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.

Points-Based Safe Path Planning of Continuum Robots

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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.

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 Methods in an Environment with Obstacles (A Review

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W. Liu

2018-01-01

Full Text Available Planning the path is the most important task in the mobile robot navigation. This task involves basically three aspects. First, the planned path must run from a given starting point to a given endpoint. Secondly, it should ensure robot’s collision-free movement. Thirdly, among all the possible paths that meet the first two requirements it must be, in a certain sense, optimal.Methods of path planning can be classified according to different characteristics. In the context of using intelligent technologies, they can be divided into traditional methods and heuristic ones. By the nature of the environment, it is possible to divide planning methods into planning methods in a static environment and in a dynamic one (it should be noted, however, that a static environment is rare. Methods can also be divided according to the completeness of information about the environment, namely methods with complete information (in this case the issue is a global path planning and methods with incomplete information (usually, this refers to the situational awareness in the immediate vicinity of the robot, in this case it is a local path planning. Note that incomplete information about the environment can be a consequence of the changing environment, i.e. in a dynamic environment, there is, usually, a local path planning.Literature offers a great deal of methods for path planning where various heuristic techniques are used, which, as a rule, result from the denotative meaning of the problem being solved. This review discusses the main approaches to the problem solution. Here we can distinguish five classes of basic methods: graph-based methods, methods based on cell decomposition, use of potential fields, optimization methods, фтв methods based on intelligent technologies.Many methods of path planning, as a result, give a chain of reference points (waypoints connecting the beginning and end of the path. This should be seen as an intermediate result. The problem

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...

Reactive Path Planning Approach for Docking Robots in Unknown Environment

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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

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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.

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.

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.

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

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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

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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

An adaptive dual-optimal path-planning technique for unmanned air vehicles

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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.

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.

Cooperative Path Planning and Constraints Analysis for Master-Slave Industrial Robots

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Yahui Gan

2012-09-01

Full Text Available A strategy of cooperative path planning for a master-slave multiple robot system is presented in this paper. The path planning method is based on motion constraints between the end-effectors of cooperative robots. Cooperation motions have been classified into three types by relative motions between end-effectors of master and slave robots, which is concurrent cooperation, coupled synchronous cooperation and combined synchronous cooperation. Based on this classification, position /orientation constraints and joint velocity constraints are explored in-depth here. In order to validate the path planning method and the theoretical developments in motion constraints analysis, representative experiments based on two industrial robots, Motoman VA1400 and HP20, are provided at the end of the paper. The experimental results have proved both the effectiveness of the path planning method and the correctness of the constraints analysis.

Path Planning Algorithms for the Adaptive Sensor Fleet

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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 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 Method in Multi-obstacle Marine Environment

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Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

A hierarchical spatial framework for forest landscape planning.

Science.gov (United States)

Pete Bettinger; Marie Lennette; K. Norman Johnson; Thomas A. Spies

2005-01-01

A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian...

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

Energy-Aware Path Planning for UAS Persistent Sampling and Surveillance

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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.

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.

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.

Aircraft path planning for optimal imaging using dynamic cost functions

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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.

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 Hybrid 3D Path Planning Method for UAVs

DEFF Research Database (Denmark)

Ortiz-Arroyo, Daniel

2015-01-01

This paper presents a hybrid method for path planning in 3D spaces. We propose an improvement to a near-optimal 2D off-line algorithm and a flexible normalized on-line fuzzy controller to find shortest paths. Our method, targeted to low altitude domains, is simple and efficient. Our preliminary resu...

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

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Qiang Zhang

2016-04-01

Full Text Available In this paper, a minimum time path planning strategy is proposed for multi points manufacturing problems in drilling/spot welding tasks. By optimizing the travelling schedule of the set points and the detailed transfer path between points, the minimum time manufacturing task is realized under fully utilizing the dynamic performance of robotic manipulator. According to the start-stop movement in drilling/spot welding task, the path planning problem can be converted into a traveling salesman problem (TSP and a series of point to point minimum time transfer path planning problems. Cubic Hermite interpolation polynomial is used to parameterize the transfer path and then the path parameters are optimized to obtain minimum point to point transfer time. A new TSP with minimum time index is constructed by using point-point transfer time as the TSP parameter. The classical genetic algorithm (GA is applied to obtain the optimal travelling schedule. Several minimum time drilling tasks of a 3-DOF robotic manipulator are used as examples to demonstrate the effectiveness of the proposed approach.

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.

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.

Research on Navigation Path Planning for An Underground Load Haul Dump

Directory of Open Access Journals (Sweden)

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.

Decision support in hierarchical planning systems: The case of procurement planning in oil refining industries

DEFF Research Database (Denmark)

Kallestrup, Kasper Bislev; Lynge, Lasse Hadberg; Akkerman, Renzo

2014-01-01

In this paper, we discuss the development of decision support systems for hierarchically structured planning approaches, such as commercially available advanced planning systems. We develop a framework to show how such a decision support system can be designed with the existing organization in mind...... and from the perspective of the organizational aspects involved. To exemplify and develop our framework, we use a case study of crude oil procurement planning in the refining industry. The results of the case study indicate an improved organizational embedding of the DSS, leading to significant savings...... in terms of planning efforts and procurement costs. In general, our framework aims to support the continuous improvement of advanced planning systems, increasing planning quality in complex supply chain settings....

The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

Directory of Open Access Journals (Sweden)

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.

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.

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

Science.gov (United States)

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.

Methodology for using root locus technique for mobile robots path planning

Directory of Open Access Journals (Sweden)

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.

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.

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.

Analysis of construction dynamic plan using fuzzy critical path method

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Kurij Kazimir V.

2014-01-01

Full Text Available Critical Path Method (CPM technique has become widely recognized as valuable tool for the planning and scheduling large construction projects. The aim of this paper is to present an analytical method for finding the Critical Path in the precedence network diagram where the duration of each activity is represented by a trapezoidal fuzzy number. This Fuzzy Critical Path Method (FCPM uses a defuzzification formula for trapezoidal fuzzy number and applies it on the total float (slack time for each activity in the fuzzy precedence network to find the critical path. The method presented in this paper is very effective in determining the critical activities and finding the critical paths.

Path Planning Method for UUV Homing and Docking in Movement Disorders Environment

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Zheping Yan

2014-01-01

Full Text Available Path planning method for unmanned underwater vehicles (UUV homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO, inertia weight particle swarm optimization (LWPSO, EPSO, and time-varying acceleration coefficient (TVAC. It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path.

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.

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.

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

Safe Maritime Autonomous Path Planning in a High Sea State

Science.gov (United States)

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.

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....

Robotic Online Path Planning on Point Cloud.

Science.gov (United States)

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.

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

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Kaijun Zhou

2017-09-01

Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.

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

Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

Science.gov (United States)

Fu, QiMing

2016-01-01

To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

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...

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.

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.

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.

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.

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.

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.

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.

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

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Yong Ma

2014-01-01

Full Text Available This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach.

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.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

Science.gov (United States)

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

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

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

Directory of Open Access Journals (Sweden)

Yong-feng Dong

2016-01-01

Full Text Available In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time.

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.

A novel approach for multiple mobile objects path planning: Parametrization method and conflict resolution strategy

International Nuclear Information System (INIS)

Ma, Yong; Wang, Hongwei; Zamirian, M.

2012-01-01

We present a new approach containing two steps to determine conflict-free paths for mobile objects in two and three dimensions with moving obstacles. Firstly, the shortest path of each object is set as goal function which is subject to collision-avoidance criterion, path smoothness, and velocity and acceleration constraints. This problem is formulated as calculus of variation problem (CVP). Using parametrization method, CVP is converted to time-varying nonlinear programming problems (TNLPP) and then resolved. Secondly, move sequence of object is assigned by priority scheme; conflicts are resolved by multilevel conflict resolution strategy. Approach efficiency is confirmed by numerical examples. -- Highlights: ► Approach with parametrization method and conflict resolution strategy is proposed. ► Approach fits for multi-object paths planning in two and three dimensions. ► Single object path planning and multi-object conflict resolution are orderly used. ► Path of each object obtained with parameterization method in the first phase. ► Conflict-free paths gained by multi-object conflict resolution in the second phase.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

Science.gov (United States)

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Path planning in uncertain flow fields using ensemble method

KAUST Repository

Wang, Tong

2016-08-20

An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.

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.

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.

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.

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.

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.

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

KAUST Repository

Wang, Tong; Le Maitre, Olivier; Hoteit, Ibrahim; Knio, Omar

2016-01-01

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

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.

A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning

Science.gov (United States)

Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei

2013-03-01

In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.

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...

An Efficient, Hierarchical Viewpoint Planning Strategy for Terrestrial Laser Scanner Networks

Science.gov (United States)

Jia, F.; Lichti, D. D.

2018-05-01

Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the "optimality" of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a "brute force" search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the "brute force" strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.

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.

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.

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

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.

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.

Heuristic methods for shared backup path protection planning

DEFF Research Database (Denmark)

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

2012-01-01

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...... present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5% was achieved for more than half of the benchmark instances (and a gap of less...

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...

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.

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

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.

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.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

Science.gov (United States)

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies

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.

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

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…

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...

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 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.

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...

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

The path to glory is paved with hierarchy: When hierarchical differentiation increases group effectiveness.

NARCIS (Netherlands)

Ronay, R.D.; Greenaway, K; Anicich, E.M; Galinsky, A.D.

2012-01-01

Two experiments examined the psychological and biological antecedents of hierarchical differentiation and the resulting consequences for productivity and conflict within small groups. In Experiment 1, which used a priming manipulation, hierarchically differentiated groups (i.e., groups comprising 1

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

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...

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.

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.

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)

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 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.

Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis

Science.gov (United States)

Krozel, James A.

1988-01-01

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

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

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

Directory of Open Access Journals (Sweden)

Yueyue Deng

2013-01-01

Full Text Available Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. This paper presents a solution for the task allocation and path planning for multiple AUVs under marginal acoustic communication conditions: a location-aided task allocation framework (LAAF algorithm for multitarget task assignment and the grid-based multiobjective optimal programming (GMOOP mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Both the LAAF and GMOOP algorithms are well suited in poor acoustic network condition and dynamic environment. Our research is based on an existing mobile ad hoc network underwater acoustic simulator and blind flooding routing protocol. Simulation results demonstrate that the location-aided auction strategy performs significantly better than the well-accepted auction algorithm developed by Bertsekas in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path-planning technique provides an efficient method for executing multiobjective tasks by cooperative agents with limited communication capabilities. This is in contrast to existing multiobjective action selection methods that are limited to networks where constant, reliable communication is assumed to be available.

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

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2018-04-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2017-08-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

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.

An Improved 6LoWPAN Hierarchical Routing Protocol

Directory of Open Access Journals (Sweden)

Xue Li

2015-10-01

Full Text Available IETF 6LoWPAN working group is engaged in the IPv6 protocol stack research work based on IEEE802.15.4 standard. In this working group, the routing protocol is one of the important research contents. In the 6LoWPAN, HiLow is a well-known layered routing protocol. This paper puts forward an improved hierarchical routing protocol GHiLow by improving HiLow parent node selection and path restoration strategy. GHiLow improves the parent node selection by increasing the choice of parameters. Simutaneously, it also improves path recovery by analysing different situations to recovery path. Therefore, GHiLow contributes to the ehancement of network performance and the decrease of network energy consumption.

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...

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.

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 ...

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.

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

Directory of Open Access Journals (Sweden)

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.

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

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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.

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

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Kun-Lin Wu

2016-01-01

Full Text Available In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.

A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

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Feng Lu

2016-10-01

Full Text Available Gas path fault diagnosis involves the effective utilization of condition-based sensor signals along engine gas path to accurately identify engine performance failure. The rapid development of information processing technology has led to the use of multiple-source information fusion for fault diagnostics. Numerous efforts have been paid to develop data-based fusion methods, such as neural networks fusion, while little research has focused on fusion architecture or the fusion of different method kinds. In this paper, a data hierarchical fusion using improved weighted Dempster–Shaffer evidence theory (WDS is proposed, and the integration of data-based and model-based methods is presented for engine gas-path fault diagnosis. For the purpose of simplifying learning machine typology, a recursive reduced kernel based extreme learning machine (RR-KELM is developed to produce the fault probability, which is considered as the data-based evidence. Meanwhile, the model-based evidence is achieved using particle filter-fuzzy logic algorithm (PF-FL by engine health estimation and component fault location in feature level. The outputs of two evidences are integrated using WDS evidence theory in decision level to reach a final recognition decision of gas-path fault pattern. The characteristics and advantages of two evidences are analyzed and used as guidelines for data hierarchical fusion framework. Our goal is that the proposed methodology provides much better performance of gas-path fault diagnosis compared to solely relying on data-based or model-based method. The hierarchical fusion framework is evaluated in terms to fault diagnosis accuracy and robustness through a case study involving fault mode dataset of a turbofan engine that is generated by the general gas turbine simulation. These applications confirm the effectiveness and usefulness of the proposed approach.

Road network safety evaluation using Bayesian hierarchical joint model.

Science.gov (United States)

Wang, Jie; Huang, Helai

2016-05-01

Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

Directory of Open Access Journals (Sweden)

Lianbo Ma

2014-01-01

Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

Science.gov (United States)

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

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

Directory of Open Access Journals (Sweden)

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.

Hierarchical control system of advanced robot manipulator

International Nuclear Information System (INIS)

Oomichi, Takeo; Okino, Akihisa; Nishihara, Masatoshi; Sakamoto, Taizou; Matsuda, Koichi; Ohnishi, Ken

1990-01-01

We introduce a double arm with 4-finger's manipulator system which process the large volume of information at high speed. This is under research/development many type of works in the harsh condition. Namely, hierarchization of instruction unit in which motion control system as real time processing unit, and task planning unit as non-real time processing unit, interface with operation through the task planning unit has been made. Also, high speed processing of large volume information has been realized by decentralizing the motion control unit by function, hierarchizing the high speed processing unit, and developing high speed transmission, IC which does not depend on computer OS to avoid the delay in transmission. (author)

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.

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

Science.gov (United States)

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.

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.

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

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.

Robust Pseudo-Hierarchical Support Vector Clustering

DEFF Research Database (Denmark)

Hansen, Michael Sass; Sjöstrand, Karl; Olafsdóttir, Hildur

2007-01-01

Support vector clustering (SVC) has proven an efficient algorithm for clustering of noisy and high-dimensional data sets, with applications within many fields of research. An inherent problem, however, has been setting the parameters of the SVC algorithm. Using the recent emergence of a method...... for calculating the entire regularization path of the support vector domain description, we propose a fast method for robust pseudo-hierarchical support vector clustering (HSVC). The method is demonstrated to work well on generated data, as well as for detecting ischemic segments from multidimensional myocardial...

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...

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...

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...

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

Runtime Concepts of Hierarchical Software Components

Czech Academy of Sciences Publication Activity Database

Bureš, Tomáš; Hnětynka, P.; Plášil, František

2007-01-01

Roč. 8, special (2007), s. 454-463 ISSN 1525-9293 R&D Projects: GA AV ČR 1ET400300504 Institutional research plan: CEZ:AV0Z10300504 Keywords : component-based development * hierarchical components * connectors * controlers * runtime environment Subject RIV: JC - Computer Hardware ; Software

Rough terrain motion planning for actively reconfigurable mobile robots

International Nuclear Information System (INIS)

Brunner, Michael

2015-01-01

In the aftermath of the Tohoku earthquake and the nuclear meltdown at the power plant of Fukushima Daiichi in 2011, reconfigurable robots like the iRobot Packbot were deployed. Instead of humans, the robots were used to investigate contaminated areas. Other incidents are the two major earthquakes in Northern Italy in May 2012. Besides many casualties, a large number of historical buildings was severely damaged. Due to the imminent danger of collapse, it was too dangerous for rescue personnel to enter many of the buildings. Therefore, the sites were inspected by reconfigurable robots, which are able to traverse the rubble and debris of the partially destroyed buildings. This thesis develops a navigation system enabling wheeled and tracked robots to safely traverse rough terrain and challenging structures. It consists of a planning mechanism and a controller. The focus of this thesis, however, is on the contribution to motion planning. The planning scheme employs a hierarchical approach to motion planning for actively reconfigurable robots in rough environments. Using a map of the environment the algorithm estimates the traversability under the consideration of uncertainties. Based on this analysis, an initial path search determines an approximate solution with respect to the robot's operating limits.Subsequently, a detailed planning step refines the initial path where it is required. The refinement step considers the robot's actuators and stability in addition to the quantities of the first search. Determining the robot-terrain interaction is very important in rough terrain. This thesis presents two path refinement approaches: a deterministic and a randomized approach. The experimental evaluation investigates the separate components of the planning scheme, the robot-terrain interaction for instance.In simulation as well as in real world experiments the evaluation demonstrates the necessity of such a planning algorithm in rough terrain and it provides

Rough terrain motion planning for actively reconfigurable mobile robots

Energy Technology Data Exchange (ETDEWEB)

Brunner, Michael

2015-02-05

In the aftermath of the Tohoku earthquake and the nuclear meltdown at the power plant of Fukushima Daiichi in 2011, reconfigurable robots like the iRobot Packbot were deployed. Instead of humans, the robots were used to investigate contaminated areas. Other incidents are the two major earthquakes in Northern Italy in May 2012. Besides many casualties, a large number of historical buildings was severely damaged. Due to the imminent danger of collapse, it was too dangerous for rescue personnel to enter many of the buildings. Therefore, the sites were inspected by reconfigurable robots, which are able to traverse the rubble and debris of the partially destroyed buildings. This thesis develops a navigation system enabling wheeled and tracked robots to safely traverse rough terrain and challenging structures. It consists of a planning mechanism and a controller. The focus of this thesis, however, is on the contribution to motion planning. The planning scheme employs a hierarchical approach to motion planning for actively reconfigurable robots in rough environments. Using a map of the environment the algorithm estimates the traversability under the consideration of uncertainties. Based on this analysis, an initial path search determines an approximate solution with respect to the robot's operating limits.Subsequently, a detailed planning step refines the initial path where it is required. The refinement step considers the robot's actuators and stability in addition to the quantities of the first search. Determining the robot-terrain interaction is very important in rough terrain. This thesis presents two path refinement approaches: a deterministic and a randomized approach. The experimental evaluation investigates the separate components of the planning scheme, the robot-terrain interaction for instance.In simulation as well as in real world experiments the evaluation demonstrates the necessity of such a planning algorithm in rough terrain and it provides

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.

An improved hierarchical A * algorithm in the optimization of parking lots

Science.gov (United States)

Wang, Yong; Wu, Junjuan; Wang, Ying

2017-08-01

In the parking lot parking path optimization, the traditional evaluation index is the shortest distance as the best index and it does not consider the actual road conditions. Now, the introduction of a more practical evaluation index can not only simplify the hardware design of the boot system but also save the software overhead. Firstly, we establish the parking lot network graph RPCDV mathematical model and all nodes in the network is divided into two layers which were constructed using different evaluation function base on the improved hierarchical A * algorithm which improves the time optimal path search efficiency and search precision of the evaluation index. The final results show that for different sections of the program attribute parameter algorithm always faster the time to find the optimal path.

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...

Noise enhances information transfer in hierarchical networks.

Science.gov (United States)

Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

Spatio-temporal structure, path characteristics and perceptual grouping in immediate serial spatial recall

Directory of Open Access Journals (Sweden)

Carlo De Lillo

2016-11-01

Full Text Available Immediate serial spatial recall measures the ability to retain sequences of locations in short-term memory and is considered the spatial equivalent of digit span. It is tested by requiring participants to reproduce sequences of movements performed by an experimenter or displayed on a monitor. Different organizational factors dramatically affect serial spatial recall but they are often confounded or underspecified. Untangling them is crucial for the characterization of working-memory models and for establishing the contribution of structure and memory capacity to spatial span. We report five experiments assessing the relative role and independence of factors that have been reported in the literature. Experiment 1 disentangled the effects of spatial clustering and path-length by manipulating the distance of items displayed on a touchscreen monitor. Long-path sequences segregated by spatial clusters were compared with short-path sequences not segregated by clusters. Recall was more accurate for sequences segregated by clusters independently from path-length. Experiment 2 featured conditions where temporal pauses were introduced between or within cluster boundaries during the presentation of sequences with the same paths. Thus, the temporal structure of the sequences was either consistent or inconsistent with a hierarchical representation based on segmentation by spatial clusters but the effect of structure could not be confounded with effects of path-characteristics. Pauses at cluster boundaries yielded more accurate recall, as predicted by a hierarchical model. In Experiment 3, the systematic manipulation of sequence structure, path-length and presence of path-crossings of sequences showed that structure explained most of the variance, followed by the presence/absence of path-crossings, and path-length. Experiments 4 and 5 replicated the results of the previous experiments in immersive virtual reality navigation tasks where the viewpoint of the

New Design of Mobile Robot Path Planning with Randomly Moving Obstacles

Directory of Open Access Journals (Sweden)

T. A. Salih

2013-05-01

Full Text Available The navigation of a mobile robot in an unknown environment has always been a very challenging task. In order to achieve safe and autonomous navigation, the mobile robot needs to sense the surrounding environment and plans a collision-free path. This paper focuses on designing and implementing a mobile robot which has the ability of navigating smoothly in an unknown environment, avoiding collisions, without having to stop in front of obstacles, detecting leakage of combustible gases and transmitting a message of detection results to the civil defense unit automatically through the Internet to the E-mail. This design uses the implementation of artificial neural network (ANN on a new technology represented by Field Programmable Analog Array (FPAA for controlling the motion of the robot. The robot with the proposed controller is tested and has completed the required objective successfully.

Hierarchical CaCO3 chromatography: a stationary phase based on biominerals.

Science.gov (United States)

Sato, Kosuke; Oaki, Yuya; Takahashi, Daisuke; Toshima, Kazunobu; Imai, Hiroaki

2015-03-23

In biomineralization, acidic macromolecules play important roles for the growth control of crystals through a specific interaction. Inspired by this interaction, we report on an application of the hierarchical structures in CaCO3 biominerals to a stationary phase of chromatography. The separation and purification of acidic small organic molecules are achieved by thin-layer chromatography and flash chromatography using the powder of biominerals as the stationary phase. The unit nanocrystals and their oriented assembly, the hierarchical structure, are suitable for the adsorption site of the target organic molecules and the flow path of the elution solvents, respectively. The separation mode is ascribed to the specific adsorption of the acidic molecules on the crystal face and the coordination of the functional groups to the calcium ions. The results imply that a new family of stationary phase of chromatography can be developed by the fine tuning of hierarchical structures in CaCO3 materials. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

Directory of Open Access Journals (Sweden)

Xin Wang

2012-01-01

Full Text Available This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

Study on the correlation between the hierarchical urban system and high-speed railway network planning in China

Directory of Open Access Journals (Sweden)

Hong Sun

2016-09-01

Full Text Available This study examines the interrelatedness between the hierarchical structure of China׳s urban system and high-speed railway (HSR network planning at the national level. As a multi-layered system, the Chinese HSR can be categorized into three sub-networks, namely, the national HSR trunk network, the national HSR extensional network, and the intercity HSR network. By examining the direct HSR network connection, HSR nodal connection, and HSR operational frequency of 287 prefecture-level cities, this study demonstrates that the hierarchies of China׳s administrative, demographic, and economic urban systems strongly influence HSR network planning. The national HSR trunk network prioritizes the connection of top-level central cities, whereas the extensional network prioritizes cities at the lower level of the urban system. Moreover, the national HSR system forms the backbone of the HSR network structure based on a national scale, whereas the intercity HSR system satisfies the travel needs within urban agglomerations based on the regional level.

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

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

Decomposition of the Strategic Plan for Restructuring a Machine-Building Enterprise in View of Continuity of the Plans for Adjacent Periods

Directory of Open Access Journals (Sweden)

Kozyr-Chepurna Mariia A.

2017-09-01

Full Text Available The aim of the article is to practically approve the authors’ multi-level hierarchical approach to the strategic planning of industrial enterprise restructuring using the example of solving the problem of disaggregating the strategic plan for restructuring a machine-building enterprise of the electrical industry providing for organization of production of railroad freight cars at the enterprise. Besides, there demonstrated the effectiveness of the mechanisms of coordinating the plans for adjacent hierarchical and time periods included in the corresponding mathematical support. In the course of the practical approval, different variants of formulating the problem of decomposing the strategic plan into plans of lower hierarchical levels differing in terms of coordination of the plans of adjacent hierarchical levels and adjacent planning periods are considered, and the solutions of corresponding optimal planning problems are analyzed. It is shown that the developed methodological approach, which is based on the methods of statistical optimization, demonstrates quite satisfactory performance characteristics in solving the problem of coordinating the plans of adjacent time periods in the mode of sliding planning in the process of decomposition of the strategic plan into lower-level plans.

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.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Science.gov (United States)

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

DICOM involving XML path-tag

Science.gov (United States)

Zeng, Qiang; Yao, Zhihong; Liu, Lei

2011-03-01

Digital Imaging and Communications in Medicine (DICOM) is a standard for handling, storing, printing, and transmitting information in medical imaging. XML (Extensible Markup Language) is a set of rules for encoding documents in machine-readable form which has become more and more popular. The combination of these two is very necessary and promising. Using XML tags instead of numeric labels in DICOM files will effectively increase the readability and enhance the clear hierarchical structure of DICOM files. However, due to the fact that the XML tags rely heavily on the orders of the tags, the strong data dependency has a lot of influence on the flexibility of inserting and exchanging data. In order to improve the extensibility and sharing of DICOM files, this paper introduces XML Path-Tag to DICOM. When a DICOM file is converted to XML format, adding simple Path-Tag into the DICOM file in place of complex tags will keep the flexibility of a DICOM file while inserting data elements and give full play to the advantages of the structure and readability of an XML file. Our method can solve the weak readability problem of DICOM files and the tedious work of inserting data into an XML file. In addition, we set up a conversion engine that can transform among traditional DICOM files, XML-DCM and XML-DCM files involving XML Path-Tag efficiently.

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang; Wang, Jun; Vouga, Etienne; Wonka, Peter

2013-01-01

We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang

2013-11-06

We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

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.

Hierarchy of Dysfunction Related to Dressing Performance in Stroke Patients: A Path Analysis Study.

Science.gov (United States)

Fujita, Takaaki; Nagayama, Hirofumi; Sato, Atsushi; Yamamoto, Yuichi; Yamane, Kazuhiro; Otsuki, Koji; Tsuchiya, Kenji; Tozato, Fusae

2016-01-01

Previous reports indicated that various dysfunctions caused by stroke affect the level of independence in dressing. These dysfunctions can be hierarchical, and these effects on dressing performance can be complicated in stroke patients. However, there are no published reports focusing on the hierarchical structure of the relationships between the activities of daily living and balance function, motor and sensory functions of the affected lower limb, strength of the abdominal muscles and knee extension on the unaffected side, and visuospatial deficits. The purpose of this study was to elucidate the hierarchical and causal relationships between dressing performance and these dysfunctions in stroke patients. This retrospective study included 104 first-time stroke patients. The causal relationship between the dressing performance and age, time post stroke, balance function, motor and sensory functions of the affected lower limb, strength of the abdominal muscles and knee extension on the unaffected side, and visuospatial deficits were examined using path analysis. A hypothetical path model was created based on previous studies, and the goodness of fit between the data and model were verified. A modified path model was created that achieved an almost perfect fit to the data. Balance function and abdominal muscle strength have direct effects on dressing performance, with standardized direct effect estimates of 0.78 and 0.15, respectively. Age, motor and sensory functions of the affected lower limb, and strength of abdominal muscle and knee extension on the unaffected side have indirect effects on dressing by influencing balance function. Our results suggest that dressing performance depends strongly on balance function, and it is mainly influenced by the motor function of the affected lower limb.

Hierarchy of Dysfunction Related to Dressing Performance in Stroke Patients: A Path Analysis Study.

Directory of Open Access Journals (Sweden)

Takaaki Fujita

Full Text Available Previous reports indicated that various dysfunctions caused by stroke affect the level of independence in dressing. These dysfunctions can be hierarchical, and these effects on dressing performance can be complicated in stroke patients. However, there are no published reports focusing on the hierarchical structure of the relationships between the activities of daily living and balance function, motor and sensory functions of the affected lower limb, strength of the abdominal muscles and knee extension on the unaffected side, and visuospatial deficits. The purpose of this study was to elucidate the hierarchical and causal relationships between dressing performance and these dysfunctions in stroke patients. This retrospective study included 104 first-time stroke patients. The causal relationship between the dressing performance and age, time post stroke, balance function, motor and sensory functions of the affected lower limb, strength of the abdominal muscles and knee extension on the unaffected side, and visuospatial deficits were examined using path analysis. A hypothetical path model was created based on previous studies, and the goodness of fit between the data and model were verified. A modified path model was created that achieved an almost perfect fit to the data. Balance function and abdominal muscle strength have direct effects on dressing performance, with standardized direct effect estimates of 0.78 and 0.15, respectively. Age, motor and sensory functions of the affected lower limb, and strength of abdominal muscle and knee extension on the unaffected side have indirect effects on dressing by influencing balance function. Our results suggest that dressing performance depends strongly on balance function, and it is mainly influenced by the motor function of the affected lower limb.

Ultra-low Thermal Conductivity in Si/Ge Hierarchical Superlattice Nanowire.

Science.gov (United States)

Mu, Xin; Wang, Lili; Yang, Xueming; Zhang, Pu; To, Albert C; Luo, Tengfei

2015-11-16

Due to interfacial phonon scattering and nanoscale size effect, silicon/germanium (Si/Ge) superlattice nanowire (SNW) can have very low thermal conductivity, which is very attractive for thermoelectrics. In this paper, we demonstrate using molecular dynamics simulations that the already low thermal conductivity of Si/Ge SNW can be further reduced by introducing hierarchical structure to form Si/Ge hierarchical superlattice nanowire (H-SNW). The structural hierarchy introduces defects to disrupt the periodicity of regular SNW and scatters coherent phonons, which are the key contributors to thermal transport in regular SNW. Our simulation results show that periodically arranged defects in Si/Ge H-SNW lead to a ~38% reduction of the already low thermal conductivity of regular Si/Ge SNW. By randomizing the arrangement of defects and imposing additional surface complexities to enhance phonon scattering, further reduction in thermal conductivity can be achieved. Compared to pure Si nanowire, the thermal conductivity reduction of Si/Ge H-SNW can be as large as ~95%. It is concluded that the hierarchical structuring is an effective way of reducing thermal conductivity significantly in SNW, which can be a promising path for improving the efficiency of Si/Ge-based SNW thermoelectrics.

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.

Hierarchical Co-based Porous Layered Double Hydroxide Arrays Derived via Alkali Etching for High-performance Supercapacitors

Science.gov (United States)

Abushrenta, Nasser; Wu, Xiaochao; Wang, Junnan; Liu, Junfeng; Sun, Xiaoming

2015-08-01

Hierarchical nanoarchitecture and porous structure can both provide advantages for improving the electrochemical performance in energy storage electrodes. Here we report a novel strategy to synthesize new electrode materials, hierarchical Co-based porous layered double hydroxide (PLDH) arrays derived via alkali etching from Co(OH)2@CoAl LDH nanoarrays. This structure not only has the benefits of hierarchical nanoarrays including short ion diffusion path and good charge transport, but also possesses a large contact surface area owing to its porous structure which lead to a high specific capacitance (23.75 F cm-2 or 1734 F g-1 at 5 mA cm-2) and excellent cycling performance (over 85% after 5000 cycles). The enhanced electrode material is a promising candidate for supercapacitors in future application.

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.

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

Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.

Science.gov (United States)

Lin, Lanny; Goodrich, Michael A

2014-12-01

During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.

Changes of hierarchical network in local and world stock market

Science.gov (United States)

Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

2017-10-01

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

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

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.

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)

Integration of relational and hierarchical network information for protein function prediction

Directory of Open Access Journals (Sweden)

Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

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…

Detailed Sponge City Planning Based on Hierarchical Fuzzy Decision-Making: A Case Study on Yangchen Lake

Directory of Open Access Journals (Sweden)

Junyu Zhang

2017-11-01

Full Text Available We proposed a Hierarchical Fuzzy Inference System (HFIS framework to offer better decision supports with fewer user-defined data (uncertainty. The framework consists two parts: a fuzzified Geographic Information System (GIS and a HFIS system. The former provides comprehensive information on the criterion unit and the latter helps in making more robust decisions. The HFIS and the traditional Multi-Criteria Decision Making (MCDM method were applied to a case study and compared. The fuzzified GIS maps maintained a majority of the dominant characteristics of the criterion unit but also revealed some non-significant information according to the surrounding environment. The urban planning map generated by the two methods shares similar strategy choices (6% difference, while the spatial distribution of strategies shares 69.7% in common. The HFIS required fewer subjective decisions than the MCDM (34 user-defined decision rules vs. 141 manual evaluations.

Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

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Ntombizodwa J. Matsoma

2017-10-01

Full Text Available Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. Findings: The results revealed that both hierarchical and optimal approaches should be considered in clothing manufacturing. Managerial implications: In order to improve demand planning practices in the clothing industry, managers are recommended to apply hierarchical and optimal demand planning approaches, which might bring about improvements to demand planning in the Gauteng clothing industry. Conclusion: It is recommended that clothing manufacturers consider the types of product offering before making decisions about adopting the hierarchical or optimal demand planning approaches. When planning for basic clothes, manufacturers should consider a hierarchical demand planning approach, whereas the optimal demand planning approach is recommended for fashion clothes.

Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets.

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Woosang Lim

Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.

Design of hierarchical CuS/graphene architectures with enhanced lithium storage capability

Energy Technology Data Exchange (ETDEWEB)

Ding, Caihua; Su, Dezhi [Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications, School of Materials Science & Engineering, Beijing Institute of Technology, Beijing, 100081 (China); Ma, Wenxian [State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing, 100083 (China); Zhao, Yongjie, E-mail: zhaoyjpeace@gmail.com [Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications, School of Materials Science & Engineering, Beijing Institute of Technology, Beijing, 100081 (China); Yan, Dong [Department of Mechanical Engineering, Tsinghua University, Beijing, 100084 (China); State Key Laboratory of Tribology, Tsinghua University, Beijing, 100084 (China); Li, Jingbo; Jin, Haibo [Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications, School of Materials Science & Engineering, Beijing Institute of Technology, Beijing, 100081 (China)

2017-05-01

Highlights: • A delicate route was proposed for rational design of CuS/graphene composite. • Hierarchical CuS was composed of large amounts of well-arranged nanosheets. • The rationally designed structure of composite offered stable-hosts for Li{sup +} insertion. • The graphene constructed conductive paths and a network for fast transport of Li{sup +}. • The presence of the graphene in the composite reduced the dissolution of polysulfides. - Abstract: Metal-sulfides electrode materials usually suffer from poor cyclability and low rate capability in rechargeable batteries as a result of the pulverization of active materials and the loss of sulfur material induced by polysulfide dissolution. Herein, we reported a delicate and scalable route for rational design of CuS/graphene composites. Hierarchical CuS microparticles comprising of large amounts of self-assembled and well-arranged nanosheets uniformly mixed with flexible graphene layers. The obtained CuS/graphene electrodes exhibited high specific capacities, excellent cycling stability and desirable rate capability when being evaluated as anode materials for lithium-ion batteries. The high specific capacities of 568 mA h g{sup −1} after 100 cycles at 50 mA g{sup −1} and 143 mA h g{sup −1} at 1000 mA g{sup −1} (in rate testing) were achieved, suggesting a very promising candidate for high-performance lithium-ion batteries. The rationally designed structures of the CuS/graphene composites offered stable-hosts for Li{sup +} insertion and alleviated the volume changes upon cycling. The presence of the graphene in composite not only constructed conductive paths and a network for fast transport of Li{sup +}, but also effectively reduced the dissolution of polysulfides into electrolyte. This graphene-based composite with hierarchical structure could be used as a safe, low-cost, and versatile material for extensively potential applications.

Design of hierarchical CuS/graphene architectures with enhanced lithium storage capability

International Nuclear Information System (INIS)

Ding, Caihua; Su, Dezhi; Ma, Wenxian; Zhao, Yongjie; Yan, Dong; Li, Jingbo; Jin, Haibo

2017-01-01

Highlights: • A delicate route was proposed for rational design of CuS/graphene composite. • Hierarchical CuS was composed of large amounts of well-arranged nanosheets. • The rationally designed structure of composite offered stable-hosts for Li + insertion. • The graphene constructed conductive paths and a network for fast transport of Li + . • The presence of the graphene in the composite reduced the dissolution of polysulfides. - Abstract: Metal-sulfides electrode materials usually suffer from poor cyclability and low rate capability in rechargeable batteries as a result of the pulverization of active materials and the loss of sulfur material induced by polysulfide dissolution. Herein, we reported a delicate and scalable route for rational design of CuS/graphene composites. Hierarchical CuS microparticles comprising of large amounts of self-assembled and well-arranged nanosheets uniformly mixed with flexible graphene layers. The obtained CuS/graphene electrodes exhibited high specific capacities, excellent cycling stability and desirable rate capability when being evaluated as anode materials for lithium-ion batteries. The high specific capacities of 568 mA h g −1 after 100 cycles at 50 mA g −1 and 143 mA h g −1 at 1000 mA g −1 (in rate testing) were achieved, suggesting a very promising candidate for high-performance lithium-ion batteries. The rationally designed structures of the CuS/graphene composites offered stable-hosts for Li + insertion and alleviated the volume changes upon cycling. The presence of the graphene in composite not only constructed conductive paths and a network for fast transport of Li + , but also effectively reduced the dissolution of polysulfides into electrolyte. This graphene-based composite with hierarchical structure could be used as a safe, low-cost, and versatile material for extensively potential applications.

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

Science.gov (United States)

Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

2017-10-12

The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

Hierarchical nanoporous metals as a path toward the ultimate three-dimensional functionality.

Science.gov (United States)

Fujita, Takeshi

2017-01-01

Nanoporous metals prepared via dealloying or selective leaching of solid solution alloys and compounds represent an emerging class of materials. They possess a three-dimensional (3D) structure of randomly interpenetrating ligaments/nanopores with sizes between 5 nm and several tens of micrometers, which can be tuned by varying their preparation conditions (such as dealloying time and temperature) or additional thermal coarsening. As compared to other nanostructured materials, nanoporous metals have many advantages, including their bicontinuous structure, tunable pore sizes, bulk form, good electrical conductivity, and high structural stability. Therefore, nanoporous metals represent ideal 3D materials with versatile functionality, which can be utilized in various fields. In this review, we describe the recent applications of nanoporous metals in molecular detection, catalysis, 3D graphene synthesis, hierarchical pore formation, and additive manufacturing (3D printing) together with our own achievements in these areas. Finally, we discuss possible ways of realizing the ultimate 3D functionality beyond the scope of nanoporous metals.

Intelligent Aircraft Damage Assessment, Trajectory Planning, and Decision-Making under Uncertainty

Science.gov (United States)

Lopez, Israel; Sarigul-Klijn, Nesrin

Situational awareness and learning are necessary to identify and select the optimal set of mutually non-exclusive hypothesis in order to maximize mission performance and adapt system behavior accordingly. This paper presents a hierarchical and decentralized approach for integrated damage assessment and trajectory planning in aircraft with uncertain navigational decision-making. Aircraft navigation can be safely accomplished by properly addressing the following: decision-making, obstacle perception, aircraft state estimation, and aircraft control. When in-flight failures or damage occur, rapid and precise decision-making under imprecise information is required in order to regain and maintain control of the aircraft. To achieve planned aircraft trajectory and complete safe landing, the uncertainties in system dynamics of the damaged aircraft need to be learned and incorporated at the level of motion planning. The damaged aircraft is simulated via a simplified kinematic model. The different sources and perspectives of uncertainties in the damage assessment process and post-failure trajectory planning are presented and classified. The decision-making process for an emergency motion planning and landing is developed via the Dempster-Shafer evidence theory. The objective of the trajectory planning is to arrive at a target position while maximizing the safety of the aircraft given uncertain conditions. Simulations are presented for an emergency motion planning and landing that takes into account aircraft dynamics, path complexity, distance to landing site, runway characteristics, and subjective human decision.

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

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

Promoting Social and Emotional Competencies among Young Children in Croatia with Preschool PATHS.

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Josipa Mihic

2016-11-01

Full Text Available Preschool PATHS (Promoting Alternative Thinking Strategies is an evidence-based universal prevention program focused on promoting children’s social and emotional competencies and reducing the likelihood of behaviour problems and negative relationships with peers and teachers. This paper examines changes in the social and emotional competencies of the first children to participate in Preschool PATHS in Croatia. This study included 164 children, ages 3-6, in 12 preschool classrooms in three cities across Croatia, who participated in the classroom-based Preschool PATHS curriculum. At the beginning and end of the preschool year, teachers completed wellvalidated and reliable assessments of social and emotional competencies on each child. Hierarchical linear models revealed statistically significant and substantial improvements in prosocial behaviour, emotion regulation, emotion symptoms, peer problems, relational aggression, conduct problems, and hyperactive-impulsive behaviour. Study findings reveal significant changes in children’s social and emotional competencies during preschool. This time may present a unique opportunity to buttress children’s skills and improve long-term school success through the implementation of a rigorous empiricallyvalidated prevention program such as Preschool PATHS.

Survival of contact processes on the hierarchical group

Czech Academy of Sciences Publication Activity Database

Athreya, S.R.; Swart, Jan M.

2010-01-01

Roč. 147, č. 3 (2010), s. 529-563 ISSN 0178-8051 R&D Projects: GA ČR GA201/06/1323 Institutional research plan: CEZ:AV0Z10750506 Keywords : contact process * survival * hierarchical group * coupling * renormalization group Subject RIV: BA - General Mathematics Impact factor: 1.590, year: 2010 http://library.utia.cas.cz/separaty/2010/SI/swart-0342729.pdf

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

The conversion of spatial planning in Denmark

DEFF Research Database (Denmark)

Galland, Daniel

2014-01-01

Danish spatial planning has been increasingly subjected to significant structural, functional and conceptual reorientations over the past two decades. The comprehensive hierarchical framework wherein planning policies and practices used to operate became considerably modified after the implementa......Danish spatial planning has been increasingly subjected to significant structural, functional and conceptual reorientations over the past two decades. The comprehensive hierarchical framework wherein planning policies and practices used to operate became considerably modified after...... the implementation of a local government reform back in 2007. The reform abolished the county level, which implied the re-scaling of planning policies, functions and responsibilities to municipal and national levels. This situation brought about radical shifts concerning the implementation of land-use tasks...

Effect of hierarchical meso–macroporous alumina-supported copper catalyst for methanol synthesis from CO2 hydrogenation

International Nuclear Information System (INIS)

Witoon, Thongthai; Bumrungsalee, Sittisut; Chareonpanich, Metta; Limtrakul, Jumras

2015-01-01

Highlights: • CO 2 hydrogenation over Cu-loaded unimodal and hierarchical alumina catalysts. • Cu-loaded hierarchical catalyst exhibited higher methanol selectivity and stability. • The presence of macropores reduced the probability of side reaction. - Abstract: Effects of pore structures of alumina on the catalytic performance of copper catalysts for CO 2 hydrogenation were investigated. Copper-loaded hierarchical meso–macroporous alumina (Cu/HAl) catalyst exhibited no significant difference in terms of CO 2 conversion with copper-loaded unimodal mesoporous alumina (Cu/UAl) catalyst. However, the selectivity to methanol and dimethyl ether of the Cu/HAl catalyst was much higher than that of the Cu/UAl catalyst. This was attributed to the presence of macropores which diminished the occurrence of side reaction by the shortening the mesopores diffusion path length. The Cu/HAl catalyst also exhibited much higher stability than the Cu/UAl catalyst due to the fast diffusion of water out from the catalyst pellets, alleviating the oxidation of metallic copper to CuO

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.

A Hierarchical Reliability Control Method for a Space Manipulator Based on the Strategy of Autonomous Decision-Making

Directory of Open Access Journals (Sweden)

Xin Gao

2016-01-01

Full Text Available In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on this, a multivariable and multiconstraint optimization model is constructed. Second, a hierarchical system control model which incorporates the operational reliability factors is constructed. The control process of the space manipulator is divided into three layers: task planning, path planning, and motion control. Operational reliability related performance parameters are measured and used as the system’s feedback. Taking the factors affecting the operational reliability into consideration, the system can autonomously decide which control layer of the system should be optimized and how to optimize it using a control level adjustment decision module. The operational reliability factors affect these three control levels in the form of control variable constraints. Simulation results demonstrate that the proposed method can achieve a greater probability of meeting the task accuracy requirements, while extending the expected lifetime of the space manipulator.

Fabrication of hierarchical porous N-doping carbon membrane by using ;confined nanospace deposition; method for supercapacitor

Science.gov (United States)

Wang, Guoxu; Liu, Meng; Du, Juan; Liu, Lei; Yu, Yifeng; Sha, Jitong; Chen, Aibing

2018-03-01

The membrane carbon materials with hierarchical porous architecture are attractive because they can provide more channels for ion transport and shorten the ions transport path. Herein, we develop a facile way based on "confined nanospace deposition" to fabricate N-dopi-ng three dimensional hierarchical porous membrane carbon material (N-THPMC) via coating the nickel nitrate, silicate oligomers and triblock copolymer P123 on the branches of commercial polyamide membrane (PAM). During high temperature treatment, the mesoporous silica layer and Ni species serve as a "confined nanospace" and catalyst respectively, which are indispensable elements for formation of carbon framework, and the gas-phase carbon precursors which derive from the decomposition of PAM are deposited into the "confined nanospace" forming carbon framework. The N-THPMC with hierarchical macro/meso/microporous structure, N-doping (2.9%) and large specific surface area (994m2 g-1) well inherits the membrane morphology and hierarchical porous structure of PAM. The N-THPMC as electrode without binder exhibits a specific capacitance of 252 F g-1 at the current density of 1 A g-1 in 6 M KOH electrolyte and excellent cycling stability of 92.7% even after 5000 cycles.

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.

In-situ preparation of Fe2O3 hierarchical arrays on stainless steel substrate for high efficient catalysis

International Nuclear Information System (INIS)

Yang, Zeheng; Wang, Kun; Shao, Zongming; Tian, Yuan; Chen, Gongde; Wang, Kai; Chen, Zhangxian; Dou, Yan; Zhang, Weixin

2017-01-01

Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe 2 O 3 hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N 2 atmosphere. As a Fenton-like catalyst, Fe 2 O 3 hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . The Fe 2 O 3 catalyst with unique hierarchical structures and efficient transport channels, effectively activates H 2 O 2 to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe 2 O 3 hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . - Highlights: • Fe 2 O 3 hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F − ions play an important role in the formation of the Fe 2 O 3 hierarchical arrays. • Fe 2 O 3 hierarchical arrays show high catalytic activity to methylene blue degradation.

Path Models of Vocal Emotion Communication.

Directory of Open Access Journals (Sweden)

Tanja Bänziger

Full Text Available We propose to use a comprehensive path model of vocal emotion communication, encompassing encoding, transmission, and decoding processes, to empirically model data sets on emotion expression and recognition. The utility of the approach is demonstrated for two data sets from two different cultures and languages, based on corpora of vocal emotion enactment by professional actors and emotion inference by naïve listeners. Lens model equations, hierarchical regression, and multivariate path analysis are used to compare the relative contributions of objectively measured acoustic cues in the enacted expressions and subjective voice cues as perceived by listeners to the variance in emotion inference from vocal expressions for four emotion families (fear, anger, happiness, and sadness. While the results confirm the central role of arousal in vocal emotion communication, the utility of applying an extended path modeling framework is demonstrated by the identification of unique combinations of distal cues and proximal percepts carrying information about specific emotion families, independent of arousal. The statistical models generated show that more sophisticated acoustic parameters need to be developed to explain the distal underpinnings of subjective voice quality percepts that account for much of the variance in emotion inference, in particular voice instability and roughness. The general approach advocated here, as well as the specific results, open up new research strategies for work in psychology (specifically emotion and social perception research and engineering and computer science (specifically research and development in the domain of affective computing, particularly on automatic emotion detection and synthetic emotion expression in avatars.

Enhanced supercapacitor performance using hierarchical TiO2 nanorod/Co(OH)2 nanowall array electrodes

International Nuclear Information System (INIS)

Ramadoss, Ananthakumar; Kim, Sang Jae

2014-01-01

Graphical abstract: - Highlights: • TiO 2 /Co(OH) 2 hierarchical nanostructure was prepared by a combination of hydrothermal and cathodic electrodeposition method. • Hierarchical nanostructure electrode exhibited a maximum capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . • Combination of Co(OH) 2 nanowall with TiO 2 NR into a single system enhanced the electrochemical behavior of supercapacitor electrode. - Abstract: We report novel hierarchical TiO 2 nanorod (NR)/porous Co(OH) 2 nanowall array electrodes for high-performance supercapacitors fabricated using a two-step process that involves hydrothermal and electrodeposition techniques. Field-emission scanning electron microscope images reveal a bilayer structure consisting of TiO 2 NR arrays with porous Co(OH) 2 nanowalls. Compared with the bare TiO 2 NRs, the hierarchical TiO 2 NRs/Co(OH) 2 electrodes showed improved pseudocapacitive performance in a 2-M KOH electrolyte solution, exhibiting an areal specific capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . The electrodes exhibited good stability, retaining 82.5% of the initial capacitance after 4000 cycles. The good pseudocapacitive performance of the hierarchical nanostructures is mainly due to the porous structure, which provides fast ion and electron transfer, a large surface area, short ion diffusion paths, and a favourable volume change during the cycling process

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.

Effects of action planning and coping planning within the theory of planned behaviour

DEFF Research Database (Denmark)

Pakpour, Amir H.; Zedi, Isa mohammadi; Chatzisarantis, Nikos

2011-01-01

Objective: Patients on dialysis have low physical activity levels. The aim of the study was to examine the validity of action planning and coping planning within the theory of planned behaviour framework, for predicting physical activity behaviour of patients on hemodialysis. Methods: One hundred...... and forty four patients who were undergoing emodialysis were selected from dialysis centers. The mean age of the patients was 56.61 (SD= 11.38) years. The patients completed a questionnaire including variables from the theory of planned behaviour, action planning and coping planning. Physical activity...... was prospectively assessed at 4-weeks with the validated International Physical Activity Questionnaire self-report measure. A hierarchical regression analysis was performed to examine the effects of action planning and coping planning on physical activity behaviour. Results: There was a main effect for coping...

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.

A Hierarchical Multiple-Level Approach to the Assessment of Interpersonal Relatedness and Self-Definition: Implications for Research, Clinical Practice, and DSM Planning.

Science.gov (United States)

Luyten, Patrick; Blatt, Sidney J

2016-01-01

Extant research suggests there is considerable overlap between so-called 2-polarities models of personality development; that is, models that propose that personality development evolves through a dialectic synergistic interaction between 2 key developmental tasks across the life span-the development of self-definition on the one hand and of relatedness on the other. These models have attracted considerable research attention and play a central role in DSM planning. This article provides a researcher- and clinician-friendly guide to the assessment of these personality theories. We argue that current theoretical models focus on issues of relatedness and self-definition at different hierarchically organized levels of analysis; that is (a) at the level of broad personality features, (b) at the motivational level (i.e., the motivational processes underlying the development of these dimensions), and (c) at the level of underlying internal working models or cognitive affective schemas, and the specific interpersonal features and problems in which they are expressed. Implications for further research and DSM planning are outlined.

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.

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.

Facile synthesis of three dimensional hierarchical Co-Al layered double hydroxides on graphene as high-performance materials for supercapacitor electrode.

Science.gov (United States)

Hao, Jinhui; Yang, Wenshu; Zhang, Zhe; Lu, Baoping; Ke, Xi; Zhang, Bailin; Tang, Jilin

2014-07-15

A facile simple hydrothermal method combined with a post-solution reaction is developed to grow interconnected three dimensional (3D) hierarchical Co-Al layered double hydroxides (LDHs) on reduced graphene oxide (rGO). The obtained 3D hierarchical rGO-LDHs are characterized by field emission scanning electron microscopy, X-ray diffraction, and X-ray photo-electron spectroscopy. As LDHs nanosheets directly grow on the surface of rGO via chemical covalent bonding, the rGO could provide facile electron transport paths in the electrode for the fast Faradaic reaction. Moreover, benefiting from the rational 3D hierarchical structural, the rGO-LDHs demonstrate excellent electrochemical properties with a combination of high charge storage capacitance, fast rate capability and stable cycling performance. Remarkably, the 3D hierarchical rGO-LDHs exhibit specific capacitance values of 599 F g(-1) at a constant current density of 4 A g(-1). The rGO-LDHs also show high charge-discharge reversibility with an efficiency of 92.4% after 5000 cycles. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

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.

Hierarchical Network Design

DEFF Research Database (Denmark)

Thomadsen, Tommy

2005-01-01

Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

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.

A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

Directory of Open Access Journals (Sweden)

Nabil Sabor

2017-01-01

Full Text Available Introducing mobility to Wireless Sensor Networks (WSNs puts new challenges particularly in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink node in the network. Many routing protocols have been developed to support the mobility of WSNs. These protocols are divided depending on the routing structure into hierarchical-based, flat-based, and location-based routing protocols. However, the hierarchical-based routing protocols outperform the other routing types in saving energy, scalability, and extending lifetime of Mobile WSNs (MWSNs. Selecting an appropriate hierarchical routing protocol for specific applications is an important and difficult task. Therefore, this paper focuses on reviewing some of the recently hierarchical-based routing protocols that are developed in the last five years for MWSNs. This survey divides the hierarchical-based routing protocols into two broad groups, namely, classical-based and optimized-based routing protocols. Also, we present a detailed classification of the reviewed protocols according to the routing approach, control manner, mobile element, mobility pattern, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated in this survey depending on delay, network size, energy-efficiency, and scalability while mentioning the advantages and drawbacks of each protocol. Finally, we summarize and conclude the paper with future directions.

Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

Energy Technology Data Exchange (ETDEWEB)

Nash, Stephen G.

2013-11-11

The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

Path Complexity in Virtual Water Maze Navigation: Differential Associations with Age, Sex, and Regional Brain Volume.

Science.gov (United States)

Daugherty, Ana M; Yuan, Peng; Dahle, Cheryl L; Bender, Andrew R; Yang, Yiqin; Raz, Naftali

2015-09-01

Studies of human navigation in virtual maze environments have consistently linked advanced age with greater distance traveled between the start and the goal and longer duration of the search. Observations of search path geometry suggest that routes taken by older adults may be unnecessarily complex and that excessive path complexity may be an indicator of cognitive difficulties experienced by older navigators. In a sample of healthy adults, we quantify search path complexity in a virtual Morris water maze with a novel method based on fractal dimensionality. In a two-level hierarchical linear model, we estimated improvement in navigation performance across trials by a decline in route length, shortening of search time, and reduction in fractal dimensionality of the path. While replicating commonly reported age and sex differences in time and distance indices, a reduction in fractal dimension of the path accounted for improvement across trials, independent of age or sex. The volumes of brain regions associated with the establishment of cognitive maps (parahippocampal gyrus and hippocampus) were related to path dimensionality, but not to the total distance and time. Thus, fractal dimensionality of a navigational path may present a useful complementary method of quantifying performance in navigation. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Detecting Hierarchical Structure in Networks

DEFF Research Database (Denmark)

Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

2012-01-01

Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

In-situ preparation of Fe{sub 2}O{sub 3} hierarchical arrays on stainless steel substrate for high efficient catalysis

Energy Technology Data Exchange (ETDEWEB)

Yang, Zeheng, E-mail: zehengyang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Wang, Kun; Shao, Zongming; Tian, Yuan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Chen, Gongde [Department of Chemical and Environmental Engineering, University of California at Riverside, Riverside, CA 92521 (United States); Wang, Kai; Chen, Zhangxian; Dou, Yan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Zhang, Weixin, E-mail: wxzhang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China)

2017-02-15

Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe{sub 2}O{sub 3} hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N{sub 2} atmosphere. As a Fenton-like catalyst, Fe{sub 2}O{sub 3} hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. The Fe{sub 2}O{sub 3} catalyst with unique hierarchical structures and efficient transport channels, effectively activates H{sub 2}O{sub 2} to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe{sub 2}O{sub 3} hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. - Highlights: • Fe{sub 2}O{sub 3} hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F{sup −} ions play an important role in the formation of the Fe{sub 2}O{sub 3} hierarchical arrays. • Fe{sub 2}O{sub 3} hierarchical arrays show high catalytic activity to methylene blue degradation.

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.

Electrochemical design of ZnO hierarchical structures for dye-sensitized solar cells

Czech Academy of Sciences Publication Activity Database

Guerin, V. M.; Rathouský, Jiří; Pauporté, T.

2012-01-01

Roč. 102, JUL 2012 (2012), s. 8-14 ISSN 0927-0248 R&D Projects: GA AV ČR KAN100400702 Institutional research plan: CEZ:AV0Z40400503 Keywords : ZnO hierarchical structures * epitaxy * dye-sensitized solar cell Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.630, year: 2012

Functional annotation of hierarchical modularity.

Directory of Open Access Journals (Sweden)

Kanchana Padmanabhan

Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

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.

Trajectory optimization of multiple quad-rotor UAVs in collaborative assembling task

Directory of Open Access Journals (Sweden)

Chen Yongbo

2016-02-01

Full Text Available A hierarchic optimization strategy based on the offline path planning process and online trajectory planning process is presented to solve the trajectory optimization problem of multiple quad-rotor unmanned aerial vehicles in the collaborative assembling task. Firstly, the path planning process is solved by a novel parallel intelligent optimization algorithm, the central force optimization-genetic algorithm (CFO-GA, which combines the central force optimization (CFO algorithm with the genetic algorithm (GA. Because of the immaturity of the CFO, the convergence analysis of the CFO is completed by the stability theory of the linear time-variant discrete-time systems. The results show that the parallel CFO-GA algorithm converges faster than the parallel CFO and the central force optimization-sequential quadratic programming (CFO-SQP algorithm. Then, the trajectory planning problem is established based on the path planning results. In order to limit the range of the attitude angle and guarantee the flight stability, the optimized object is changed from the ordinary six-degree-of-freedom rigid-body dynamic model to the dynamic model with an inner-loop attitude controller. The results show that the trajectory planning process can be solved by the mature SQP algorithm easily. Finally, the discussion and analysis of the real-time performance of the hierarchic optimization strategy are presented around the group number of the waypoints and the equal interval time.

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.

Co3O4 based non-enzymatic glucose sensor with high sensitivity and reliable stability derived from hollow hierarchical architecture

Science.gov (United States)

Tian, Liangliang; He, Gege; Cai, Yanhua; Wu, Shenping; Su, Yongyao; Yan, Hengqing; Yang, Cong; Chen, Yanling; Li, Lu

2018-02-01

Inspired by kinetics, the design of hollow hierarchical electrocatalysts through large-scale integration of building blocks is recognized as an effective approach to the achievement of superior electrocatalytic performance. In this work, a hollow, hierarchical Co3O4 architecture (Co3O4 HHA) was constructed using a coordinated etching and precipitation (CEP) method followed by calcination. The resulting Co3O4 HHA electrode exhibited excellent electrocatalytic activity in terms of high sensitivity (839.3 μA mM-1 cm-2) and reliable stability in glucose detection. The high sensitivity could be attributed to the large specific surface area (SSA), ample unimpeded penetration diffusion paths and high electron transfer rate originating from the unique two-dimensional (2D) sheet-like character and hollow porous architecture. The hollow hierarchical structure also affords sufficient interspace for accommodation of volume change and structural strain, resulting in enhanced stability. The results indicate that Co3O4 HHA could have potential for application in the design of non-enzymatic glucose sensors, and that the construction of hollow hierarchical architecture provides an efficient way to design highly active, stable electrocatalysts.

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.

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

Directory of Open Access Journals (Sweden)

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.

Catalysis with hierarchical zeolites

DEFF Research Database (Denmark)

Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

2011-01-01

Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

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...

Parallel hierarchical radiosity rendering

Energy Technology Data Exchange (ETDEWEB)

Carter, Michael [Iowa State Univ., Ames, IA (United States)

1993-07-01

In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

A new approach to calculate charge carrier transport mobility in organic molecular crystals from imaginary time path integral simulations

International Nuclear Information System (INIS)

Song, Linze; Shi, Qiang

2015-01-01

We present a new non-perturbative method to calculate the charge carrier mobility using the imaginary time path integral approach, which is based on the Kubo formula for the conductivity, and a saddle point approximation to perform the analytic continuation. The new method is first tested using a benchmark calculation from the numerical exact hierarchical equations of motion method. Imaginary time path integral Monte Carlo simulations are then performed to explore the temperature dependence of charge carrier delocalization and mobility in organic molecular crystals (OMCs) within the Holstein and Holstein-Peierls models. The effects of nonlocal electron-phonon interaction on mobility in different charge transport regimes are also investigated

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

Science.gov (United States)

Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

2017-07-01

Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

Micromechanics of hierarchical materials

DEFF Research Database (Denmark)

Mishnaevsky, Leon, Jr.

2012-01-01

A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

How hierarchical is language use?

Science.gov (United States)

Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

2012-01-01

It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

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.

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.”.

Ontological Planning

Directory of Open Access Journals (Sweden)

Ahmet Alkan

2017-12-01

• Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

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.

Determinants of falls in community-dwelling elderly: hierarchical analysis.

Science.gov (United States)

Brito, Thais Alves; Coqueiro, Raildo da Silva; Fernandes, Marcos Henrique; de Jesus, Cleber Souza

2014-01-01

To analyze the fall-related factors in community-dwelling elderly. Epidemiologic cross-sectional population-based household study with hierarchical interrelationships among the potential risk factors. The sample was made up of noninstitutionalized individuals over age 60, who were resident of a city in Brazil's Northeast Region. The dependent variable was fall occurrence in the last 12 months; independent variables were sociodemographic, behavioral, health, and functional status factors. Multivariate hierarchical Poisson regression analysis was used based on a proposed theoretic model. Three hundred and sixteen (89.0%) elderly participated of the survey, average age 74.2 years; the majority was female, with limited literacy and had low-medium family income. The fall prevalence was of 25.8%; occurrence was related to depression symptoms (PR = 1.55) and balance limitation (PR = 1.56). The high fall prevalence among elderly necessitates the identification of fall-related factors for action planning prevention programs with this group. © 2014 Wiley Periodicals, Inc.

Hierarchical architecture of active knits

International Nuclear Information System (INIS)

Abel, Julianna; Luntz, Jonathan; Brei, Diann

2013-01-01

Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm. (paper)

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...

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius

2017-07-03

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

2017-01-01

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

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...

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.

Settlement Networks in Polish Spatial Development Regional Plans

Science.gov (United States)

Sołtys, Jacek

2017-10-01

In 1999, ten years after the great political changes in Poland, 16 self-governed regions (in Polish: voivodeship) were created. According to Polish law, voivodeship spatial development plans, or regional plans in short, determine basic elements of the settlement network. No detailed regulations indicate the specific elements of the settlement network or what features of these elements should be determined. For this reason, centres as elements of the settlement network are variously named in different regions and take the form of various models. The purposes of the research described in this article are: (1) recognition and systematization of settlement network models determined in regional plans; and (2) assessment of the readability of determination in planning and its usefulness in the practice of regional policy. Six models of settlement networks in regional plans have been identified and classified into types and sub-types. Names of specific levels of centres indicate that they were classified according to two criteria: (1) level of services, which concerns only 5 voivodships; and (2) importance in development, which concerns the 11 other voivodships. The hierarchical model referring to the importance of development is less understandable than the one related to services. In the text of most plans, centres of services and centres of development are treated independently from their names. In some plans the functional types of towns and cities are indicated. In some voivodships, specifications in the plan text are too general and seem to be rather useless in the practice of regional policy. The author suggests that regional plans should determine two kinds of centres: hierarchical service centres and non-hierarchical centres of development. These centres should be further distinguished according to: (1) their role in the activation of surroundings; (2) their level of development and the necessity of action for their development; and (3) the types of actions

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.

Class hierarchical test case generation algorithm based on expanded EMDPN model

Institute of Scientific and Technical Information of China (English)

LI Jun-yi; GONG Hong-fang; HU Ji-ping; ZOU Bei-ji; SUN Jia-guang

2006-01-01

A new model of event and message driven Petri network(EMDPN) based on the characteristic of class interaction for messages passing between two objects was extended. Using EMDPN interaction graph, a class hierarchical test-case generation algorithm with cooperated paths (copaths) was proposed, which can be used to solve the problems resulting from the class inheritance mechanism encountered in object-oriented software testing such as oracle, message transfer errors, and unreachable statement. Finally, the testing sufficiency was analyzed with the ordered sequence testing criterion(OSC). The results indicate that the test cases stemmed from newly proposed automatic algorithm of copaths generation satisfies synchronization message sequences testing criteria, therefore the proposed new algorithm of copaths generation has a good coverage rate.

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

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....

Quivers of Bound Path Algebras and Bound Path Coalgebras

Directory of Open Access Journals (Sweden)

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.

Operational workforce planning for check-in counters at airports

DEFF Research Database (Denmark)

Stolletz, Raik

2010-01-01

This paper addresses operation models for workforce planning for check-in systems at airports. We characterize different tasks of the hierarchical workforce planning problem with time-dependent demand. A binary linear programming formulation is developed for the fortnightly tour scheduling problem...

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.

Operating Theatre Planning and Scheduling.

NARCIS (Netherlands)

Hans, Elias W.; Vanberkel, P.T.; Hall, R.

2012-01-01

In this chapter we present a number of approaches to operating theatre planning and scheduling. We organize these approaches hierarchically which serves to illustrate the breadth of problems confronted by researchers. At each hierarchicalplanning level we describe common problems, solution

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

Science.gov (United States)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

An adaptive dual-optimal path-planning technique for unmanned air vehicles with application to solar-regenerative high altitude long endurance flight

Science.gov (United States)

Whitfield, Clifford A.

2009-12-01

A multi-objective technique for Unmanned Air Vehicle (UAV) path and trajectory autonomy generation, through task allocation and sensor fusion has been developed. The Dual-Optimal Path-Planning (D-O.P-P.) Technique generates on-line adaptive flight paths for UAVs based on available flight windows and environmental influenced objectives. The environmental influenced optimal condition, known as the driver' determines the condition, within a downstream virtual window of possible vehicle destinations and orientation built from the UAV kinematics. The intermittent results are pursued by a dynamic optimization technique to determine the flight path. This sequential optimization technique is a multi-objective optimization procedure consisting of two goals, without requiring additional information to combine the conflicting objectives into a single-objective. An example case-study and additional applications are developed and the results are discussed; including the application to the field of Solar Regenerative (SR) High Altitude Long Endurance (HALE) UAV flight. Harnessing solar energy has recently been adapted for use on high altitude UAV platforms. An aircraft that uses solar panels and powered by the sun during the day and through the night by SR systems, in principle could sustain flight for weeks or months. The requirements and limitations of solar powered flight were determined. The SR-HALE UAV platform geometry and flight characteristics were selected from an existing aircraft that has demonstrated the capability for sustained flight through flight tests. The goals were to maintain continual Situational Awareness (SA) over a case-study selected Area of Interest (AOI) and existing UAV power and surveillance systems. This was done for still wind and constant wind conditions at altitude along with variations in latitude. The characteristics of solar flux and the dependence on the surface location and orientation were established along with fixed flight maneuvers for

Hierarchical evolution and thermal stability of microstructure with deformation twins in 316 stainless steel

Energy Technology Data Exchange (ETDEWEB)

Wang, S.J. [Department of Materials Science and Engineering, Texas A& M University, College Station, TX 77843 (United States); Jozaghi, T. [Department of Mechanical Engineering, Texas A& M University, College Station, TX 77843 (United States); Karaman, I., E-mail: ikaraman@tamu.edu [Department of Materials Science and Engineering, Texas A& M University, College Station, TX 77843 (United States); Department of Mechanical Engineering, Texas A& M University, College Station, TX 77843 (United States); Arroyave, R. [Department of Materials Science and Engineering, Texas A& M University, College Station, TX 77843 (United States); Department of Mechanical Engineering, Texas A& M University, College Station, TX 77843 (United States); Chumlyakov, Y.I. [Siberian Physical Technical Institute, Tomsk State University, Tomsk 634050 (Russian Federation)

2017-05-10

We report extensive nano-twin formation in 316 stainless steel (SS) and the evolution of a hierarchical microstructure through the formation of multi-scale twin bundles after uniaxial tension with uniform elongation levels of 20%, 30%, and 40%. Multiscale characterization techniques were employed to reveal the nature of these twins. The twin density increases with the increasing strain level, however, the twin width remains the same, notably reducing the mean free path of dislocations. Concurrently, significant work hardening is observed during subsequent deformation. The deformation-induced nano-twins are thermally stable up to ~800 °C, shown by both interrupted and in-situ transmission electron microscopy experiments, above which the recrystallization takes place in the vicinity of the twins. Such favorable thermal stability of the twins in nano-twin strengthened 316 SS offers a promising approach for microstructurally engineering these materials for potential applications at elevated temperatures. The related strengthening mechanisms are discussed in the light of the mean free path of dislocations and the dislocation interactions with twin boundaries.

Neutrosophic Hierarchical Clustering Algoritms

Directory of Open Access Journals (Sweden)

Rıdvan Şahin

2014-03-01

Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

Feynman's path integrals and Bohm's particle paths

International Nuclear Information System (INIS)

Tumulka, Roderich

2005-01-01

Both Bohmian mechanics, a version of quantum mechanics with trajectories, and Feynman's path integral formalism have something to do with particle paths in space and time. The question thus arises how the two ideas relate to each other. In short, the answer is, path integrals provide a re-formulation of Schroedinger's equation, which is half of the defining equations of Bohmian mechanics. I try to give a clear and concise description of the various aspects of the situation. (letters and comments)

The Hierarchical Perspective

Directory of Open Access Journals (Sweden)

Daniel Sofron

2015-05-01

Full Text Available This paper is focused on the hierarchical perspective, one of the methods for representing space that was used before the discovery of the Renaissance linear perspective. The hierarchical perspective has a more or less pronounced scientific character and its study offers us a clear image of the way the representatives of the cultures that developed it used to perceive the sensitive reality. This type of perspective is an original method of representing three-dimensional space on a flat surface, which characterises the art of Ancient Egypt and much of the art of the Middle Ages, being identified in the Eastern European Byzantine art, as well as in the Western European Pre-Romanesque and Romanesque art. At the same time, the hierarchical perspective is also present in naive painting and infantile drawing. Reminiscences of this method can be recognised also in the works of some precursors of the Italian Renaissance. The hierarchical perspective can be viewed as a subjective ranking criterion, according to which the elements are visually represented by taking into account their relevance within the image while perception is ignored. This paper aims to show how the main objective of the artists of those times was not to faithfully represent the objective reality, but rather to emphasize the essence of the world and its perennial aspects. This may represent a possible explanation for the refusal of perspective in the Egyptian, Romanesque and Byzantine painting, characterised by a marked two-dimensionality.

Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

Directory of Open Access Journals (Sweden)

Bin Ahmad Fawzan Mohammed Ridha

2018-01-01

Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

An Approximation Approach for Solving the Subpath Planning Problem

OpenAIRE

Safilian, Masoud; Tashakkori, S. Mehdi; Eghbali, Sepehr; Safilian, Aliakbar

2016-01-01

The subpath planning problem is a branch of the path planning problem, which has widespread applications in automated manufacturing process as well as vehicle and robot navigation. This problem is to find the shortest path or tour subject for travelling a set of given subpaths. The current approaches for dealing with the subpath planning problem are all based on meta-heuristic approaches. It is well-known that meta-heuristic based approaches have several deficiencies. To address them, we prop...

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.

Multi-Dimensional Path Queries

DEFF Research Database (Denmark)

Bækgaard, Lars

1998-01-01

to create nested path structures. We present an SQL-like query language that is based on path expressions and we show how to use it to express multi-dimensional path queries that are suited for advanced data analysis in decision support environments like data warehousing environments......We present the path-relationship model that supports multi-dimensional data modeling and querying. A path-relationship database is composed of sets of paths and sets of relationships. A path is a sequence of related elements (atoms, paths, and sets of paths). A relationship is a binary path...

The Mission Operations Planning Assistant

Science.gov (United States)

Schuetzle, James G.

1987-01-01

The Mission Operations Planning Assistant (MOPA) is a knowledge-based system developed to support the planning and scheduling of instrument activities on the Upper Atmospheric Research Satellite (UARS). The MOPA system represents and maintains instrument plans at two levels of abstraction in order to keep plans comprehensible to both UARS Principal Investigators and Command Management personnel. The hierarchical representation of plans also allows MOPA to automatically create detailed instrument activity plans from which spacecraft command loads may be generated. The MOPA system was developed on a Symbolics 3640 computer using the ZetaLisp and ART languages. MOPA's features include a textual and graphical interface for plan inspection and modification, recognition of instrument operational constraint violations during the planning process, and consistency maintenance between the different planning levels. This paper describes the current MOPA system.

Polygonal-path approximations on the path spaces of quantum-mechanical systems: properties of the polygonal paths

International Nuclear Information System (INIS)

Exner, P.; Kolerov, G.I.

1981-01-01

Properties of the subset of polygonal paths in the Hilbert space H of paths referring to a d-dimensional quantum-mechanical system are examined. Using the reproduction kernel technique we prove that each element of H is approximated by polygonal paths uniformly with respect to the ''norm'' of time-interval partitions. This result will be applied in the second part of the present paper to prove consistency of the uniform polygonal-path extension of the Feynman maps [ru

Adaptive hierarchical multi-agent organizations

NARCIS (Netherlands)

Ghijsen, M.; Jansweijer, W.N.H.; Wielinga, B.J.; Babuška, R.; Groen, F.C.A.

2010-01-01

In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the

Planning applications in image analysis

Science.gov (United States)

Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

1994-01-01

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

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.

Hierarchical video summarization

Science.gov (United States)

Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

1998-12-01

We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

LANDSCAPE PLANNING IN UKRAINE: THE FIRST LANDSCAPE-PLANNING PROGRAM

Directory of Open Access Journals (Sweden)

Leonid Rudenko

2013-01-01

Full Text Available The paper presents the results of the first, in Ukraine; project on landscape planning widely accepted in European countries. Under the project implemented in 2010–2013, a landscape-planning program has been developed for the Cherkassy oblast. This is the first document of this kind in Ukraine. The program is mainly based on the experience of the German and Russian schools of landscape planning and on research and assessment conducted by the authors, which allowed identifying approaches to landscape planning, principles of the national policy, and characteristics and potential of environmentally friendly planning in Ukraine. The paper discusses the main phases of the work on the development of the landscape program for the oblast. It also identifies the main stages and key concepts and principles of landscape planning. The paper presents the results of integrated research on the identification and classification of conflicts in land use and the integral concept of the developmental goals for the oblast. The results can be the foundation for adopting management decisions and development of action plans for the lower hierarchal branches.

Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

Science.gov (United States)

2016-10-04

5], [6], [7], but the formulations have been limited to restricted cases, such as a single object or a constrained action space. Little attention has...solution paths. Object parts are shown in the coloured point clouds. Viewpoint regions are coloured black (low reward), orange (medium) and yellow (high

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.

Acidic and catalytic properties of hierarchical zeolites and hybrid ordered mesoporous materials assembled from MFI protozeolitic units

Czech Academy of Sciences Publication Activity Database

Serrano, D. P.; García, R. A.; Vicente, G.; Linares, M.; Vitvarová, Dana; Čejka, Jiří

2011-01-01

Roč. 279, č. 2 (2011), s. 366-380 ISSN 0021-9517 Institutional research plan: CEZ:AV0Z40400503 Keywords : hierarchical zeolites * hybrid zeolitic-mesostructured materials * Bronsted and Lewis acid centres Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 6.002, year: 2011

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.

Plans to Observe the 2017 Total Solar Eclipse from near the Path Edges

Science.gov (United States)

Waring Dunham, David; Nugent, Richard; Guhl, Konrad; Bode, Hans-Joachim

2015-08-01

The August 21st, 2017 solar eclipse provides a good opportunity, to time the totality contacts, other Baily’s bead phenomena, and observe other dynamic edge phenomena, from locations near the edges of the path of totality. A good network of roads and generally favorable weather prospects means that more observers will likely be able to deploy more equipment than during most previous eclipses. The value of contact and Baily’s bead timings of total solar eclipses, for determining solar diameter and intensity variations, was described in an earlier presentation in Focus Meeting 13. This presentation will concentrate on how observations of different types that have been used during past eclipses can be made by different observers, to obtain better information about the accuracy of the different types of observations for determining the mean solar diameter, and the systematic differences between them. A problem has been that the few observers who have attempted recording Baily’s beads from path edge locations have wanted to use the latest technology, to try to record the observations better, rather than try to make the observations in the same ways that were used for many past eclipses. Several observers trying different techniques at the same location, and doing that at several locations at different places along the path, is needed. Past techniques that we would like to compare include direct visual observation (but keeping eye safety in mind); visual observation of telescopically projected images; direct filtered video telescopic observations; and recording the flash spectrum. There are several towns that straddle the path edges. The International Occultation Timing Association would like to mobilize people in those towns to observe the eclipse from many places, to say whether or not the eclipse happened, and if it did, time it. A suitable cell phone app could be designed to report observations, including the observer’s location, as was attempted for an

Relações hierárquicas entre os traços amplos do Big Five Hierarchical relationship between the broad traits of the Big Five

Directory of Open Access Journals (Sweden)

Cristiano Mauro Assis Gomes

2012-01-01

Full Text Available O modelo Big Five sustenta que a personalidade humana é composta por dezenas de fatores específicos. Apesar dessa diversidade, esses fatores confluem para cinco traços amplos que estão em um mesmo nível de hierarquia. O presente estudo apresenta uma hipótese alternativa, postulando níveis entre os traços amplos do modelo. Fizeram parte do estudo 684 estudantes do ensino fundamental e médio de uma escola particular de Belo Horizonte, MG, com idades entre 10 e 18 anos (m = 13,71 e DP= 2,11. Para medir os fatores do Big Five foi utilizado o Inventário de Características de Personalidade, anteriormente chamado de Inventário dos Adjetivos de Personalidade, de Pinheiro, Gomes e Braga (2009. O instrumento mensura oito polaridades das 10 polaridades presentes nos cinco traços amplos do Big Five. Dois modelos foram comparados via método path analysis: um modelo de quatro níveis hierárquicos e um modelo não hierárquico. O modelo hierárquico apresentou adequado grau de ajuste aos dados e mostrou-se superior ao modelo não hierárquico, que não se ajusta aos dados. Implicações são discutidas para o modelo Big Five.The Big Five model sustains that human personality is composed by dozens of specific factors. Despite of diversity, specific factors are integrated in five broad traits that are in the same hierarchical level. The current study presents an alternative hypothesis arguing that there are hierarchical levels between the broad traits of the model. Six hundred and eighty-four junior and high school level students from 10 to 18 years old (M = 13.71 and SD= 2.11 of a private school in the city of Belo Horizonte, Minas Gerais, Brazil participated in the study. The Big Five was measured by an Inventory of Personality Traits, initially named as Personality Adjective Inventory, elaborated by Pinheiro, Gomes and Braga (2009. This instrument measures eight polarities of the ten presented in the Big Five Model. Two models were compared

Synergy of multi-scale toughening and protective mechanisms at hierarchical branch-stem interfaces

Science.gov (United States)

Müller, Ulrich; Gindl-Altmutter, Wolfgang; Konnerth, Johannes; Maier, Günther A.; Keckes, Jozef

2015-09-01

Biological materials possess a variety of artful interfaces whose size and properties are adapted to their hierarchical levels and functional requirements. Bone, nacre, and wood exhibit an impressive fracture resistance based mainly on small crystallite size, interface organic adhesives and hierarchical microstructure. Currently, little is known about mechanical concepts in macroscopic biological interfaces like the branch-stem junction with estimated 1014 instances on earth and sizes up to few meters. Here we demonstrate that the crack growth in the upper region of the branch-stem interface of conifer trees proceeds along a narrow predefined region of transversally loaded tracheids, denoted as sacrificial tissue, which fail upon critical bending moments on the branch. The specific arrangement of the tracheids allows disconnecting the overloaded branch from the stem in a controlled way by maintaining the stem integrity. The interface microstructure based on the sharply adjusted cell orientation and cell helical angle secures a zig-zag crack propagation path, mechanical interlock closing after the bending moment is removed, crack gap bridging and self-repairing by resin deposition. The multi-scale synergetic concepts allows for a controllable crack growth between stiff stem and flexible branch, as well as mechanical tree integrity, intact physiological functions and recovery after the cracking.

Pulled Motzkin paths

International Nuclear Information System (INIS)

Janse van Rensburg, E J

2010-01-01

In this paper the models of pulled Dyck paths in Janse van Rensburg (2010 J. Phys. A: Math. Theor. 43 215001) are generalized to pulled Motzkin path models. The generating functions of pulled Motzkin paths are determined in terms of series over trinomial coefficients and the elastic response of a Motzkin path pulled at its endpoint (see Orlandini and Whittington (2004 J. Phys. A: Math. Gen. 37 5305-14)) is shown to be R(f) = 0 for forces pushing the endpoint toward the adsorbing line and R(f) = f(1 + 2cosh f))/(2sinh f) → f as f → ∞, for forces pulling the path away from the X-axis. In addition, the elastic response of a Motzkin path pulled at its midpoint is shown to be R(f) = 0 for forces pushing the midpoint toward the adsorbing line and R(f) = f(1 + 2cosh (f/2))/sinh (f/2) → 2f as f → ∞, for forces pulling the path away from the X-axis. Formal combinatorial identities arising from pulled Motzkin path models are also presented. These identities are the generalization of combinatorial identities obtained in directed paths models to their natural trinomial counterparts.

Pulled Motzkin paths

Energy Technology Data Exchange (ETDEWEB)

Janse van Rensburg, E J, E-mail: rensburg@yorku.c [Department of Mathematics and Statistics, York University, Toronto, ON, M3J 1P3 (Canada)

2010-08-20

In this paper the models of pulled Dyck paths in Janse van Rensburg (2010 J. Phys. A: Math. Theor. 43 215001) are generalized to pulled Motzkin path models. The generating functions of pulled Motzkin paths are determined in terms of series over trinomial coefficients and the elastic response of a Motzkin path pulled at its endpoint (see Orlandini and Whittington (2004 J. Phys. A: Math. Gen. 37 5305-14)) is shown to be R(f) = 0 for forces pushing the endpoint toward the adsorbing line and R(f) = f(1 + 2cosh f))/(2sinh f) {yields} f as f {yields} {infinity}, for forces pulling the path away from the X-axis. In addition, the elastic response of a Motzkin path pulled at its midpoint is shown to be R(f) = 0 for forces pushing the midpoint toward the adsorbing line and R(f) = f(1 + 2cosh (f/2))/sinh (f/2) {yields} 2f as f {yields} {infinity}, for forces pulling the path away from the X-axis. Formal combinatorial identities arising from pulled Motzkin path models are also presented. These identities are the generalization of combinatorial identities obtained in directed paths models to their natural trinomial counterparts.

Pulled Motzkin paths

Science.gov (United States)

Janse van Rensburg, E. J.

2010-08-01

In this paper the models of pulled Dyck paths in Janse van Rensburg (2010 J. Phys. A: Math. Theor. 43 215001) are generalized to pulled Motzkin path models. The generating functions of pulled Motzkin paths are determined in terms of series over trinomial coefficients and the elastic response of a Motzkin path pulled at its endpoint (see Orlandini and Whittington (2004 J. Phys. A: Math. Gen. 37 5305-14)) is shown to be R(f) = 0 for forces pushing the endpoint toward the adsorbing line and R(f) = f(1 + 2cosh f))/(2sinh f) → f as f → ∞, for forces pulling the path away from the X-axis. In addition, the elastic response of a Motzkin path pulled at its midpoint is shown to be R(f) = 0 for forces pushing the midpoint toward the adsorbing line and R(f) = f(1 + 2cosh (f/2))/sinh (f/2) → 2f as f → ∞, for forces pulling the path away from the X-axis. Formal combinatorial identities arising from pulled Motzkin path models are also presented. These identities are the generalization of combinatorial identities obtained in directed paths models to their natural trinomial counterparts.

Evaluating Hierarchical Structure in Music Annotations.

Science.gov (United States)

McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

2017-01-01

Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

Evaluating Hierarchical Structure in Music Annotations

Directory of Open Access Journals (Sweden)

Brian McFee

2017-08-01

Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

Learning Through Scenario Planning

DEFF Research Database (Denmark)

Balarezo, Jose

level variables, this research corrects this void by investigating the dynamics of organizational learning through the lenses of a corporate scenario planning process. This enhances our scientific understanding of the role that scenario planning might play in the context of organizational learning......This project investigates the uses and effects of scenario planning in companies operating in highly uncertain and dynamic environments. Whereas previous research on scenario planning has fallen short of providing sufficient evidence of its mechanisms and effects on individual or organizational...... and strategic renewal. Empirical evidence of the various difficulties that learning flows has to overcome as it journeys through organizational and hierarchical levels are presented. Despite various cognitive and social psychological barriers identified along the way, the results show the novel...

The path to active living: physical activity through community design in Somerville, Massachusetts.

Science.gov (United States)

Burke, Noreen M; Chomitz, Virginia R; Rioles, Nicole A; Winslow, Stephen P; Brukilacchio, Lisa B; Baker, Jessie C

2009-12-01

Somerville, Massachusetts, an ethnically diverse, urban community northwest of Boston, presents opportunities and challenges for active living. With a dense street grid, well-maintained sidewalks, neighborhood parks, and existing Community Path, Somerville is very walkable. However, two major surface arteries traverse and bisect neighborhoods, creating pedestrian safety and environmental justice issues. Major goals included promoting increased collaboration and communication among existing active-living efforts; managing the Community Path extension project; encouraging Portuguese-speaking adults to incorporate daily physical activity; leveraging existing urban planning work to establish secure, attractive walking/biking corridors; and embedding active-living messages in everyday life. The Somerville Active Living by Design Partnership (ALbD) successfully created a robust task force that was integrated with citywide active-living efforts, secured resources to increase infrastructure and support for active living, including city-level coordinator positions, and changed decision-making practices that led to incorporation of pedestrian and bicycle transportation priorities into city planning and that influenced the extension of the Community Path. Partnerships must employ sustainability planning early on, utilize skilled facilitative leaders to manage leadership transitions, and engage new partners. Identifying, cultivating, and celebrating champions, especially those with political power, are critical. Working closely with research partners leads to rich data sources for planning and evaluation. Changing the built environment is difficult; working toward smaller wins is realistic and achievable. The synergy of ALbD and other community interventions created a foundation for short-term successes and accelerated political-cultural changes already underway with respect to active living.

Path Expressions

Science.gov (United States)

1975-06-01

Traditionally, synchronization of concurrent processes is coded in line by operations on semaphores or similar objects. Path expressions move the...discussion about a variety of synchronization primitives . An analysis of their relative power is found in [3]. Path expressions do not introduce yet...another synchronization primitive . A path expression relates to such primitives as a for- or while-statement of an ALGOL-like language relates to a JUMP

Using Genetic Algorithms for Navigation Planning in Dynamic Environments

Directory of Open Access Journals (Sweden)

Ferhat Uçan

2012-01-01

Full Text Available Navigation planning can be considered as a combination of searching and executing the most convenient flight path from an initial waypoint to a destination waypoint. Generally the aim is to follow the flight path, which provides minimum fuel consumption for the air vehicle. For dynamic environments, constraints change dynamically during flight. This is a special case of dynamic path planning. As the main concern of this paper is flight planning, the conditions and objectives that are most probable to be used in navigation problem are considered. In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. The evolutionary dynamic navigation planning algorithm is developed for compensating the existing deficiencies of the other approaches. The existing fully dynamic algorithms process unit changes to topology one modification at a time, but when there are several such operations occurring in the environment simultaneously, the algorithms are quite inefficient. The proposed algorithm may respond to the concurrent constraint updates in a shorter time for dynamic environment. The most secure navigation of the air vehicle is planned and executed so that the fuel consumption is minimum.

Hierarchically Nanostructured Materials for Sustainable Environmental Applications

Directory of Open Access Journals (Sweden)

Zheng eRen

2013-11-01

Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong; Wu, Tao

2017-01-01

The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced

视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach

Institute of Scientific and Technical Information of China (English)

张一巍; 黄源清

2002-01-01

The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.

Hierarchically organized layout for visualization of biochemical pathways.

Science.gov (United States)

Tsay, Jyh-Jong; Wu, Bo-Liang; Jeng, Yu-Sen

2010-01-01

Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

Spreading paths in partially observed social networks

OpenAIRE

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-01-01

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 a static, s...

Solving a Class of Spatial Reasoning Problems: Minimal-Cost Path Planning in the Cartesian Plane.

Science.gov (United States)

1987-06-01

as in Figure 72. By the Theorem of Pythagoras : Z1 <a z 2 < C Yl(bl+b 2)uI, the cost of going along (a,b,c) is greater that the...preceding lemmas to an indefinite number of boundary-crossing episodes is accomplished by the following theorems . Theorem 1 extends the result of Lemma 1... Theorem 1: Any two Snell’s-law paths within a K-explored wedge defined by Snell’s-law paths RL and R. do not intersect within the K-explored portion of

Air Pollution alongside Bike-Paths in Bogota - Colombia

Directory of Open Access Journals (Sweden)

Juan Felipe Franco

2016-11-01

Full Text Available The study we present in this paper aims at characterizing the range of fine particulate matter (PM2.5 and black carbon (BC concentrations to which bike-path users in Bogotá are exposed to. Using a bike equipped with a DustTrak and a micro-aethalometer we measured PM2.5 and BC concentration levels along bike-paths corridors, during weekdays and weekends. Experiments were conducted in fours streets, representing four typical configurations of bike-paths in the city. Traffic data for workdays was also available from local mobility authority. Results indicate that bike-paths users in Bogota are exposed to air pollution levels far exceeding the threshold values established as potentially dangerous for human health. Average concentrations for PM2.5 ranged between 80 and 136 ug/m3 in workdays and between 30 and 72 ug/m3 in weekends. BC mean concentrations were between 16 and 38 µg/m3 during workdays and in the range 10 to 32 µg/m3 during weekends. A statistically significant difference exists in the levels of pollutants concentrations measured during workdays and weekends for all the considered bike paths. According to our results, both traffic volume and diffusions conditions, which are affected by many factors including street geometry, affect bike-path user’s exposure levels. Taking into account the important role that bicycling is playing as an alternative transport mode in Latin American cities, we consider these results provide useful insights to increase the appreciation of the excessive bikers´ exposure to air pollution in Bogotá. Moreover, these findings contribute with technical elements that should lead to the inclusion of air quality variable when designing and planning sustainable urban mobility infrastructures.

Hierarchical screening for multiple mental disorders.

Science.gov (United States)

Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

2013-10-01

There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

Self-assembled biomimetic superhydrophobic hierarchical arrays.

Science.gov (United States)

Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

2013-09-01

Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

Environmental support FY 1995 multi-year program plan/fiscal year work plan WBS 1.5.2/7.4.11

International Nuclear Information System (INIS)

Moore, D.A.

1994-09-01

The multi-Year Program Plan (MYPP) is the programmatic planning baseline document for technical, schedule, and cost data. The MYPP contains data by which all work is managed, performed and controlled. The integrated planning process, defined by RL, is redicted on establishment of detailed data in the MYPP. The MYPP includes detailed information for the data elements including Level II critical path schedules, cost estimate detail, and updated technical data to be done annually. There will be baseline execution year and out year approval with work authorization for execution. The MYPP will concentrate on definition of the scope, schedule, cost and program element level critical path schedules that show the relationship of planned activities. The Fiscal Year Work Plan (FYWP) is prepared for each program to provide the basis for authorizing fiscal year work. The MYPP/FYWP will be structured into three main areas: (1) Program Overview; (2) Program Baselines; (3) Fiscal Year Work Plan

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong

2017-08-03

The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

Hierarchical Rhetorical Sentence Categorization for Scientific Papers

Science.gov (United States)

Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.

2018-03-01

Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.

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…

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

Science.gov (United States)

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

A hierarchical approach to multi-project planning under uncertainty

NARCIS (Netherlands)

Leus, R.; Wullink, Gerhard; Hans, Elias W.; Herroelen, W.

2004-01-01

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the

A hierarchical approach to multi-project planning under uncertainty

NARCIS (Netherlands)

Hans, Elias W.; Herroelen, W.; Wullink, Gerhard; Leus, R.

2007-01-01

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. Based on these viewpoints we propose a positioning framework to distinguish between different types of project-driven organisations. This framework is meant to aid project

Multi-scale path planning for reduced environmental impact of aviation

Science.gov (United States)

Campbell, Scot Edward

A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.

Zeolitic materials with hierarchical porous structures.

Science.gov (United States)

Lopez-Orozco, Sofia; Inayat, Amer; Schwab, Andreas; Selvam, Thangaraj; Schwieger, Wilhelm

2011-06-17

During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Processing of hierarchical syntactic structure in music.

Science.gov (United States)

Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian

2013-09-17

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

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

Hierarchical Nanoceramics for Industrial Process Sensors

Energy Technology Data Exchange (ETDEWEB)

Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

2011-07-15

This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

Tuning of Lee Path Loss Model based on recent RF measurements in 400 MHZ conducted in Riyadh City, Saudi Arabia

International Nuclear Information System (INIS)

Alotaibi, Faihan D.; Ali, Adel A.

2008-01-01

In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequently assignments and cell parameters which are basic for network planning process as well as Location Based Services (LBS) techniques that are not based on GPS system. Empirical models are the most adjustable models that can be suited to different types of environments. In this paper, the Lee path loss model has been tuned using Least Square (LS) algorithm to fit measured data for TETRA system operating 400 MHz in Riyadh urban and suburbs. Consequently, Lee model's parameter (L0, y) are obtained for the targeted areas. The performance of the tuned Lee model is then compared to the three most widely used empirical path loss models: Hat, ITU-R and Cost 231 Walfisch-Ikegami non line-of-sight (CWI-NLOS) path loss models. The performance criterion selected for the comparison of various empirical path loss models are the Root Mean Square Error (RMSE) and goodness of fit (R2). The RMSE and R2between the actual and predicted data are calculated for various path loss models. It turned that the tuned Lee model outperforms the other empirical models. (author)

The Case for a Hierarchical Cosmology

Science.gov (United States)

Vaucouleurs, G. de

1970-01-01

The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)

Path Creation, Path Dependence and Breaking Away from the Path: Re-Examining the Case of Nokia

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...

Classification using Hierarchical Naive Bayes models

DEFF Research Database (Denmark)

Langseth, Helge; Dyhre Nielsen, Thomas

2006-01-01

Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

Path-dependent functions

International Nuclear Information System (INIS)

Khrapko, R.I.

1985-01-01

A uniform description of various path-dependent functions is presented with the help of expansion of the type of the Taylor series. So called ''path-integrals'' and ''path-tensor'' are introduced which are systems of many-component quantities whose values are defined for arbitrary paths in coordinated region of space in such a way that they contain a complete information on the path. These constructions are considered as elementary path-dependent functions and are used instead of power monomials in the usual Taylor series. Coefficients of such an expansion are interpreted as partial derivatives dependent on the order of the differentiations or else as nonstandard cavariant derivatives called two-point derivatives. Some examples of pathdependent functions are presented.Space curvature tensor is considered whose geometrica properties are determined by the (non-transitive) translator of parallel transport of a general type. Covariant operation leading to the ''extension'' of tensor fiels is pointed out

Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

Science.gov (United States)

Li, Yasong; Gates, Byron D; Menon, Carlo

2015-08-05

The gecko relies on van der Waals forces to cling onto surfaces with a variety of topography and composition. The hierarchical fibrillar structures on their climbing feet, ranging from mesoscale to nanoscale, are hypothesized to be key elements for the animal to conquer both smooth and rough surfaces. An epoxy-based artificial hierarchical fibrillar adhesive was prepared to study the influence of the hierarchical structures on the properties of a dry adhesive. The presented experiments highlight the advantages of a hierarchical structure despite a reduction of overall density and aspect ratio of nanofibrils. In contrast to an adhesive containing only nanometer-size fibrils, the hierarchical fibrillar adhesives exhibited a higher adhesion force and better compliancy when tested on an identical substrate.

A dynamical model of hierarchical selection and coordination in speech planning.

Directory of Open Access Journals (Sweden)

Sam Tilsen

Full Text Available studies of the control of complex sequential movements have dissociated two aspects of movement planning: control over the sequential selection of movement plans, and control over the precise timing of movement execution. This distinction is particularly relevant in the production of speech: utterances contain sequentially ordered words and syllables, but articulatory movements are often executed in a non-sequential, overlapping manner with precisely coordinated relative timing. This study presents a hybrid dynamical model in which competitive activation controls selection of movement plans and coupled oscillatory systems govern coordination. The model departs from previous approaches by ascribing an important role to competitive selection of articulatory plans within a syllable. Numerical simulations show that the model reproduces a variety of speech production phenomena, such as effects of preparation and utterance composition on reaction time, and asymmetries in patterns of articulatory timing associated with onsets and codas. The model furthermore provides a unified understanding of a diverse group of phonetic and phonological phenomena which have not previously been related.

The Japanese energy sector: Current situation, and future paths

International Nuclear Information System (INIS)

Takase, Kae; Suzuki, Tatsujiro

2011-01-01

As the world's third leading economy and a major importer of fuels, the choice of future energy paths and policies that Japan makes in the next few years will have a significant influence on the energy security of the world as a whole, and of the Northeast Asia region in particular. In this article we describe the current status of and recent trends in the Japanese energy sector, including energy demand and supply by fuel and by sector. We then discuss the current energy policy situation in Japan, focusing on policies related to climate change targets, renewable energy development and deployment, liberalization of energy markets, and the evolution of the Japanese nuclear power sector. The final section of the article presents the structure of the Japan LEAP (long-range energy alternatives planning software system) dataset, describes several alternative energy paths for Japan - with an emphasis on alternative paths for nuclear power development and GHG emission abatement - and touches upon key current issues of energy policy facing Japan, as reflected in the modeling inputs and results.

The Japanese energy sector: Current situation, and future paths

Energy Technology Data Exchange (ETDEWEB)

Takase, Kae, E-mail: kae@gdl.jp [Governance Design Laboratory, Inc., 2301 City Tower Bashamichi 5-71 Onoe-cho, Naka-ku, Yokohama, Kanagawa 231-0015 (Japan); Suzuki, Tatsujiro [University of Tokyo, Graduate School of Public Policy, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0081 (Japan)

2011-11-15

As the world's third leading economy and a major importer of fuels, the choice of future energy paths and policies that Japan makes in the next few years will have a significant influence on the energy security of the world as a whole, and of the Northeast Asia region in particular. In this article we describe the current status of and recent trends in the Japanese energy sector, including energy demand and supply by fuel and by sector. We then discuss the current energy policy situation in Japan, focusing on policies related to climate change targets, renewable energy development and deployment, liberalization of energy markets, and the evolution of the Japanese nuclear power sector. The final section of the article presents the structure of the Japan LEAP (long-range energy alternatives planning software system) dataset, describes several alternative energy paths for Japan - with an emphasis on alternative paths for nuclear power development and GHG emission abatement - and touches upon key current issues of energy policy facing Japan, as reflected in the modeling inputs and results.

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.

Optimal Path Choice in Railway Passenger Travel Network Based on Residual Train Capacity

Directory of Open Access Journals (Sweden)

Fei Dou

2014-01-01

Full Text Available Passenger’s optimal path choice is one of the prominent research topics in the field of railway passenger transport organization. More and more different train types are available, increasing path choices from departure to destination for travelers are unstoppable. However, travelers cannot avoid being confused when they hope to choose a perfect travel plan based on various travel time and cost constraints before departure. In this study, railway passenger travel network is constructed based on train timetable. Both the generalized cost function we developed and the residual train capacity are considered to be the foundation of path searching procedure. The railway passenger travel network topology is analyzed based on residual train capacity. Considering the total travel time, the total travel cost, and the total number of passengers, we propose an optimal path searching algorithm based on residual train capacity in railway passenger travel network. Finally, the rationale of the railway passenger travel network and the optimal path generation algorithm are verified positively by case study.

Individual Educational Paths in the Universities of Russia and Great Britain (Theoretical Aspects

Directory of Open Access Journals (Sweden)

Natalya Yu. Shaposhnikova

2015-01-01

Full Text Available The author highlights the necessity for higher education institutions to form and realize students' individual educational paths in the learning process, which is stated in the Federal Law on Education and FSES HPE of the third generation. The article presents an overview of the different approaches to the definition of the term «individual educational path» (IEP. It also gives a brief overview of the existing terms in the Russian terminological system, which are close in meaning to the term above. The author formulates her own tentative definition of the term «IEP» which is based on the analysis made. The article further addresses the solution to the problem of the individualization of higher education learning process in Great Britain, which is described through the term «Personal Development Planning». The meaning of the term is shown through the set of actions: planning, doing things, recording of the self experience, reviewing and evaluating, using the personal knowledge derived from reflection and self understanding as well as own learning abilities to plan future actions. In conclusion, the meanings of the terms «IEP» and «PDP» are compared. The author emphasires the importance of studying Great Britain's experience - the practice of solving problems connected with the individualization of the university learning process and the possibilities to use it to facilitate the implementation of students' individual educational paths in Russian higher education institutions.

Hierarchical core-shell NiCo2O4@NiMoO4 nanowires grown on carbon cloth as integrated electrode for high-performance supercapacitors

Science.gov (United States)

Huang, Liang; Zhang, Wei; Xiang, Jinwei; Xu, Henghui; Li, Guolong; Huang, Yunhui

2016-08-01

Hierarchical core-shell NiCo2O4@NiMoO4 nanowires were grown on carbon cloth (CC@NiCo2O4@NiMoO4) by a two-step hydrothermal route to fabricate a flexible binder-free electrode. The prepared CC@NiCo2O4@NiMoO4 integrated electrode was directly used as an electrode for faradaic supercapacitor. It shows a high areal capacitance of 2.917 F cm-2 at 2 mA cm-2 and excellent cycling stability with 90.6% retention over 2000 cycles at a high current density of 20 mA cm-2. The superior specific capacitance, rate and cycling performance can be ascribed to the fast transferring path for electrons and ions, synergic effect and the stability of the hierarchical core-shell structure.

A new intrusion prevention model using planning knowledge graph

Science.gov (United States)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Review of a land use planning programme through the soft systems methodology

NARCIS (Netherlands)

Nidumolu, U.B.; Bie, de C.A.J.M.; Keulen, van H.; Skidmore, A.K.; Harmsen, K.

2006-01-01

Traditional land use planning approaches relied significantly on biophysical data and followed a hierarchical top-down approach. The component of primary stakeholders as being critical to the success of implementing such plans is often ignored. In India, a large-scale geo-information project called

Fiscal Policy Trends: The Path to Balance or the Road to Ruin?

Directory of Open Access Journals (Sweden)

Bev Dahlby

2018-03-01

Full Text Available The NDP government’s plan to balance the provincial budget by 2023-24 is based on drastically cutting capital spending and on optimistic revenue projections. In order to show that these are the key elements of the “Path to Balance”, we need to know how interest payments on debt, total operating expenditures, and the cash deficits will evolve under the government’s plan, but these key fiscal variables are not reported in the budget documents.

Leadership styles across hierarchical levels in nursing departments.

Science.gov (United States)

Stordeur, S; Vandenberghe, C; D'hoore, W

2000-01-01

Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.

Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior.

Science.gov (United States)

Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D

2016-08-01

Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Entropy Minimizing Curves with Application to Flight Path Design and Clustering

Directory of Open Access Journals (Sweden)

Stéphane Puechmorel

2016-09-01

Full Text Available Air traffic management (ATM aims at providing companies with a safe and ideally optimal aircraft trajectory planning. Air traffic controllers act on flight paths in such a way that no pair of aircraft come closer than the regulatory separation norms. With the increase of traffic, it is expected that the system will reach its limits in the near future: a paradigm change in ATM is planned with the introduction of trajectory-based operations. In this context, sets of well-separated flight paths are computed in advance, tremendously reducing the number of unsafe situations that must be dealt with by controllers. Unfortunately, automated tools used to generate such planning generally issue trajectories not complying with operational practices or even flight dynamics. In this paper, a means of producing realistic air routes from the output of an automated trajectory design tool is investigated. For that purpose, the entropy of a system of curves is first defined, and a mean of iteratively minimizing it is presented. The resulting curves form a route network that is suitable for use in a semi-automated ATM system with human in the loop. The tool introduced in this work is quite versatile and may be applied also to unsupervised classification of curves: an example is given for French traffic.

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

A Robust Planning Algorithm for Groups of Entities in Discrete Spaces

Directory of Open Access Journals (Sweden)

Igor Wojnicki

2015-07-01

Full Text Available Automated planning is a well-established field of artificial intelligence (AI, with applications in route finding, robotics and operational research, among others. The task of developing a plan is often solved by finding a path in a graph representing the search domain; a robust plan consists of numerous paths that can be chosen if the execution of the best (optimal one fails. While robust planning for a single entity is rather simple, development of a robust plan for multiple entities in a common environment can lead to combinatorial explosion. This paper proposes a novel hybrid approach, joining heuristic search and the wavefront algorithm to provide a plan featuring robustness in areas where it is needed, while maintaining a low level of computational complexity.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

Science.gov (United States)

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with 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...

On path generation and feedforward control for a class of surface sailing vessels

DEFF Research Database (Denmark)

Xiao, Lin; Jouffroy, Jerome

2010-01-01

Sailing vessels with wind as their main means of propulsion possess a unique property that the paths they take depend on the wind direction, which, in the literature, has attracted less attention than normal vehicles propelled by propellers or thrusters. This paper considers the problem of motion...... planning and controllability for sailing vehicles representing the no-sailing zone effect in sailing. Following our previous work, we present an extended algorithm for automatic path generation with a prescribed initial heading for a simple model of sailing vehicles, together with a feedforward controller...

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.

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.

Risk-Aware Planetary Rover Operation: Autonomous Terrain Classification and Path Planning

Science.gov (United States)

Ono, Masahiro; Fuchs, Thoams J.; Steffy, Amanda; Maimone, Mark; Yen, Jeng

2015-01-01

Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed groundbased Mars rover operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers.

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production.

Science.gov (United States)

Sauppe, Sebastian

2017-01-01

Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

Education - path towards solution regarding disposal of spent nuclear fuel

International Nuclear Information System (INIS)

Klein, D.E.

1991-01-01

Education, not emotional reaction, is the path to take in the safe disposal of spent nuclear fuel. Education is needed at all levels: Elementary schools, secondary schools, two-year colleges, four-year colleges, graduate schools, and adult education. The Office of Civilian Radioactive Waste Management (OCRWM) should not be expected to tackle this problem alone. Assistance is needed from local communities, schools, and state and federal governments. However, OCRWM can lay the foundation for a comprehensive educational plan directed specifically at educating the public on the spent nuclear fuel issue and OCRWM can begin the implementation of this plan

Enabling Agility through Coordinating Temporally Constrained Planning Agents

NARCIS (Netherlands)

Steenhuisen, J.R.; De Weerdt, M.M.; Witteveen, C.

2007-01-01

In crisis response, hierarchical organizations are being replaced by dynamic assemblies of autonomous agents that promise more agility. However, these autonomous agents might cause a decrease in effectiveness when individually constructed plans for moderately-coupled tasks are not jointly feasible.

Flight Planning

Science.gov (United States)

1991-01-01

Seagull Technology, Inc., Sunnyvale, CA, produced a computer program under a Langley Research Center Small Business Innovation Research (SBIR) grant called STAFPLAN (Seagull Technology Advanced Flight Plan) that plans optimal trajectory routes for small to medium sized airlines to minimize direct operating costs while complying with various airline operating constraints. STAFPLAN incorporates four input databases, weather, route data, aircraft performance, and flight-specific information (times, payload, crew, fuel cost) to provide the correct amount of fuel optimal cruise altitude, climb and descent points, optimal cruise speed, and flight path.

Motor planning is facilitated by adopting an action's goal posture: An fMRI study

NARCIS (Netherlands)

Zimmermann, M.; Meulenbroek, R.G.J.; Lange, F.P. de

2012-01-01

Abstract: Motor planning is a hierarchical process that is typically organized around an action's goal (e.g., drinking from a cup). However, the motor plan depends not only on the goal but also on the current body state. Here, we investigated how one's own body posture interacts with planning of

Hierarchical analysis of acceptable use policies

Directory of Open Access Journals (Sweden)

P. A. Laughton

2008-01-01

Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

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.

Virtual timers in hierarchical real-time systems

NARCIS (Netherlands)

Heuvel, van den M.M.H.P.; Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.; Zhu, D.

2009-01-01

Hierarchical scheduling frameworks (HSFs) provide means for composing complex real-time systems from welldefined subsystems. This paper describes an approach to provide hierarchically scheduled real-time applications with virtual event timers, motivated by the need for integrating priority

Hierarchical modeling and analysis for spatial data

CERN Document Server

Banerjee, Sudipto; Gelfand, Alan E

2003-01-01

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

Reaction-diffusion path planning in a hybrid chemical and cellular-automaton processor

International Nuclear Information System (INIS)

Adamatzky, Andrew; Lacy Costello, Benjamin de

2003-01-01

To find the shortest collision-free path in a room containing obstacles we designed a chemical processor and coupled it with a cellular-automaton processor. In the chemical processor obstacles are represented by sites of high concentration of potassium iodide and a planar substrate is saturated with palladium chloride. Potassium iodide diffuses into the substrate and reacts with palladium chloride. A dark coloured precipitate of palladium iodide is formed almost everywhere except sites where two or more diffusion wavefronts collide. The less coloured sites are situated at the furthest distance from obstacles. Thus, the chemical processor develops a repulsive field, generated by obstacles. A snapshot of the chemical processor is inputted to a cellular automaton. The automaton behaves like a discrete excitable media; also, every cell of the automaton is supplied with a pointer that shows an origin of the cell's excitation. The excitation spreads along the cells corresponding to precipitate depleted sites of the chemical processor. When the destination-site is excited, waves travel on the lattice and update the orientations of the pointers. Thus, the automaton constructs a spanning tree, made of pointers, that guides a traveler towards the destination point. Thus, the automaton medium generates an attractive field and combination of this attractive field with the repulsive field, generated by the chemical processor, provides us with a solution of the collision-free path problem

Hierarchical decision modeling essays in honor of Dundar F. Kocaoglu

CERN Document Server

2016-01-01

This volume, developed in honor of Dr. Dundar F. Kocaoglu, aims to demonstrate the applications of the Hierarchical Decision Model (HDM) in different sectors and its capacity in decision analysis. It is comprised of essays from noted scholars, academics and researchers of engineering and technology management around the world. This book is organized into four parts: Technology Assessment, Strategic Planning, National Technology Planning and Decision Making Tools. Dr. Dundar F. Kocaoglu is one of the pioneers of multiple decision models using hierarchies, and creator of the HDM in decision analysis. HDM is a mission-oriented method for evaluation and/or selection among alternatives. A wide range of alternatives can be considered, including but not limited to, different technologies, projects, markets, jobs, products, cities to live in, houses to buy, apartments to rent, and schools to attend. Dr. Kocaoglu’s approach has been adopted for decision problems in many industrial sectors, including electronics rese...

Planning for the future.

Science.gov (United States)

Stiewing, Janis

2002-01-01

Revising the strategic plan was the beginning of a multiyear initiative that will determine the path of the JRCERT. The key word in the preceding statement is beginning. The strategic plan is an ever-changing document. Although some components, such as the values statements, will stand over time, other components will change as accreditation and educational arenas change. That is the paradox of strategic planning: Remaining true to the vision, values and mission statements requires knowing when to change to keep the JRCERT aligned with the responsive to its communities of interest.

Hierarchical organization versus self-organization

OpenAIRE

Busseniers, Evo

2014-01-01

In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

Integral transforms of the quantum mechanical path integral: Hit function and path-averaged potential

Science.gov (United States)

Edwards, James P.; Gerber, Urs; Schubert, Christian; Trejo, Maria Anabel; Weber, Axel

2018-04-01

We introduce two integral transforms of the quantum mechanical transition kernel that represent physical information about the path integral. These transforms can be interpreted as probability distributions on particle trajectories measuring respectively the relative contribution to the path integral from paths crossing a given spatial point (the hit function) and the likelihood of values of the line integral of the potential along a path in the ensemble (the path-averaged potential).

Effect of State-Specific Factors on Acquisition Path Ranking

International Nuclear Information System (INIS)

Vincze, A.; Nemeth, A.

2015-01-01

The ''directed graph analysis'' has been shown to be a promising methodology to implement acquisition path analysis by the IAEA to support the State evaluation process. Based on this methodology a material flow network model has been developed under the Hungarian Support Programme to the IAEA, in which materials in different chemical and physical form can flow through pipes representing declared processes, material transports, diversions or undeclared processes. The ranking of the resulting acquisition paths of the analysis is a key step to facilitate the determination of technical objectives and the planning of safeguards implementation on State-level. These are determined by the attributes of the processes included into the graph and different state-specific factors. In this paper different set of attributes, State-specific factors and their functional combination will be tested for hypothetical case studies. (author)

Cancer risk and survival in path_MMR carriers by gene and gender up to 75 years of age

DEFF Research Database (Denmark)

Møller, Pål; Seppälä, Toni; Bernstein, Inge

2017-01-01

BACKGROUND: Most patients with path_MMR gene variants (Lynch syndrome (LS)) now survive both their first and subsequent cancers, resulting in a growing number of older patients with LS for whom limited information exists with respect to cancer risk and survival. OBJECTIVE AND DESIGN......%, duodenum 67%, stomach 61%, bile duct 29%, brain 22% and pancreas 0%. Path_PMS2 carriers had lower risk for cancer. CONCLUSION: Carriers of different path_MMR variants exhibit distinct patterns of cancer risk and survival as they age. Risk estimates for counselling and planning of surveillance and treatment...

Deliberate change without hierarchical influence?

DEFF Research Database (Denmark)

Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

2017-01-01

reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

Multiparty hierarchical quantum-information splitting

International Nuclear Information System (INIS)

Wang Xinwen; Zhang Dengyu; Tang Shiqing; Xie Lijun

2011-01-01

We propose a scheme for multiparty hierarchical quantum-information splitting (QIS) with a multipartite entangled state, where a boss distributes a secret quantum state to two grades of agents asymmetrically. The agents who belong to different grades have different authorities for recovering the boss's secret. Except for the boss's Bell-state measurement, no nonlocal operation is involved. The presented scheme is also shown to be secure against eavesdropping. Such a hierarchical QIS is expected to find useful applications in the field of modern multipartite quantum cryptography.

Biased trapping issue on weighted hierarchical networks

Indian Academy of Sciences (India)

archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

The Research on International Development Path of China’s Marine Biopharmaceutical Industry

Directory of Open Access Journals (Sweden)

Xiu-Mei Fu

2018-02-01

Full Text Available Under the backdrop of the Maritime Silk Road Initiative, the study on the international development of China’s marine biopharmaceutical industry based on factor allocation is of great practical significance for industrial sustainability and building the industry into a leading international player in the global market. In this paper, we first identify the leading factors that influence the development of the marine biopharmaceutical industry, namely, resources, technologies, talents, investments and policies. Furthermore, the hierarchical structure model of these factors was established and analyzed using the analytic hierarchy process (AHP. The importance ranking of these constraints was identified, as follows: technologies > talents > resources > policies > investments. Then, based on the theory of comparative advantage and game theory, we analyzed the necessity of China’s marine biopharmaceutical industry going global, that is, international cooperation may lay a solid foundation for the win-win outcome of this industry in countries along the Maritime Silk Road. According to the status quo of China’s marine biopharmaceutical industry, based on these findings, an international factor–allocation cooperation path was designed, and the path chart of the international development of the marine biopharmaceutical industry was drawn. Finally, methods for the development of China’s marine biopharmaceutical industry were proposed, which covers efforts to protect marine resources, promote R&D for core technologies, establish a strong talent pool, encourage more investments, provide policy support and promote worldwide cooperation. It is the first report to investigate the path of the sustainable exploitation of the marine biopharmaceutical industry from the perspective of factor allocation amidst the backdrop of the Maritime Silk Road Initiative.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

International Nuclear Information System (INIS)

Enoki, Motohiro; Ishiyama, Tomoaki; Kobayashi, Masakazu A. R.; Nagashima, Masahiro

2014-01-01

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

Energy Technology Data Exchange (ETDEWEB)

Enoki, Motohiro [Faculty of Business Administration, Tokyo Keizai University, Kokubunji, Tokyo 185-8502 (Japan); Ishiyama, Tomoaki [Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Kobayashi, Masakazu A. R. [Research Center for Space and Cosmic Evolution, Ehime University, Matsuyama, Ehime 790-8577 (Japan); Nagashima, Masahiro, E-mail: enokimt@tku.ac.jp [Faculty of Education, Nagasaki University, Nagasaki, Nagasaki 852-8521 (Japan)

2014-10-10

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production

Directory of Open Access Journals (Sweden)

Sebastian Sauppe

2017-09-01

Full Text Available Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

Extension of mixture-of-experts networks for binary classification of hierarchical data.

Science.gov (United States)

Ng, Shu-Kay; McLachlan, Geoffrey J

2007-09-01

For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another extension is to quantify cluster-specific information on data hierarchy by random effects via the generalized linear mixed-effects model (GLMM). The extension of ME networks is implemented by allowing for correlation in the hierarchical data in both the gating and expert networks via the GLMM. The proposed model is illustrated using a real thyroid disease data set. In our study, we consider 7652 thyroid diagnosis records from 1984 to early 1987 with complete information on 20 attribute values. We obtain 10 independent random splits of the data into a training set and a test set in the proportions 85% and 15%. The test sets are used to assess the generalization performance of the proposed model, based on the percentage of misclassifications. For comparison, the results obtained from the ME network with independence assumption are also included. With the thyroid disease data, the misclassification rate on test sets for the extended ME network is 8.9%, compared to 13.9% for the ME network. In addition, based on model selection methods described in Section 2, a network with two experts is selected. These two expert networks can be considered as modeling two groups of patients with high and low incidence rates. Significant variation among the predicted cluster-specific random effects is detected in the patient group with low incidence rate. It is shown that the extended ME network outperforms the ME network for binary classification of hierarchical data. With the thyroid disease data, useful information on the relative log odds of patients with diagnosed conditions at different periods can be

Microgrids and distributed generation systems: Control, operation, coordination and planning

Science.gov (United States)

Che, Liang

Distributed Energy Resources (DERs) which include distributed generations (DGs), distributed energy storage systems, and adjustable loads are key components in microgrid operations. A microgrid is a small electric power system integrated with on-site DERs to serve all or some portion of the local load and connected to the utility grid through the point of common coupling (PCC). Microgrids can operate in both grid-connected mode and island mode. The structure and components of hierarchical control for a microgrid at Illinois Institute of Technology (IIT) are discussed and analyzed. Case studies would address the reliable and economic operation of IIT microgrid. The simulation results of IIT microgrid operation demonstrate that the hierarchical control and the coordination strategy of distributed energy resources (DERs) is an effective way of optimizing the economic operation and the reliability of microgrids. The benefits and challenges of DC microgrids are addressed with a DC model for the IIT microgrid. We presented the hierarchical control strategy including the primary, secondary, and tertiary controls for economic operation and the resilience of a DC microgrid. The simulation results verify that the proposed coordinated strategy is an effective way of ensuring the resilient response of DC microgrids to emergencies and optimizing their economic operation at steady state. The concept and prototype of a community microgrid that interconnecting multiple microgrids in a community are proposed. Two works are conducted. For the coordination, novel three-level hierarchical coordination strategy to coordinate the optimal power exchanges among neighboring microgrids is proposed. For the planning, a multi-microgrid interconnection planning framework using probabilistic minimal cut-set (MCS) based iterative methodology is proposed for enhancing the economic, resilience, and reliability signals in multi-microgrid operations. The implementation of high-reliability microgrids

Discovering hierarchical structure in normal relational data

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

2014-01-01

-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

Path to Market for Compact Modular Fusion Power Cores

Science.gov (United States)

Woodruff, Simon; Baerny, Jennifer K.; Mattor, Nathan; Stoulil, Don; Miller, Ronald; Marston, Theodore

2012-08-01

The benefits of an energy source whose reactants are plentiful and whose products are benign is hard to measure, but at no time in history has this energy source been more needed. Nuclear fusion continues to promise to be this energy source. However, the path to market for fusion systems is still regularly a matter for long-term (20 + year) plans. This white paper is intended to stimulate discussion of faster commercialization paths, distilling guidance from investors, utilities, and the wider energy research community (including from ARPA-E). There is great interest in a small modular fusion system that can be developed quickly and inexpensively. A simple model shows how compact modular fusion can produce a low cost development path by optimizing traditional systems that burn deuterium and tritium, operating not only at high magnetic field strength, but also by omitting some components that allow for the core to become more compact and easier to maintain. The dominant hurdles to the development of low cost, practical fusion systems are discussed, primarily in terms of the constraints placed on the cost of development stages in the private sector. The main finding presented here is that the bridge from DOE Office of Science to the energy market can come at the Proof of Principle development stage, providing the concept is sufficiently compact and inexpensive that its development allows for a normal technology commercialization path.

Road Network Selection Based on Road Hierarchical Structure Control

Directory of Open Access Journals (Sweden)

HE Haiwei

2015-04-01

Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

Software for Project-Based Learning of Robot Motion Planning

Science.gov (United States)

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-01-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…

Hierarchically Structured Electrospun Fibers

Directory of Open Access Journals (Sweden)

Nicole E. Zander

2013-01-01

Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

Hierarchical control of electron-transfer

DEFF Research Database (Denmark)

Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis

1997-01-01

In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

Maslow and Motherboards: Taking a Hierarchical View of Technology Planning.

Science.gov (United States)

Johnson, Doug

2003-01-01

Presents a planning model for educational uses of technology that is based on Maslow's hierarchy of needs. Topics include established infrastructure; effective administration; extensive resources; enhanced teaching, including creating distance learning opportunities; empowered students, including evaluation methods and information literacy skills;…

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

Hierarchical Neural Regression Models for Customer Churn Prediction

Directory of Open Access Journals (Sweden)

Golshan Mohammadi

2013-01-01

Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

Maintaining consistency between planning hierarchies: Techniques and applications

Science.gov (United States)

Zoch, David R.

1987-01-01

In many planning and scheduling environments, it is desirable to be able to view and manipulate plans at different levels of abstraction, allowing the users the option of viewing and manipulating either a very detailed representation of the plan or a high-level more abstract version of the plan. Generating a detailed plan from a more abstract plan requires domain-specific planning/scheduling knowledge; the reverse process of generating a high-level plan from a detailed plan Reverse Plan Maintenance, or RPM) requires having the system remember the actions it took based on its domain-specific knowledge and its reasons for taking those actions. This reverse plan maintenance process is described as implemented in a specific planning and scheduling tool, The Mission Operations Planning Assistant (MOPA), as well as the applications of RPM to other planning and scheduling problems; emphasizing the knowledge that is needed to maintain the correspondence between the different hierarchical planning levels.

Formalizing a hierarchical file system

NARCIS (Netherlands)

Hesselink, Wim H.; Lali, Muhammad Ikram

An abstract file system is defined here as a partial function from (absolute) paths to data. Such a file system determines the set of valid paths. It allows the file system to be read and written at a valid path, and it allows the system to be modified by the Unix operations for creation, removal,

Hierarchical Traces for Reduced NSM Memory Requirements

Science.gov (United States)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

Formalizing a Hierarchical File System

NARCIS (Netherlands)

Hesselink, Wim H.; Lali, M.I.

2009-01-01

In this note, we define an abstract file system as a partial function from (absolute) paths to data. Such a file system determines the set of valid paths. It allows the file system to be read and written at a valid path, and it allows the system to be modified by the Unix operations for removal

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Is regional planning dead or just coping?

DEFF Research Database (Denmark)

Galland, Daniel

2012-01-01

and welfarist state project towards being a domain characterised by growth-oriented strategies that stand for neoliberal political agendas. In analysing this process I show that hierarchical forms of governance and statutory mechanisms embedded within them have been largely substituted by emerging soft spaces......How is regional planning transformed in increasingly changing socioeconomic and political contexts? How are regional planning policies and practices ultimately shaped and why? With this paper I propose and apply an analytical model based on notions of state theory, state spatial selectivity, new...

Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

DEFF Research Database (Denmark)

He, W.; Min, D.D.; Zhang, X.D.

2014-01-01

Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...... and products of catalytic reactions can freely diffuse through open mesopores (2–40 nm). The formation mechanism of hierarchically structured porous bioactive glasses, the immobilization mechanism of enzyme and the catalysis mechanism of immobilized enzyme are then discussed. The novel nanostructure...

Correlation between hierarchical structure of crystal networks and macroscopic performance of mesoscopic soft materials and engineering principles.

Science.gov (United States)

Lin, Naibo; Liu, Xiang Yang

2015-11-07

This review examines how the concepts and ideas of crystallization can be extended further and applied to the field of mesoscopic soft materials. It concerns the structural characteristics vs. the macroscopic performance, and the formation mechanism of crystal networks. Although this subject can be discussed in a broad sense across the area of mesoscopic soft materials, our main focus is on supramolecular materials, spider and silkworm silks, and biominerals. First, the occurrence of a hierarchical structure, i.e. crystal network and domain network structures, will facilitate the formation kinetics of mesoscopic phases and boost up the macroscopic performance of materials in some cases (i.e. spider silk fibres). Second, the structure and performance of materials can be correlated in some way by the four factors: topology, correlation length, symmetry/ordering, and strength of association of crystal networks. Moreover, four different kinetic paths of crystal network formation are identified, namely, one-step process of assembly, two-step process of assembly, mixed mode of assembly and foreign molecule mediated assembly. Based on the basic mechanisms of crystal nucleation and growth, the formation of crystal networks, such as crystallographic mismatch (or noncrystallographic) branching (tip branching and fibre side branching) and fibre/polymeric side merging, are reviewed. This facilitates the rational design and construction of crystal networks in supramolecular materials. In this context, the (re-)construction of a hierarchical crystal network structure can be implemented by thermal, precipitate, chemical, and sonication stimuli. As another important class of soft materials, the unusual mechanical performance of spider and silkworm silk fibres are reviewed in comparison with the regenerated silk protein derivatives. It follows that the considerably larger breaking stress and unusual breaking strain of spider silk fibres vs. silkworm silk fibres can be interpreted

Path integration quantization

International Nuclear Information System (INIS)

DeWitt-Morette, C.

1983-01-01

Much is expected of path integration as a quantization procedure. Much more is possible if one recognizes that path integration is at the crossroad of stochastic and differential calculus and uses the full power of both stochastic and differential calculus in setting up and computing path integrals. In contrast to differential calculus, stochastic calculus has only comparatively recently become an instrument of thought. It has nevertheless already been used in a variety of challenging problems, for instance in the quantization problem. The author presents some applications of the stochastic scheme. (Auth.)

Three Ways to Link Merge with Hierarchical Concept-Combination

Directory of Open Access Journals (Sweden)

Chris Thornton

2016-11-01

Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

Hierarchical modeling and its numerical implementation for layered thin elastic structures

Energy Technology Data Exchange (ETDEWEB)

Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

2017-05-15

Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

Energy-oriented planning of enterprises. Energieorientierte Unternehmensplanung

Energy Technology Data Exchange (ETDEWEB)

Hoffmann, H

1983-01-01

The book first of all analysis, from an energy point of view, the planning field, which can be characterized by factors relating to the enterprise, environmental factors and the basic business policy pursued. Chapter 2 deals with the enterprise parameters that form the object of planning. Different variables of action are pointed out: aims, strategies (and/or stratetic paths), and actions related to certain areas of function. The aims to be fixed are closely connected with the basic business policy and are discussed in this context. In the part dealing with strategies, particular attention is paid to the efficiency-oriented path ''rational energy utilization'' and the effectiveness-oriented path ''energy-oriented product and market design''. Both strategic framework concepts are viewed in close relation to the aims envisaged, the basic business policy and the environmental and business analysis, and are worked out in this connection. The general strategy discussion covering all sectors is followed by a detailed analysis of the action potential specific to certain areas of function. The physical transformation stages procurement, production and sale are chosen as areas of function to be investigated. Finally the book discusses questions related to the realization of energy concepts. These are, besides implementation conditions and control tasks, resistances encountered and the limits of energy-oriented planning.

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...

A cost effective topology migration path towards fibre

OpenAIRE

Phillipson, F.

2013-01-01

If an operator has as starting position a Full Copper topology in which ADSL or VDSL is offered from the Central Office, the next choice he has to make is to provide Full FttH or use an other topology option, e.g. FttCab, first as intermediate step to provide a next generation service package. In this paper we present a gradual topology migration path from Full Copper via FttCab and Hybrid FttH towards Full FttH. We look at the planning issues of this topology migration and the financial impa...

Hierarchical surfaces for enhanced self-cleaning applications

Science.gov (United States)

Fernández, Ariadna; Francone, Achille; Thamdrup, Lasse H.; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus; Sotomayor Torres, Clivia M.; Kehagias, Nikolaos

2017-04-01

In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets.

A metal-organic framework derived hierarchical nickel-cobalt sulfide nanosheet array on Ni foam with enhanced electrochemical performance for supercapacitors.

Science.gov (United States)

Tao, Kai; Han, Xue; Ma, Qingxiang; Han, Lei

2018-03-06

Metal-organic frameworks (MOFs) have emerged as a new platform for the construction of various functional materials for energy related applications. Here, a facile MOF templating method is developed to fabricate a hierarchical nickel-cobalt sulfide nanosheet array on conductive Ni foam (Ni-Co-S/NF) as a binder-free electrode for supercapacitors. A uniform 2D Co-MOF nanowall array is first grown in situ on Ni foam in aqueous solution at room temperature, and then the Co-MOF nanowalls are converted into hierarchical Ni-Co-S nanoarchitectures via an etching and ion-exchange reaction with Ni(NO 3 ) 2 , and a subsequent solvothermal sulfurization. Taking advantage of the compositional and structural merits of the hierarchical Ni-Co-S nanosheet array and conductive Ni foam, such as fast electron transportation, short ion diffusion path, abundant active sites and rich redox reactions, the obtained Ni-Co-S/NF electrode exhibits excellent electrochemical capacitive performance (1406.9 F g -1 at 0.5 A g -1 , 53.9% retention at 10 A g -1 and 88.6% retention over 1000 cycles), which is superior to control CoS/NF. An asymmetric supercapacitor (ASC) assembled by using the as-fabricated Ni-Co-S/NF as the positive electrode and activated carbon (AC) as the negative electrode delivers a high energy density of 24.8 W h kg -1 at a high power density of 849.5 W kg -1 . Even when the power density is as high as 8.5 kW kg -1 , the ASC still exhibits a high energy density of 12.5 W h kg -1 . This facile synthetic strategy can also be extended to fabricate other hierarchical integrated electrodes for high-efficiency electrochemical energy conversion and storage devices.

Reparametrization in the path integral

International Nuclear Information System (INIS)

Storchak, S.N.

1983-01-01

The question of the invariance of a measure in the n-dimensional path integral under the path reparametrization is considered. The non-invariance of the measure through the jacobian is suggeste. After the path integral reparametrization the representatioq for the Green's function of the Hamilton operator in terms of the path integral with the classical Hamiltonian has been obtained

Unique Path Partitions

DEFF Research Database (Denmark)

Bessenrodt, Christine; Olsson, Jørn Børling; Sellers, James A.

2013-01-01

We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions.......We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions....

Design and analysis of advanced flight planning concepts

Science.gov (United States)

Sorensen, John A.

1987-01-01

The objectives of this continuing effort are to develop and evaluate new algorithms and advanced concepts for flight management and flight planning. This includes the minimization of fuel or direct operating costs, the integration of the airborne flight management and ground-based flight planning processes, and the enhancement of future traffic management systems design. Flight management (FMS) concepts are for on-board profile computation and steering of transport aircraft in the vertical plane between a city pair and along a given horizontal path. Flight planning (FPS) concepts are for the pre-flight ground based computation of the three-dimensional reference trajectory that connects the city pair and specifies the horizontal path, fuel load, and weather profiles for initializing the FMS. As part of these objectives, a new computer program called EFPLAN has been developed and utilized to study advanced flight planning concepts. EFPLAN represents an experimental version of an FPS. It has been developed to generate reference flight plans compatible as input to an FMS and to provide various options for flight planning research. This report describes EFPLAN and the associated research conducted in its development.

Hierarchical Micro-Nano Coatings by Painting

Science.gov (United States)

Kirveslahti, Anna; Korhonen, Tuulia; Suvanto, Mika; Pakkanen, Tapani A.

2016-03-01

In this paper, the wettability properties of coatings with hierarchical surface structures and low surface energy were studied. Hierarchically structured coatings were produced by using hydrophobic fumed silica nanoparticles and polytetrafluoroethylene (PTFE) microparticles as additives in polyester (PES) and polyvinyldifluoride (PVDF). These particles created hierarchical micro-nano structures on the paint surfaces and lowered or supported the already low surface energy of the paint. Two standard application techniques for paint application were employed and the presented coatings are suitable for mass production and use in large surface areas. By regulating the particle concentrations, it was possible to modify wettability properties gradually. Highly hydrophobic surfaces were achieved with the highest contact angle of 165∘. Dynamic contact angle measurements were carried out for a set of selected samples and low hysteresis was obtained. Produced coatings possessed long lasting durability in the air and in underwater conditions.

Hierarchical virtual screening approaches in small molecule drug discovery.

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Entrepreneurial intention modeling using hierarchical multiple regression

Directory of Open Access Journals (Sweden)

Marina Jeger

2014-12-01

Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

Gibbon travel paths are goal oriented.

Science.gov (United States)

Asensio, Norberto; Brockelman, Warren Y; Malaivijitnond, Suchinda; Reichard, Ulrich H

2011-05-01

Remembering locations of food resources is critical for animal survival. Gibbons are territorial primates which regularly travel through small and stable home ranges in search of preferred, limited and patchily distributed resources (primarily ripe fruit). They are predicted to profit from an ability to memorize the spatial characteristics of their home range and may increase their foraging efficiency by using a 'cognitive map' either with Euclidean or with topological properties. We collected ranging and feeding data from 11 gibbon groups (Hylobates lar) to test their navigation skills and to better understand gibbons' 'spatial intelligence'. We calculated the locations at which significant travel direction changes occurred using the change-point direction test and found that these locations primarily coincided with preferred fruit sources. Within the limits of biologically realistic visibility distances observed, gibbon travel paths were more efficient in detecting known preferred food sources than a heuristic travel model based on straight travel paths in random directions. Because consecutive travel change-points were far from the gibbons' sight, planned movement between preferred food sources was the most parsimonious explanation for the observed travel patterns. Gibbon travel appears to connect preferred food sources as expected under the assumption of a good mental representation of the most relevant sources in a large-scale space.

Hierarchical multi-scale classification of nearshore aquatic habitats of the Great Lakes: Western Lake Erie

Science.gov (United States)

McKenna, J.E.; Castiglione, C.

2010-01-01

Classification is a valuable conservation tool for examining natural resource status and problems and is being developed for coastal aquatic habitats. We present an objective, multi-scale hydrospatial framework for nearshore areas of the Great Lakes. The hydrospatial framework consists of spatial units at eight hierarchical scales from the North American Continent to the individual 270-m spatial cell. Characterization of spatial units based on fish abundance and diversity provides a fish-guided classification of aquatic areas at each spatial scale and demonstrates how classifications may be generated from that framework. Those classification units then provide information about habitat, as well as biotic conditions, which can be compared, contrasted, and hierarchically related spatially. Examples within several representative coastal or open water zones of the Western Lake Erie pilot area highlight potential application of this classification system to management problems. This classification system can assist natural resource managers with planning and establishing priorities for aquatic habitat protection, developing rehabilitation strategies, or identifying special management actions.

Intersection Recognition and Guide-Path Selection for a Vision-Based AGV in a Bidirectional Flow Network

Directory of Open Access Journals (Sweden)

Wu Xing

2014-03-01

Full Text Available Vision recognition and RFID perception are used to develop a smart AGV travelling on fixed paths while retaining low-cost, simplicity and reliability. Visible landmarks can describe features of shapes and geometric dimensions of lines and intersections, and RFID tags can directly record global locations on pathways and the local topological relations of crossroads. A topological map is convenient for building and editing without the need for accurate poses when establishing a priori knowledge of a workplace. To obtain the flexibility of bidirectional movement along guide-paths, a camera placed in the centre of the AGV looks downward vertically at landmarks on the floor. A small visual field presents many difficulties for vision guidance, especially for real-time, correct and reliable recognition of multi-branch crossroads. First, the region projection and contour scanning methods are both used to extract the features of shapes. Then LDA is used to reduce the number of the features' dimensions. Third, a hierarchical SVM classifier is proposed to classify their multi-branch patterns once the features of the shapes are complete. Our experiments in landmark recognition and navigation show that low-cost vision systems are insusceptible to visual noises, image breakages and floor changes, and a vision-based AGV can locate itself precisely on its paths, recognize different crossroads intelligently by verifying the conformance of vision and RFID information, and select its next pathway efficiently in a bidirectional flow network.

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.

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-01-01

Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-12-05

Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

Work-in-process clearing in supply chain operations planning

NARCIS (Netherlands)

Selcuk, B.; Fransoo, J.C.; Kok, de A.G.

2008-01-01

In this study we provide insights into the effectiveness of the clearing function concept in a hierarchical planning context. The clearing function is a mathematical representation of the relation between the Work-In-Process (WIP) and the throughput of a production process. We use it in a

Iterated Leavitt Path Algebras

International Nuclear Information System (INIS)

Hazrat, R.

2009-11-01

Leavitt path algebras associate to directed graphs a Z-graded algebra and in their simplest form recover the Leavitt algebras L(1,k). In this note, we introduce iterated Leavitt path algebras associated to directed weighted graphs which have natural ± Z grading and in their simplest form recover the Leavitt algebras L(n,k). We also characterize Leavitt path algebras which are strongly graded. (author)