Path Planning with a Lazy Significant Edge Algorithm (LSEA

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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.

Feasible Path Planning for Autonomous Vehicles

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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.

Autonomous path planning solution for industrial robot manipulator using backpropagation algorithm

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PeiJiang Yuan

2015-12-01

Full Text Available Here, we propose an autonomous path planning solution using backpropagation algorithm. The mechanism of movement used by humans in controlling their arms is analyzed and then applied to control a robot manipulator. Autonomous path planning solution is a numerical method. The model of industrial robot manipulator used in this article is a KUKA KR 210 R2700 EXTRA robot. In order to show the performance of the autonomous path planning solution, an experiment validation of path tracking is provided. Experiment validation consists of implementation of the autonomous path planning solution and the control of physical robot. The process of converging to target solution is provided. The mean absolute error of position for tool center point is also analyzed. Comparison between autonomous path planning solution and the numerical methods based on Newton–Raphson algorithm is provided to demonstrate the efficiency and accuracy of the autonomous path planning solution.

Path planning algorithms for assembly sequence planning. [in robot kinematics

Science.gov (United States)

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.

Time-optimal path planning in uncertain flow fields using ensemble method

KAUST Repository

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.

Cooperative path planning of unmanned aerial vehicles

CERN Document Server

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. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in...

A bat algorithm with mutation for UCAV path planning.

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Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

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.

Cooperative organic mine avoidance path planning

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McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David

2005-06-01

The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.

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.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

Energy Technology Data Exchange (ETDEWEB)

Vandewouw, Marlee M., E-mail: marleev@mie.utoronto.ca; Aleman, Dionne M. [Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8 (Canada); Jaffray, David A. [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada)

2016-08-15

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

International Nuclear Information System (INIS)

Vandewouw, Marlee M.; Aleman, Dionne M.; Jaffray, David A.

2016-01-01

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.

A novel algorithm for solving optimal path planning problems based on parametrization method and fuzzy aggregation

International Nuclear Information System (INIS)

Zamirian, M.; Kamyad, A.V.; Farahi, M.H.

2009-01-01

In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

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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.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

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Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.

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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.

Knowledge-inducing Global Path Planning for Robots in Environment with Hybrid Terrain

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Yi-nan Guo

2010-09-01

Full Text Available In complex environment with hybrid terrain, different regions may have different terrain. Path planning for robots in such environment is an open NP-complete problem, which lacks effective methods. The paper develops a novel global path planning method based on common sense and evolution knowledge by adopting dual evolution structure in culture algorithms. Common sense describes terrain information and feasibility of environment, which is used to evaluate and select the paths. Evolution knowledge describes the angle relationship between the path and the obstacles, or the common segments of paths, which is used to judge and repair infeasible individuals. Taken two types of environments with different obstacles and terrain as examples, simulation results indicate that the algorithm can effectively solve path planning problem in complex environment and decrease the computation complexity for judgment and repair of infeasible individuals. It also can improve the convergence speed and have better computation stability.

Mission-directed path planning for planetary rover exploration

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Tompkins, Paul

2005-07-01

Robotic rovers uniquely benefit planetary exploration---they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander. Mission planning for planetary rover exploration currently utilizes sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. This approach is insufficient for the investigation of multiple, regionally distributed targets in a single command cycle. Path planning tailored for this task must consider the impact of large scale terrain on power, speed and regional access; the effect of route timing on resource availability; the limitations of finite resource capacity and other operational constraints on vehicle range and timing; and the mutual influence between traverses and upstream and downstream stationary activities. Encapsulating this reasoning in an efficient autonomous planner would allow a rover to continue operating rationally despite significant deviations from an initial plan. This research presents mission-directed path planning that enables an autonomous, strategic reasoning capability for robotic explorers. Planning operates in a space of position, time and energy. Unlike previous hierarchical approaches, it treats these dimensions simultaneously to enable globally-optimal solutions. The approach calls on a near incremental search algorithm designed for planning and re-planning under global constraints, in spaces of higher than two dimensions. Solutions under this method specify routes that avoid terrain obstacles, optimize the collection and use of rechargable energy, satisfy local and global mission constraints, and account for the time and energy of interleaved mission activities. Furthermore, the approach efficiently re-plans in response to updates in vehicle state and world models, and is well suited to online operation aboard a robot

Shore-based Path Planning for Marine Vehicles Using a Model of Ocean Currents

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National Aeronautics and Space Administration — Develop path planning methods that incorporate an approximate model of ocean currents in path planning for a range of autonomous marine vehicles such as surface...

A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments

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Yun Chen

2018-01-01

Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.

Methodology for using root locus technique for mobile robots path planning

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Mario Ricardo Arbulú Saavedra

2015-11-01

Full Text Available This paper shows the analysis and the implementation methodology of the technique of dynamic systems roots location used in free-obstacle path planning for mobile robots. First of all, the analysis and morphologic behavior identification of the paths depending on roots location in complex plane are performed, where paths type and their attraction and repulsion features in the presence of other roots similarly to the obtained with artificial potential fields are identified. An implementation methodology for this technique of mobile robots path planning is proposed, starting from three different methods of roots location for obstacles in the scene. Those techniques change depending on the obstacle key points selected for roots, such as borders, crossing points with original path, center and vertices. Finally, a behavior analysis of general technique and the effectiveness of each tried method is performed, doing 20 tests for each one, obtaining a value of 65% for the selected method. Modifications and possible improvements to this methodology are also proposed.

Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment

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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.

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.

Robotic Online Path Planning on Point Cloud.

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Liu, Ming

2016-05-01

This paper deals with the path-planning problem for mobile wheeled- or tracked-robot which drive in 2.5-D environments, where the traversable surface is usually considered as a 2-D-manifold embedded in a 3-D ambient space. Specially, we aim at solving the 2.5-D navigation problem using raw point cloud as input. The proposed method is independent of traditional surface parametrization or reconstruction methods, such as a meshing process, which generally has high-computational complexity. Instead, we utilize the output of 3-D tensor voting framework on the raw point clouds. The computation of tensor voting is accelerated by optimized implementation on graphics computation unit. Based on the tensor voting results, a novel local Riemannian metric is defined using the saliency components, which helps the modeling of the latent traversable surface. Using the proposed metric, we prove that the geodesic in the 3-D tensor space leads to rational path-planning results by experiments. Compared to traditional methods, the results reveal the advantages of the proposed method in terms of smoothing the robot maneuver while considering the minimum travel distance.

Reasoning on the Self-Organizing Incremental Associative Memory for Online Robot Path Planning

Science.gov (United States)

Kawewong, Aram; Honda, Yutaro; Tsuboyama, Manabu; Hasegawa, Osamu

Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily generated common patterns (CPs). In an online manner, a robot regards the current path as the associative path-fragments, each connected by junctions. The reasoning technique is additionally proposed for decision making at each junction to speed up the exploration time. Distinct from other methods, our method does not ignore the important information about the regions between junctions (path-fragments). The resultant number of path-fragments is also less than other method. Evaluation is done via Webots physical 3D-simulated and real robot experiments, where only distance sensors are available. Results show that our method can represent the environment effectively; it enables the robot to solve the goal-oriented navigation problem in only one episode, which is actually less than that necessary for most of the Reinforcement Learning (RL) based methods. The running time is proved finite and scales well with the environment. The resultant number of path-fragments matches well to the environment.

Learning to improve path planning performance

International Nuclear Information System (INIS)

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

Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces.

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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.

Cooperative Path-Planning for Multi-Vehicle Systems

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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.

Autonomous Path Planning for Road Vehicles in Narrow Environments: An Efficient Continuous Curvature Approach

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Domokos Kiss

2017-01-01

Full Text Available In this paper we introduce a novel method for obtaining good quality paths for autonomous road vehicles (e.g., cars or buses in narrow environments. There are many traffic situations in urban scenarios where nontrivial maneuvering in narrow places is necessary. Navigating in cluttered parking lots or having to avoid obstacles blocking the way and finding a detour even in narrow streets are challenging, especially if the vehicle has large dimensions like a bus. We present a combined approximation-based approach to solve the path planning problem in such situations. Our approach consists of a global planner which generates a preliminary path consisting of straight and turning-in-place primitives and a local planner which is used to make the preliminary path feasible to car-like vehicles. The approximation methodology is well known in the literature; however, both components proposed in this paper differ from existing similar planning methods. The approximation process with the proposed local planner is proven to be convergent for any preliminary global paths. The resulting path has continuous curvature which renders our method well suited for application on real vehicles. Simulation experiments show that the proposed method outperforms similar approaches in terms of path quality in complicated planning tasks.

Safe Maritime Autonomous Path Planning in a High Sea State

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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.

Image-based path planning for automated virtual colonoscopy navigation

Science.gov (United States)

Hong, Wei

2008-03-01

Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.

Globally Optimal Path Planning with Anisotropic Running Costs

Science.gov (United States)

2013-03-01

Eikonal equation and has numerous applications, for exam- ple, in path planning, computational geometry, computer vision, and image enhancement...Sethian 1999b]. Numerical methods for solving the Eikonal equation include Tsitsiklis’ control-theoretic algorithm [Tsitsiklis 1995], Fast Marching Methods...methods for Eikonal equations on triangular meshes, SIAM J. Numer. Anal. 45(1), 83—107. Rowe, M. P., Sidhu, H. S. & Mercer, G. N. (2009) Military

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.

Path Planning Algorithms for the Adaptive Sensor Fleet

Science.gov (United States)

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.

Robust path planning for flexible needle insertion using Markov decision processes.

Science.gov (United States)

Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong

2018-05-11

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Research and Implementation of Robot Path Planning Based onVSLAM

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Wang Zi-Qiang

2018-01-01

Full Text Available In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.

Integrated assignment and path planning

Science.gov (United States)

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

Aircraft path planning for optimal imaging using dynamic cost functions

Science.gov (United States)

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.

Aircraft path planning with the use of smooth trajectories

Science.gov (United States)

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.

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.

TP-Space RRT – Kinematic Path Planning of Non-Holonomic Any-Shape Vehicles

Directory of Open Access Journals (Sweden)

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.

Static and Dynamic Path Planning Using Incremental Heuristic Search

OpenAIRE

Khattab, Asem

2018-01-01

Path planning is an important component in any highly automated vehicle system. In this report, the general problem of path planning is considered first in partially known static environments where only static obstacles are present but the layout of the environment is changing as the agent acquires new information. Attention is then given to the problem of path planning in dynamic environments where there are moving obstacles in addition to the static ones. Specifically, a 2D car-like agent t...

A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.

Science.gov (United States)

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.

Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics

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Wenfu Xu

2007-03-01

Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of free-floating 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.

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.

Reactive Path Planning Approach for Docking Robots in Unknown Environment

Directory of Open Access Journals (Sweden)

Peng Cui

2017-01-01

Full Text Available Autonomous robots need to be recharged and exchange information with the host through docking in the long-distance tasks. Therefore, feasible path is required in the docking process to guide the robot and adjust its pose. However, when there are unknown obstacles in the work area, it becomes difficult to determine the feasible path for docking. This paper presents a reactive path planning approach named Dubins-APF (DAPF to solve the path planning problem for docking in unknown environment with obstacles. In this proposed approach the Dubins curves are combined with the designed obstacle avoidance potential field to plan the feasible path. Firstly, an initial path is planned and followed according to the configurations of the robot and the docking station. Then when the followed path is evaluated to be infeasible, the intermediate configuration is calculated as well as the replanned path based on the obstacle avoidance potential field. The robot will be navigated to the docking station with proper pose eventually via the DAPF approach. The proposed DAPF approach is efficient and does not require the prior knowledge about the environment. Simulation results are given to validate the effectiveness and feasibility of the proposed approach.

Flexible integration of path-planning capabilities

Science.gov (United States)

Stobie, Iain C.; Tambe, Milind; Rosenbloom, Paul S.

1993-05-01

Robots pursuing complex goals must plan paths according to several criteria of quality, including shortness, safety, speed and planning time. Many sources and kinds of knowledge, such as maps, procedures and perception, may be available or required. Both the quality criteria and sources of knowledge may vary widely over time, and in general they will interact. One approach to address this problem is to express all criteria and goals numerically in a single weighted graph, and then to search this graph to determine a path. Since this is problematic with symbolic or uncertain data and interacting criteria, we propose that what is needed instead is an integration of many kinds of planning capabilities. We describe a hybrid approach to integration, based on experiments with building simulated mobile robots using Soar, an integrated problem-solving and learning system. For flexibility, we have implemented a combination of internal planning, reactive capabilities and specialized tools. We illustrate how these components can complement each other's limitations and produce plans which integrate geometric and task knowledge.

Three-Dimensional Path Planning Software-Assisted Transjugular Intrahepatic Portosystemic Shunt: A Technical Modification

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.

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

Science.gov (United States)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

Science.gov (United States)

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.

Multi-AGV path planning with double-path constraints by using an improved genetic algorithm.

Directory of Open Access Journals (Sweden)

Zengliang Han

Full Text Available This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm.

Active Path Planning for Drones in Object Search

OpenAIRE

Wang, Zeyangyi

2017-01-01

Object searching is one of the most popular applications of unmanned aerial vehicles. Low cost small drones are particularly suited for surveying tasks in difficult conditions. With their limited on-board processing power and battery life, there is a need for more efficient search algorithm. The proposed path planning algorithm utilizes AZ-net, a deep learning network to process images captured on drones for adaptive flight path planning. Search simulation based on videos and actual experimen...

Interactive multi-objective path planning through a palette-based user interface

Science.gov (United States)

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

Planning of optimal work path for minimizing exposure dose during radiation work in radwaste storage

International Nuclear Information System (INIS)

Kim, Yoon Hyuk; Park, Won Man; Kim, Kyung Soo; Whang, Joo Ho

2005-01-01

Since the safety of nuclear power plant has been becoming a big social issue, the exposure dose of radiation for workers has been one of the important factors concerning the safety problem. The existing calculation methods of radiation dose used in the planning of radiation work assume that dose rate dose not depend on the location within a work space, thus the variation of exposure dose by different work path is not considered. In this study, a modified numerical method was presented to estimate the exposure dose during radiation work in radwaste storage considering the effects of the distance between a worker and sources. And a new numerical algorithm was suggested to search the optimal work path minimizing the exposure dose in pre-defined work space with given radiation sources. Finally, a virtual work simulation program was developed to visualize the exposure dose of radiation during radiation works in radwaste storage and provide the capability of simulation for work planning. As a numerical example, a test radiation work was simulated under given space and two radiation sources, and the suggested optimal work path was compared with three predefined work paths. The optimal work path obtained in the study could reduce the exposure dose for the given test work. Based on the results, the developed numerical method and simulation program could be useful tools in the planning of radiation work

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.

The force control and path planning of electromagnetic induction-based massage robot.

Science.gov (United States)

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

Autonomously Implemented Versatile Path Planning for Mobile Robots Based on Cellular Automata and Ant Colony

Directory of Open Access Journals (Sweden)

Adel Akbarimajd

2012-02-01

Full Text Available A path planning method for mobile robots based on two dimensional cellular automata is proposed. The method can be applied for environments with both concave and convex obstacles. It is also appropriate for multi-robot problems as well as dynamic environments. In order to develop the planning method, environment of the robot is decomposed to a rectangular grid and the automata is defined with four states including Robot cell, Free cell, Goal cell and Obstacle cell. Evolution rules of automata are proposed in order to direct the robot toward its goal. CA based path planner method is afterwards modified by a colony technique to be applicable for concave obstacles. Then a layered architecture is proposed to autonomously implement the planning algorithm. The architecture employs an abstraction approach which makes the complexity manageable. An important feature of the architecture is internal artifacts that have some beliefs about the world. Most actions of the robot are planned and performed with respect to these artifacts.

A Novel Path Planning for Robots Based on Rapidly-Exploring Random Tree and Particle Swarm Optimizer Algorithm

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.

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

Directory of Open Access Journals (Sweden)

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.

Autonomous guided vehicles methods and models for optimal path planning

CERN Document Server

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...

Energy-Aware Path Planning for UAS Persistent Sampling and Surveillance

Science.gov (United States)

Shaw-Cortez, Wenceslao

The focus of this work is to develop an energy-aware path planning algorithm that maximizes UAS endurance, while performing sampling and surveillance missions in a known, stationary wind environment. The energy-aware aspect is specifically tailored to extract energy from the wind to reduce thrust use, thereby increasing aircraft endurance. Wind energy extraction is performed by static soaring and dynamic soaring. Static soaring involves using upward wind currents to increase altitude and potential energy. Dynamic soaring involves taking advantage of wind gradients to exchange potential and kinetic energy. The path planning algorithm developed in this work uses optimization to combine these soaring trajectories with the overarching sampling and surveillance mission. The path planning algorithm uses a simplified aircraft model to tractably optimize soaring trajectories. This aircraft model is presented and along with the derivation of the equations of motion. A nonlinear program is used to create the soaring trajectories based on a given optimization problem. This optimization problem is defined using a heuristic decision tree, which defines appropriate problems given a sampling and surveillance mission and a wind model. Simulations are performed to assess the path planning algorithm. The results are used to identify properties of soaring trajectories as well as to determine what wind conditions support minimal thrust soaring. Additional results show how the path planning algorithm can be tuned between maximizing aircraft endurance and performing the sampling and surveillance mission. A means of trajectory stitching is demonstrated to show how the periodic soaring segments can be combined together to provide a full solution to an infinite/long horizon problem.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

Science.gov (United States)

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…

Minimum Time Path Planning for Robotic Manipulator in Drilling/ Spot Welding Tasks

Directory of Open Access Journals (Sweden)

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.

Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

Science.gov (United States)

Cao, Lu; Chen, Qiwei

2018-03-01

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

Visibility-based optimal path and motion planning

CERN Document Server

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...

Welding Robot Collision-Free Path Optimization

Directory of Open Access Journals (Sweden)

Xuewu Wang

2017-02-01

Full Text Available Reasonable welding path has a significant impact on welding efficiency, and a collision-free path should be considered first in the process of welding robot path planning. The shortest path length is considered as an optimization objective, and obstacle avoidance is considered as the constraint condition in this paper. First, a grid method is used as a modeling method after the optimization objective is analyzed. For local collision-free path planning, an ant colony algorithm is selected as the search strategy. Then, to overcome the shortcomings of the ant colony algorithm, a secondary optimization is presented to improve the optimization performance. Finally, the particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the desired welding path can be obtained based on the optimization strategy.

A Novel Randomized Search Technique for Multiple Mobile Robot Paths Planning In Repetitive Dynamic Environment

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.

The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

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Yi Zhang

2016-01-01

Full Text Available Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.

Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Directory of Open Access Journals (Sweden)

B. Mashadi

Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.

System Design and Implementation of Intelligent Fire Engine Path Planning based on SAT Algorithm

Institute of Scientific and Technical Information of China (English)

CAI Li-sha[1; ZENG Wei-peng[1; HAN Bao-ru[1

2016-01-01

In this paper, in order to make intelligent fi re car complete autonomy path planning in simulation map. Proposed system design of intelligent fi re car path planning based on SAT. The system includes a planning module, a communication module, a control module. Control module via the communication module upload the initial state and the goal state to planning module. Planning module solve this planning solution,and then download planning solution to control module, control the movement of the car fi re. Experiments show this the system is tracking short time, higher planning effi ciency.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

Science.gov (United States)

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.

Task Allocation and Path Planning for Collaborative Autonomous Underwater Vehicles Operating through an Underwater Acoustic Network

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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.

Rapidly Exploring Random Trees Used for Mobile Robots Path Planning

Czech Academy of Sciences Publication Activity Database

Krejsa, Jiří; Věchet, S.

2005-01-01

Roč. 12, č. 4 (2005), s. 231-238 ISSN 1802-1484. [Mechatronics, Robotics and Biomechanics 2005. Třešť, 26.09.2005-29.09.2005] Institutional research plan: CEZ:AV0Z20760514 Keywords : path planning * mobile robot Subject RIV: JD - Computer Applications, Robotics

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....

Path Planning & Measurement Registration for Robotic Structural Asset Monitoring

OpenAIRE

Pierce , Stephen Gareth; Macleod , Charles Norman; Dobie , Gordon; Summan , Rahul

2014-01-01

International audience; The move to increased levels of autonomy for robotic delivery of inspection for asset monitoring, demands a structured approach to path planning and measurement data presentation that greatly surpasses the more ad‐,hoc approach typically employed by remotely controlled, but manually driven robotic inspection vehicles. The authors describe a traditional CAD/CAM approach to motion planning (as used in machine tool operation) which has numerous benefits including the...

Critical path method applied to research project planning: Fire Economics Evaluation System (FEES)

Science.gov (United States)

Earl B. Anderson; R. Stanton Hales

1986-01-01

The critical path method (CPM) of network analysis (a) depicts precedence among the many activities in a project by a network diagram; (b) identifies critical activities by calculating their starting, finishing, and float times; and (c) displays possible schedules by constructing time charts. CPM was applied to the development of the Forest Service's Fire...

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

Science.gov (United States)

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

Science.gov (United States)

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Path planning in uncertain flow fields using ensemble method

KAUST Repository

Wang, Tong; Le Maî tre, Olivier P.; Hoteit, Ibrahim; Knio, Omar

2016-01-01

, 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

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

Science.gov (United States)

Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve

2011-01-01

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields

Science.gov (United States)

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

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

Science.gov (United States)

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.

Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination

Directory of Open Access Journals (Sweden)

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.

OSM-ORIENTED METHOD OF MULTIMODAL ROUTE PLANNING

Directory of Open Access Journals (Sweden)

X. Li

2015-07-01

Full Text Available With the increasing pervasiveness of basic facilitate of transportation and information, the need of multimodal route planning is becoming more essential in the fields of communication and transportation, urban planning, logistics management, etc. This article mainly described an OSM-oriented method of multimodal route planning. Firstly, it introduced how to extract the information we need from OSM data and build proper network model and storage model; then it analysed the accustomed cost standard adopted by most travellers; finally, we used shortest path algorithm to calculate the best route with multiple traffic means.

Smooth Jerk-Bounded Optimal Path Planning of Tricycle Wheeled Mobile Manipulators in the Presence of Environmental Obstacles

Directory of Open Access Journals (Sweden)

Moharam Habibnejad Korayem

2012-10-01

Full Text Available In this work, a computational algorithm is developed for the smooth-jerk optimal path planning of tricycle wheeled mobile manipulators in an obstructed environment. Due to a centred orientable wheel, the tricycle mobile manipulator exhibits more steerability and manoeuvrability over traditional mobile manipulators, especially in the presence of environmental obstacles. This paper presents a general formulation based on the combination of the potential field method and optimal control theory in order to plan the smooth point-to-point path of the tricycle mobile manipulators. The nonholonomic constraints of the tricycle mobile base are taken into account in the dynamic formulation of the system and then the optimality conditions are derived considering jerk restrictions and obstacle avoidance. Furthermore, by means of the potential field method, a new formulation of a repulsive potential function is proposed for collision avoidance between any obstacle and each part of the mobile manipulator. In addition, to ensure the accurate placement of the end effector on the target point an attractive potential function is applied to the optimal control formulation. Next, a mixed analytical-numerical algorithm is proposed to generate the point-to-point optimal path. Finally, the proposed method is verified by a number of simulations on a two-link tricycle manipulator.

Singularities of robot mechanisms numerical computation and avoidance path planning

CERN Document Server

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...

Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation

Science.gov (United States)

Jung, Dongwon

2007-12-01

Recently there has been a tremendous growth of research emphasizing control of unmanned aerial vehicles (UAVs) either in isolation or in teams. As a matter of fact, UAVs increasingly find their way into military and law enforcement applications (e.g., reconnaissance, remote delivery of urgent equipment/material, resource assessment, environmental monitoring, battlefield monitoring, ordnance delivery, etc.). This trend will continue in the future, as UAVs are poised to replace the human-in-the-loop during dangerous missions. Civilian applications of UAVs are also envisioned such as crop dusting, geological surveying, search and rescue operations, etc. In this thesis we propose a new online multiresolution path planning algorithm for a small UAV with limited on-board computational resources. The proposed approach assumes that the UAV has detailed information of the environment and the obstacles only in its vicinity. Information about far-away obstacles is also available, albeit less accurately. The proposed algorithm uses the fast lifting wavelet transform (FLWT) to get a multiresolution cell decomposition of the environment, whose dimension is commensurate to the on-board computational resources. A topological graph representation of the multiresolution cell decomposition is constructed efficiently, directly from the approximation and detail wavelet coefficients. Dynamic path planning is sequentially executed for an optimal path using the A* algorithm over the resulting graph. The proposed path planning algorithm is implemented on-line on a small autopilot. Comparisons with the standard D*-lite algorithm are also presented. We also investigate the problem of generating a smooth, planar reference path from a discrete optimal path. Upon the optimal path being represented as a sequence of cells in square geometry, we derive a smooth B-spline path that is constrained inside a channel that is induced by the geometry of the cells. To this end, a constrained optimization

Integrated flight path planning system and flight control system for unmanned helicopters.

Science.gov (United States)

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

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).

Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters

Science.gov (United States)

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

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). PMID:22164029

Path optimization method for the sign problem

Directory of Open Access Journals (Sweden)

Ohnishi Akira

2018-01-01

Full Text Available We propose a path optimization method (POM to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t(f ϵ R and by optimizing f(t to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.

Critical path method as the criterion for optimization of business planning process

OpenAIRE

Butsenko Elena V.

2016-01-01

In today's economy the task of improving business planning is considered a necessary component of any enterprise management process and is precisely the solution drawn from that task which determines the financial policy and economic structure. The development of technologies based on the optimization of business planning is a very urgent scientific challenge. In this paper we propose to use the methods of network planning and management as a tool for economic and mathematical modeling to...

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

Science.gov (United States)

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.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

Science.gov (United States)

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning

Directory of Open Access Journals (Sweden)

Lan Anh Trinh

2018-06-01

Full Text Available Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta* algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta* algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The

Robot path planning using expert systems and machine vision

Science.gov (United States)

Malone, Denis E.; Friedrich, Werner E.

1992-02-01

This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.

Heuristic methods for single link shared backup path protection

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin

2014-01-01

schemes are employed. In contrast to manual intervention, automatic protection schemes such as shared backup path protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... 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 5 of 7 benchmark instances (and a gap of less than 11 % for the remaining...

Vehicle path-planning in three dimensions using optics analogs for optimizing visibility and energy cost

Science.gov (United States)

Rowe, Neil C.; Lewis, David H.

1989-01-01

Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.

Toward solving the sign problem with path optimization method

Science.gov (United States)

Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira

2017-12-01

We propose a new approach to circumvent the sign problem in which the integration path is optimized to control the sign problem. We give a trial function specifying the integration path in the complex plane and tune it to optimize the cost function which represents the seriousness of the sign problem. We call it the path optimization method. In this method, we do not need to solve the gradient flow required in the Lefschetz-thimble method and then the construction of the integration-path contour arrives at the optimization problem where several efficient methods can be applied. In a simple model with a serious sign problem, the path optimization method is demonstrated to work well; the residual sign problem is resolved and precise results can be obtained even in the region where the global sign problem is serious.

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

Science.gov (United States)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent

An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

Directory of Open Access Journals (Sweden)

German Gramajo

2017-01-01

Full Text Available A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.

A human-machine cooperation route planning method based on improved A* algorithm

Science.gov (United States)

Zhang, Zhengsheng; Cai, Chao

2011-12-01

To avoid the limitation of common route planning method to blindly pursue higher Machine Intelligence and autoimmunization, this paper presents a human-machine cooperation route planning method. The proposed method includes a new A* path searing strategy based on dynamic heuristic searching and a human cooperated decision strategy to prune searching area. It can overcome the shortage of A* algorithm to fall into a local long term searching. Experiments showed that this method can quickly plan a feasible route to meet the macro-policy thinking.

Towards heterogeneous robot team path planning: acquisition of multiple routes with a modified spline-based algorithm

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.

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

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.

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

International Nuclear Information System (INIS)

Tuvshinjargal, Doopalam; Lee, Deok Jin

2015-01-01

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

Intelligent coverage path planning for agricultural robots and autonomous machines on three-dimensional terrain

DEFF Research Database (Denmark)

Hameed, Ibahim

2014-01-01

Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage...

Task path planning, scheduling and learning for free-ranging robot systems

Science.gov (United States)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

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.

Evaluation of a New Backtrack Free Path Planning Algorithm for Manipulators

Science.gov (United States)

Islam, Md. Nazrul; Tamura, Shinsuke; Murata, Tomonari; Yanase, Tatsuro

This paper evaluates a newly proposed backtrack free path planning algorithm (BFA) for manipulators. BFA is an exact algorithm, i.e. it is resolution complete. Different from existing resolution complete algorithms, its computation time and memory space are proportional to the number of arms. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments while changing the number of arms and obstacle placements. Its performance under locus and attitude constraints is also evaluated. Evaluation results show that the computation volume of the algorithm is almost the same as the theoretical one, i.e. it increases linearly with the number of arms even in complicated environments. Moreover BFA achieves the constant performance independent of environments.

Social network analysis using k-Path centrality method

Science.gov (United States)

Taniarza, Natya; Adiwijaya; Maharani, Warih

2018-03-01

k-Path centrality is deemed as one of the effective methods to be applied in centrality measurement in which the influential node is estimated as the node that is being passed by information path frequently. Regarding this, k-Path centrality has been employed in the analysis of this paper specifically by adapting random-algorithm approach in order to: (1) determine the influential user’s ranking in a social media Twitter; and (2) ascertain the influence of parameter α in the numeration of k-Path centrality. According to the analysis, the findings showed that the method of k-Path centrality with random-algorithm approach can be used to determine user’s ranking which influences in the dissemination of information in Twitter. Furthermore, the findings also showed that parameter α influenced the duration and the ranking results: the less the α value, the longer the duration, yet the ranking results were more stable.

Path Planning and Replanning for Mobile Robot Navigation on 3D Terrain: An Approach Based on Geodesic

Directory of Open Access Journals (Sweden)

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.

Optimal path planning for a mobile robot using cuckoo search algorithm

Science.gov (United States)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Path-Constrained Motion Planning for Robotics Based on Kinematic Constraints

NARCIS (Netherlands)

Dijk, van N.J.M.; Wouw, van de N.; Pancras, W.C.M.; Nijmeijer, H.

2007-01-01

Common robotic tracking tasks consist of motions along predefined paths. The design of time-optimal path-constrained trajectories for robotic applications is discussed in this paper. To increase industrial applicability, the proposed method accounts for robot kinematics together with actuator

Electron beam treatment planning: A review of dose computation methods

International Nuclear Information System (INIS)

Mohan, R.; Riley, R.; Laughlin, J.S.

1983-01-01

Various methods of dose computations are reviewed. The equivalent path length methods used to account for body curvature and internal structure are not adequate because they ignore the lateral diffusion of electrons. The Monte Carlo method for the broad field three-dimensional situation in treatment planning is impractical because of the enormous computer time required. The pencil beam technique may represent a suitable compromise. The behavior of a pencil beam may be described by the multiple scattering theory or, alternatively, generated using the Monte Carlo method. Although nearly two orders of magnitude slower than the equivalent path length technique, the pencil beam method improves accuracy sufficiently to justify its use. It applies very well when accounting for the effect of surface irregularities; the formulation for handling inhomogeneous internal structure is yet to be developed

Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains

OpenAIRE

Jun , Jae-Yun; Saut , Jean-Philippe; Benamar , Faïz

2015-01-01

International audience; A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot-terrain interaction with the robot’s quasi-static tip-over stability measure (assuming that the robot traverses uneven ter...

Path planning of master-slave manipulator using graphic simulator

International Nuclear Information System (INIS)

Lee, J. Y.; Kim, S. H.; Song, T. K.; Park, B. S.; Yoon, J. S.

2002-01-01

To handle the high level radioactive materials such as spent fuels remotely, the master-slave manipulator is generally used as a remote handling equipment in the hot cell. To analyze the motion and to implement the training system by virtual reality technology, the simulator for M-S manipulator using the computer graphics is developed. The parts are modelled in 3-D graphics, assembled, and kinematics are assigned. The inverse kinematics of the manipulator is defined, and the slave of manipulator is coupled with master by the manipulator's specification. Also, the virtual work cell is implemented in the graphical environment which is the same as the real environment and the path planning method using the function of the collision detection for a manipulator are proposed. This graphic simulator of manipulator can be effectively used in designing of the maintenance processes for the hot cell equipment and enhance the reliability of the spent fuel management

Hybrid path planning for non-holonomic autonomous vehicles: An experimental evaluation

NARCIS (Netherlands)

Esposto, F.; Goos, J.; Teerhuis, A.; Alirezaei, M.

2017-01-01

Path planning of an autonomous vehicle as a non-holonomic system is an essential part for many automated driving applications. Parking a car into a parking lot and maneuvering it through a narrow corridor would be a common driving scenarios in an urban environment. In this study a hybrid approach

Path Searching Based Fault Automated Recovery Scheme for Distribution Grid with DG

Science.gov (United States)

Xia, Lin; Qun, Wang; Hui, Xue; Simeng, Zhu

2016-12-01

Applying the method of path searching based on distribution network topology in setting software has a good effect, and the path searching method containing DG power source is also applicable to the automatic generation and division of planned islands after the fault. This paper applies path searching algorithm in the automatic division of planned islands after faults: starting from the switch of fault isolation, ending in each power source, and according to the line load that the searching path traverses and the load integrated by important optimized searching path, forming optimized division scheme of planned islands that uses each DG as power source and is balanced to local important load. Finally, COBASE software and distribution network automation software applied are used to illustrate the effectiveness of the realization of such automatic restoration program.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

Science.gov (United States)

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 Following in the Exact Penalty Method of Convex Programming.

Science.gov (United States)

Zhou, Hua; Lange, Kenneth

2015-07-01

Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value.

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

Science.gov (United States)

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.

Creep analysis by the path function method

International Nuclear Information System (INIS)

Akin, J.E.; Pardue, R.M.

1977-01-01

The finite element method has become a common analysis procedure for the creep analysis of structures. The most recent programs are designed to handle a general class of material properties and are able to calculate elastic, plastic, and creep components of strain under general loading histories. The constant stress approach is too crude a model to accurately represent the actual behaviour of the stress for large time steps. The true path of a point in the effective stress-effective strain (sigmasup(e)-epsilonsup(c)) plane is often one in which the slope is rapidly changing. Thus the stress level quickly moves away from the initial stress level and then gradually approaches the final one. The result is that the assumed constant stress level quickly becomes inaccurate. What is required is a better method of approximation of the true path in the sigmasup(e)-epsilonsup(c) space. The method described here is called the path function approach because it employs an assumed function to estimate the motion of points in the sigmasup(e)-epsilonsup(c) space. (Auth.)

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Directory of Open Access Journals (Sweden)

Zheng Zhang

2013-03-01

Full Text Available In a hybrid wireless sensor network with mobile and static nodes, which have no prior geographical knowledge, successful navigation for mobile robots is one of the main challenges. In this paper, we propose two novel navigation algorithms for outdoor environments, which permit robots to travel from one static node to another along a planned path in the sensor field, namely the RAC and the IMAP algorithms. Using this, the robot can navigate without the help of a map, GPS or extra sensor modules, only using the received signal strength indication (RSSI and odometry. Therefore, our algorithms have the advantage of being cost-effective. In addition, a path planning algorithm to schedule mobile robots' travelling paths is presented, which focuses on shorter distances and robust paths for robots by considering the RSSI-Distance characteristics. The simulations and experiments conducted with an autonomous mobile robot show the effectiveness of the proposed algorithms in an outdoor environment.

A path planning method for robot end effector motion using the curvature theory of the ruled surfaces

Science.gov (United States)

Güler, Fatma; Kasap, Emin

Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

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.

A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems

KAUST Repository

Abdelkader, Mohamed; Jaleel, Hassan; Shamma, Jeff S.

2017-01-01

We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which

Solving the empty space problem in robot path planning by mathematical morphology

NARCIS (Netherlands)

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

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...

Path-integral method for the source apportionment of photochemical pollutants

Science.gov (United States)

Dunker, A. M.

2015-06-01

A new, path-integral method is presented for apportioning the concentrations of pollutants predicted by a photochemical model to emissions from different sources. A novel feature of the method is that it can apportion the difference in a species concentration between two simulations. For example, the anthropogenic ozone increment, which is the difference between a simulation with all emissions present and another simulation with only the background (e.g., biogenic) emissions included, can be allocated to the anthropogenic emission sources. The method is based on an existing, exact mathematical equation. This equation is applied to relate the concentration difference between simulations to line or path integrals of first-order sensitivity coefficients. The sensitivities describe the effects of changing the emissions and are accurately calculated by the decoupled direct method. The path represents a continuous variation of emissions between the two simulations, and each path can be viewed as a separate emission-control strategy. The method does not require auxiliary assumptions, e.g., whether ozone formation is limited by the availability of volatile organic compounds (VOCs) or nitrogen oxides (NOx), and can be used for all the species predicted by the model. A simplified configuration of the Comprehensive Air Quality Model with Extensions (CAMx) is used to evaluate the accuracy of different numerical integration procedures and the dependence of the source contributions on the path. A Gauss-Legendre formula using three or four points along the path gives good accuracy for apportioning the anthropogenic increments of ozone, nitrogen dioxide, formaldehyde, and nitric acid. Source contributions to these increments were obtained for paths representing proportional control of all anthropogenic emissions together, control of NOx emissions before VOC emissions, and control of VOC emissions before NOx emissions. There are similarities in the source contributions from the

A SIMPLE ANALYTICAL METHOD TO DETERMINE SOLAR ENERGETIC PARTICLES' MEAN FREE PATH

International Nuclear Information System (INIS)

He, H.-Q.; Qin, G.

2011-01-01

To obtain the mean free path of solar energetic particles (SEPs) for a solar event, one usually has to fit time profiles of both flux and anisotropy from spacecraft observations to numerical simulations of SEPs' transport processes. This method can be called a simulation method. But a reasonably good fitting needs a lot of simulations, which demand a large amount of calculation resources. Sometimes, it is necessary to find an easy way to obtain the mean free path of SEPs quickly, for example, in space weather practice. Recently, Shalchi et al. provided an approximate analytical formula of SEPs' anisotropy time profile as a function of particles' mean free path for impulsive events. In this paper, we determine SEPs' mean free path by fitting the anisotropy time profiles from Shalchi et al.'s analytical formula to spacecraft observations. This new method can be called an analytical method. In addition, we obtain SEPs' mean free path with the traditional simulation methods. Finally, we compare the mean free path obtained with the simulation method to that of the analytical method to show that the analytical method, with some minor modifications, can give us a good, quick approximation of SEPs' mean free path for impulsive events.

Path Planning Software and Graphics Interface for an Autonomous Vehicle, Accounting for Terrain Features

National Research Council Canada - National Science Library

Hurezeanu, Vlad

2000-01-01

.... This vehicle performs tasks to include surveying fields, laying mines, and teleoperation. The capability of the vehicle will be increased if its supporting software plans paths that take into account the terrain features...

Mathematical optimization for planning and design of cycle paths

Energy Technology Data Exchange (ETDEWEB)

LiÑan Ruiz, R.J.; Perez Aracil, J.; Cabrera Cañizares, V.

2016-07-01

The daily need for citizens to move for different activities, whatever its nature, has been greatly affected by the changes. The advantages resulting from the inclusion of the bicycle as a mode of transport and the proliferation of its use among citizens are numerous and extend both in the field of urban mobility and sustainable development.Currently, there are a number of programs for the implementation, promotion or increased public participation related to cycling in cities. But ultimately, each and every one of these initiatives have the same goal, to create a mesh of effective, useful and cycling trails that allow the use of bicycles in preferred routes with high guarantees of security, incorporating bicycle model intermodal urban transport.With the gradual implementation of bike lanes, many people have begun to use them to get around the city. But everything again needs a period of adaptation, and the reality is that the road network for these vehicles is full of obstacles to the rider. The current situation has led to the proposal that many kilometers of cycle paths needed to supply the demand of this mode of transport and, if implemented and planned are correct and sufficient.This paper presents a mathematical programming model for optimal design of a network for cyclists is presented. Specifically, the model determines a network of bicycle infrastructure, appropriate to the characteristics of a network of existing roads.As an application of the proposed model, the result of these experiments give a number of useful conclusions for planning and designing networks of cycle paths from a social perspective, applied to the case in the city of Malaga. (Author)

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Directory of Open Access Journals (Sweden)

JingRui Zhang

2015-03-01

Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

AEDT sensor path methods using BADA4

Science.gov (United States)

2017-06-01

This report documents the development and use of sensor path data processing in the Federal Aviation Administration's (FAAs) Aviation Environmental Design Tool (AEDT). The methods are primarily intended to assist analysts with using AEDT to determ...

Arctic curves in path models from the tangent method

Science.gov (United States)

Di Francesco, Philippe; Lapa, Matthew F.

2018-04-01

Recently, Colomo and Sportiello introduced a powerful method, known as the tangent method, for computing the arctic curve in statistical models which have a (non- or weakly-) intersecting lattice path formulation. We apply the tangent method to compute arctic curves in various models: the domino tiling of the Aztec diamond for which we recover the celebrated arctic circle; a model of Dyck paths equivalent to the rhombus tiling of a half-hexagon for which we find an arctic half-ellipse; another rhombus tiling model with an arctic parabola; the vertically symmetric alternating sign matrices, where we find the same arctic curve as for unconstrained alternating sign matrices. The latter case involves lattice paths that are non-intersecting but that are allowed to have osculating contact points, for which the tangent method was argued to still apply. For each problem we estimate the large size asymptotics of a certain one-point function using LU decomposition of the corresponding Gessel–Viennot matrices, and a reformulation of the result amenable to asymptotic analysis.

MR-based real time path planning for cardiac operations with transapical access.

Science.gov (United States)

Yeniaras, Erol; Navkar, Nikhil V; Sonmez, Ahmet E; Shah, Dipan J; Deng, Zhigang; Tsekos, Nikolaos V

2011-01-01

Minimally invasive surgeries (MIS) have been perpetually evolving due to their potential high impact on improving patient management and overall cost effectiveness. Currently, MIS are further strengthened by the incorporation of magnetic resonance imaging (MRI) for amended visualization and high precision. Motivated by the fact that real-time MRI is emerging as a feasible modality especially for guiding interventions and surgeries in the beating heart; in this paper we introduce a real-time path planning algorithm for intracardiac procedures. Our approach creates a volumetric safety zone inside a beating heart and updates it on-the-fly using real-time MRI during the deployment of a robotic device. In order to prove the concept and assess the feasibility of the introduced method, a realistic operational scenario of transapical aortic valve replacement in a beating heart is chosen as the virtual case study.

Panning for Gold: The personal journey of mental health wellness and its relationships with Planning Alternatives Tomorrows with Hope (PATH

Directory of Open Access Journals (Sweden)

Matthew Lyndon Armstrong

2015-12-01

Full Text Available This study explored how the Planning Alternatives Tomorrows with Hope (PATH process could enhance and strengthen an individual’s personal journey of recovery. This article utilised the knowledge base of members of a Community of Practice, located in Brisbane Australia. Members had a deep concern and passion to promote and strengthen wellbeing for people who live with the experience of mental ill health. They were invited to form a focus group to explore the use of PATH and its relationship with mental health wellness. After contemplating and reflecting on an example of the PATH process, the focus group explored opportunities for PATH to become one of many wellness resources for people experiencing and overcoming mental ill health. Through the exploration of personal meaning, storytelling and community connection (anchored in the visuals and graphics of the PATH example, the study found that PATH can make a valuable contribution by restoring some of the power inbalances in traditonal service frameworks and enhancing personal self direction. Keywords: mental health distress, practitioners, recovery, facilitation, creativity, planning

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

Directory of Open Access Journals (Sweden)

Liang Shen

2017-01-01

Full Text Available There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K-shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

Optimal Paths in Gliding Flight

Science.gov (United States)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

Directory of Open Access Journals (Sweden)

Jiang Zhao

2016-01-01

Full Text Available This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

Path coupling and aggregate path coupling

CERN Document Server

Kovchegov, Yevgeniy

2018-01-01

This book describes and characterizes an extension to the classical path coupling method applied to statistical mechanical models, referred to as aggregate path coupling. In conjunction with large deviations estimates, the aggregate path coupling method is used to prove rapid mixing of Glauber dynamics for a large class of statistical mechanical models, including models that exhibit discontinuous phase transitions which have traditionally been more difficult to analyze rigorously. The book shows how the parameter regions for rapid mixing for several classes of statistical mechanical models are derived using the aggregate path coupling method.

A path flux analysis method for the reduction of detailed chemical kinetic mechanisms

Energy Technology Data Exchange (ETDEWEB)

Sun, Wenting; Ju, Yiguang [Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544 (United States); Chen, Zheng [State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871 (China); Gou, Xiaolong [School of Power Engineering, Chongqing University, Chongqing 400044 (China)

2010-07-15

A direct path flux analysis (PFA) method for kinetic mechanism reduction is proposed and validated by using high temperature ignition, perfect stirred reactors, and steady and unsteady flame propagations of n-heptane and n-decane/air mixtures. The formation and consumption fluxes of each species at multiple reaction path generations are analyzed and used to identify the important reaction pathways and the associated species. The formation and consumption path fluxes used in this method retain flux conservation information and are used to define the path indexes for the first and the second generation reaction paths related to a targeted species. Based on the indexes of each reaction path for the first and second generations, different sized reduced chemical mechanisms which contain different number of species are generated. The reduced mechanisms of n-heptane and n-decane obtained by using the present method are compared to those generated by the direct relation graph (DRG) method. The reaction path analysis for n-decane is conducted to demonstrate the validity of the present method. The comparisons of the ignition delay times, flame propagation speeds, flame structures, and unsteady spherical flame propagation processes showed that with either the same or significantly less number of species, the reduced mechanisms generated by the present PFA are more accurate than that of DRG in a broad range of initial pressures and temperatures. The method is also integrated with the dynamic multi-timescale method and a further increase of computation efficiency is achieved. (author)

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.

The intertwining paths of the density managment and riparian buffer study and the Northwest Forest Plan

Science.gov (United States)

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...

PRELIMINARY PROJECT PLAN FOR LANSCE INTEGRATED FLIGHT PATHS 11A, 11B, 12, and 13

International Nuclear Information System (INIS)

Bultman, D. H.; Weinacht, D.

2000-01-01

This Preliminary Project Plan Summarizes the Technical, Cost, and Schedule baselines for an integrated approach to developing several flight paths at the Manual Lujan Jr. Neutron Scattering Center at the Los Alamos Neutron Science Center. For example, the cost estimate is intended to serve only as a rough order of magnitude assessment of the cost that might be incurred as the flight paths are developed. Further refinement of the requirements and interfaces for each beamline will permit additional refinement and confidence in the accuracy of all three baselines (Technical, Cost, Schedule)

Lagrangian coherent structure assisted path planning for transoceanic autonomous underwater vehicle missions.

Science.gov (United States)

Ramos, A G; García-Garrido, V J; Mancho, A M; Wiggins, S; Coca, J; Glenn, S; Schofield, O; Kohut, J; Aragon, D; Kerfoot, J; Haskins, T; Miles, T; Haldeman, C; Strandskov, N; Allsup, B; Jones, C; Shapiro, J

2018-03-15

Transoceanic Gliders are Autonomous Underwater Vehicles (AUVs) for which there is a developing and expanding range of applications in open-seas research, technology and underwater clean transport. Mature glider autonomy, operating depth (0-1000 meters) and low energy consumption without a CO 2 footprint enable evolutionary access across ocean basins. Pursuant to the first successful transatlantic glider crossing in December 2009, the Challenger Mission has opened the door to long-term, long-distance routine transoceanic AUV missions. These vehicles, which glide through the water column between 0 and 1000 meters depth, are highly sensitive to the ocean current field. Consequently, it is essential to exploit the complex space-time structure of the ocean current field in order to plan a path that optimizes scientific payoff and navigation efficiency. This letter demonstrates the capability of dynamical system theory for achieving this goal by realizing the real-time navigation strategy for the transoceanic AUV named Silbo, which is a Slocum deep-glider (0-1000 m), that crossed the North Atlantic from April 2016 to March 2017. Path planning in real time based on this approach has facilitated an impressive speed up of the AUV to unprecedented velocities resulting in major battery savings on the mission, offering the potential for routine transoceanic long duration missions.

Side-to-side 3D coverage path planning approach for agricultural robots to minimize skip/overlap areas between swaths

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...... operations are usually repeated in the same field and from year to year as well, therefore, it should be carried out in a manner that minimizes environmental impact and cost taking into account the topographic land features. Current 3D terrain field coverage path planning algorithms are simply 2D coverage...

An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

OpenAIRE

Gramajo, German; Shankar, Praveen

2017-01-01

A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of ...

Study on State Transition Method Applied to Motion Planning for a Humanoid Robot

Directory of Open Access Journals (Sweden)

Xuyang Wang

2008-11-01

Full Text Available This paper presents an approach of motion planning for a humanoid robot using a state transition method. In this method, motion planning is simplified by introducing a state-space to describe the whole motion series. And each state in the state-space corresponds to a contact state specified during the motion. The continuous motion is represented by a sequence of discrete states. The concept of the transition between two neighboring states, that is the state transition, can be realized by using some traditional path planning methods. Considering the dynamical stability of the robot, a state transition method based on search strategy is proposed. Different sets of trajectories are generated by using a variable 5th-order polynomial interpolation method. After quantifying the stabilities of these trajectories, the trajectories with the largest stability margin are selected as the final state transition trajectories. Rising motion process is exemplified to validate the method and the simulation results show the proposed method to be feasible and effective.

MEASURING PATH DEPENDENCY

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

STRATEGIC INFORMATION SYSTEMS PLANNING IN THE BANKING SECTOR—A PATH ANALYTIC MODEL STUDY IN THE INDIAN CONTEXT

Directory of Open Access Journals (Sweden)

A. M. Rawani

2002-01-01

Full Text Available This paper presents a path analytic model showing the cause and effect relationships among various Information Systems (IS planning variables for the banking sector in India. In recent years, there has been an increased awareness among banks of the potential of Information Technology (IT and the use of information systems. Strategic information system planning (SISP becomes an important issue in the use of IS strategically. In India, banks have now started realizing the importance of SISP. In this study, 11 IS planning variables for the banking sector in India are examined and the influence of one over the other is investigated using path analysis. Data for the study are collected from 52 banks operating in India. The results of the study indicate that top management involvement in IS planning greatly influences the whole planning exercise. Moreover, top management involvement is higher when they foresee greater future impact of IS. The study also highlights the need and importance of user training in the banking sector. Change in the focus and orientation of user-training will make the users competent to conceive with innovative IS applications.

AN IMPROVEMENT ON GEOMETRY-BASED METHODS FOR GENERATION OF NETWORK PATHS FROM POINTS

Directory of Open Access Journals (Sweden)

Z. Akbari

2014-10-01

Full Text Available Determining network path is important for different purposes such as determination of road traffic, the average speed of vehicles, and other network analysis. One of the required input data is information about network path. Nevertheless, the data collected by the positioning systems often lead to the discrete points. Conversion of these points to the network path have become one of the challenges which different researchers, presents many ways for solving it. This study aims at investigating geometry-based methods to estimate the network paths from the obtained points and improve an existing point to curve method. To this end, some geometry-based methods have been studied and an improved method has been proposed by applying conditions on the best method after describing and illustrating weaknesses of them.

IRP methods for Environmental Impact Statements of utility expansion plans

International Nuclear Information System (INIS)

Cavallo, J.D.; Hemphill, R.C.; Veselka, T.D.

1992-01-01

Most large electric utilities and a growing number of gas utilities in the United States are using a planning method -- Integrated Resource Planning (IRP) - which incorporates demand-side management (DSM) programs whenever the marginal cost of the DSM programs are lower than the marginal cost of supply-side expansion options. Argonne National Laboratory has applied the IRP method in its socio-economic analysis of an Environmental Impact Statement (EIS) of power marketing for a system of electric utilities in the mountain and western regions of the United States. Applying the IRP methods provides valuable information to the participants in an EIS process involving capacity expansion of an electric or gas utility. The major challenges of applying the IRP method within an EIS are the time consuming and costly task of developing a least cost expansion path for each altemative, the detailed quantification of environmental damages associated with capacity expansion, and the explicit inclusion of societal-impacts to the region

The study of system function analysis method for success path alarm design

International Nuclear Information System (INIS)

Kang, S. K.; Shin, Y. C.

1999-01-01

The key benefit to the common use of the critical function approach for safety and mission functions is that monitoring methods expected to be used by operaotrs during emergency condition are used continuously during normal operation. For each critical safety function there exists two or more success paths. Information Processing System monitors the availability, operation state and performance of the critical function success paths. In this paper, We have studied System Function Analysis(SFA) for the design of Success Path Alarm(SPA) for applying in KNGR. In here, we thought that SFA will help the design of SPA. The SFA can be applicable to the design of SPA according to NUREG-0711, also can induce the algorithm for alarm of system, train and flow path. We present a method of system function analysis for designing Success Path Alarm

A new multiple robot path planning algorithm: dynamic distributed particle swarm optimization.

Science.gov (United States)

Ayari, Asma; Bouamama, Sadok

2017-01-01

Multiple robot systems have become a major study concern in the field of robotic research. Their control becomes unreliable and even infeasible if the number of robots increases. In this paper, a new dynamic distributed particle swarm optimization (D 2 PSO) algorithm is proposed for trajectory path planning of multiple robots in order to find collision-free optimal path for each robot in the environment. The proposed approach consists in calculating two local optima detectors, LOD pBest and LOD gBest . Particles which are unable to improve their personal best and global best for predefined number of successive iterations would be replaced with restructured ones. Stagnation and local optima problems would be avoided by adding diversity to the population, without losing the fast convergence characteristic of PSO. Experiments with multiple robots are provided and proved effectiveness of such approach compared with the distributed PSO.

A path method for finding energy barriers and minimum energy paths in complex micromagnetic systems

International Nuclear Information System (INIS)

Dittrich, R.; Schrefl, T.; Suess, D.; Scholz, W.; Forster, H.; Fidler, J.

2002-01-01

Minimum energy paths and energy barriers are calculated for complex micromagnetic systems. The method is based on the nudged elastic band method and uses finite-element techniques to represent granular structures. The method was found to be robust and fast for both simple test problems as well as for large systems such as patterned granular media. The method is used to estimate the energy barriers in CoCr-based perpendicular recording media

Aircraft Engine Gas Path Diagnostic Methods: Public Benchmarking Results

Science.gov (United States)

Simon, Donald L.; Borguet, Sebastien; Leonard, Olivier; Zhang, Xiaodong (Frank)

2013-01-01

Recent technology reviews have identified the need for objective assessments of aircraft engine health management (EHM) technologies. To help address this issue, a gas path diagnostic benchmark problem has been created and made publicly available. This software tool, referred to as the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES), has been constructed based on feedback provided by the aircraft EHM community. It provides a standard benchmark problem enabling users to develop, evaluate and compare diagnostic methods. This paper will present an overview of ProDiMES along with a description of four gas path diagnostic methods developed and applied to the problem. These methods, which include analytical and empirical diagnostic techniques, will be described and associated blind-test-case metric results will be presented and compared. Lessons learned along with recommendations for improving the public benchmarking processes will also be presented and discussed.

A fast tomographic method for searching the minimum free energy path

International Nuclear Information System (INIS)

Chen, Changjun; Huang, Yanzhao; Xiao, Yi; Jiang, Xuewei

2014-01-01

Minimum Free Energy Path (MFEP) provides a lot of important information about the chemical reactions, like the free energy barrier, the location of the transition state, and the relative stability between reactant and product. With MFEP, one can study the mechanisms of the reaction in an efficient way. Due to a large number of degrees of freedom, searching the MFEP is a very time-consuming process. Here, we present a fast tomographic method to perform the search. Our approach first calculates the free energy surfaces in a sequence of hyperplanes perpendicular to a transition path. Based on an objective function and the free energy gradient, the transition path is optimized in the collective variable space iteratively. Applications of the present method to model systems show that our method is practical. It can be an alternative approach for finding the state-to-state MFEP

Based on Short Motion Paths and Artificial Intelligence Method for Chinese Chess Game

Directory of Open Access Journals (Sweden)

Chien-Ming Hung

2017-08-01

Full Text Available The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots. Player can play the Chinese chess game according to the game rules with the supervised computer. The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface. We uses enhance A* searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously. We implement a famous set to be called lwild horses run in farmr using the proposed method. First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer. Then the supervised computer implements the simulation results on the chessboard platform using mobile robots. Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses, and detect the cross point of the platform using three reflective IR modules.

Optimal path planning for single and multiple aircraft using a reduced order formulation

Science.gov (United States)

Twigg, Shannon S.

High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

Science.gov (United States)

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.

CPM (Critical Path Method) as a Curriculum Tool.

Science.gov (United States)

Mongerson, M. Duane

This document discusses and illustrates the use of the Critical Path Method (CPM) as a tool for developing curriculum. In so doing a brief review of the evolution of CPM as a management tool developed by E. I. duPont de Nemours Company is presented. It is also noted that CPM is only a method of sequencing learning activities and not an end unto…

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

Science.gov (United States)

Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

A Vision-Aided 3D Path Teaching Method before Narrow Butt Joint Welding.

Science.gov (United States)

Zeng, Jinle; Chang, Baohua; Du, Dong; Peng, Guodong; Chang, Shuhe; Hong, Yuxiang; Wang, Li; Shan, Jiguo

2017-05-11

For better welding quality, accurate path teaching for actuators must be achieved before welding. Due to machining errors, assembly errors, deformations, etc., the actual groove position may be different from the predetermined path. Therefore, it is significant to recognize the actual groove position using machine vision methods and perform an accurate path teaching process. However, during the teaching process of a narrow butt joint, the existing machine vision methods may fail because of poor adaptability, low resolution, and lack of 3D information. This paper proposes a 3D path teaching method for narrow butt joint welding. This method obtains two kinds of visual information nearly at the same time, namely 2D pixel coordinates of the groove in uniform lighting condition and 3D point cloud data of the workpiece surface in cross-line laser lighting condition. The 3D position and pose between the welding torch and groove can be calculated after information fusion. The image resolution can reach 12.5 μm. Experiments are carried out at an actuator speed of 2300 mm/min and groove width of less than 0.1 mm. The results show that this method is suitable for groove recognition before narrow butt joint welding and can be applied in path teaching fields of 3D complex components.

Feasible Path Generation Using Bezier Curves for Car-Like Vehicle

Science.gov (United States)

Latip, Nor Badariyah Abdul; Omar, Rosli

2017-08-01

When planning a collision-free path for an autonomous vehicle, the main criteria that have to be considered are the shortest distance, lower computation time and completeness, i.e. a path can be found if one exists. Besides that, a feasible path for the autonomous vehicle is also crucial to guarantee that the vehicle can reach the target destination considering its kinematic constraints such as non-holonomic and minimum turning radius. In order to address these constraints, Bezier curves is applied. In this paper, Bezier curves are modeled and simulated using Matlab software and the feasibility of the resulting path is analyzed. Bezier curve is derived from a piece-wise linear pre-planned path. It is found that the Bezier curves has the capability of making the planned path feasible and could be embedded in a path planning algorithm for an autonomous vehicle with kinematic constraints. It is concluded that the length of segments of the pre-planned path have to be greater than a nominal value, derived from the vehicle wheelbase, maximum steering angle and maximum speed to ensure the path for the autonomous car is feasible.

A Collision-Free G2 Continuous Path-Smoothing Algorithm Using Quadratic Polynomial Interpolation

Directory of Open Access Journals (Sweden)

Seong-Ryong Chang

2014-12-01

Full Text Available Most path-planning algorithms are used to obtain a collision-free path without considering continuity. On the other hand, a continuous path is needed for stable movement. In this paper, the searched path was converted into a G2 continuous path using the modified quadratic polynomial and membership function interpolation algorithm. It is simple, unique and provides a good geometric interpretation. In addition, a collision-checking and improvement algorithm is proposed. The collision-checking algorithm can check the collisions of a smoothed path. If collisions are detected, the collision improvement algorithm modifies the collision path to a collision-free path. The collision improvement algorithm uses a geometric method. This method uses the perpendicular line between a collision position and the collision piecewise linear path. The sub-waypoint is added, and the QPMI algorithm is applied again. As a result, the collision-smoothed path is converted into a collision-free smooth path without changing the continuity.

The shortest-path problem analysis and comparison of methods

CERN Document Server

Ortega-Arranz, Hector; Gonzalez-Escribano, Arturo

2014-01-01

Many applications in different domains need to calculate the shortest-path between two points in a graph. In this paper we describe this shortest path problem in detail, starting with the classic Dijkstra's algorithm and moving to more advanced solutions that are currently applied to road network routing, including the use of heuristics and precomputation techniques. Since several of these improvements involve subtle changes to the search space, it may be difficult to appreciate their benefits in terms of time or space requirements. To make methods more comprehensive and to facilitate their co

Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles

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Pablo Marin-Plaza

2018-01-01

Full Text Available The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.

User's guide to Monte Carlo methods for evaluating path integrals

Science.gov (United States)

Westbroek, Marise J. E.; King, Peter R.; Vvedensky, Dimitri D.; Dürr, Stephan

2018-04-01

We give an introduction to the calculation of path integrals on a lattice, with the quantum harmonic oscillator as an example. In addition to providing an explicit computational setup and corresponding pseudocode, we pay particular attention to the existence of autocorrelations and the calculation of reliable errors. The over-relaxation technique is presented as a way to counter strong autocorrelations. The simulation methods can be extended to compute observables for path integrals in other settings.

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

Science.gov (United States)

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.

An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

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Nizar Hadi Abbas

2016-07-01

Full Text Available This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

Tool path in torus tool CNC machining

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XU Ying

2016-10-01

Full Text Available This paper is about tool path in torus tool CNC machining.The mathematical model of torus tool is established.The tool path planning algorithm is determined through calculation of the cutter location,boundary discretization,calculation of adjacent tool path and so on,according to the conversion formula,the cutter contact point will be converted to the cutter location point and then these points fit a toolpath.Lastly,the path planning algorithm is implemented by using Matlab programming.The cutter location points for torus tool are calculated by Matlab,and then fit these points to a toolpath.While using UG software,another tool path of free surface is simulated of the same data.It is drew compared the two tool paths that using torus tool is more efficient.

Employing Multiple Unmanned Aerial Vehicles for Co-Operative Path Planning

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Durdana Habib

2013-05-01

Full Text Available Abstract 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.

An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

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.

Entropic sampling in the path integral Monte Carlo method

International Nuclear Information System (INIS)

Vorontsov-Velyaminov, P N; Lyubartsev, A P

2003-01-01

We have extended the entropic sampling Monte Carlo method to the case of path integral representation of a quantum system. A two-dimensional density of states is introduced into path integral form of the quantum canonical partition function. Entropic sampling technique within the algorithm suggested recently by Wang and Landau (Wang F and Landau D P 2001 Phys. Rev. Lett. 86 2050) is then applied to calculate the corresponding entropy distribution. A three-dimensional quantum oscillator is considered as an example. Canonical distributions for a wide range of temperatures are obtained in a single simulation run, and exact data for the energy are reproduced

A low complexity method for the optimization of network path length in spatially embedded networks

International Nuclear Information System (INIS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li; Ming, Yong; Chen, Sheng-Yong; Wang, Wan-Liang

2014-01-01

The average path length of a network is an important index reflecting the network transmission efficiency. In this paper, we propose a new method of decreasing the average path length by adding edges. A new indicator is presented, incorporating traffic flow demand, to assess the decrease in the average path length when a new edge is added during the optimization process. With the help of the indicator, edges are selected and added into the network one by one. The new method has a relatively small time computational complexity in comparison with some traditional methods. In numerical simulations, the new method is applied to some synthetic spatially embedded networks. The result shows that the method can perform competitively in decreasing the average path length. Then, as an example of an application of this new method, it is applied to the road network of Hangzhou, China. (paper)

Path-Wise Test Data Generation Based on Heuristic Look-Ahead Methods

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Ying Xing

2014-01-01

Full Text Available Path-wise test data generation is generally considered an important problem in the automation of software testing. In essence, it is a constraint optimization problem, which is often solved by search methods such as backtracking algorithms. In this paper, the backtracking algorithm branch and bound and state space search in artificial intelligence are introduced to tackle the problem of path-wise test data generation. The former is utilized to explore the space of potential solutions and the latter is adopted to construct the search tree dynamically. Heuristics are employed in the look-ahead stage of the search. Dynamic variable ordering is presented with a heuristic rule to break ties, values of a variable are determined by the monotonicity analysis on branching conditions, and maintaining path consistency is achieved through analysis on the result of interval arithmetic. An optimization method is also proposed to reduce the search space. The results of empirical experiments show that the search is conducted in a basically backtrack-free manner, which ensures both test data generation with promising performance and its excellence over some currently existing static and dynamic methods in terms of coverage. The results also demonstrate that the proposed method is applicable in engineering.

Enroute flight-path planning - Cooperative performance of flight crews and knowledge-based systems

Science.gov (United States)

Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Galdes, Deb

1989-01-01

Interface design issues associated with the introduction of knowledge-based systems into the cockpit are discussed. Such issues include not only questions about display and control design, they also include deeper system design issues such as questions about the alternative roles and responsibilities of the flight crew and the computer system. In addition, the feasibility of using enroute flight path planning as a context for exploring such research questions is considered. In particular, the development of a prototyping shell that allows rapid design and study of alternative interfaces and system designs is discussed.

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.

Zero-Slack, Noncritical Paths

Science.gov (United States)

Simons, Jacob V., Jr.

2017-01-01

The critical path method/program evaluation and review technique method of project scheduling is based on the importance of managing a project's critical path(s). Although a critical path is the longest path through a network, its location in large projects is facilitated by the computation of activity slack. However, logical fallacies in…

A touch-probe path generation method through similarity analysis between the feature vectors in new and old models

Energy Technology Data Exchange (ETDEWEB)

Jeon, Hye Sung; Lee, Jin Won; Yang, Jeong Sam [Dept. of Industrial Engineering, Ajou University, Suwon (Korea, Republic of)

2016-10-15

The On-machine measurement (OMM), which measures a work piece during or after the machining process in the machining center, has the advantage of measuring the work piece directly within the work space without moving it. However, the path generation procedure used to determine the measuring sequence and variables for the complex features of a target work piece has the limitation of requiring time-consuming tasks to generate the measuring points and mostly relies on the proficiency of the on-site engineer. In this study, we propose a touch-probe path generation method using similarity analysis between the feature vectors of three-dimensional (3-D) shapes for the OMM. For the similarity analysis between a new 3-D model and existing 3-D models, we extracted the feature vectors from models that can describe the characteristics of a geometric shape model; then, we applied those feature vectors to a geometric histogram that displays a probability distribution obtained by the similarity analysis algorithm. In addition, we developed a computer-aided inspection planning system that corrects non-applied measuring points that are caused by minute geometry differences between the two models and generates the final touch-probe path.

An adaptation of Krylov subspace methods to path following

Energy Technology Data Exchange (ETDEWEB)

Walker, H.F. [Utah State Univ., Logan, UT (United States)

1996-12-31

Krylov subspace methods at present constitute a very well known and highly developed class of iterative linear algebra methods. These have been effectively applied to nonlinear system solving through Newton-Krylov methods, in which Krylov subspace methods are used to solve the linear systems that characterize steps of Newton`s method (the Newton equations). Here, we will discuss the application of Krylov subspace methods to path following problems, in which the object is to track a solution curve as a parameter varies. Path following methods are typically of predictor-corrector form, in which a point near the solution curve is {open_quotes}predicted{close_quotes} by some easy but relatively inaccurate means, and then a series of Newton-like corrector iterations is used to return approximately to the curve. The analogue of the Newton equation is underdetermined, and an additional linear condition must be specified to determine corrector steps uniquely. This is typically done by requiring that the steps be orthogonal to an approximate tangent direction. Augmenting the under-determined system with this orthogonality condition in a straightforward way typically works well if direct linear algebra methods are used, but Krylov subspace methods are often ineffective with this approach. We will discuss recent work in which this orthogonality condition is imposed directly as a constraint on the corrector steps in a certain way. The means of doing this preserves problem conditioning, allows the use of preconditioners constructed for the fixed-parameter case, and has certain other advantages. Experiments on standard PDE continuation test problems indicate that this approach is effective.

Pedestrian flow-path modeling to support tsunami evacuation and disaster relief planning in the U.S. Pacific Northwest

Science.gov (United States)

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.

Path-based Queries on Trajectory Data

DEFF Research Database (Denmark)

Krogh, Benjamin Bjerre; Pelekis, Nikos; Theodoridis, Yannis

2014-01-01

In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot...... sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path...... a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set...

A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

Science.gov (United States)

Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

2018-05-01

A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the

Visibility-Based Goal Oriented Metrics and Application to Navigation and Path Planning Problems

Science.gov (United States)

2017-12-14

Oriented Metrics and Application to Navigation and Path Planning Problems Report Term: 0-Other Email : ytsai@math.utexas.edu Distribution Statement: 1...error bounds that we have obtained. Report Date: 06-Dec-2017 INVESTIGATOR(S): Phone Number: 5122327757 Principal: Y Name: Yen-Hsi Tsai Email ...w1 w2 ◆ and ~z = ✓ z1 z2 ◆ . Then we can write D0 h (PN (xi,j)) = Rp (R+⌘)2+h2 + 1 2h (µ2w1 µ2z1) 0 µ2w2µ3z2 2h 0 ! . It follows that the non

Optimal path planning for video-guided smart munitions via multitarget tracking

Science.gov (United States)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

A focussed dynamic path finding algorithm with constraints

CSIR Research Space (South Africa)

Leenen, L

2013-11-01

Full Text Available heuristic to focus the search for an optimal path. Existing approaches to solving path planning problems tend to combine path costs with various other criteria such as obstacle avoidance in the objective function which is being optimised. The authors...

Reflector construction by sound path curves - A method of manual reflector evaluation in the field

International Nuclear Information System (INIS)

Siciliano, F.; Heumuller, R.

1985-01-01

In order to describe the time-of-flight behavior of various reflectors we have set up models and derived from them analytical and graphic approaches to reflector reconstruction. In the course of this work, maximum achievable accuracy and possible simplifications were investigated. The aim of the time-of-flight reconstruction method is to determine the points of a reflector on the basis of a sound path function (sound path as the function of the probe index position). This method can only be used on materials which are isotropic in terms of sound velocity since the method relies on time of flight being converted into sound path. This paper deals only with two-dimensional reconstruction, in other words all statements relate to the plane of incidence. The method is based on the fact that the geometrical location of the points equidistant from a certain probe index position is a circle. If circles with radiuses equal to the associated sound path are drawn for various search unit positions the points of intersection of the circles are the desired reflector points

Semantic text relatedness on Al-Qur’an translation using modified path based method

Science.gov (United States)

Irwanto, Yudi; Arif Bijaksana, Moch; Adiwijaya

2018-03-01

Abdul Baquee Muhammad [1] have built Corpus that contained AlQur’an domain, WordNet and dictionary. He has did initialisation in the development of knowledges about AlQur’an and the knowledges about relatedness between texts in AlQur’an. The Path based measurement method that proposed by Liu, Zhou and Zheng [3] has never been used in the AlQur’an domain. By using AlQur’an translation dataset in this research, the path based measurement method proposed by Liu, Zhou and Zheng [3] will be used to test this method in AlQur’an domain to obtain similarity values and to measure its correlation value. In this study the degree value is proposed to be used in modifying the path based method that proposed in previous research. Degree Value is the number of links that owned by a lcs (lowest common subsumer) node on a taxonomy. The links owned by a node on the taxonomy represent the semantic relationship that a node has in the taxonomy. By using degree value to modify the path-based method that proposed in previous research is expected that the correlation value obtained will increase. After running some experiment by using proposed method, the correlation measurement value can obtain fairly good correlation ties with 200 Word Pairs derive from Noun POS SimLex-999. The correlation value that be obtained is 93.3% which means their bonds are strong and they have very strong correlation. Whereas for the POS other than Noun POS vocabulary that owned by WordNet is incomplete therefore many pairs of words that the value of its similarity is zero so the correlation value is low.

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.

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

Qualification paths of adult educators in Sweden and Denmark

DEFF Research Database (Denmark)

Andersson, Per; Köpsén, Susanne; Larson, Anne

2013-01-01

fields of education and training. In this study, we analyse the qualification paths, or learning trajectories, of prospective adult educators in Sweden and Denmark. The analysis is based on narrative interviews with 29 students in training to become adult educators. The career paths of adult educators...... are often long and winding roads. Becoming an adult educator could be their primary desire, but it could also be their ‘Plan B’, a second choice. Individual motives and external demands interact in the professionalisation process. A shift in focus from teaching subject and methods to teaching context...... and the relation to the learners is part of the professional development. Finally, we argue that both academic studies and hands-on work in the adult education community are crucial parts of the adult educator’s qualification path....

Introduction to functional and path integral methods in quantum field theory

International Nuclear Information System (INIS)

Strathdee, J.

1991-11-01

The following aspects concerning the use of functional and path integral methods in quantum field theory are discussed: generating functionals and the effective action, perturbation series, Yang-Mills theory and BRST symmetry. 10 refs, 3 figs

A new online secondary path modeling method for adaptive active structure vibration control

International Nuclear Information System (INIS)

Pu, Yuxue; Zhang, Fang; Jiang, Jinhui

2014-01-01

This paper proposes a new variable step size FXLMS algorithm with an auxiliary noise power scheduling strategy for online secondary path modeling. The step size for the secondary path modeling filter and the gain of auxiliary noise are varied in accordance with the parameters available directly. The proposed method has a low computational complexity. Computer simulations show that an active vibration control system with the proposed method gives much better vibration attenuation and modeling accuracy at a faster convergence rate than existing methods. National Instruments’ CompactRIO is used as an embedded processor to control simply supported beam vibration. Experimental results indicate that the vibration of the beam has been effectively attenuated. (papers)

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

Science.gov (United States)

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

The Path Resistance Method for Bounding the Smallest Nontrivial Eigenvalue of a Laplacian

Science.gov (United States)

Guattery, Stephen; Leighton, Tom; Miller, Gary L.

1997-01-01

We introduce the path resistance method for lower bounds on the smallest nontrivial eigenvalue of the Laplacian matrix of a graph. The method is based on viewing the graph in terms of electrical circuits; it uses clique embeddings to produce lower bounds on lambda(sub 2) and star embeddings to produce lower bounds on the smallest Rayleigh quotient when there is a zero Dirichlet boundary condition. The method assigns priorities to the paths in the embedding; we show that, for an unweighted tree T, using uniform priorities for a clique embedding produces a lower bound on lambda(sub 2) that is off by at most an 0(log diameter(T)) factor. We show that the best bounds this method can produce for clique embeddings are the same as for a related method that uses clique embeddings and edge lengths to produce bounds.

Application of a path sensitizing method on automated generation of test specifications for control software

International Nuclear Information System (INIS)

Morimoto, Yuuichi; Fukuda, Mitsuko

1995-01-01

An automated generation method for test specifications has been developed for sequential control software in plant control equipment. Sequential control software can be represented as sequential circuits. The control software implemented in a control equipment is designed from these circuit diagrams. In logic tests of VLSI's, path sensitizing methods are widely used to generate test specifications. But the method generates test specifications at a single time only, and can not be directly applied to sequential control software. The basic idea of the proposed method is as follows. Specifications of each logic operator in the diagrams are defined in the software design process. Therefore, test specifications of each operator in the control software can be determined from these specifications, and validity of software can be judged by inspecting all of the operators in the logic circuit diagrams. Candidates for sensitized paths, on which test data for each operator propagates, can be generated by the path sensitizing method. To confirm feasibility of the method, it was experimentally applied to control software in digital control equipment. The program could generate test specifications exactly, and feasibility of the method was confirmed. (orig.) (3 refs., 7 figs.)

A Piecewise Acceleration-Optimal and Smooth-Jerk Trajectory Planning Method for Robot Manipulator along a Predefined Path

Directory of Open Access Journals (Sweden)

Yuan Chen

2011-09-01

Full Text Available This paper proposes a piecewise acceleration-optimal and smooth-jerk trajectory planning method of robot manipulator. The optimal objective function is given by the weighted sum of two terms having opposite effects: the maximal acceleration and the minimal jerk. Some computing techniques are proposed to determine the optimal solution. These techniques take both the time intervals between two interpolation points and the control points of B-spline function as optimal variables, redefine the kinematic constraints as the constraints of optimal variables, and reformulate the objective function in matrix form. The feasibility of the optimal method is illustrated by simulation and experimental results with pan mechanism for cooking robot.

A Motion Planning Method for Omnidirectional Mobile Robot Based on the Anisotropic Characteristics

Directory of Open Access Journals (Sweden)

Chuntao Leng

2008-11-01

Full Text Available A more suitable motion planning method for an omni-directional mobile robot (OMR, an improved APF method (iAPF, is proposed in this paper by introducing the revolving factor into the artificial potential field (APF. Accordingly, the motion direction derived from traditional artificial potential field (tAPF is regulated. The maximum velocity, maximum acceleration and energy consumption of the OMR moving in different directions are analyzed, based on the kinematic and dynamic constraints of an OMR, and the anisotropy of OMR is presented in this paper. Then the novel concept of an Anisotropic-Function is proposed to indicate the quality of motion in different directions, which can make a very favorable trade-off between time-optimality, stability and efficacy-optimality. In order to obtain the optimal motion, the path that the robot can take in order to avoid the obstacle safely and reach the goal in a shorter path is deduced. Finally, simulations and experiments are carried out to demonstrate that the motion resulting from the iAPF is high-speed, highly stable and highly efficient when compared to the tAPF.

Assessment of Masonry Buildings Subjected to Landslide-Induced Settlements: From Load Path Method to Evolutionary Optimization Method

Science.gov (United States)

Palmisano, Fabrizio; Elia, Angelo

2017-10-01

One of the main difficulties, when dealing with landslide structural vulnerability, is the diagnosis of the causes of crack patterns. This is also due to the excessive complexity of models based on classical structural mechanics that makes them inappropriate especially when there is the necessity to perform a rapid vulnerability assessment at the territorial scale. This is why, a new approach, based on a ‘simple model’ (i.e. the Load Path Method, LPM), has been proposed by Palmisano and Elia for the interpretation of the behaviour of masonry buildings subjected to landslide-induced settlements. However, the LPM is very useful for rapidly finding the 'most plausible solution' instead of the exact solution. To find the solution, optimization algorithms are necessary. In this scenario, this article aims to show how the Bidirectional Evolutionary Structural Optimization method by Huang and Xie, can be very useful to optimize the strut-and-tie models obtained by using the Load Path Method.

Multiagent path-finding in strategic games

OpenAIRE

Mihevc, Simon

2014-01-01

In this thesis I worked on creating, comparing and improving algorithms for multi-agent path planning on a domain typical for real-time strategy games. I implemented and compared Multiagent pathfinding using clearance and Multiagent pathfinding using independence detection and operator decomposition. I discovered that they had problems maintaining group compactness and took too long to calculate the path. I considerably improved the efficiency of both algorithms.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

Science.gov (United States)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

Science.gov (United States)

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.

Machine learning methods for planning

CERN Document Server

Minton, Steven

1993-01-01

Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credi

Semi-automated segmentation of the sigmoid and descending colon for radiotherapy planning using the fast marching method

International Nuclear Information System (INIS)

Losnegaard, Are; Hodneland, Erlend; Lundervold, Arvid; Hysing, Liv Bolstad; Muren, Ludvig Paul

2010-01-01

A fast and accurate segmentation of organs at risk, such as the healthy colon, would be of benefit for planning of radiotherapy, in particular in an adaptive scenario. For the treatment of pelvic tumours, a great challenge is the segmentation of the most adjacent and sensitive parts of the gastrointestinal tract, the sigmoid and descending colon. We propose a semi-automated method to segment these bowel parts using the fast marching (FM) method. Standard 3D computed tomography (CT) image data obtained from routine radiotherapy planning were used. Our pre-processing steps distinguish the intestine, muscles and air from connective tissue. The core part of our method separates the sigmoid and descending colon from the muscles and other segments of the intestine. This is done by utilizing the ability of the FM method to compute a specified minimal energy functional integrated along a path, and thereby extracting the colon centre line between user-defined control points in the sigmoid and descending colon. Further, we reconstruct the tube-shaped geometry of the sigmoid and descending colon by fitting ellipsoids to points on the path and by adding adjacent voxels that are likely voxels belonging to these bowel parts. Our results were compared to manually outlined sigmoid and descending colon, and evaluated using the Dice coefficient (DC). Tests on 11 patients gave an average DC of 0.83 (±0.07) with little user interaction. We conclude that the proposed method makes it possible to fast and accurately segment the sigmoid and descending colon from routine CT image data.

H∞ control for path tracking of autonomous underwater vehicle motion

Directory of Open Access Journals (Sweden)

Lin-Lin Wang

2015-05-01

Full Text Available In order to simplify the design of path tracking controller and solve the problem relating to nonlinear dynamic model of autonomous underwater vehicle motion planning, feedback linearization method is first adopted to transform the nonlinear dynamic model into an equivalent pseudo-linear dynamic model in horizontal coordinates. Then considering wave disturbance effect, mixed-sensitivity method of H∞ robust control is applied to design state-feedback controller for this equivalent dynamic model. Finally, control law of pseudo-linear dynamic model is transformed into state (surge velocity and yaw angular rate tracking control law of nonlinear dynamic model through inverse coordinate transformation. Simulation indicates that autonomous underwater vehicle path tracking is successfully implemented with this proposed method, and the influence of parameter variation in autonomous underwater vehicle dynamic model on its tracking performance is reduced by H∞ controller. All the results show that the method proposed in this article is effective and feasible.

Local and Global Path Generation for Autonomous Vehicles Using SplinesGeneración Local y Global de Trayectorias para Vehículo Autónomos Usando Splines

Directory of Open Access Journals (Sweden)

Randerson Lemos

2016-05-01

Full Text Available Abstract Context: Before autonomous vehicles being a reality in daily situations, outstanding issues regarding the techniques of autonomous mobility must be solved. Hence, relevant aspects of a path planning for terrestrial vehicles are shown. Method: The approached path planning technique uses splines to generate the global route. For this goal, waypoints obtained from online map services are used. With the global route parametrized in the arc-length, candidate local paths are computed and the optimal one is selected by cost functions. Results: Different routes are used to show that the number and distribution of waypoints are highly correlated to a satisfactory arc-length parameterization of the global route, which is essential to the proper behavior of the path planning technique. Conclusions: The cubic splines approach to the path planning problem successfully generates the global and local paths. Nevertheless, the use of raw data from the online map services showed to be unfeasible due the consistency of the data. Hence, a preprocessing stage of the raw data is proposed to guarantee the well behavior and robustness of the technique.

Generating Approximative Minimum Length Paths in 3D for UAVs

DEFF Research Database (Denmark)

Schøler, Flemming; la Cour-Harbo, Anders; Bisgaard, Morten

2012-01-01

We consider the challenge of planning a minimum length path from an initial position to a desired position for a rotorcraft. The path is found in a 3-dimensional Euclidean space containing a geometric obstacle. We base our approach on visibility graphs which have been used extensively for path pl...

Path to a Research Plan

Science.gov (United States)

Chiaramonte, Fran

2003-01-01

This viewgraph presentation discusses the status and goals for the NASA OBPR Physical Science Research Program. The following text was used to summarize the presentation. The OBPR Physical Sciences Research program has been comprehensively reviewed and endorsed by National Research Council. The value and need for the research have been re-affirmed. The research program has been prioritized and resource re-allocations have been carried out through an OBPR-wide process. An increasing emphasis on strategic, mission-oriented research is planned. The program will strive to maintain a balance between strategic and fundamental research. A feasible ISS flight research program fitting within the budgetary and ISS resource envelopes has been formulated for the near term (2003-2007). The current ISS research program will be significantly strengthened starting 2005 by using discipline dedicated research facility racks. A research re-planning effort has been initiated and will include active participation from the research community in the next few months. The research re-planning effort will poise PSR to increase ISS research utilization for a potential enhancement beyond ISS IP Core Complete. The Physical Sciences research program readily integrates the cross-disciplinary requirements of the NASA and OBPR strategic objectives. Each fundamental research thrust will develop a roadmap through technical workshops and Discipline Working Groups (DWGs). Most fundamental research thrusts will involve cross-disciplinary efforts. A Technology Roadmap will guide the Strategic Research for Exploration thrust. The Research Plan will integrate and coordinate fundamental Research Thrusts Roadmaps with the Technology Roadmap. The Technology Roadmap will be developed in coordination with other OBPR programs as well as other Enterprise (R,S,M,N). International Partners will contribute to the roadmaps and through research coordination. The research plan will be vetted with the discipline

Triangular Geometrized Sampling Heuristics for Fast Optimal Motion Planning

Directory of Open Access Journals (Sweden)

Ahmed Hussain Qureshi

2015-02-01

Full Text Available Rapidly-exploring Random Tree (RRT-based algorithms have become increasingly popular due to their lower computational complexity as compared with other path planning algorithms. The recently presented RRT* motion planning algorithm improves upon the original RRT algorithm by providing optimal path solutions. While RRT determines an initial collision-free path fairly quickly, RRT* guarantees almost certain convergence to an optimal, obstacle-free path from the start to the goal points for any given geometrical environment. However, the main limitations of RRT* include its slow processing rate and high memory consumption, due to the large number of iterations required for calculating the optimal path. In order to overcome these limitations, we present another improvement, i.e, the Triangular Geometerized-RRT* (TG-RRT* algorithm, which utilizes triangular geometrical methods to improve the performance of the RRT* algorithm in terms of the processing time and a decreased number of iterations required for an optimal path solution. Simulations comparing the performance results of the improved TG-RRT* with RRT* are presented to demonstrate the overall improvement in performance and optimal path detection.

On the orthogonalised reverse path method for nonlinear system identification

Science.gov (United States)

Muhamad, P.; Sims, N. D.; Worden, K.

2012-09-01

The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.

Spreading paths in partially observed social networks

Science.gov (United States)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Spreading paths in partially observed social networks.

Science.gov (United States)

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

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.

Study on the dominant reaction path in nucleosynthesis during stellar evolution by means of the Monte Carlo method

International Nuclear Information System (INIS)

Yamamoto, K.; Hashizume, K.; Wada, T.; Ohta, M.; Suda, T.; Nishimura, T.; Fujimoto, M. Y.; Kato, K.; Aikawa, M.

2006-01-01

We propose a Monte Carlo method to study the reaction paths in nucleosynthesis during stellar evolution. Determination of reaction paths is important to obtain the physical picture of stellar evolution. The combination of network calculation and our method gives us a better understanding of physical picture. We apply our method to the case of the helium shell flash model in the extremely metal poor star

High-order Path Integral Monte Carlo methods for solving strongly correlated fermion problems

Science.gov (United States)

Chin, Siu A.

2015-03-01

In solving for the ground state of a strongly correlated many-fermion system, the conventional second-order Path Integral Monte Carlo method is plagued with the sign problem. This is due to the large number of anti-symmetric free fermion propagators that are needed to extract the square of the ground state wave function at large imaginary time. In this work, I show that optimized fourth-order Path Integral Monte Carlo methods, which uses no more than 5 free-fermion propagators, in conjunction with the use of the Hamiltonian energy estimator, can yield accurate ground state energies for quantum dots with up to 20 polarized electrons. The correlations are directly built-in and no explicit wave functions are needed. This work is supported by the Qatar National Research Fund NPRP GRANT #5-674-1-114.

Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

Science.gov (United States)

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-09-18

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

Acquisition Path Analysis as a Collaborative Activity

International Nuclear Information System (INIS)

Nakao, A.; Grundule, R.; Gushchyn, K.; El Gebaly, A.; Higgy, R.; Tsvetkov, I.; Mandl, W.

2015-01-01

In the International Atomic Energy Agency, acquisition path analysis (APA) is indispensable to safeguards implementation. It is an integral part of both State evaluation process and the development of State level safeguards approaches, all performed through ongoing collaborative analysis of all available safeguards relevant information by State evaluation groups (SEG) with participation of other contributors, as required. To perform comprehensive State evaluation, to develop and revise State-level safeguards approaches, and to prepare annual implementation plans, the SEG in its collaborative analysis follows accepted safeguards methodology and guidance. In particular, the guide ''Performing Acquisition Path Analysis for the Development of a State-level Safeguards Approach for a State with a CSA'' is used. This guide identifies four major steps of the APA process: 1. Consolidating information about the State's past, present and planned nuclear fuel cycle-related capabilities and infrastructure; 2. Identifying and visually presenting technically plausible acquisition paths for the State; 3. Assessing acquisition path steps (State's technical capabilities and possible actions) along the identified acquisition paths; and 4. Assessing the time needed to accomplish each identified technically plausible acquisition path for the State. The paper reports on SEG members' and other contributors' experience with APA when following the above steps, including the identification of plausible acquisition pathways, estimation of time frames for all identified steps and determination of the time needed to accomplish each acquisition path. The difficulties that the SEG encountered during the process of performing the APA are also addressed. Feedback in the form of practical suggestions for improving the clarity of the acquisition path step assessment forms and a proposal for software support are also included. (author)

A Systematic, Automated Network Planning Method

DEFF Research Database (Denmark)

Holm, Jens Åge; Pedersen, Jens Myrup

2006-01-01

This paper describes a case study conducted to evaluate the viability of a systematic, automated network planning method. The motivation for developing the network planning method was that many data networks are planned in an adhoc manner with no assurance of quality of the solution with respect...... structures, that are ready to implement in a real world scenario, are discussed in the end of the paper. These are in the area of ensuring line independence and complexity of the design rules for the planning method....

A chain-of-states acceleration method for the efficient location of minimum energy paths

Energy Technology Data Exchange (ETDEWEB)

Hernández, E. R., E-mail: Eduardo.Hernandez@csic.es; Herrero, C. P. [Instituto de Ciencia de Materiales de Madrid (ICMM–CSIC), Campus de Cantoblanco, 28049 Madrid (Spain); Soler, J. M. [Departamento de Física de la Materia Condensada and IFIMAC, Universidad Autónoma de Madrid, 28049 Madrid (Spain)

2015-11-14

We describe a robust and efficient chain-of-states method for computing Minimum Energy Paths (MEPs) associated to barrier-crossing events in poly-atomic systems, which we call the acceleration method. The path is parametrized in terms of a continuous variable t ∈ [0, 1] that plays the role of time. In contrast to previous chain-of-states algorithms such as the nudged elastic band or string methods, where the positions of the states in the chain are taken as variational parameters in the search for the MEP, our strategy is to formulate the problem in terms of the second derivatives of the coordinates with respect to t, i.e., the state accelerations. We show this to result in a very simple and efficient method for determining the MEP. We describe the application of the method to a series of test cases, including two low-dimensional problems and the Stone-Wales transformation in C{sub 60}.

A chain-of-states acceleration method for the efficient location of minimum energy paths

International Nuclear Information System (INIS)

Hernández, E. R.; Herrero, C. P.; Soler, J. M.

2015-01-01

We describe a robust and efficient chain-of-states method for computing Minimum Energy Paths (MEPs) associated to barrier-crossing events in poly-atomic systems, which we call the acceleration method. The path is parametrized in terms of a continuous variable t ∈ [0, 1] that plays the role of time. In contrast to previous chain-of-states algorithms such as the nudged elastic band or string methods, where the positions of the states in the chain are taken as variational parameters in the search for the MEP, our strategy is to formulate the problem in terms of the second derivatives of the coordinates with respect to t, i.e., the state accelerations. We show this to result in a very simple and efficient method for determining the MEP. We describe the application of the method to a series of test cases, including two low-dimensional problems and the Stone-Wales transformation in C 60

Pure-Pursuit Reactive Path Tracking for Nonholonomic Mobile Robots with a 2D Laser Scanner

Directory of Open Access Journals (Sweden)

Jesús Morales

2009-01-01

Full Text Available Due to its simplicity and efficiency, the pure-pursuit path tracking method has been widely employed for planned navigation of nonholonomic ground vehicles. In this paper, we investigate the application of this technique for reactive tracking of paths that are implicitly defined by perceived environmental features. Goal points are obtained through an efficient interpretation of range data from an onboard 2D laser scanner to follow persons, corridors, and walls. Moreover, this formulation allows that a robotic mission can be composed of a combination of different types of path segments. These techniques have been successfully tested in the tracked mobile robot Auriga-α in an indoor environment.

The Unplanned Paths of Planning Schools.

Science.gov (United States)

Alonso, William

1986-01-01

Describes the evolving emphasis of schools of urban planning from concentration on scientific management, beautifying cities, and educating the public in the 1920s to solving the social problems in the 1960s. Calls for a collaboration of business and other professional schools to redefine the function and purpose of urban planning schools to…

Path integral methods via the use of the central limit theorem and application

International Nuclear Information System (INIS)

Thrapsaniotis, E G

2008-01-01

We consider a path integral in the phase space possibly with an influence functional in it and we use a method based on the use of the central limit theorem on the phase of the path integral representation to extract an equivalent expression which can be used in numerical calculations. Moreover we give conditions under which we can extract closed analytical results. As a specific application we consider a general system of two coupled and forced harmonic oscillators with coupling of the form x 1 x α 2 and we derive the relevant sign solved propagator

Transport coefficients for deeply inelastic scattering from the Feynman path integral method

International Nuclear Information System (INIS)

Brink, D.M.; Neto, J.; Weidenmueller, H.A.

1979-01-01

Friction and diffusion coefficients can be derived simply by combining statistical arguments with the Feynman path integral method. A transport equation for Feynman's influence functional is obtained, and transport coefficients are deduced from it. The expressions are discussed in the limits of weak, and of strong coupling. (Auth.)

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

Science.gov (United States)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

A Meta-Path-Based Prediction Method for Human miRNA-Target Association

Directory of Open Access Journals (Sweden)

Jiawei Luo

2016-01-01

Full Text Available MicroRNAs (miRNAs are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

MO-F-CAMPUS-T-05: SQL Database Queries to Determine Treatment Planning Resource Usage

International Nuclear Information System (INIS)

Fox, C; Gladstone, D

2015-01-01

Purpose: A radiation oncology clinic’s treatment capacity is traditionally thought to be limited by the number of machines in the clinic. As the number of fractions per course decrease and the number of adaptive plans increase, the question of how many treatment plans a clinic can plan becomes increasingly important. This work seeks to lay the ground work for assessing treatment planning resource usage. Methods: Care path templates were created using the Aria 11 care path interface. Care path tasks included key steps in the treatment planning process from the completion of CT simulation through the first radiation treatment. SQL Server Management Studio was used to run SQL queries to extract task completion time stamps along with care path template information and diagnosis codes from the Aria database. 6 months of planning cycles were evaluated. Elapsed time was evaluated in terms of work hours within Monday – Friday, 7am to 5pm. Results: For the 195 validated treatment planning cycles, the average time for planning and MD review was 22.8 hours. Of those cases 33 were categorized as urgent. The average planning time for urgent plans was 5 hours. A strong correlation between diagnosis code and range of elapsed planning time was as well as between elapsed time and select diagnosis codes was observed. It was also observed that tasks were more likely to be completed on the date due than the time that they were due. Follow-up confirmed that most users did not look at the due time. Conclusion: Evaluation of elapsed planning time and other tasks suggest that care paths should be adjusted to allow for different contouring and planning times for certain diagnosis codes and urgent cases. Additional clinic training around task due times vs dates or a structuring of care paths around due dates is also needed

MO-F-CAMPUS-T-05: SQL Database Queries to Determine Treatment Planning Resource Usage

Energy Technology Data Exchange (ETDEWEB)

Fox, C; Gladstone, D [Dartmouth Hitchcock-Medical Center, Hanover, NH (United States)

2015-06-15

Purpose: A radiation oncology clinic’s treatment capacity is traditionally thought to be limited by the number of machines in the clinic. As the number of fractions per course decrease and the number of adaptive plans increase, the question of how many treatment plans a clinic can plan becomes increasingly important. This work seeks to lay the ground work for assessing treatment planning resource usage. Methods: Care path templates were created using the Aria 11 care path interface. Care path tasks included key steps in the treatment planning process from the completion of CT simulation through the first radiation treatment. SQL Server Management Studio was used to run SQL queries to extract task completion time stamps along with care path template information and diagnosis codes from the Aria database. 6 months of planning cycles were evaluated. Elapsed time was evaluated in terms of work hours within Monday – Friday, 7am to 5pm. Results: For the 195 validated treatment planning cycles, the average time for planning and MD review was 22.8 hours. Of those cases 33 were categorized as urgent. The average planning time for urgent plans was 5 hours. A strong correlation between diagnosis code and range of elapsed planning time was as well as between elapsed time and select diagnosis codes was observed. It was also observed that tasks were more likely to be completed on the date due than the time that they were due. Follow-up confirmed that most users did not look at the due time. Conclusion: Evaluation of elapsed planning time and other tasks suggest that care paths should be adjusted to allow for different contouring and planning times for certain diagnosis codes and urgent cases. Additional clinic training around task due times vs dates or a structuring of care paths around due dates is also needed.

A chord error conforming tool path B-spline fitting method for NC machining based on energy minimization and LSPIA

OpenAIRE

He, Shanshan; Ou, Daojiang; Yan, Changya; Lee, Chen-Han

2015-01-01

Piecewise linear (G01-based) tool paths generated by CAM systems lack G1 and G2 continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical...

Accelerating cleanup. Paths to closure Hanford Site

International Nuclear Information System (INIS)

Edwards, C.

1998-01-01

This document was previously referred to as the Draft 2006 Plan. As part of the DOE's national strategy, the Richland Operations Office's Paths to Closure summarizes an integrated path forward for environmental cleanup at the Hanford Site. The Hanford Site underwent a concerted effort between 1994 and 1996 to accelerate the cleanup of the Site. These efforts are reflected in the current Site Baseline. This document describes the current Site Baseline and suggests strategies for further improvements in scope, schedule and cost. The Environmental Management program decided to change the name of the draft strategy and the document describing it in response to a series of stakeholder concerns, including the practicality of achieving widespread cleanup by 2006. Also, EM was concerned that calling the document a plan could be misconstrued to be a proposal by DOE or a decision-making document. The change in name, however, does not diminish the 2006 vision. To that end, Paths to Closure retains a focus on 2006, which serves as a point in time around which objectives and goals are established

Travel path and transport mode identification method using ''less-frequently-detected'' position data

International Nuclear Information System (INIS)

Shimizu, T; Yamaguchi, T; Ai, H; Katagiri, Y; Kawase, J

2014-01-01

This study aims to seek method on travel path and transport mode identification in case positions of travellers are detected in low frequency. The survey in which ten test travellers with GPS logger move around Tokyo city centre was conducted. Travel path datasets of each traveller in which position data are selected every five minutes are processed from our survey data. Coverage index analysis based on the buffer analysis using GIS software is conducted. The condition and possibility to identify a path and a transport mode used are discussed

Path diversity improves the identification of influential spreaders

Science.gov (United States)

Chen, Duan-Bing; Xiao, Rui; Zeng, An; Zhang, Yi-Cheng

2013-12-01

Identifying influential spreaders in complex networks is a crucial problem which relates to wide applications. Many methods based on the global information such as K-shell and PageRank have been applied to rank spreaders. However, most of the related previous works overwhelmingly focus on the number of paths for propagation, while whether the paths are diverse enough is usually overlooked. Generally, the spreading ability of a node might not be strong if its propagation depends on one or two paths while the other paths are dead ends. In this letter, we introduced the concept of path diversity and find that it can largely improve the ranking accuracy. We further propose a local method combining the information of path number and path diversity to identify influential nodes in complex networks. This method is shown to outperform many well-known methods in both undirected and directed networks. Moreover, the efficiency of our method makes it possible to apply it to very large systems.

Navigating the Path to a Biomedical Science Career

Science.gov (United States)

Zimmerman, Andrea McNeely

The number of biomedical PhD scientists being trained and graduated far exceeds the number of academic faculty positions and academic research jobs. If this trend is compelling biomedical PhD scientists to increasingly seek career paths outside of academia, then more should be known about their intentions, desires, training experiences, and career path navigation. Therefore, the purpose of this study was to understand the process through which biomedical PhD scientists are trained and supported for navigating future career paths. In addition, the study sought to determine whether career development support efforts and opportunities should be redesigned to account for the proportion of PhD scientists following non-academic career pathways. Guided by the social cognitive career theory (SCCT) framework this study sought to answer the following central research question: How does a southeastern tier 1 research university train and support its biomedical PhD scientists for navigating their career paths? Key findings are: Many factors influence PhD scientists' career sector preference and job search process, but the most influential were relationships with faculty, particularly the mentor advisor; Planned activities are a significant aspect of the training process and provide skills for career success; and Planned activities provided skills necessary for a career, but influential factors directed the career path navigated. Implications for practice and future research are discussed.

Computing the optimal path in stochastic dynamical systems

International Nuclear Information System (INIS)

Bauver, Martha; Forgoston, Eric; Billings, Lora

2016-01-01

In stochastic systems, one is often interested in finding the optimal path that maximizes the probability of escape from a metastable state or of switching between metastable states. Even for simple systems, it may be impossible to find an analytic form of the optimal path, and in high-dimensional systems, this is almost always the case. In this article, we formulate a constructive methodology that is used to compute the optimal path numerically. The method utilizes finite-time Lyapunov exponents, statistical selection criteria, and a Newton-based iterative minimizing scheme. The method is applied to four examples. The first example is a two-dimensional system that describes a single population with internal noise. This model has an analytical solution for the optimal path. The numerical solution found using our computational method agrees well with the analytical result. The second example is a more complicated four-dimensional system where our numerical method must be used to find the optimal path. The third example, although a seemingly simple two-dimensional system, demonstrates the success of our method in finding the optimal path where other numerical methods are known to fail. In the fourth example, the optimal path lies in six-dimensional space and demonstrates the power of our method in computing paths in higher-dimensional spaces.

Comparison of attitudes related with family planning methods before and after effective family planning counseling.

Directory of Open Access Journals (Sweden)

Esra Esim Büyükbayrak

2010-09-01

Full Text Available Objective: To evaluate the effect of family planning counseling on the changeover of the family planning method and to determine level of knowledge of participants on family planning methods and their attitude towards changeover of the method after counseling. Setting: Kartal education and reseach hospital obstetrics and gynecology clinic, department of family planning. Patients. 500 consecutive women applying to family planning department for any reason. Interventions: Effective family planning counseling service was given to each participant then a questioner containin 14 questions was applied with face to face technique. Main Outcome Measures: Attitude towards family planning counseling, comparison of the preference of family planning method before and after family planning counseling service and influential sociodemographic parameters on method choise were studied. Results: 45,2% of the participants were not taken family planning counseling service before. knowledge on family planning methods was sufficient in 25,2% of the participants, insufficient in 56,8% of the participants and 18% of the participants reported that they have no idea. 57,8% of the participants change mind about family planning counseling. 52,2% of the participants changeover perious method after counseling. 99,4% of the participants said that family planning counseling service should be given to every women. Preference of family planning method before and after family planning counseling service was statistically significantly different (p<0.01. Educational level, income and age were found to be influential sociodemographic factors for method preference. Conclusions: Effective family planning counseling service is found to have favorable effect on attitude and knowledge about family planning methods. Modern method usage increase as educational level and income of the participants increase.

Formal language constrained path problems

Energy Technology Data Exchange (ETDEWEB)

Barrett, C.; Jacob, R.; Marathe, M.

1997-07-08

In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvable efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.

A geometrically based method for automated radiosurgery planning

International Nuclear Information System (INIS)

Wagner, Thomas H.; Yi Taeil; Meeks, Sanford L.; Bova, Francis J.; Brechner, Beverly L.; Chen Yunmei; Buatti, John M.; Friedman, William A.; Foote, Kelly D.; Bouchet, Lionel G.

2000-01-01

Purpose: A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Methods and Materials: Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. Results: This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. Conclusions: This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

Hamiltonian path integrals

International Nuclear Information System (INIS)

Prokhorov, L.V.

1982-01-01

The properties of path integrals associated with the allowance for nonstandard terms reflecting the operator nature of the canonical variables are considered. Rules for treating such terms (''equivalence rules'') are formulated. Problems with a boundary, the behavior of path integrals under canonical transformations, and the problem of quantization of dynamical systems with constraints are considered in the framework of the method

Directional spectrum of ocean waves from array measurements using phase/time/path difference methods

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.

Wave direction has for the first time been consistently, accurately and unambiguously evaluated from array measurements using the phase/time/path difference (PTPD) methods of Esteva in case of polygonal arrays and Borgman in case of linear arrays...

Application of path integral method to heavy ion reactions, 1. General formalism

Energy Technology Data Exchange (ETDEWEB)

Fujita, J; Negishi, T [Tokyo Univ. of Education (Japan). Dept. of Physics

1976-03-01

The semiclassical approach for heavy ion reactions has become more and more important in analyzing rapidly accumulating data. The purpose of this paper is to lay a quantum-mechanical foundation of the conventional semiclassical treatments in heavy ion physics by using Feynman's path integral method on the basis of the second paper of Pechukas, and discuss simple consequences of the formalism.

Development of preoperative planning software for transforaminal endoscopic surgery and the guidance for clinical applications.

Science.gov (United States)

Chen, Xiaojun; Cheng, Jun; Gu, Xin; Sun, Yi; Politis, Constantinus

2016-04-01

Preoperative planning is of great importance for transforaminal endoscopic techniques applied in percutaneous endoscopic lumbar discectomy. In this study, a modular preoperative planning software for transforaminal endoscopic surgery was developed and demonstrated. The path searching method is based on collision detection, and the oriented bounding box was constructed for the anatomical models. Then, image reformatting algorithms were developed for multiplanar reconstruction which provides detailed anatomical information surrounding the virtual planned path. Finally, multithread technique was implemented to realize the steady-state condition of the software. A preoperative planning software for transforaminal endoscopic surgery (TE-Guider) was developed; seven cases of patients with symptomatic lumbar disc herniations were planned preoperatively using TE-Guider. The distances to the midlines and the direction of the optimal paths were exported, and each result was in line with the empirical value. TE-Guider provides an efficient and cost-effective way to search the ideal path and entry point for the puncture. However, more clinical cases will be conducted to demonstrate its feasibility and reliability.

Trajectory planning of mobile robots using indirect solution of optimal control method in generalized point-to-point task

Science.gov (United States)

Nazemizadeh, M.; Rahimi, H. N.; Amini Khoiy, K.

2012-03-01

This paper presents an optimal control strategy for optimal trajectory planning of mobile robots by considering nonlinear dynamic model and nonholonomic constraints of the system. The nonholonomic constraints of the system are introduced by a nonintegrable set of differential equations which represent kinematic restriction on the motion. The Lagrange's principle is employed to derive the nonlinear equations of the system. Then, the optimal path planning of the mobile robot is formulated as an optimal control problem. To set up the problem, the nonlinear equations of the system are assumed as constraints, and a minimum energy objective function is defined. To solve the problem, an indirect solution of the optimal control method is employed, and conditions of the optimality derived as a set of coupled nonlinear differential equations. The optimality equations are solved numerically, and various simulations are performed for a nonholonomic mobile robot to illustrate effectiveness of the proposed method.

A DIRECT METHOD TO DETERMINE THE PARALLEL MEAN FREE PATH OF SOLAR ENERGETIC PARTICLES WITH ADIABATIC FOCUSING

International Nuclear Information System (INIS)

He, H.-Q.; Wan, W.

2012-01-01

The parallel mean free path of solar energetic particles (SEPs), which is determined by physical properties of SEPs as well as those of solar wind, is a very important parameter in space physics to study the transport of charged energetic particles in the heliosphere, especially for space weather forecasting. In space weather practice, it is necessary to find a quick approach to obtain the parallel mean free path of SEPs for a solar event. In addition, the adiabatic focusing effect caused by a spatially varying mean magnetic field in the solar system is important to the transport processes of SEPs. Recently, Shalchi presented an analytical description of the parallel diffusion coefficient with adiabatic focusing. Based on Shalchi's results, in this paper we provide a direct analytical formula as a function of parameters concerning the physical properties of SEPs and solar wind to directly and quickly determine the parallel mean free path of SEPs with adiabatic focusing. Since all of the quantities in the analytical formula can be directly observed by spacecraft, this direct method would be a very useful tool in space weather research. As applications of the direct method, we investigate the inherent relations between the parallel mean free path and various parameters concerning physical properties of SEPs and solar wind. Comparisons of parallel mean free paths with and without adiabatic focusing are also presented.

Perturbative method for the derivation of quantum kinetic theory based on closed-time-path formalism

International Nuclear Information System (INIS)

Koide, Jun

2002-01-01

Within the closed-time-path formalism, a perturbative method is presented, which reduces the microscopic field theory to the quantum kinetic theory. In order to make this reduction, the expectation value of a physical quantity must be calculated under the condition that the Wigner distribution function is fixed, because it is the independent dynamical variable in the quantum kinetic theory. It is shown that when a nonequilibrium Green function in the form of the generalized Kadanoff-Baym ansatz is utilized, this condition appears as a cancellation of a certain part of contributions in the diagrammatic expression of the expectation value. Together with the quantum kinetic equation, which can be derived in the closed-time-path formalism, this method provides a basis for the kinetic-theoretical description

AUDIT plan documenting method

International Nuclear Information System (INIS)

Cornecsu, M.

1995-01-01

The work describes a method of documenting the AUDIT plan upon the basis of two quantitative elements resulting from quality assurance program appraisal system function implementation degree as established from the latest AUDIT performed an system function weight in QAP, respectively, appraised by taking into account their significance for the activities that are to be performed in the period for which the AUDITs are planned. (Author) 3 Figs., 2 Refs

Kinodynamic Motion Planning for Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Jiwung Choi

2014-06-01

Full Text Available This article proposes a computationally effective motion planning algorithm for autonomous ground vehicles operating in a semi-structured environment with a mission specified by waypoints, corridor widths and obstacles. The algorithm switches between two kinds of planners, (i static planners and (ii moving obstacle avoidance manoeuvre planners, depending on the mobility of any detected obstacles. While the first is broken down into a path planner and a controller, the second generates a sequence of controls without global path planning. Each subsystem is implemented as follows. The path planner produces an optimal piecewise linear path by applying a variant of cell decomposition and dynamic programming. The piecewise linear path is smoothed by Bézier curves such that the maximum curvatures of the curves are minimized. The controller calculates the highest allowable velocity profile along the path, consistent with the limits on both tangential and radial acceleration and the steering command for the vehicle to track the trajectory using a pure pursuit method. The moving obstacle avoidance manoeuvre produces a sequence of time-optimal local velocities, by minimizing the cost as determined by the safety of the current velocity against obstacles in the velocity obstacle paradigm and the deviation of the current velocity relative to the desired velocity, to satisfy the waypoint constraint. The algorithms are shown to be robust and computationally efficient, and to demonstrate a viable methodology for autonomous vehicle control in the presence of unknown obstacles.

Teaching Basic Quantum Mechanics in Secondary School Using Concepts of Feynman Path Integrals Method

Science.gov (United States)

Fanaro, Maria de los Angeles; Otero, Maria Rita; Arlego, Marcelo

2012-01-01

This paper discusses the teaching of basic quantum mechanics in high school. Rather than following the usual formalism, our approach is based on Feynman's path integral method. Our presentation makes use of simulation software and avoids sophisticated mathematical formalism. (Contains 3 figures.)

Measurements of isocenter path characteristics of the gantry rotation axis with a smartphone application

International Nuclear Information System (INIS)

Schiefer, H.; Peters, S.; Plasswilm, L.; Ingulfsen, N.; Kluckert, J.

2015-01-01

Purpose: For stereotactic radiosurgery, the AAPM Report No. 54 [AAPM Task Group 42 (AAPM, 1995)] requires the overall stability of the isocenter (couch, gantry, and collimator) to be within a 1 mm radius. In reality, a rotating system has no rigid axis and thus no isocenter point which is fixed in space. As a consequence, the isocenter concept is reviewed here. It is the aim to develop a measurement method following the revised definitions. Methods: The mechanical isocenter is defined here by the point which rotates on the shortest path in the room coordinate system. The path is labeled as “isocenter path.” Its center of gravity is assumed to be the mechanical isocenter. Following this definition, an image-based and radiation-free measurement method was developed. Multiple marker pairs in a plane perpendicular to the assumed gantry rotation axis of a linear accelerator are imaged with a smartphone application from several rotation angles. Each marker pair represents an independent measuring system. The room coordinates of the isocenter path and the mechanical isocenter are calculated based on the marker coordinates. The presented measurement method is by this means strictly focused on the mechanical isocenter. Results: The measurement result is available virtually immediately following completion of measurement. When 12 independent measurement systems are evaluated, the standard deviations of the isocenter path points and mechanical isocenter coordinates are 0.02 and 0.002 mm, respectively. Conclusions: The measurement is highly accurate, time efficient, and simple to adapt. It is therefore suitable for regular checks of the mechanical isocenter characteristics of the gantry and collimator rotation axis. When the isocenter path is reproducible and its extent is in the range of the needed geometrical accuracy, it should be taken into account in the planning process. This is especially true for stereotactic treatments and radiosurgery

Measurements of isocenter path characteristics of the gantry rotation axis with a smartphone application

Energy Technology Data Exchange (ETDEWEB)

Schiefer, H., E-mail: johann.schiefer@kssg.ch; Peters, S.; Plasswilm, L. [Klinik für Radio-Onkologie, Kantonsspital St.Gallen, Rorschacherstrasse 107, St.Gallen CH-9007 (Switzerland); Ingulfsen, N.; Kluckert, J. [Kantonsschule am Burggraben St.Gallen, Burggraben 21, St.Gallen CH-9000 (Switzerland)

2015-03-15

Purpose: For stereotactic radiosurgery, the AAPM Report No. 54 [AAPM Task Group 42 (AAPM, 1995)] requires the overall stability of the isocenter (couch, gantry, and collimator) to be within a 1 mm radius. In reality, a rotating system has no rigid axis and thus no isocenter point which is fixed in space. As a consequence, the isocenter concept is reviewed here. It is the aim to develop a measurement method following the revised definitions. Methods: The mechanical isocenter is defined here by the point which rotates on the shortest path in the room coordinate system. The path is labeled as “isocenter path.” Its center of gravity is assumed to be the mechanical isocenter. Following this definition, an image-based and radiation-free measurement method was developed. Multiple marker pairs in a plane perpendicular to the assumed gantry rotation axis of a linear accelerator are imaged with a smartphone application from several rotation angles. Each marker pair represents an independent measuring system. The room coordinates of the isocenter path and the mechanical isocenter are calculated based on the marker coordinates. The presented measurement method is by this means strictly focused on the mechanical isocenter. Results: The measurement result is available virtually immediately following completion of measurement. When 12 independent measurement systems are evaluated, the standard deviations of the isocenter path points and mechanical isocenter coordinates are 0.02 and 0.002 mm, respectively. Conclusions: The measurement is highly accurate, time efficient, and simple to adapt. It is therefore suitable for regular checks of the mechanical isocenter characteristics of the gantry and collimator rotation axis. When the isocenter path is reproducible and its extent is in the range of the needed geometrical accuracy, it should be taken into account in the planning process. This is especially true for stereotactic treatments and radiosurgery.

A method of signal transmission path analysis for multivariate random processes

International Nuclear Information System (INIS)

Oguma, Ritsuo

1984-04-01

A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)

Distribution Route Planning of Clean Coal Based on Nearest Insertion Method

Science.gov (United States)

Wang, Yunrui

2018-01-01

Clean coal technology has made some achievements for several ten years, but the research in its distribution field is very small, the distribution efficiency would directly affect the comprehensive development of clean coal technology, it is the key to improve the efficiency of distribution by planning distribution route rationally. The object of this paper was a clean coal distribution system which be built in a county. Through the surveying of the customer demand and distribution route, distribution vehicle in previous years, it was found that the vehicle deployment was only distributed by experiences, and the number of vehicles which used each day changed, this resulted a waste of transport process and an increase in energy consumption. Thus, the mathematical model was established here in order to aim at shortest path as objective function, and the distribution route was re-planned by using nearest-insertion method which been improved. The results showed that the transportation distance saved 37 km and the number of vehicles used had also been decreased from the past average of 5 to fixed 4 every day, as well the real loading of vehicles increased by 16.25% while the current distribution volume staying same. It realized the efficient distribution of clean coal, achieved the purpose of saving energy and reducing consumption.

Automated Planning and Scheduling for Planetary Rover Distributed Operations

Science.gov (United States)

Backes, Paul G.; Rabideau, Gregg; Tso, Kam S.; Chien, Steve

1999-01-01

Automated planning and Scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences by a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed collaboration, the Automated Scheduling and Planning Environment (ASPEN) provides automated planning and scheduling, and an automated path planner provided path planning. The system was demonstrated on the Rocky 7 research rover at JPL.

Bragg peak prediction from quantitative proton computed tomography using different path estimates

International Nuclear Information System (INIS)

Wang Dongxu; Mackie, T Rockwell; Tome, Wolfgang A

2011-01-01

This paper characterizes the performance of the straight-line path (SLP) and cubic spline path (CSP) as path estimates used in reconstruction of proton computed tomography (pCT). The GEANT4 Monte Carlo simulation toolkit is employed to simulate the imaging phantom and proton projections. SLP, CSP and the most-probable path (MPP) are constructed based on the entrance and exit information of each proton. The physical deviations of SLP, CSP and MPP from the real path are calculated. Using a conditional proton path probability map, the relative probability of SLP, CSP and MPP are calculated and compared. The depth dose and Bragg peak are predicted on the pCT images reconstructed using SLP, CSP, and MPP and compared with the simulation result. The root-mean-square physical deviations and the cumulative distribution of the physical deviations show that the performance of CSP is comparable to MPP while SLP is slightly inferior. About 90% of the SLP pixels and 99% of the CSP pixels lie in the 99% relative probability envelope of the MPP. Even at an imaging dose of ∼0.1 mGy the proton Bragg peak for a given incoming energy can be predicted on the pCT image reconstructed using SLP, CSP, or MPP with 1 mm accuracy. This study shows that SLP and CSP, like MPP, are adequate path estimates for pCT reconstruction, and therefore can be chosen as the path estimation method for pCT reconstruction, which can aid the treatment planning and range prediction of proton radiation therapy.

Bragg peak prediction from quantitative proton computed tomography using different path estimates

Energy Technology Data Exchange (ETDEWEB)

Wang Dongxu; Mackie, T Rockwell; Tome, Wolfgang A, E-mail: tome@humonc.wisc.edu [Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705 (United States)

2011-02-07

This paper characterizes the performance of the straight-line path (SLP) and cubic spline path (CSP) as path estimates used in reconstruction of proton computed tomography (pCT). The GEANT4 Monte Carlo simulation toolkit is employed to simulate the imaging phantom and proton projections. SLP, CSP and the most-probable path (MPP) are constructed based on the entrance and exit information of each proton. The physical deviations of SLP, CSP and MPP from the real path are calculated. Using a conditional proton path probability map, the relative probability of SLP, CSP and MPP are calculated and compared. The depth dose and Bragg peak are predicted on the pCT images reconstructed using SLP, CSP, and MPP and compared with the simulation result. The root-mean-square physical deviations and the cumulative distribution of the physical deviations show that the performance of CSP is comparable to MPP while SLP is slightly inferior. About 90% of the SLP pixels and 99% of the CSP pixels lie in the 99% relative probability envelope of the MPP. Even at an imaging dose of {approx}0.1 mGy the proton Bragg peak for a given incoming energy can be predicted on the pCT image reconstructed using SLP, CSP, or MPP with 1 mm accuracy. This study shows that SLP and CSP, like MPP, are adequate path estimates for pCT reconstruction, and therefore can be chosen as the path estimation method for pCT reconstruction, which can aid the treatment planning and range prediction of proton radiation therapy.

Bragg peak prediction from quantitative proton computed tomography using different path estimates

Science.gov (United States)

Wang, Dongxu; Mackie, T Rockwell

2015-01-01

This paper characterizes the performance of the straight-line path (SLP) and cubic spline path (CSP) as path estimates used in reconstruction of proton computed tomography (pCT). The GEANT4 Monte Carlo simulation toolkit is employed to simulate the imaging phantom and proton projections. SLP, CSP and the most-probable path (MPP) are constructed based on the entrance and exit information of each proton. The physical deviations of SLP, CSP and MPP from the real path are calculated. Using a conditional proton path probability map, the relative probability of SLP, CSP and MPP are calculated and compared. The depth dose and Bragg peak are predicted on the pCT images reconstructed using SLP, CSP, and MPP and compared with the simulation result. The root-mean-square physical deviations and the cumulative distribution of the physical deviations show that the performance of CSP is comparable to MPP while SLP is slightly inferior. About 90% of the SLP pixels and 99% of the CSP pixels lie in the 99% relative probability envelope of the MPP. Even at an imaging dose of ~0.1 mGy the proton Bragg peak for a given incoming energy can be predicted on the pCT image reconstructed using SLP, CSP, or MPP with 1 mm accuracy. This study shows that SLP and CSP, like MPP, are adequate path estimates for pCT reconstruction, and therefore can be chosen as the path estimation method for pCT reconstruction, which can aid the treatment planning and range prediction of proton radiation therapy. PMID:21212472

Quickly Planning TF/TA2 Trajectory by Artificial Immune Algorithm

Directory of Open Access Journals (Sweden)

LIU Lifeng

2015-04-01

Full Text Available Flight path planning by artificial immune algorithm approach met the requirements of aircraft's flyability and operation is proposed for the problem of single and double TF/TA2 flight path planning. Punishment function (affinity function with comprehensive 3D threat information is designed. A comprehensive threat model is formed including dynamic and static threats and no-fly-zone. Accordingly, single and dual flight paths are planned by AIA, which have been compared with the paths by GA. The results show that, GA's planned a quick and longer path compared under simple threat environment; in complex environments, GA has high failure rate (greater than 95% for single aircraft, but it is failed for double aircrafts. For the single and double aircrafts, AIA can provides one optimal and more candidate optimal flight paths.

Project planning and project management of Baseball II-T

International Nuclear Information System (INIS)

Kozman, T.A.; Chargin, A.K.

1975-01-01

The details of the project planning and project management work done on the Baseball II-T experiment are reviewed. The LLL Baseball program is a plasma confinement experiment accomplished with a superconducting magnet in the shape of a baseball seam. Both project planning and project management made use of the Critical Path Management (CPM) computer code. The computer code, input, and results from the project planning and project management runs, and the cost and effectiveness of this method of systems planning are discussed

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

Science.gov (United States)

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

A Method of Forming the Optimal Set of Disjoint Path in Computer Networks

Directory of Open Access Journals (Sweden)

As'ad Mahmoud As'ad ALNASER

2017-04-01

Full Text Available This work provides a short analysis of algorithms of multipath routing. The modified algorithm of formation of the maximum set of not crossed paths taking into account their metrics is offered. Optimization of paths is carried out due to their reconfiguration with adjacent deadlock path. Reconfigurations are realized within the subgraphs including only peaks of the main and an adjacent deadlock path. It allows to reduce the field of formation of an optimum path and time complexity of its formation.

Flight Path Recovery System (FPRS) design study

International Nuclear Information System (INIS)

1978-09-01

The study contained herein presents a design for a Flight Path Recovery System (FPPS) for use in the NURE Program which will be more accurate than systems presently used, provide position location data in digital form suitable for automatic data processing, and provide for flight path recovery in a more economic and operationally suitable manner. The design is based upon the use of presently available hardware and technoloy, and presents little, it any, development risk. In addition, a Flight Test Plan designed to test the FPRS design concept is presented

Flight Path Recovery System (FPRS) design study

Energy Technology Data Exchange (ETDEWEB)

1978-09-01

The study contained herein presents a design for a Flight Path Recovery System (FPPS) for use in the NURE Program which will be more accurate than systems presently used, provide position location data in digital form suitable for automatic data processing, and provide for flight path recovery in a more economic and operationally suitable manner. The design is based upon the use of presently available hardware and technoloy, and presents little, it any, development risk. In addition, a Flight Test Plan designed to test the FPRS design concept is presented.

Effectiveness of Family Planning Methods

Science.gov (United States)

... women in a year Effectiveness of Family Planning Methods Implant Reversible Intrauterine Device (IUD) Permanent Male Sterilization ... 0.5 % Diaphragm 12 % How to make your method most effective After procedure, little or nothing to ...

Nonadiabatic transition path sampling

International Nuclear Information System (INIS)

Sherman, M. C.; Corcelli, S. A.

2016-01-01

Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.

Presentation of a Modified Boustrophedon Decomposition Algorithm for Optimal Configuration of Flat Fields to use in Path Planning Systems of Agricultural Vehicles

Directory of Open Access Journals (Sweden)

R Goudarzi

2018-03-01

Full Text Available Introduction The demand of pre-determined optimal coverage paths in agricultural environments have been increased due to the growing application of field robots and autonomous field machines. Also coverage path planning problem (CPP has been extensively studied in robotics and many algorithms have been provided in many topics, but differences and limitations in agriculture lead to several different heuristic and modified adaptive methods from robotics. In this paper, a modified and enhanced version of currently used decomposition algorithm in robotics (boustrophedon cellular decomposition has been presented as a main part of path planning systems of agricultural vehicles. Developed algorithm is based on the parallelization of the edges of the polygon representing the environment to satisfy the requirements of the problem as far as possible. This idea is based on "minimum facing to the cost making condition" in turn, it is derived from encounter concept as a basis of cost making factors. Materials and Methods Generally, a line termed as a slice in boustrophedon cellular decomposition (BCD, sweeps an area in a pre-determined direction and decomposes the area only at critical points (where two segments can be extended to top and bottom of the point. Furthermore, sweep line direction does not change until the decomposition finish. To implement the BCD for parallelization method, two modifications were applied in order to provide a modified version of the boustrophedon cellular decomposition (M-BCD. In the first modification, the longest edge (base edge is targeted, and sweep line direction is set in line with the base edge direction (sweep direction is set perpendicular to the sweep line direction. Then Sweep line moves through the environment and stops at the first (nearest critical point. Next sweep direction will be the same as previous, If the length of those polygon's newly added edges, during the decomposition, are less than or equal to the

Multi-criteria ACO-based Algorithm for Ship’s Trajectory Planning

Directory of Open Access Journals (Sweden)

Agnieszka Lazarowska

2017-03-01

Full Text Available The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a multi-criteria optimization task. The criteria taken into account during problem solving are: path safety, path length, the International Regulations for Preventing Collisions at Sea (COLREGs compliance and path smoothness. The paper includes the description of the new multi-criteria ACO-based algorithm along with the presentation and discussion of simulation tests results.

Calibration of neural networks using genetic algorithms, with application to optimal path planning

Science.gov (United States)

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.

The Toggle Local Planner for sampling-based motion planning

KAUST Repository

Denny, Jory

2012-05-01

Sampling-based solutions to the motion planning problem, such as the probabilistic roadmap method (PRM), have become commonplace in robotics applications. These solutions are the norm as the dimensionality of the planning space grows, i.e., d > 5. An important primitive of these methods is the local planner, which is used for validation of simple paths between two configurations. The most common is the straight-line local planner which interpolates along the straight line between the two configurations. In this paper, we introduce a new local planner, Toggle Local Planner (Toggle LP), which extends local planning to a two-dimensional subspace of the overall planning space. If no path exists between the two configurations in the subspace, then Toggle LP is guaranteed to correctly return false. Intuitively, more connections could be found by Toggle LP than by the straight-line planner, resulting in better connected roadmaps. As shown in our results, this is the case, and additionally, the extra cost, in terms of time or storage, for Toggle LP is minimal. Additionally, our experimental analysis of the planner shows the benefit for a wide array of robots, with DOF as high as 70. © 2012 IEEE.

Fuzzy based method for project planning of the infrastructure design for the diagnostic in ITER

International Nuclear Information System (INIS)

Piros, Attila; Veres, Gábor

2013-01-01

The long-term design projects need special preparation before the start of the execution. This preparation usually includes the drawing of the network diagram for the whole procedure. This diagram includes the time estimation of the individual subtasks and gives us information about the predicted dates of the milestones. The calculated critical path in this network characterizes a specific design project concerning to its duration very well. Several methods are available to support this step of preparation. This paper describes a new method to map the structure of the design process and clarify the milestones and predict the dates of these milestones. The method is based on the PERT (Project Evaluation and Review Technique) network but as a novelty it applies fuzzy logic to find out the concerning times in this graph. With the application of the fuzzy logic the handling of the different kinds of design uncertainties becomes feasible. Many kinds of design uncertainties exist from the possible electric blackout up to the illness of an engineer. In many cases these uncertainties are related with human errors and described with linguistic expressions. The fuzzy logic enables to transform these ambiguous expressions into numeric values for further mathematical evaluation. The method is introduced in the planning of the design project of the infrastructure for the diagnostic systems of ITER. The method not only helps the project in the planning phase, but it will be a powerful tool in mathematical modeling and monitoring of the project execution

Fuzzy based method for project planning of the infrastructure design for the diagnostic in ITER

Energy Technology Data Exchange (ETDEWEB)

Piros, Attila, E-mail: attila.piros@gt3.bme.hu [Department of Machine and Product Design, Budapest University of Technology and Economics, Budapest (Hungary); Veres, Gábor [Department of Plasma Physics, Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest (Hungary)

2013-10-15

The long-term design projects need special preparation before the start of the execution. This preparation usually includes the drawing of the network diagram for the whole procedure. This diagram includes the time estimation of the individual subtasks and gives us information about the predicted dates of the milestones. The calculated critical path in this network characterizes a specific design project concerning to its duration very well. Several methods are available to support this step of preparation. This paper describes a new method to map the structure of the design process and clarify the milestones and predict the dates of these milestones. The method is based on the PERT (Project Evaluation and Review Technique) network but as a novelty it applies fuzzy logic to find out the concerning times in this graph. With the application of the fuzzy logic the handling of the different kinds of design uncertainties becomes feasible. Many kinds of design uncertainties exist from the possible electric blackout up to the illness of an engineer. In many cases these uncertainties are related with human errors and described with linguistic expressions. The fuzzy logic enables to transform these ambiguous expressions into numeric values for further mathematical evaluation. The method is introduced in the planning of the design project of the infrastructure for the diagnostic systems of ITER. The method not only helps the project in the planning phase, but it will be a powerful tool in mathematical modeling and monitoring of the project execution.

Path integral in Snyder space

Energy Technology Data Exchange (ETDEWEB)

Mignemi, S., E-mail: smignemi@unica.it [Dipartimento di Matematica e Informatica, Università di Cagliari, Viale Merello 92, 09123 Cagliari (Italy); INFN, Sezione di Cagliari, Cittadella Universitaria, 09042 Monserrato (Italy); Štrajn, R. [Dipartimento di Matematica e Informatica, Università di Cagliari, Viale Merello 92, 09123 Cagliari (Italy); INFN, Sezione di Cagliari, Cittadella Universitaria, 09042 Monserrato (Italy)

2016-04-29

The definition of path integrals in one- and two-dimensional Snyder space is discussed in detail both in the traditional setting and in the first-order formalism of Faddeev and Jackiw. - Highlights: • The definition of the path integral in Snyder space is discussed using phase space methods. • The same result is obtained in the first-order formalism of Faddeev and Jackiw. • The path integral formulation of the two-dimensional Snyder harmonic oscillator is outlined.

Path integral in Snyder space

International Nuclear Information System (INIS)

Mignemi, S.; Štrajn, R.

2016-01-01

The definition of path integrals in one- and two-dimensional Snyder space is discussed in detail both in the traditional setting and in the first-order formalism of Faddeev and Jackiw. - Highlights: • The definition of the path integral in Snyder space is discussed using phase space methods. • The same result is obtained in the first-order formalism of Faddeev and Jackiw. • The path integral formulation of the two-dimensional Snyder harmonic oscillator is outlined.

Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications

KAUST Repository

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.

The development of radiation hardened tele-robot system - Development of path-planning and control technology for tele-operated redundant manipulator

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)

A chord error conforming tool path B-spline fitting method for NC machining based on energy minimization and LSPIA

Directory of Open Access Journals (Sweden)

Shanshan He

2015-10-01

Full Text Available Piecewise linear (G01-based tool paths generated by CAM systems lack G1 and G2 continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical instability, lack of chord error constraint, and lack of assurance of a usable result. Progressive and Iterative Approximation for Least Squares (LSPIA is an efficient method for data fitting that solves the numerical instability problem. However, it does not consider chord errors and needs more work to ensure ironclad results for commercial applications. In this paper, we use LSPIA method incorporating Energy term (ELSPIA to avoid the numerical instability, and lower chord errors by using stretching energy term. We implement several algorithm improvements, including (1 an improved technique for initial control point determination over Dominant Point Method, (2 an algorithm that updates foot point parameters as needed, (3 analysis of the degrees of freedom of control points to insert new control points only when needed, (4 chord error refinement using a similar ELSPIA method with the above enhancements. The proposed approach can generate a shape-preserving B-spline curve. Experiments with data analysis and machining tests are presented for verification of quality and efficiency. Comparisons with other known solutions are included to evaluate the worthiness of the proposed solution.

Improved initial guess for minimum energy path calculations

International Nuclear Information System (INIS)

Smidstrup, Søren; Pedersen, Andreas; Stokbro, Kurt; Jónsson, Hannes

2014-01-01

A method is presented for generating a good initial guess of a transition path between given initial and final states of a system without evaluation of the energy. An objective function surface is constructed using an interpolation of pairwise distances at each discretization point along the path and the nudged elastic band method then used to find an optimal path on this image dependent pair potential (IDPP) surface. This provides an initial path for the more computationally intensive calculations of a minimum energy path on an energy surface obtained, for example, by ab initio or density functional theory. The optimal path on the IDPP surface is significantly closer to a minimum energy path than a linear interpolation of the Cartesian coordinates and, therefore, reduces the number of iterations needed to reach convergence and averts divergence in the electronic structure calculations when atoms are brought too close to each other in the initial path. The method is illustrated with three examples: (1) rotation of a methyl group in an ethane molecule, (2) an exchange of atoms in an island on a crystal surface, and (3) an exchange of two Si-atoms in amorphous silicon. In all three cases, the computational effort in finding the minimum energy path with DFT was reduced by a factor ranging from 50% to an order of magnitude by using an IDPP path as the initial path. The time required for parallel computations was reduced even more because of load imbalance when linear interpolation of Cartesian coordinates was used

Fourier path-integral Monte Carlo methods: Partial averaging

International Nuclear Information System (INIS)

Doll, J.D.; Coalson, R.D.; Freeman, D.L.

1985-01-01

Monte Carlo Fourier path-integral techniques are explored. It is shown that fluctuation renormalization techniques provide an effective means for treating the effects of high-order Fourier contributions. The resulting formalism is rapidly convergent, is computationally convenient, and has potentially useful variational aspects

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

Science.gov (United States)

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.

Combined Monte Carlo and path-integral method for simulated library of time-resolved reflectance curves from layered tissue models

Science.gov (United States)

Wilson, Robert H.; Vishwanath, Karthik; Mycek, Mary-Ann

2009-02-01

Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert factor to scale the time-resolved reflectance of the simulated zero-absorption tissue model. This method is a unique alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on the accuracy of the method will be discussed.

Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions

Science.gov (United States)

Wutich, A.; White, A. C.; White, D. D.; Larson, K. L.; Brewis, A.; Roberts, C.

2014-01-01

In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences associated with development status and, to a lesser extent, water scarcity. People in the two less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in the more developed sites. Thematically, people in the two less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community-based solutions, while people in the more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in the two water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in the water-rich sites. Thematically, people in the two water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in the water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.

Trajectory Planning with Pose Feedback for a Dual-Arm Space Robot

Directory of Open Access Journals (Sweden)

Yicheng Liu

2016-01-01

Full Text Available In order to obtain high precision path tracking for a dual-arm space robot, a trajectory planning method with pose feedback is proposed to be introduced into the design process in this paper. Firstly, pose error kinematic models are derived from the related kinematics and desired pose command for the end-effector and the base, respectively. On this basis, trajectory planning with pose feedback is proposed from a control perspective. Theoretical analyses show that the proposed trajectory planning algorithm can guarantee that pose error converges to zero exponentially for both the end-effector and the base when the robot is out of singular configuration. Compared with the existing algorithms, the proposed algorithm can lead to higher precision path tracking for the end-effector. Furthermore, the algorithm renders the system good anti-interference property for the base. Simulation results demonstrate the effectiveness of the proposed trajectory planning algorithm.

Transition Analysis and Its Application to Global Path Determination for a Biped Climbing Robot

Directory of Open Access Journals (Sweden)

Haifei Zhu

2018-01-01

Full Text Available Biped climbing robots are considered good assistants and (or substitutes for human workers carrying out high-rise truss-associated routine tasks. Flexible locomotion on three-dimensional complex trusses is a fundamental skill for these robots. In particular, the capability to transit from one structural member to another is paramount for switching objects to be climbed upon. In this paper, we study member-to-member transition and its utility in global path searching for biped climbing robots. To compute operational regions for transition, hierarchical inspection of safety, reachability, and accessibility of grips is taken into account. A novel global path rapid determination approach is subsequently proposed based on the transition analysis. This scheme is efficient for finding feasible routes with respect to the overall structural environment, which also benefits the subsequent grip and motion planning. Simulations are conducted with Climbot, our self-developed biped climbing robot, to verify the efficiency of the presented method. Results show that our proposed method is able to accurately determine the operational region for transition within tens of milliseconds and can obtain global paths within seconds in general.

Preparation and tomographic reconstruction of an arbitrary single-photon path qubit

International Nuclear Information System (INIS)

Baek, So-Young; Kim, Yoon-Ho

2011-01-01

We report methods for preparation and tomographic reconstruction of an arbitrary single-photon path qubit. The arbitrary single-photon path qubit is prepared losslessly by passing the heralded single-photon state from spontaneous parametric down-conversion through variable beam splitter. Quantum state tomography of the single-photon path qubit is implemented by introducing path-projection measurements based on the first-order single-photon quantum interference. Using the state preparation and path-projection measurements methods for the single-photon path qubit, we demonstrate preparation and complete tomographic reconstruction of the single-photon path qubit with arbitrary purity. -- Highlights: → We report methods for preparation and tomographic reconstruction of an arbitrary single-photon path qubit. → We implement path-projection measurements based on the first-order single-photon quantum interference. → We demonstrate preparation and complete tomographic reconstruction of the single-photon path qubit with arbitrary purity.

A Method for Automated Planning of FTTH Access Network Infrastructures

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Pedersen, Jens Myrup; Madsen, Ole Brun

2005-01-01

In this paper a method for automated planning of Fiber to the Home (FTTH) access networks is proposed. We introduced a systematic approach for planning access network infrastructure. The GIS data and a set of algorithms were employed to make the planning process more automatic. The method explains...... method. The method, however, does not fully automate the planning but make the planning process significantly fast. The results and discussion are presented and conclusion is given in the end....

Comparison of classical reaction paths and tunneling paths studied with the semiclassical instanton theory.

Science.gov (United States)

Meisner, Jan; Markmeyer, Max N; Bohner, Matthias U; Kästner, Johannes

2017-08-30

Atom tunneling in the hydrogen atom transfer reaction of the 2,4,6-tri-tert-butylphenyl radical to 3,5-di-tert-butylneophyl, which has a short but strongly curved reaction path, was investigated using instanton theory. We found the tunneling path to deviate qualitatively from the classical intrinsic reaction coordinate, the steepest-descent path in mass-weighted Cartesian coordinates. To perform that comparison, we implemented a new variant of the predictor-corrector algorithm for the calculation of the intrinsic reaction coordinate. We used the reaction force analysis method as a means to decompose the reaction barrier into structural and electronic components. Due to the narrow energy barrier, atom tunneling is important in the abovementioned reaction, even above room temperature. Our calculated rate constants between 350 K and 100 K agree well with experimental values. We found a H/D kinetic isotope effect of almost 10 6 at 100 K. Tunneling dominates the protium transfer below 400 K and the deuterium transfer below 300 K. We compared the lengths of the tunneling path and the classical path for the hydrogen atom transfer in the reaction HCl + Cl and quantified the corner cutting in this reaction. At low temperature, the tunneling path is about 40% shorter than the classical path.

Optimal Path Planner for Mobile Robot in 2D Environment

Directory of Open Access Journals (Sweden)

Valeri Kroumov

2004-06-01

Full Text Available The problem of path planning for the case of a mobile robot moving in an environment filled with obstacles with known shapes and positions is studied. A path planner based on the genetic algorithm approach, which generates optimal in length path is proposed. The population member paths are generated by another algorithm, which uses for description of the obstacles an artificial annealing neural network and is based on potential field approach. The resulting path is piecewise linear with changing directions at the corners of the obstacles. Because of this feature, the inverse kinematics problems in controlling differential drive robots are simply solved: to drive the robot to some goal pose (x, y, theta, the robot can be spun in place until it is aimed at (x, y, then driven forward until it is at (x, y, and then spun in place until the required goal orientation

Path Creation, Path Dependence and Breaking Away from the Path

OpenAIRE

Wang, Jens; Hedman, Jonas; Tuunainen, Virpi Kristiina

2016-01-01

The explanation of how and why firms succeed or fail is a recurrent research challenge. This is particularly important in the context of technological innovations. We focus on the role of historical events and decisions in explaining such success and failure. Using a case study of Nokia, we develop and extend a multi-layer path dependence framework. We identify four layers of path dependence: technical, strategic and leadership, organizational, and external collaboration. We show how path dep...

Path integral solutions of the master equation. [Lagrangian function, Ehrenfest-type theorem, Cauchy method, inverse functions

Energy Technology Data Exchange (ETDEWEB)

Etim, E; Basili, C [Rome Univ. (Italy). Ist. di Matematica

1978-08-21

The lagrangian in the path integral solution of the master equation of a stationary Markov process is derived by application of the Ehrenfest-type theorem of quantum mechanics and the Cauchy method of finding inverse functions. Applied to the non-linear Fokker-Planck equation the authors reproduce the result obtained by integrating over Fourier series coefficients and by other methods.

Quadcopter Path Following Control Design Using Output Feedback with Command Generator Tracker LOS Based At Square Path

Science.gov (United States)

Nugraha, A. T.; Agustinah, T.

2018-01-01

Quadcopter an unstable system, underactuated and nonlinear in quadcopter control research developments become an important focus of attention. In this study, following the path control method for position on the X and Y axis, used structure-Generator Tracker Command (CGT) is tested. Attitude control and position feedback quadcopter is compared using the optimal output. The addition of the H∞ performance optimal output feedback control is used to maintain the stability and robustness of quadcopter. Iterative numerical techniques Linear Matrix Inequality (LMI) is used to find the gain controller. The following path control problems is solved using the method of LQ regulators with output feedback. Simulations show that the control system can follow the paths that have been defined in the form of a reference signal square shape. The result of the simulation suggest that the method which used can bring the yaw angle at the expected value algorithm. Quadcopter can do automatically following path with cross track error mean X=0.5 m and Y=0.2 m.

Path integration in conical space

International Nuclear Information System (INIS)

Inomata, Akira; Junker, Georg

2012-01-01

Quantum mechanics in conical space is studied by the path integral method. It is shown that the curvature effect gives rise to an effective potential in the radial path integral. It is further shown that the radial path integral in conical space can be reduced to a form identical with that in flat space when the discrete angular momentum of each partial wave is replaced by a specific non-integral angular momentum. The effective potential is found proportional to the squared mean curvature of the conical surface embedded in Euclidean space. The path integral calculation is compatible with the Schrödinger equation modified with the Gaussian and the mean curvature. -- Highlights: ► We study quantum mechanics on a cone by the path integral approach. ► The path integral depends only on the metric and the curvature effect is built in. ► The approach is consistent with the Schrödinger equation modified by an effective potential. ► The effective potential is found to be of the “Jensen–Koppe” and “da Costa” type.

Path Transmissibility Analysis Considering Two Types of Correlations in Hydropower Stations

Directory of Open Access Journals (Sweden)

Baoping Zhi

2013-01-01

Full Text Available A new vibration model is built by introducing the head-cover vibration transfer path based on a previous analysis of the vertical vibration model for hydropower station units and powerhouses. This research focuses on disturbance- and parameter-related transfer paths in a practical situation. In a complex situation, the application of the stochastic perturbation method is expanded using an algebra synthesis method the Hadamard product, and theoretical analyses, and numerical simulations of transfer paths in the new vibration model are carried out through the expanded perturbation method. The path transfer force, the path transmissibility, and the path disturbance ranges in the frequency domain are provided. The results indicate that the methods proposed in this study can efficiently reduce the disturbance range and can accurately analyze the transfer paths of hydraulic-source vertical vibration in hydropower stations.

Study on Top-Down Estimation Method of Software Project Planning

Institute of Scientific and Technical Information of China (English)

ZHANG Jun-guang; L(U) Ting-jie; ZHAO Yu-mei

2006-01-01

This paper studies a new software project planning method under some actual project data in order to make software project plans more effective. From the perspective of system theory, our new method regards a software project plan as an associative unit for study. During a top-down estimation of a software project, Program Evaluation and Review Technique (PERT) method and analogy method are combined to estimate its size, then effort estimation and specific schedules are obtained according to distributions of the phase effort. This allows a set of practical and feasible planning methods to be constructed. Actual data indicate that this set of methods can lead to effective software project planning.

Crystal structure and ionic conduction path of solid electrolytic materials by high temperature neutron diffraction method

International Nuclear Information System (INIS)

Yashima, Masatomo; Nomura, Katsuhiro

2005-01-01

Research of the distribution of oxide ions and the ionic conduction path of bismuth oxide (Bi 2 O 3 ), cerium oxide (CeO 2 ) and lanthanum gallate ((La 0.8 Sr 0.2 )(Ga 0.8 Mg 0.15 Co 0.05 )O 3-δ ) is stated. The high temperature neutron diffraction method, analytical method such as Rietveld method, crystal structure analysis of ionic conductor and MEM (Maximum- Entropy Method) are explained. The nuclear density distribution of oxide ions in bismuth oxide showed so larger distribution in the direction of and than Bi ions that the oxide ions conducted these direction in the crystal. The nuclear density distribution of oxide ions of cerium oxide indicated larger distribution in the direction of than Ce ions and its tendency was remarkable at high temperature. Accordingly, the oxide ions conducted in the direction of and . The oxide ions distribution in lanthanum gallate compound was larger and complicated than positive ions. The oxide ions conducted to by describing an arc between the two stable positions. The nuclear density on the conduction path increased with increasing temperature. This above result corresponded to increase of oxide ion conductivity in the area. (S.Y.)

Synchronous method and engineering tool for the strategic factory planning

OpenAIRE

Abdul Rahman, O.; Jaeger, J.; Constantinescu, C.

2011-01-01

This paper presents the approach to combine two reference methods and engineering tools, for "Factory Performance and Investment Planning«as well as "Value Added Ideal Production Network Planning". The resulted synchronous method aims to support factories in the strategic planning as well as in the network planning. The corresponding engineering tool is employed for assessment planning, sales planning, capacity planning and production costs planning under the consideration of dynamic and stoc...

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

Science.gov (United States)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Optimized path planning for soft tissue resection via laser vaporization

Science.gov (United States)

Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick

2018-02-01

Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.

Diagrammatical methods within the path integral representation for quantum systems

International Nuclear Information System (INIS)

Alastuey, A

2014-01-01

The path integral representation has been successfully applied to the study of equilibrium properties of quantum systems for a long time. In particular, such a representation allowed Ginibre to prove the convergence of the low-fugacity expansions for systems with short-range interactions. First, I will show that the crucial trick underlying Ginibre's proof is the introduction of an equivalent classical system made with loops. Within the Feynman-Kac formula for the density matrix, such loops naturally emerge by collecting together the paths followed by particles exchanged in a given cyclic permutation. Two loops interact via an average of two- body genuine interactions between particles belonging to different loops, while the interactions between particles inside a given loop are accounted for in a loop fugacity. It turns out that the grand-partition function of the genuine quantum system exactly reduces to its classical counterpart for the gas of loops. The corresponding so-called magic formula can be combined with standard Mayer diagrammatics for the classical gas of loops. This provides low-density representations for the quantum correlations or thermodynamical functions, which are quite useful when collective effects must be taken into account properly. Indeed, resummations and or reorganizations of Mayer graphs can be performed by exploiting their remarkable topological and combinatorial properties, while statistical weights and bonds are purely c-numbers. The interest of that method will be illustrated through a brief description of its application to two long-standing problems, namely recombination in Coulomb systems and condensation in the interacting Bose gas.

Using Multiple Methods to teach ASTR 101 students the Path of the Sun and Shadows

Science.gov (United States)

D'Cruz, Noella L.

2015-01-01

It seems surprising that non-science major introductory astronomy students find the daily path of the Sun and shadows created by the Sun challenging to learn even though both can be easily observed (provided students do not look directly at the Sun). In order for our students to master the relevant concepts, we have usually used lecture, a lecture tutorial (from Prather, et al.) followed by think-pair-share questions, a planetarium presentation and an animation from the Nebraska Astronomy Applet Project to teach these topics. We cover these topics in a lecture-only, one semester introductory astronomy course at Joliet Junior College. Feedback from our Spring 2014 students indicated that the planetarium presentation was the most helpful in learning the path of the Sun while none of the four teaching methods was helpful when learning about shadows cast by the Sun. Our students did not find the lecture tutorial to be much help even though such tutorials have been proven to promote deep conceptual change. In Fall 2014, we continued to use these four methods, but we modified how we teach both topics so our students could gain more from the tutorial. We hoped our modifications would cause students to have a better overall grasp of the concepts. After our regular lecture, we gave a shorter than usual planetarium presentation on the path of the Sun and we asked students to work through a shadow activity from Project Astro materials. Then students completed the lecture tutorial and some think-pair-share questions. After this, we asked students to predict the Sun's path on certain days of the year and we used the planetarium projector to show them how well their predictions matched up. We ended our coverage of these topics by asking students a few more think-pair-share questions. In our poster, we will present our approach to teaching these topics in Fall 2014, how our Fall 2014 students feel about our teaching strategies and how they fared on related test questions.

A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems

KAUST Repository

Abdelkader, Mohamed

2017-10-19

We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

Science.gov (United States)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

Efficient methods for including quantum effects in Monte Carlo calculations of large systems: extension of the displaced points path integral method and other effective potential methods to calculate properties and distributions.

Science.gov (United States)

Mielke, Steven L; Dinpajooh, Mohammadhasan; Siepmann, J Ilja; Truhlar, Donald G

2013-01-07

We present a procedure to calculate ensemble averages, thermodynamic derivatives, and coordinate distributions by effective classical potential methods. In particular, we consider the displaced-points path integral (DPPI) method, which yields exact quantal partition functions and ensemble averages for a harmonic potential and approximate quantal ones for general potentials, and we discuss the implementation of the new procedure in two Monte Carlo simulation codes, one that uses uncorrelated samples to calculate absolute free energies, and another that employs Metropolis sampling to calculate relative free energies. The results of the new DPPI method are compared to those from accurate path integral calculations as well as to results of two other effective classical potential schemes for the case of an isolated water molecule. In addition to the partition function, we consider the heat capacity and expectation values of the energy, the potential energy, the bond angle, and the OH distance. We also consider coordinate distributions. The DPPI scheme performs best among the three effective potential schemes considered and achieves very good accuracy for all of the properties considered. A key advantage of the effective potential schemes is that they display much lower statistical sampling variances than those for accurate path integral calculations. The method presented here shows great promise for including quantum effects in calculations on large systems.

Research on atmospheric CO2 remote sensing with open-path tunable diode laser absorption spectroscopy and comparison methods

Science.gov (United States)

Xin, Fengxin; Guo, Jinjia; Sun, Jiayun; Li, Jie; Zhao, Chaofang; Liu, Zhishen

2017-06-01

An open-path atmospheric CO2 measurement system was built based on tunable diode laser absorption spectroscopy (TDLAS). The CO2 absorption line near 2 μm was selected, measuring the atmospheric CO2 with direct absorption spectroscopy and carrying on the comparative experiment with multipoint measuring instruments of the open-path. The detection limit of the TDLAS system is 1.94×10-6. The calibration experiment of three AZ-7752 handheld CO2 measuring instruments was carried out with the Los Gatos Research gas analyzer. The consistency of the results was good, and the handheld instrument could be used in the TDLAS system after numerical calibration. With the contrast of three AZ-7752 and their averages, the correlation coefficients are 0.8828, 0.9004, 0.9079, and 0.9393 respectively, which shows that the open-path TDLAS has the best correlation with the average of three AZ-7752 and measures the concentration of atmospheric CO2 accurately. Multipoint measurement provides a convenient comparative method for open-path TDLAS.

Robust Path Planning for Space Exploration Rovers

Data.gov (United States)

National Aeronautics and Space Administration — Motion planning considers the problem of moving a system from a starting position to a desired goal position. This problem has been shown to be a computationally...

Adaptive Planning for Resilient Coastal Waterfronts

Directory of Open Access Journals (Sweden)

Peter Christiaan van Veelen

2016-11-01

The method follows three basic steps: (1 assessing the spatial and timely synchronisation of adaptation measures with planned urban development projects and public and private infrastructure maintenance investments; (2 assessing the institutional and financial barriers to be removed in order to mainstream climate adaptation measures in these urban development processes, and (3 assessing what opportunities derived from urban development are able to ‘break through’ the path dependencies that lock-in more sustainable adaptive paths. The method is based on mapping all planned spatial investments in brownfield development, urban renovation, and maintenance projects of public and private infrastructure and assets and by assessing the effectiveness of prevailing policies. Using design research, new opportunities for adaptation are explored and assessed. The urban dynamics based adaptation pathways method is tested at two waterfront areas in Rotterdam (Feijenoord and New York (Red Hook. Both cases show that identifying intervention opportunities and potential transitional interventions is helpful in selecting and assessing adaptive pathways. Moreover, it helps to identify legal or financial arrangements that are needed to unlock the potential of adaptation paths. One of the key findings of the case study research is that in high density urban conditions there is limited potential to build resilience from household redevelopment or renovation, even when new complementary policies and regulative instruments that support buildinglevel resilience would be developed. District-wide flood protection is effective in terms of flood risk, but requires large-scale transformations of the waterfront zone to seize opportunities to develop integrated protection at low costs. This strategy, however, needs new governance structures and financial arrangements to redistribute costs and benefits fairly among stakeholders.

Lattice Paths and the Constant Term

International Nuclear Information System (INIS)

Brak, R; Essam, J; Osborn, J; Owczarek, A L; Rechnitzer, A

2006-01-01

We firstly review the constant term method (CTM), illustrating its combinatorial connections and show how it can be used to solve a certain class of lattice path problems. We show the connection between the CTM, the transfer matrix method (eigenvectors and eigenvalues), partial difference equations, the Bethe Ansatz and orthogonal polynomials. Secondly, we solve a lattice path problem first posed in 1971. The model stated in 1971 was only solved for a special case - we solve the full model

Path Planning of Mobile Elastic Robotic Arms by Indirect Approach of Optimal Control

Directory of Open Access Journals (Sweden)

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.

Phase-space path-integral calculation of the Wigner function

International Nuclear Information System (INIS)

Samson, J H

2003-01-01

The Wigner function W(q, p) is formulated as a phase-space path integral, whereby its sign oscillations can be seen to follow from interference between the geometrical phases of the paths. The approach has similarities to the path-centroid method in the configuration-space path integral. Paths can be classified by the midpoint of their ends; short paths where the midpoint is close to (q, p) and which lie in regions of low energy (low P function of the Hamiltonian) will dominate, and the enclosed area will determine the sign of the Wigner function. As a demonstration, the method is applied to a sequence of density matrices interpolating between a Poissonian number distribution and a number state, each member of which can be represented exactly by a discretized path integral with a finite number of vertices. Saddle-point evaluation of these integrals recovers (up to a constant factor) the WKB approximation to the Wigner function of a number state

Study on k-shortest paths with behavioral impedance domain from the intermodal public transportation system perspective

OpenAIRE

Pereira, Hernane Borges de Barros; Pérez Vidal, Lluís; Lozada, Eleazar G. Madrid

2003-01-01

Behavioral impedance domain consists of a theory on route planning for pedestrians, within which constraint management is considered. The goal of this paper is to present the k-shortest path model using the behavioral impedance approach. After the mathematical model building, optimization problem and resolution problem by a behavioral impedance algorithm, it is discussed how behavioral impedance cost function is embedded in the k-shortest path model. From the pedestrian's route planning persp...

Construction of a path of MHD equilibrium solutions by an iterative method

International Nuclear Information System (INIS)

Kikuchi, Fumio.

1979-09-01

This paper shows a constructive proof of the existence of a path of solutions to a nonlinear eigenvalue problem expressed by -Δu = lambda u + in Ω, and u = -1 on deltaΩ where Ω is a two-dimensional domain with a boundary deltaΩ. This problem arises from the ideal MHD equilibria in tori. The existence proof is based on the principle of contraction mappings, which is widely employed in nonlinear problems such as those associated with bifurcation phenomena. Some comments are also given on the application of the present iteration techniques to numerical method. (author)

Unusual bond paths in organolithium compounds

International Nuclear Information System (INIS)

Bachrach, S.M.; Ritchie, J.P.

1986-01-01

We have applied the topological method to a number of organolithium compounds. The wavefunctions were determined with GAUSSIAN-82 using 3-21G basis set and fully optimized geometries. Gradient paths were obtained using the RHODER package and critical points were located using EXTREME. These results indicate the unusual nature of organolithium compounds. The strange bond paths arise mainly from the ionic nature of the C-Li interaction. We suggest that the term ''bond path'' may best be suited for covalent bonds. 4 figs., 1 tab

Path Dependency

OpenAIRE

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.

An industrial robot singular trajectories planning based on graphs and neural networks

Science.gov (United States)

Łęgowski, Adrian; Niezabitowski, Michał

2016-06-01

Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

Plan demographics, participants' saving behavior, and target-date fund investments.

Science.gov (United States)

Park, Youngkyun

2009-05-01

This analysis explores (1) whether plan demographic characteristics would affect individual participant contribution rates and target-date fund investments and (2) equity glide paths for participants in relation to plan demographics by considering target replacement income and its success rate. PLAN DEMOGRAPHIC CHARACTERISTICS IN PARTICIPANT CONTRIBUTION RATES: This study finds empirical evidence that 401(k) plan participants' contribution rates differ by plan demographics based on participants' income and/or tenure. In particular, participants in 401(k) plans dominated by those with low income and short tenure tend to contribute less than those in plans dominated by participants with high income and long tenure. Future research will explore how participant contribution behavior may also be influenced by incentives provided by employers through matching formulae. PLAN DEMOGRAPHIC CHARACTERISTICS IN TARGET-DATE FUND INVESTMENTS: The study also finds empirical evidence that participants' investments in target-date funds with different equity allocations differ by plan demographics based on participants' income and/or tenure. In particular, target-date fund users with 90 percent or more of their account balances in target-date funds who are in 401(k) plans dominated by low-income and short-tenure participants tend to hold target-date funds with lower equity allocations, compared with their counterparts in plans dominated by high-income and long-tenure participants. Future research will focus on the extent to which these characteristics might influence the selection of target-date funds by plan sponsors. EQUITY GLIDE PATHS: Several stylized equity glide paths as well as alternative asset allocations are compared for participants at various starting ages to demonstrate the interaction between plan demographics and equity glide paths/asset allocations in terms of success rates in meeting various replacement income targets. The equity glide path/asset allocation providing

Vervet monkeys use paths consistent with context-specific spatial movement heuristics.

Science.gov (United States)

Teichroeb, Julie A

2015-10-01

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles

Science.gov (United States)

2006-02-17

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles Report Title ABSTRACT In this work we proposed two semi-analytic...298-102 Enclosure 1 On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles by...Specifically, the following problems will be addressed during this project: 2.1 Challenges The problem of trajectory planning for high-speed autonomous vehicles is

Hot gas path component having near wall cooling features

Science.gov (United States)

Miranda, Carlos Miguel; Kottilingam, Srikanth Chandrudu; Lacy, Benjamin Paul

2017-11-28

A method for providing micro-channels in a hot gas path component includes forming a first micro-channel in an exterior surface of a substrate of the hot gas path component. A second micro-channel is formed in the exterior surface of the hot gas path component such that it is separated from the first micro-channel by a surface gap having a first width. The method also includes disposing a braze sheet onto the exterior surface of the hot gas path component such that the braze sheet covers at least of portion of the first and second micro-channels, and heating the braze sheet to bond it to at least a portion of the exterior surface of the hot gas path component.

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Directory of Open Access Journals (Sweden)

Chelsea Sabo

2012-01-01

Full Text Available There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

Science.gov (United States)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Land management planning: a method of evaluating alternatives

Science.gov (United States)

Andres Weintraub; Richard Adams; Linda Yellin

1982-01-01

A method is described for developing and evaluating alternatives in land management planning. A structured set of 15 steps provides a framework for such an evaluation. when multiple objectives and uncertainty must be considered in the planning process. The method is consistent with other processes used in organizational evaluation, and allows for the interaction of...

Use of family planning methods in Kassala, Eastern Sudan

Directory of Open Access Journals (Sweden)

Mamoun Mona

2011-02-01

Full Text Available Abstract Background Investigating use and determinants of family planning methods may be instructive in the design of interventions to improve reproductive health services. Findings Across sectional community-based study was conducted during the period February-April 2010 to investigate the use of family planning in Kassala, eastern Sudan. Structured questionnaires were used to gather socio-demographic data and use of family planning. The mean ± SD of the age and parity of 613 enrolled women was 31.1 ± 7 years and 3.4 ± 1.9, respectively. Only 44.0% of these women had previously or currently used one or more of the family planning methods. Combined pills (46.7% and progesterone injection (17.8% were the predominant method used by the investigated women. While age, residence were not associated with the use of family planning, parity (> five, couple education (≥ secondary level were significantly associated with the use of family planning. Husband objection and religious beliefs were the main reasons of non-use of family planning. Conclusion Education, encouragement of health education programs and involvement of the religious persons might promote family planning in eastern Sudan.

Fast exploration of an optimal path on the multidimensional free energy surface

Science.gov (United States)

Chen, Changjun

2017-01-01

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475

Application of Statistical Method of Path Analysis to Describe Soil Biological Indices

Directory of Open Access Journals (Sweden)

Y. Kooch

2016-09-01

Full Text Available Introduction: Among the collection of natural resources in the world, soil is considered as one of the most important components of the environment. Protect and improve the properties of this precious resource, requires a comprehensive and coordinated action that only through a deep understanding of quantitative (not only recognition of the quality the origin, distribution and functionality in a natural ecosystem is possible. Many researchers believe that due to the quick reactions of soil organisms to environmental changes, soil biological survey to estimate soil quality is more important than the chemical and physical properties. For this reason, in many studies the nitrogen mineralization and microbial respiration indices are regarded. The aim of the present study were to study the direct and indirect effects of soil physicochemical characteristics on the most important biological indicators (nitrogen mineralization and microbial respiration, which has not been carefully considered up to now. This research is the first study to provide evidence to the future planning and management of soil sciences. Materials and Methods: For this, a limitation of 20 ha area of Experimental Forest Station of Tarbiat Modares University was considered. Fifty five soil samples, from the top 15 cm of soil, were taken, from which bulk density, texture, organic C, total N, cation exchange capacity (CEC, nitrogen mineralization and microbial respiration were determined at the laboratory. The data stored in Excel as a database. To determine the relationship between biological indices and soil physicochemical characteristics, correlation analysis and factor analysis using principal component analysis (PCA were employed. To investigate all direct and indirect relationships between biological indices and different soil characteristics, path analysis (path analysis was used. Results and Discussion: Results showed significant positive relations between biological indices

Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach.

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Hyunseok Park

Full Text Available The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents.

Quivers of Bound Path Algebras and Bound Path Coalgebras

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Dr. Intan Muchtadi

2010-09-01

Full Text Available bras and coalgebras can be represented as quiver (directed graph, and from quiver we can construct algebras and coalgebras called path algebras and path coalgebras. In this paper we show that the quiver of a bound path coalgebra (resp. algebra is the dual quiver of its bound path algebra (resp. coalgebra.

Teleconnection Paths via Climate Network Direct Link Detection.

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Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Automatic NC-Data generation method for 5-axis cutting of turbine-blades by finding Safe heel-angles and adaptive path-intervals

International Nuclear Information System (INIS)

Piao, Cheng Dao; Lee, Cheol Soo; Cho, Kyu Zong; Park, Gwang Ryeol

2004-01-01

In this paper, an efficient method for generating 5-axis cutting data for a turbine blade is presented. The interference elimination of 5-axis cutting currently is very complicated, and it takes up a lot of time. The proposed method can generate an interference-free tool path, within an allowance range. Generating the cutting data just point to the cutting process and using it to obtain NC data by calculating the feed rate, allows us to maintain the proper feed rate of the 5-axis machine. This paper includes the algorithms for: (1) CL data generation by detecting an interference-free heel angle, (2) finding the optimal tool path interval considering the cusp-height, (3) finding the adaptive feed rate values for each cutter path, and (4) the inverse kinematics depending on the structure of the 5-axis machine, for generating the NC data

Reaction path simulations in multicomponent materials

International Nuclear Information System (INIS)

Seifert, H.J.

1999-01-01

The CALPHAD (calculation of phase diagrams) method is used in combination with selected experimental investigations to derive reaction paths in multicomponent systems. The method is illustrated by applying computerized thermodynamic databases and suitable software to explain quantitatively the thermal degradation of precursor-derived Si-C-N ceramics and the nitridation of titanium carbide. Reaction sequences in the Si 3 N 4 -SiC-TiC x N l-x -C-N system are illustrated by graphical representation of compatibility regions and indicated reaction paths. From these results the experimentally known microstructure development of TiC reinforced Si 3 N 4 ceramics is explained and quantitative information is provided to optimize the microstructure of such materials. The concept of reaction paths for the understanding of rapid solidification processes is shown by the example of AZ type Mg casting alloys. (orig.)

The High Field Path to Practical Fusion Energy

Science.gov (United States)

Mumgaard, Robert; Whyte, D.; Greenwald, M.; Hartwig, Z.; Brunner, D.; Sorbom, B.; Marmar, E.; Minervini, J.; Bonoli, P.; Irby, J.; Labombard, B.; Terry, J.; Vieira, R.; Wukitch, S.

2017-10-01

We propose a faster, lower cost development path for fusion energy enabled by high temperature superconductors, devices at high magnetic field, innovative technologies and modern approaches to technology development. Timeliness, scale, and economic-viability are the drivers for fusion energy to combat climate change and aid economic development. The opportunities provided by high-temperature superconductors, innovative engineering and physics, and new organizational structures identified over the last few years open new possibilities for realizing practical fusion energy that could meet mid-century de-carbonization needs. We discuss re-factoring the fusion energy development path with an emphasis on concrete risk retirement strategies utilizing a modular approach based on the high-field tokamak that leverages the broader tokamak physics understanding of confinement, stability, and operational limits. Elements of this plan include development of high-temperature superconductor magnets, simplified immersion blankets, advanced long-leg divertors, a compact divertor test tokamak, efficient current drive, modular construction, and demountable magnet joints. An R&D plan culminating in the construction of an integrated pilot plant and test facility modeled on the ARC concept is presented.

[Dual insertion paths design characteristics and short-term clinical observation of rotational path removable partial dentures].

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Li, Jian; Jiang, Ting; Li, Sai; Chen, Wei

2013-02-18

To investigate design methods of dual insertion paths and observe a short-term clinic overview of rotational path removable partial dentures (RPDs). In the study, 40 patients with partial edentulous arches were included and divided into two groups. The patients in group one were restored with rotational path RPDs (10 Kennedy class III and 10 Kennedy class IV respectively). The patients in group two (20 patients), whose edentulous area was matched with the patients' in group one, were restored with the linear path RPDs. After surveying and simulative preparation on diagnostic casts, the basic laws of designing rotational path RPDs were summarized. The oral preparation was accurately performed under the guidance of indices made on diagnostic casts after simulative preparation. The 40 dentures were recalled two weeks and one year after the insertion. The evaluations of the clinic outcome, including retention, stability, mastication function, esthetics and wearing convenience, were marked out as good, acceptable, and poor. The comparison of the evaluation results was performed between the two groups. In the rotational path design for Kennedy class III or IV RPDs, the angles (α) of dual insertion paths should be designed within a scope, approximate 10°-15°.When the angle (α) became larger, the denture retention turned to be better, but accordingly the posterior abutments needed more preparation. In the clinical application, the first insertions of the 40 dentures were all favorably accomplished. When the rotational path RPDs were compared to linear path RPDs, the time consuming on first insertion had no statistical difference[(32±8) min and (33±8) min respectively, P>0.05]. Recalled two weeks and one year after the insertion, in the esthetics evaluation, 20 rotational path RPDs were all evaluated as "A", but only 7(two weeks after) and 6 (one year after) linear path RPDs were evaluated as "A"(P<0.05). There was no significant difference in other evaluation results

The Relationship between Management, Career Planning and Career Development of Medical and Non-medical Faculty Members of Kohgiluyeh and Boyerahmad Province, Iran

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G Sajjadikhah

2016-10-01

Full Text Available Abstract Background & aim: There are many mechanisms for the development of human resources, which career development is one of its central components. The aim of this study was to determine the factors related to career development faculty members (Medical and Non-medical of Kohgiluyeh and Boyer-Ahmad province, Iran. Methods: The present paper was a cross-sectional, descriptive correlation method study.  The study population consisted of 535 faculty members (medical, government, NGOs in Kohgiluyeh and Boyer province, Iran, of which 400 participants were randomly selected for the present study. Data were collected through standard questionnaires as a research tool, of career development, career planning and career management for data analysis and statistical tests including linear regression, t-test, regression, and correlation coefficient was used. Results: Career development status and its related factors (Career management and career planning scientific faculty members was desirable. The findings show that between career planning and career management, career development, a significant positive correlation was observed (P