtained results by the shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm are compared with each other. It is seen from the obtained results that the results of proposed modified shuffled frog leaping algorithm are superior to those obtained using shuffled frog leaping algorithm.
Institute of Scientific and Technical Information of China (English)
魏瑞轩; 许卓凡; 王树磊; 吕明海
2015-01-01
In order to relieve the operation burden and time consume for unmanned aerial vehicle (UAV) path planning,a novel UAV path planning method named LA-Star algorithm is proposed which as well guaran-tees the adaption in scenarios of various threat areas and terrains.Under the roundness assumption of all threat areas and no-fly-zones,the Laguerre diagram algorithm is applied to pre-plan the flight path which largely bene-fits path re-plan because of shrunk operation space.With the original shape of threat areas,improved A-Star al-gorithm is then applied in path re-planning with reference to pre-planned path.Finally,optimize the path planned above.Simulations show the LA-Star algorithm satisfies time and veracity requirements.%为了降低无人机航路规划的运算量，减少规划时间，确保算法对于任意形状威胁区域和地形的适应性以及所规划航路的准确性，提出了一种新颖的 LA-Star 算法用于无人机航路规划。首先把威胁区域和禁飞区域简化为圆形，利用 Laguerre 图算法进行航路预规划，在此基础上简化二次规划空间的范围，之后恢复威胁区域和禁飞区域的真实形状，在简化后的规划空间内使用改进 A-Star 算法实施二次航路规划，最后对生成的航路进行自优化处理。仿真结果证明了 LA-Star 算法满足航路规划的实时性和准确性要求。
威胁联网下无人机路径在线规划%Exploring Further UAV On-Line Path Planning in the Presence of Threat Netting
Institute of Scientific and Technical Information of China (English)
田阔; 符小卫; 高晓光
2011-01-01
Aim. The introduction of the full paper reviews a few papers in the open literature and then, in its fourth paragraph, outlines our further exploration, which is explained in sections 1 through 4. Section 1 is entitled threat netting; its core is that we treat a fire unit as threat and analyze the influence of threat netting on the radar scanning area of the fire unit and its kill area and the effects of threat netting on on-line path planning. Section 3 is entitled threat netting model; its core consists of: (1) we propose the target instruction probability suitable for threat netting; (2) we establish a simplified threat netting model based on UAV' s probability of detecting threats. Section 4 is entitled threat cost model; its core consists of: (1) we define the time needed for a radar to track UAV as the threat time window according to the radar response time and missile flyout time; (2) we use the maximum minimization concept in Ref. 8 to derive the threat cost objective function, which is given in eq. (11). Section 5 uses the model predictive control (MPC) algorithm to simulate the effects of threat netting on the on-line path planning of UAV; the simulation results, given in Figs. 2 through 6, and their analysis show preliminarily that our on-line path planning in the presence of threat netting can help UAV dodge threats and reduce its kill probability, thus being more effective and reasonable than other methods.%文章以火力单元为威胁建立威胁联网模型,分析了威胁联网对火力单元的雷达扫描区和杀伤区的影响,以及威胁联网对路径规划的影响;针对威胁联网下各主动威胁进行信息交流与资源共享的模式,提出了适用于威胁联网的目标指示概率,并以威胁对无人机的探测概率为基础,给出了简化的威胁联网模型.根据雷达响应时间和导弹外部飞行时间提出了威胁时间窗概念,并结合威胁联网模型改进了威胁代价目标函数.最后运用模型
Dynamic differential evolution algorithm for swarm robots search path planning%复杂环境移动群机器人最优路径规划方法
Institute of Scientific and Technical Information of China (English)
徐雪松; 杨胜杰; 陈荣元
2016-01-01
研究了一类复杂环境下移动群机器人的建模与控制策略.采用栅格法对机器人工作环境进行建模,基于个体的有限感知能力和局部的交互机制设计了响应概率函数,解决群机器人任务分配与信息共享难题.通过施加螺旋控制于早期信号搜索,并将该搜索信息作为启发因子改进动态差分进化算法,对群机器人进行路径优化.仿真结果表明,当响应概率函数中距离变量调节因子β=0.006时,任务分配控制算法达到最好效果.同时,移动群机器人路径规划的平均路径长度ˉS,平均移动时间Tˉ以及平均收敛代数Mˉ,相比扩展PSO算法分别提高了16%、57%及230%.最后,将该算法应用于AS-UⅢ型轮式移动群机器人物理实验,并设计了协同控制平台,具有较好的工程应用价值.%A novel optimization algorithm based on differential evolution is proposed in this paper .The modeling and the control strategies of swarming robots for search planning in a complex environment are discussed .Grid method is used for robot working environment modeling .The response probability function is designed based on in-dividual's limited cognitive ability and local interaction mechanism , which can solve the problem of the swarm robot task allocation and information sharing.Robots moving spirally to search cues can offer evidence for using dynamic differential evolution algorithm to search target optimally.The simulation results show that when the response proba-bility function distance variable regulating factorβ=0.006, task allocation control algorithm can achieve the best effect .At the same time , the mobile robot path planning group of average path length , average moving time and av-erage convergence algebraic extension compared to PSO algorithm is enhanced by 16%, 57% and 230% respec-tively.This algorithm is introduced to AS-UⅢ wheel mobile robots real experiments and illustrated its engineering application value.
动态未知环境下一种新的机器人路径规划方法%A new path planning for robot in dynamic and unknown environments
Institute of Scientific and Technical Information of China (English)
白金柯; 陈立家; 金何; 陈瑞霞; 毛海涛
2011-01-01
Aiming at the dynamic path planning problem of robot,a new method which implements real-time path planning of mobile robot in complex dynamic environment is proposed. This method is based on path planning and obstacle avoidance strategy for rolling windows,according to visible point sub-goal setting,obstacle detour,analysis and forecast for moving obstacle, path planning for robot in complex dynamic environment is realized. Aiming at obstacles distribution, reasonable design on exchange between visible point and circumvent algorithm based on the obstacle distribution state, this could resolve infinite loop and minima problem that happened in local path planning. This proposed method is suitable for dynamic environment that both convex and concave obstacle exist. Simulation result proves its validity and feasibility.%针对机器人动态路径规划问题,提出了一种机器人在复杂动态环境中实时路径规划方法.该方法基于滚动窗口的路径规划和避障策略,通过设定可视点子目标、绕行障碍物和对动态障碍物的分析预测,实现机器人在复杂动态环境下的路径规划.针对障碍物分布情况,合理设计可视点法和绕行算法之间转换,有效地解决了局部路径规划的死循环与极小值问题.该方法用于凸形障碍物、凹形障碍物共存的动态环境,仿真结果证明了该方法的有效性和可行性.
Institute of Scientific and Technical Information of China (English)
刘伟; 郑征; 蔡开元
2012-01-01
A smooth real-time path planning approach is proposed based on the bilevel programming (BLP) for unmanned aerial vehicles (UAVs) in complex environments, to improve the flight path smoothness which has not been achieved by most existing methods. Firstly we define the measure for the path smoothness, and then we build the model for the bi-level decision objectives, the model of obstacle avoidances and the model of performances of the UAV, and introduce a variable planning time interval. On this basis, we proceed to develop the path planning model based on the bi-level decision. In the process of the planning, we introduce heuristic optimal strategies to further improve the smoothness for the local path and the global path, and to raise the efficiency in path searching. Results from simulations of the proposed approach in complex scenarios are compared with those obtained from classical methods; the conclusions indicate that the proposed approach can successfully plan a shorter and smoother flight path in real-time when passing around a wide dangerous region.%针对无人机实时路径规划问题,提出了一种基于双层决策的平滑路径规划方法,以弥补现有方法在复杂飞行环境中对路径平滑性优化的不足,增强路径的易跟踪性.本文首先给出路径平滑性度量,然后建模上、下层决策目标、威胁规避与无人机性能约束并引入变长规划时间,进而设计基于双层决策的路径规划模型.规划过程中通过嵌入启发式优化策略来进一步改善路径的全局与局部平滑度,并提高路径搜索效率.大量复杂场景中的仿真及与现有经典方法的对比结果表明:该方法能够实时避开复杂危险区域,规划适合飞行的、较短的平滑路径.
Institute of Scientific and Technical Information of China (English)
张纯刚; 席裕庚
2003-01-01
本文研究了一般障碍环境下全局信息未知的机器人路径规划问题,分析了基于实时探测信息的滚动路径规划算法可能遇到的振荡和死循环现象,提出了增加适量记忆的改进滚动路径规划算法,不仅有效地克服了振荡和死循环的发生,而且保证了机器人对全局目标的可达性,为移动机器人在一般未知障碍环境下的路径规划提供了快速、有效的方法.%Robot path planning in a globally unknown environment with general obstacles is studied in this paper. Oscillation and dead circulation possibly encountered in rolling path planning are studied. And an improved planning method is proposed by storing detected environmental information. The planning method could prevent mobile robot from oscillation and dead circulation efficiently and guarantee the accessibility to the global goal. It is a fast and effective path planning method for mobile robot in an unknown obstacle environment.
Institute of Scientific and Technical Information of China (English)
傅阳光; 周成平; 胡汉平
2012-01-01
To investigate the path of unmanned aerial vehicle ( UA) in ocean environment, a method based on the differential evolution(DE) is proposed. It pretreats the planning environment and takes all islands as threatened areas, the path planning problem is simplified as a two-dimensional planning problem. A real number coding is used to represent the candidate paths, and a mathematical model of path cost is established. The performance of differential evolution algorithm is compared with that of genetic algorithm ( GA) and particle swarm optimization ( PSO) in terms of path quality, robustness and convergence speed. The experimental results demonstrate that the proposed method is able to generate a safe and flya-ble path for UAV in a complex ocean environment.%为研究海洋环境下的无人飞行器(UAv)航迹规划问题,提出了一种基于差分进化算法(DE)的航迹规划方法.该方法通过对规划环境进行预处理将岛屿处理成地形威胁区,使问题简化为二维平面规划.采用实数编码方式对航迹进行编码,建立了航迹代价函数的数学模型,从航迹质量、算法稳定性和收敛速度3个方面比较了DE与遗传算法(GA)和粒子群优化算法(PSO)的性能.仿真实验结果表明,所提方法能在复杂的海洋环境下为飞行器规划出一条安全的可飞航迹.
An algorithm for the path-planning with multiple constraints%一种多约束条件下路径规划算法研究
Institute of Scientific and Technical Information of China (English)
李汉轩; 李志华; 吕春生
2012-01-01
针对目前导航系统中重要的多约束条件下路径规划功能,结合A＊算法和蚁群算法提出一种新的不确定算法,该算法首先将多约束条件进行融合使其适合蚁群转移,并在基本蚁群算法基础上采用了A＊算法的评估指标,为蚁群转移时提供最优预测收敛点。通过实验证明该算法可以大幅度降低时间消耗,并且全局收敛性强,计算结果稳定。%In view of the important path planning function under multi-constraint conditions in current navigation systems,a new uncertainty algorithm is proposed which is the connection of A＊ algorithm and ant Colony algorithm.To adapt transfer of ant Colony algorithm,firstly,multiple constraints is integrated.Then,I took use of the concept of evaluation indicators in A＊ algorithm to get the optimal forecast convergence point for ant colony transfer.Basing on above operation,the results show that the algorithn has,strong global convergence,and substantially reduced time consumption.
Application of ALGA in Path Planning of Shore-Based Missiles%ALGA在岸基导弹航路规划中的应用研究
Institute of Scientific and Technical Information of China (English)
王光源; 汲万峰; 张非非; 章尧卿; 孙钧正
2012-01-01
针对基本遗传算法(GA)易局部收敛的缺陷,设计了基于模式搜索的自学习算子,提出一种基于模式搜索的自学习遗传算法(ALGA).通过仿真测试函数将ALGA与基本遗传算法、自适应遗传算法(AGA)进行比较,显示改进的ALGA提高了算法的综合搜索能力.将改进的ALGA运用到岸基导弹航路规划中,并进行仿真实验,仿真结果验证了改进算法的有效性.%The Genetic Algorithm(GA) has the shortcoming of easy to get into local convergence. To solve the problem, we designed a self-learning operator based on pattern search, and proposed an improved Genetic algorithm, Active Learning Genetic Algorithm (ALGA) with pattern search. Simulation test was made to compare ALGA with standard GA and Adaptive Genetic algorithm ( AGA), and the result showed that ALGA can enhance the general search ability. The ALGA was used in the shore-based missiles path planning and validated by simulation.
Energy Technology Data Exchange (ETDEWEB)
Chang, Pyung Hun; Park, Ki Cheol; Park, Suk Ho [Korea Advanced Institute of Science and Technology, Taejon (Korea)
1999-04-01
This project focuses on the development of the control system for a teleoperated redundant manipulator, which performs many tasks dexterously, while avoiding obstacles, instead of human workers in the extreme situations like nuclear power plants. To this end, four consecutive research works have been performed. First, two new methods for global path-planning have been developed to inspect the global behavior of the redundant manipulator. Second, characteristics of optimal solutions(COS) under inequality constraints have been analyzed and, using the COS, how to greatly enhance the conventional redundancy resolution methods in terms of performance and repeatability has also been proposed. Third, an effective control method for a redundant manipulator has been developed, which incorporates all kinds of physical limits into practical inequality constraints and is computationally efficient for real-time purposes. Finally, using this control method as the controller of the slave redundant manipulator and developing a master manipulator, the inertial torque and gravitation torque of which are negligible, a force-reflected teleoperation control system has been developed. Through the teleoperation control system, human operator can accurately control the position and the force of the end-effector of the slave manipulator while feeling the interaction force between the slave and the workpiece. In addition, the slave redundant manipulator autonomously can control the impedance and can optimize a given performance measure while avoiding physical limits such as joint angle limits and obstacles. 49 refs., 43 figs., 10 tabs. (Author)
基于在线支持向量机的无人机航路规划技术%Path Planning of UAVs Based on Online Support Vector Machine
Institute of Scientific and Technical Information of China (English)
李晓俊; 陈瑞
2013-01-01
研究了一种基于在线支持向量机的无人机航路规划方法,以保证无人机在完成任务时候能以最小的被发现概率以及最短航程安全到达目标点.首先建立多约束的无人机航路规划数学模型,并进行分析.应用A*算法产生初始航迹获取样本数据,在此基础上应用在线支持向量机具有在线训练、模型精确度高、需要样本少、泛化能力强等特点,实现无人机航路优化.最后将所研究的方法应用于无人机的航路规划仿真,仿真结果表明所研究的基于在线支持向量机的无人机航路规划方法是有效的.%A path planning method for Unmanned Aerial Vehicles (UAV) was proposed based on the onlineSupport Vector Machine ( SVM) to ensure UAVs reach the destination safely with the minimum probability of being found and through the shortest path. Firstly, the mathematic model was established and analyzed for the path planning of UAV considering the various constraints. The initial path was given by using A * algorithm to obtain the sample data for UAV. On the basis of the initial path, the online SVM, which has the features of online training, high precision model, small training sample and strong approximation ability, was employed to optimize the path of UAV. Finally, the path planning based on the online SVM was used to the simulation of path planning for UAV. The simulation results proved the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Mireille Bousquet-Mélou
2008-04-01
Full Text Available Let a and b be two positive integers. A culminating path is a path of ℤ 2 that starts from (0,0, consists of steps (1,a and (1,-b, stays above the x-axis and ends at the highest ordinate it ever reaches. These paths were first encountered in bioinformatics, in the analysis of similarity search algorithms. They are also related to certain models of Lorentzian gravity in theoretical physics. We first show that the language on a two letter alphabet that naturally encodes culminating paths is not context-free. Then, we focus on the enumeration of culminating paths. A step by step approach, combined with the kernel method, provides a closed form expression for the generating function of culminating paths ending at a (generic height k. In the case a = b, we derive from this expression the asymptotic behaviour of the number of culminating paths of length n. When a > b, we obtain the asymptotic behaviour by a simpler argument. When a < b, we only determine the exponential growth of the number of culminating paths. Finally, we study the uniform random generation of culminating paths via various methods. The rejection approach, coupled with a symmetry argument, gives an algorithm that is linear when a ≥ b, with no precomputation stage nor non-linear storage required. The choice of the best algorithm is not as clear when a < b. An elementary recursive approach yields a linear algorithm after a precomputation stage involving O (n 3 arithmetic operations, but we also present some alternatives that may be more efficient in practice.
DEFF Research Database (Denmark)
Thomadsen, Tommy
2005-01-01
of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...
Institute of Scientific and Technical Information of China (English)
赵仁青
2016-01-01
同心思想与最大同心圆理论是党的统战理论的最新发展，剥离其论证对象的差异，正确理解和运用这两大一脉相承的理论内涵，对从意识形态路径建构和谐的阶层关系具有重要的借鉴价值，即在全体人民中凝聚科学理性的阶层共识，树立舆论风向标，制定属于中国人自己的思想标准。共识是谋事的前提，凝聚阶层政治共识，同心同德，找到圆点，即始终坚持中国共产党的领导；凝聚阶层道路共识，同心同向，找到画圆方向，即坚定不移走中国特色社会主义道路；凝聚阶层价值共识，同心同行，找到画圆驱动力，即努力实现中华民族伟大复兴的中国梦。%The concentric thought and the theory of the biggest concentric circle are the latest theory of China Communist Party’s united front.The analysis of the differences between objects argued by the two and the correct understanding and application of the two in succession are of great referential value to construct harmonious hierarchical relationships from ideological perspective.Specifically,we need to build a scientific and rational consensus for hierarchy among all the people,set up public opinion indicators and establish the ideological criteria specified for the Chinese people.Consensus is the prerequisite for decision making.To build political hierarchical consensus,pool joint efforts and work around the same center are to adhere to the leadership of CPC;to build the consensus for hierarchical pathway,work around the same center and towards the same goal are to steadfastly follow the path of socialism with Chinese characteristics;to build the hierarchical value consensus, work around the same center and march forward together and locate the driving force for drawing the circle are to achieve the Chinese Dream of realizing the great rejuvenation of Chinese nation.
一种三维环境中的无人机多路径规划方法%A Multi-Path Planning Method for Unmanned Aerial Vehicle (UAV) in 3D Environment
Institute of Scientific and Technical Information of China (English)
刘洋; 章卫国; 李广文; 史静平
2014-01-01
In order to solve the problems existing in the multi-path planning for UAV in the 3D environment, we improve the probability roadmap method ( PRM) by moving the sampling points to increase their number in their narrow passage so that the PRM can better serve the multi-path planning environment. Then we propose the multi-objective ant colony algorithm ( MACA) based on the PRM and apply it to the multi-path planning of the UAV. The MACA can optimize the path length and threat size of the UAV at the same time by updating their pheromones, thus obtaining a set of non-dominant solutions for the decision maker to select appropriate paths. To verify the effective-ness of the MACA, we simulate the multi-path planning environment as shown in Fig. 1; the simulation results, given in Fig.4 and 5 and Tables 1 and 2, and their analysis show preliminarily that our MACA based on PRM serves the 3D multi-path planning environment very well and can obtain a set of non-dominant solutions and con-verge to optimal solutions quickly.%为了解决三维环境中的无人机多路径规划问题，提出了一种基于改进概率地图的多目标蚁群算法。在构建地图时为了增加窄通道中的采样点数量，改进了概率地图法的采样策略，将落在威胁上的采样点移动到自由空间中，可以更好地覆盖规划环境。为了使蚁群算法可以得到多个解，提出了一种多目标蚁群算法。通过引入Pareto解集，播撒不同种类的信息素，使蚁群算法可以同时优化路径长度和威胁大小2个目标，并能得到一组非支配解，有利于决策者选择合适的路径。仿真结果表明，改进的概率地图法可以更好地覆盖规划环境，多目标蚁群算法可以得到一组解，并能收敛到最终解集。
Hierarchical Multiagent Reinforcement Learning
2004-01-25
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In
Institute of Scientific and Technical Information of China (English)
赵著行; 闵应骅; 等
1997-01-01
For different delay models,the concept of sensitization can be very different.Traditonal concepts of sensitization cannot precisely describe circuit behavior when the input vectors change very fast.Using Boolean process aporoach,this paper presents a new definition of sensitization for arbitrary input waveforms.By this new concept it is found that if the inputs of a combinational circuit can change at any time,and each gate's delay varies within an interval (bounded gate delay model),then every path,which is not necessarily a single topological path,is sensitizable.From the experimental results it can be seen that,all nonsensitizable paths for traditional concepts actually can propagate transitions along them for some input waveforms.However,specified time between input transitions(STBIT) and minimum permissible pulse width(ε）are two major factors to make some paths non-sensitizable.
Institute of Scientific and Technical Information of China (English)
彭松; 贾阳
2012-01-01
In the tele-operation system of lunar rover,the path planning contains three levels： mission-level path planning,global path planning and local path planning.Based on the requirements of the global path planning of the lunar rover,the Particle Swarm Optimization（PSO） algorithm is introduced in the global navigation point planning.Since the PSO algorithm may converge ill or not converge in path planning, the algorithm is modified.In the modified algorithm,the velocity inertial weight is deleted,but the cognitive and social coefficients are kept,with the aim at making the algorithm converge quickly in path planning.Also the variation coefficient in evolution algorithm is imported to enhance the global optimization ability.Simulation results show the improved algorithm is simple and has high ability to find the best path.Also simulation tests are done in several different simulated lunar terrain maps,and optimization methods are given to make the planning result better.%在月面巡视器遥操作系统中,路径规划分为任务级路径规划、全局路径规划和局部路径规划。根据巡视器全局路径规划的应用要求,引入粒子群优化算法应用于全局导航点的规划。针对粒子群算法在路径规划中容易造成不收敛或病态收敛的问题,对算法进行了修改,去掉了速度更新中的速度惯性因子,只保留自身认识因子和社会认识因子,使其在全局路径规划中能够快速收敛;同时引入经典遗传算法中的变异因子以增强算法的全局优化能力。仿真结果表明该算法具有计算简单、全局寻优能力强等特点,能够快速地找到优化的全局导航点。同时在不同的模拟月面地形上进行仿真试验,针对存在的问题提出了对应的二次优化方法,结果表明该方法较好地满足了巡视器全局路径规划的应用需求。
基于遗传算法的多边形分割AUV全局路径规划%Genetic algorithm based on polygon segmentation AUV global path planning
Institute of Scientific and Technical Information of China (English)
李建文; 李沙沙
2013-01-01
Appear in the actual AUV global path planning applications for genetic algorithm computed data,path planning issues such as spikes,a new path planning method is proposed.Plane rectangular coordinate system environment modeling obstacle simplified polygon is divided into triangles.End-to-end path segment,the fixed abscissa,ordinate randomly generated binary-coded genetic algorithm obstacle triangle intersection determination,the path from the operation prepared by the applicable function.After genetic path through the obstacle avoidance,delete nodes,smooth operation to determine the final optimization path.Results show that the simplified implementation obstacles triangle program optimization in genetic operation,use of obstacle avoidance,remove redundant node,smooth operation,can very good eliminate peak,can find a relatively optimal path.%针对遗传算法在实际AUV全局路径规划应用中出现运算数据大、路径规划有尖峰等问题,提出了新型路径规划方法.利用平面直角坐标系实现环境的建模,将障碍物简化成多边形并分割为三角形.路径用首尾相接的线段表示,通过固定横坐标,随机生成纵坐标的方式实现遗传算法二进制编码,对障碍物三角形交叉判断,路径距离运算实现适用度函数编写.对遗传之后的路径通过避障、删除节点、平滑的操作确定最终优化路径.结果表明,对障碍物的三角形简化实现了在遗传操作中的程序优化,利用避障、删除多余节点、平滑操作实可很好的消除尖峰,可寻找一条相对较优的路径.
Institute of Scientific and Technical Information of China (English)
汪华兵
2015-01-01
A path planning algorithm of fire suppression is proposed based on multiple binary tree Pareto optimal solution set , the fire scene environment map and fire evolvement trend is reconstructed, realize the optimization of path, using the Pareto optimal solution set, the construction of fire fighting path planning model of dynamic development trend of multi tree Pareto optimal solution set based on the fire. The experimental results show that, the model can quickly achieve the recogni⁃tion of fire hot, and it can effectively avoid the interference of path planning in complex building of obstacles, to achieve the optimal path selection for fire fighting. In dynamic unknown environment, the fire fighting path planning and selection can achieve the optimal segmentation, shortest path is obtained, it can effectively avoid the stop complex building, effectively save the fire fighting time.%提出一种基于多叉树Pareto最优解集的火灾扑救路径规划算法，对火灾现场的环境地图和火灾演化态势进行重构，实现对路径的优选，采用Pareto最优解集，构建基于多叉树Pareto最优解集的火源动态发展态势下的火灾扑救路径规划模型。实验结果表明，该模型能快速实现对火源热点的识别，并且规划路径能有效规避复杂建筑障碍物的干扰，实现对火灾扑救路径的最优选择。在动态未知环境中，对火灾扑救路径的规划和选择能达到最优，路径最短，分段较少，能有效地避免复杂建筑物的阻挡，有效节省了火灾扑救时间。
DEFF Research Database (Denmark)
Thomadsen, Tommy
2005-01-01
Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...
Institute of Scientific and Technical Information of China (English)
王怿; 祝小平; 周洲
2012-01-01
提出了一种新的基于Clothoid曲线的无人机复合路径规划算法.该算法考虑了无人机在起点和目标点的方向以及无人机转弯半径的约束,能够在任意起止点位置和方向下得到更短的曲率连续的便于无人机飞行控制跟踪实现的Clothoid复合路径.与现有的基于微分几何的迭代算法相比,该算法迭代简单在给定范围内选择迭代初值,可以得到惟一解.%A new algorithm producing Clothoid composite path is proposed in this paper. A shorter path with continuous curvature which is easy to follow for UAVs can be obtained by this algorithm in any start and finish poses, with the constraints of the start and finish poses and the turning radius of UAV taken into consideration. Sections 1 through 3 of the full paper explain and evaluate the path planning algorithm mentioned in the title, which we believe is better than the existing differential geometry algorithm. The core of sections 1 through 3 consists of; ( 1) section 1 briefs Clothoid curve; ( 2 ) section 2 explains our path planning algorithm; for convenience, it is divided into two subsections (2. 1 and 2. 2); Figs. 1 and 2 are worth noticing; (3) section 3 evaluates our path planning algorithm ; simulation results are presented in Figs. 3 through 5; the simulation results and their analysis show preliminarily that, compared with the differential geometry algorithm, the proposed iteration algorithm is indeed simpler and the nonlinear equation has a unique solution by choosing the starting value in the starting interval.
Adaptive Path Planning of the UAV Based on Genetic Algorithm%基于遗传算法的UAV自适应航迹规划
Institute of Scientific and Technical Information of China (English)
王琪; 马璐; 邓会亨
2013-01-01
根据遗传算法与动态的稀疏A*搜索(Dynamic Sparse A* Search, DASA)算法各自的特点,提出一种组合优化算法来实现在不确定战场环境中自适应航迹规划。在无人机(UAV, Unmanned Aerial Vehicles)飞行前,采用全局搜索能力强的遗传算法进行全局搜索,对从起始点到目标点的飞行航线进行规划,生成全局最优或次优的可行参考飞行航线；在无人机任务执行阶段,以参考飞行航线为基准,采用 DASA 算法进行在线实时航迹再规划。仿真结果表明,与遗传算法相比,该组合算法不但能生成近似最优解,而且能够满足在线实时应用的要求。%According to the characteristics of genetic algorithm and the Dynamic Sparse A*Search (Dynamic Sparse A*Search, DASA) algorithm, this paper puts forward a combinational optimal algorithm fulfilling adaptive path planning in flying environment with unknown threat. Before flight, the ground station adopt genetic algorithm which possess the powerful ability of global search to realize Universal Search, we proceed programme from the starting point to the target point to generate the global optimal or suboptimal feasible reference airline. When the UAV is executing fly missions, DASA algorithm is used for on line route re planning based on the reference flight line as the benchmark. The simulation results show that compared with the genetic algorithm, the combined algorithm cannot only produce an approximate optimal solution, but also meet the requirements of real-time online application.
Institute of Scientific and Technical Information of China (English)
卢恩超; 张万绪
2013-01-01
When the obstacles are large, or the complex environment space is relatively narrow, Artificial Potential Field method (APF)is prone to appear repeated shocks, long time planning and obstacle avoidance of difficulty nearby the large obstacles. This paper presents an adaptive dynamic step length adjustment method based on the APF path planning which is combined with the edge detection method to overcome the proposed defects of APF, achieving mobile robot smooth path planning in the complex environment. Hence it can not only improve APF algorithm convergence speed and the safety of path planning, but at the same time ensure the approximate optimum path. Experiments are carried out by simulation to verify the effectiveness of the afore-mentioned methods.%针对移动机器人在有大型障碍物和运动空间相对狭窄的复杂环境中，人工势场法（APF）容易出现反复震荡、路径规划时间较长以及大型障碍物附近避障困难的问题，提出了在结合边缘探测法的APF路径规划基础上，加入自适应动态步长调整算法来克服APF的上述缺陷，实现移动机器人在复杂环境下的平滑路径规划，在确保路径近似最优的同时提高APF算法的收敛速度和路经规划的避障性能。实验结果证明了上述方法的有效性。
DEFF Research Database (Denmark)
Madsen, Mogens Ove
Begrebet Path Dependence blev oprindelig udviklet inden for New Institutionel Economics af bl.a. David, Arthur og North. Begrebet har spredt sig vidt i samfundsvidenskaberne og undergået en udvikling. Dette paper propagerer for at der er sket så en så omfattende udvikling af begrebet, at man nu kan...... tale om 1. og 2. generation af Path Dependence begrebet. Den nyeste udvikling af begrebet har relevans for metodologi-diskusionerne i relation til Keynes...
Institute of Scientific and Technical Information of China (English)
寇雪芹
2011-01-01
远程协同故障诊断的一个关键环节是诊断任务分配,而多个分解后诊断任务执行顺序确定也是诊断任务分配环节中不可避免的一个内容;基于D算法,建立了关键路径规划方法来进行诊断任务执行路径规划,包括最长和最短关键路径规划算法；从诊断任务模型自身出发,研究了基于结构矩阵方法的路径规划方法；并以混凝土运输车制动系统故障诊断任务执行路径规划为例,进行了方法应用,验证了其有效性.%Diagnosis task allocation is a key content of Remote Cooperative Fault Diagnosis (RCFD), and multi -task implementation path planning also is a necessary issue of task allocation. Based on D algorithm, critical path planning method was established to solve this problem, and this method includes longest and shortest critical path planning algorithms. Another planning method is Structure Matrix Method which based on diagnosis task model self. Taking concrete truck fault diagnosis as example, these two planning method were applied, and it verified that the method possesses easy to computer realization, simple and practical characteristics, etc.
Institute of Scientific and Technical Information of China (English)
陈侠; 刘冬
2013-01-01
With respect to the problem of 3D path planning of Unmanned Aerial Vehicles ( UAV) under uncertain environments when the target is moving,a method of fast 3D path planning was designed based on the improved D*Lite algorithm .By use of the improved cost evaluating function and the real-time information of unanticipated threats and moving targets,and based on the constraints together with the improved search algorithm,a method of 3D path planning for UAVs was given .The simulation results demonstrated that the algorithm can not only meet the real-time path planning demands,avoid the unanticipated threats and attack the moving targets,but also reduce the search space,improve the search efficiency and optimizing capability,which is a good method for path planning of UAV under uncertain environments .% 针对不确定环境下目标移动时的无人飞行器三维航迹规划问题，采用改进的D*Lite搜索算法，设计了一种三维航迹快速规划方法。利用改进的代价评估函数，根据突发威胁和移动目标的实时信息，将航迹规划约束条件和改进的搜索算法相结合，给出了地面目标移动时的无人飞行器三维航迹规划方法。仿真结果表明，该算法不但可以满足实时在线的航迹规划要求，能够有效躲避突发威胁，打击移动目标，还能有效地缩小搜索空间，提高搜索效率及寻优能力，能较好地解决不确定环境下目标移动时的航迹规划问题。
Institute of Scientific and Technical Information of China (English)
庄慧忠; 李晗; 陆震宇
2011-01-01
提出一种基于极坐标空间的、以机器人期望运动方向角为路径优化指标的动态不确定环境下移动机器人的在线实时路径规划方法.该法通过机器人的传感器系统,实时探测局部环境信息,在每一采样时刻,机器人首先对"视野"内的动态障碍物的位置进行采样,然后根据所采样的位置信息,利用自回归模型预测出下一采样时刻动态障碍物的位置,再将预测位置上的动态障碍物当作静态障碍物来处理,然后对其规划避碰路径,从而将动态路径规划转化为静态路径规划.仿真和实验结果验证了该方法有效可行,具有实时规划性和良好的避障能力.%This paper presents an on-line real-time path planning method for mobile robots in dynamic uncertain environment. Based on polar coordinates space, this method uses expected movement direction angle of robots as the index of path optimization. It explores information of local environment in time through sensor system of robots. At each sampling time, the robot firstly takes the sample of positions of dynamic obstacles within its ”visual field”, and then predicts the positions of dynamic obstacles at next sampling time with autoregressive model according to sampled positions information, and deals with dynamic obstacles at predicting positions as the static ones afterwards. Then it plans collision avoidance path for them so as to have transformed the dynamic path planning into static path planning. The method is available and feasible, it has real-time planning property and preferably good collision avoidance capacity, all of these are demonstrated by the simulations and experimental results.
Institute of Scientific and Technical Information of China (English)
高晓光; 李青原; 邸若海
2014-01-01
模型预测控制（model predictive control，MPC）路径规划算法适用于三维动态环境下的无人机（un-manned aerial vehicle，UAV）路径规划；动态贝叶斯网络（dynamic Bayesian network，DBN）能够有效推理战场态势，对无人机进行威胁评估。针对威胁尾随无人机时的路径规划问题，构建 DBN 威胁评估模型，将 UAV 在战场环境中的威胁态势用威胁等级概率表示，与 MPC 路径规划算法相结合，得到基于 DBN 威胁评估的 MPC UAV 路径规划算法。通过多组仿真分析表明，在三维动态环境下，特别是威胁尾随无人机时，基于 DBN 威胁评估的 MPC无人机路径规划算法可以得到有效的无人机路径。%The model predictive control (MPC)path planning algorithm can solve the problem of dynamic unmanned aerial vehicle (UAV)path planning.Dynamic Bayesian network (DBN)is an effective tool for rea-soning and threat assessment.Considering the problem of path planning when the dynamic threat tags the UAV,the MPC path planning algorithm combined with DBN threat assessment is presented,which used the threat lever probability to describe the threat situation.A group of simulations demonstrate the efficiency of MPC three-dimensional dynamic path planning algorithm for UAV based on DBN threat assessment especially when the dynamic threat tags the UAV.
Institute of Scientific and Technical Information of China (English)
王玮; 王玉惠; 王文敬; 张洪波
2016-01-01
The path planning for warship-aircraft joint operation is studied. Firstly, the weapon system of the destroyer is analyzed to obtain the safe distance when the shipboard helicopter and the destroyer are performing a task cooperatively. Since the traditional A∗ algorithm cannot be applied directly to the path planning for warship-aircraft joint operation, the security costs and the path safety factor are introduced. An improved weighted A∗ algorithm is given based on the traditional algorithm, to solve the path planning problem for warship-aircraft joint operation. Finally, a case simulation is given to verify the effectiveness of the improved algorithm.%基于改进加权A∗算法研究了舰机联合航迹规划问题。首先，通过分析驱逐舰的武器系统结构，得出驱逐舰和舰载直升机在联合执行任务时的安全距离；由于传统A∗算法运用于舰机联合航迹规划问题的局限性，引入安全代价和路径安全值加权系数，基于传统A∗算法给出了改进加权A∗算法，协同规划舰艇和舰载机的路径；最后，通过案例仿真验证了算法的有效性。
Dynamic path planning using velocity obstacles and behavior dynamics%基于速度障碍和行为动力学的动态路径规划
Institute of Scientific and Technical Information of China (English)
雷艳敏; 朱齐丹; 冯志彬
2011-01-01
针对基本行为动力学在解决多机器人动态路径规划中存在的问题,充分考虑运动障碍物和其他机器人的速度信息,利用速度障碍为机器人规划了避障和避碰区域.根据路径规划的要求,利用行为动力学设计了奔向目标行为、避障行为和避碰行为3个基本行为,并提出利用粒子群优化方法对基本行为进行融合.利用Matlab对所提出的算法进行仿真,结果表明利用速度障碍、行为动力学和粒子群相结合的方法可以实现多机器人系统的动态路径规划,且方法简单,路径光滑.%Aimed at the problem existing in behavior dynamics method to carry out the path planning of multi-robot systems, considering the velocity of the mobile obstacles and the other robots, the obstacle avoidance and collision avoidance region were confirmed by the velocity obstacle.On the basis of the request of path planning, the behavior of moving to goals, one of avoiding obstacles, and one of collision avoidance were devised through the behavior dynamics method.Behavior fusion was achieved by using particle swarm optimization method.The proposed arithmetic was simulated by utilizing Matlab.Simulation results show that the combination method of velocity obstacle, behavior dynamics, and particle swarm may achieve path planning of multi-robot systems, and the arithmetic is simple and the path is smooth.
Institute of Scientific and Technical Information of China (English)
邓博文; 张春华; 李娟; 雷雨能; 王钤; 张穗华
2016-01-01
In order to meet the requirement of autonomous driving and avoiding obstacles for unmanned construction machinery in autonomous task, design a kind of local path plan method for unmanned construction machinery in autonomous task. First, using environmental perception system to collect environmental data and using grid map to show the surrounding environment. Then according to the size of the construction machinery, the obstacles are expanded. At last, using D* algorithm to get a safe travel path with minimum cost. Experimental results demonstrate that this method can re-plan the path of unmanned construction machinery in real-time according to the surrounding environment, and meets the requirement of local path plan for unmanned construction machinery in complex terrain environment.%为实现无人工程机械在自主作业过程中自主行驶和自主避障的目的，设计一种适用于无人工程机械自主作业的局部路径规划方法。利用环境感知系统采集环境数据，分析处理后得到环境栅格地图，并根据无人工程机械尺寸对障碍物进行膨胀处理，应用D*算法搜索出一条代价最小的无碰撞安全行驶路径。实验结果表明：该方法能根据周围环境实时规划无人工程机械行驶路径，满足复杂地形环境的路径规划要求。
Multi-UAVs cooperative path planning based on A* fixed length search algorithm%基于A*定长搜索算法的多无人机协同航迹规划
Institute of Scientific and Technical Information of China (English)
肖自兵; 袁冬莉; 屈耀红
2012-01-01
An improved A * algorithm for fixed length path searching was proposed based on the path planning problems of multiple unmanned aerial vehicles ( UAVs) operating simultaneously. A path with fixed length was obtained by choosing nodes with costs closest to given value as best nodes in the algorithm. Then, the path was smoothed by limiting the range of the best nodes choosing from in the algorithm. Simulation results show that length error of the fixed length path obtained from the algorithm can be controlled within 1. 4% , and length error of collaborative paths is less than 0. 8%. It basically meets the requirements of multi-UAVs arriving at the same time.%基于多无人机同时作业情况下的航迹规划问题,提出了一种A*定长航迹搜索算法.该算法通过选择代价值最接近给定值的节点作为最佳节点,得到定长规划航迹,接着进一步通过限定最佳节点的选择范围,改善了航迹的可飞性.仿真结果表明,利用该算法规划的定长航迹长度误差可以控制在1.4％以内,协同航迹长度误差可以控制在0.8％以内,能够满足多无人机同时到达的一般要求.
Dynamic path planning by using dual-layer fuzzy controllers%基于双层模糊控制器的动态路径规划
Institute of Scientific and Technical Information of China (English)
雷艳敏; 朱齐丹; 关秀丽; 冯志彬
2011-01-01
为解决没有通信情况下的多机器人系统在未知动态环境下的路径规划问题,设计了采用双层模糊控制器方法的危险度模糊控制器和速度模糊控制器.危险度模糊控制器充分考虑了运动障碍物的速度信息,把机器人同障碍物之间的碰撞可能性用基于碰撞时间因子和碰撞距离因子的碰撞危险度来表示,使之更适合于动态的环境.速度模糊控制器的输入充分考虑了目标方位角、障碍物方位角和碰撞危险度,采用行为思想设计模糊规则,规则中体现了奔向目标行为、躲避障碍物行为和沿着障碍物行走行为,使之更适合复杂的环境.仿真结果表明：该算法具有可行性、有效性和快速反应的能力.%To solve path planning problem of multi-robot systems with no communication in unknown dynamic environment, a dual-layer fuzzy controller was proposed. Danger degree fuzzy and velocity fuzzy controllers were designed in this controller. The velocity information of the moving obstacles was fully considered in the danger fuzzy controller, and it was more appropriate for dynamic environ- ment. Based on the time and distance factors of the collision, the danger degree of collision denoted the possibility that the robot collided with obstacles. The velocity fuzzy controller took full account of target azimuth, obstacle azimuth and danger degree of collision and designed fuzzy rules using behav- ior ideas. Fuzzy rules reflected the move-to-goal behavior, avoid-obstacle behavior and follow-obstacle behavior, and made velocity fuzzy controller suit to the complicated environment. Simulation results show that the proposed method is feasible and valid.
Motion Planning Using a Memetic Evolution Algorithm for Swarm Robots
Directory of Open Access Journals (Sweden)
Chien-Chou Lin
2012-05-01
Full Text Available A hierarchical memetic algorithm (MA is proposed for the path planning and formation control of swarm robots. The proposed algorithm consists of a global path planner (GPP and a local motion planner (LMP. The GPP plans a trajectory within the Voronoi diagram (VD of the free space. An MA with a non‐random initial population plans a series of configurations along the path given by the former stage. The MA locally adjusts the robot positions to search for better fitness along the gradient direction of the distance between the swarm robots and the intermediate goals (IGs. Once the optimal configuration is obtained, the best chromosomes are reserved as the initial population for the next generation. Since the proposed MA has a non‐random initial population and local searching, it is more efficient and the planned path is faster compared to a traditional genetic algorithm (GA. The simulation results show that the proposed algorithm works well in terms of path smoothness and computation efficiency.
Institute of Scientific and Technical Information of China (English)
贾翠玲; 王利利; 徐明娜
2012-01-01
提出一种适用于灭火机器人避障路径规划的改进蚁群优化算法，采用自适应更新策略的方法规划最佳避障路径，建立了简洁、严谨的蚁群优化算法函数，以达到对灭火机器人避障路径的优化。这种方法能够使灭火机器人在未知环境寻找火源时有效避开障碍物并且使机器人所走路径最短，所用时间最少。经实验证明了该方法的可行性和有效性。%This paper put forward a kind of improved ant colony algorithm used in fire fighting robot path planning of obstacle avoidance. The algorithm using the adaptive updating strategy planed the best obstacle avoidance path. The method established a concise, rigorous ant colony optimization function, which could optimize the path of the robot obstacle avoidance. This method not only made fire -fighting robots in unknown environment when looking for fire avoiding obstacles effectively, but also made the robot have walked shortest path. The simulation and experiment results indicate the feasibility and validity of this algorithm.
Institute of Scientific and Technical Information of China (English)
贾翠玲; 王利利; 徐明娜
2012-01-01
提出一种适用于灭火机器人避障路径规划的改进蚁群优化算法,采用自适应更新策略的方法规划最佳避障路径,建立了简洁、严谨的蚁群优化算法函数,以达到对灭火机器人避障路径的优化.这种方法能够使灭火机器人在未知环境寻找火源时有效避开障碍物并且使机器人所走路径最短,所用时间最少.经实验证明了该方法的可行性和有效性.%This paper put forward a kind of improved ant colony algorithm used in fire fighting robot path planning of obstacle avoidance.The algorithm using the adaptive updating strategy planed the best obstacle avoidance path.The method established a concise,rigorous ant colony optimization function,which could optimize the path of the robot obstacle avoidance.This method not only made fire -fighting robots in unknown environment when looking for fire avoiding obstacles effectively,but also made the robot have walked shortest path.The simulation and experiment results indicate the feasibility and validity of this algorithm.
DEFF Research Database (Denmark)
Karnøe, Peter; Garud, Raghu
2012-01-01
This paper employs path creation as a lens to follow the emergence of the Danish wind turbine cluster. Supplier competencies, regulations, user preferences and a market for wind power did not pre-exist; all had to emerge in a tranformative manner involving multiple actors and artefacts. Competenc......This paper employs path creation as a lens to follow the emergence of the Danish wind turbine cluster. Supplier competencies, regulations, user preferences and a market for wind power did not pre-exist; all had to emerge in a tranformative manner involving multiple actors and artefacts....... Competencies emerged through processes and mechanisms such as co-creation that implicated multiple learning processes. The process was not an orderly linear one as emergent contingencies influenced the learning processes. An implication is that public policy to catalyse clusters cannot be based...
Application of Artificial Immune Algorithm in Path Planning of Mobile Robot%免疫算法在移动机器人路径规划中的应用
Institute of Scientific and Technical Information of China (English)
赵娜
2012-01-01
The article expounds in details the application of immune algorithm in the path planning of mobile robot.It makes the robot avoiding obstacles and finding a shortest path from starting point to the target point.To build the mathematical model and affinity function of mobile robot,it gives the control method for robot;also the algorithm description and simulation experiment are given in detail in this paper.The experiment result shows that the immune algorithm has good performance when applying into the path planning.%具体阐述了免疫算法在移动机器人路径规划中的应用,使机器人从给定点到目标点可以有效地躲避障碍物而且找到一条最短的路径;构建了机器人的数学模型和亲和力函数,并且说明了机器人的控制方式,给出了算法的具体实现步骤以及仿真实验。实验结果表明,免疫算法在应用到移动机器人路径规划时具有良好的性能。
Global optimization of tool path for five-axis flank milling with a cylindrical cutter
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
In this paper, optimum positioning of cylindrical cutter for five-axis flank milling of non-developable ruled surface is addressed from the perspective of surface approximation. Based on the developed interchangeability principle, global optimization of the five-axis tool path is modeled as approximation of the tool envelope surface to the data points on the design surface following the minimum zone criterion recommended by ANSI and ISO standards for tolerance evaluation. By using the signed point-to-surface distance function, tool path plannings for semi-finish and finish millings are formulated as two constrained optimization problems in a unified framework. Based on the second order Taylor approximation of the distance function, a sequential approximation algorithm along with a hierarchical algorithmic structure is developed for the optimization. Numerical examples are presented to confirm the validity of the proposed approach.
Global optimization of tool path for five-axis flank milling with a cylindrical cutter
Institute of Scientific and Technical Information of China (English)
DING Han; ZHU LiMin
2009-01-01
In this paper,optimum positioning of cylindrical cutter for five-axis flank milling of non-developable ruled surface is addressed from the perspective of surface approximation.Based on the developed interchangeability principle,global optimization of the five-axis tool path is modeled as approximation of the tool envelope surface to the data points on the design surface following the minimum zone criterion recommended by ANSI and ISO standards for tolerance evaluation.By using the signed point-to-surface distance function,tool path plannings for semi-finish and finish millings are formulated as two constrained optimization problems in a unified framework.Based on the second order Taylor approximation of the distance function,a sequential approximation algorithm along with a hierarchical algorithmic structure is developed for the optimization.Numerical examples are presented to confirm the validity of the proposed approach.
Directory of Open Access Journals (Sweden)
Peter Juhasz
2017-03-01
Full Text Available While risk management gained popularity during the last decades even some of the basic risk types are still far out of focus. One of these is path dependency that refers to the uncertainty of how we reach a certain level of total performance over time. While decision makers are careful in accessing how their position will look like the end of certain periods, little attention is given how they will get there through the period. The uncertainty of how a process will develop across a shorter period of time is often “eliminated” by simply choosing a longer planning time interval, what makes path dependency is one of the most often overlooked business risk types. After reviewing the origin of the problem we propose and compare seven risk measures to access path. Traditional risk measures like standard deviation of sub period cash flows fail to capture this risk type. We conclude that in most cases considering the distribution of the expected cash flow effect caused by the path dependency may offer the best method, but we may need to use several measures at the same time to include all the optimisation limits of the given firm