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Proceedings ArticleDOI

An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot

01 Oct 2006-pp 3331-3336
TL;DR: A new APF method for path-planning of mobile robots in a dynamic environment where the target and obstacles are moving is proposed, and the new force function and the relative threat coefficient function are defined.
Abstract: The artificial potential field (APF) method is widely used for autonomous mobile robot path planning due to its simplicity and mathematical elegance. However, most researches are focused on solving the path-planning problem in a stationary environment, where both targets and obstacles are stationary. This paper proposes a new APF method for path planning of mobile robots in a dynamic environment where the target and obstacles are moving. Firstly, the new force function and the relative threat coefficient function are defined. Then, a new APF path-planning algorithm based on the relative threat coefficient is presented. Finally, computer simulation and experiment are used to demonstrate the effectiveness of the dynamic path-planning scheme.
Citations
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Journal ArticleDOI
TL;DR: It was demonstrated that the BPF outperforms the APF, GPF, and the PBPF methods by reducing the computational time to find the optimal path at least by a factor of 1.59.
Abstract: The BPF proposal ensures a feasible, optimal and safe path for robot navigation.The results of BPF overcomes APF and other EAPF methods like those based in GAs.The BPF is quite faster in optimization leading to reduction in computation burden.The BPF running in parallel mode is the most suitable to fulfill local and global controllability.The BPF is capable to work in offline and online mode with static and dynamic obstacles. In this paper, optimal paths in environments with static and dynamic obstacles for a mobile robot (MR) are computed using a new method for path planning. The proposed method called Bacterial Potential Field (BPF) ensures a feasible, optimal and safe path. This novel proposal makes use of the Artificial Potential Field (APF) method with a Bacterial Evolutionary Algorithm (BEA) to obtain an enhanced flexible path planner method taking all the advantages of using the APF method, strongly reducing its disadvantages. Comparative experiments for sequential and parallel implementations of the BPF method against the classic APF method, as well as with the Pseudo-Bacterial Potential Field (PBPF) method, and with the Genetic Potential Field (GPF) method, all of them based on evolutionary computation to optimize the APF parameters, were achieved. A simulation platform that uses an MR realistic model was designed to test the path planning algorithms. In general terms, it was demonstrated that the BPF outperforms the APF, GPF, and the PBPF methods by reducing the computational time to find the optimal path at least by a factor of 1.59. These results have a positive impact in the ability of the BPF path planning method to satisfy local and global controllability in dynamic complex environments, avoiding collisions with objects that will interfere the navigation of the MR.

266 citations

Journal ArticleDOI
01 Oct 2018-Symmetry
TL;DR: The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot.
Abstract: Good path planning technology of mobile robot can not only save a lot of time, but also reduce the wear and capital investment of mobile robot. Several methodologies have been proposed and reported in the literature for the path planning of mobile robot. Although these methodologies do not guarantee an optimal solution, they have been successfully applied in their works. The purpose of this paper is to review the modeling, optimization criteria and solution algorithms for the path planning of mobile robot. The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot. Finally, future research is discussed which could provide reference for the path planning of mobile robot.

199 citations


Cites background from "An Evolutionary Artificial Potentia..."

  • ...[57] proposed a modified APF approach for the path planning of mobile robot in a dynamic environment....

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Journal ArticleDOI
TL;DR: This innovative proposal integrates the original APF, evolutionary computation and parallel computation for taking advantages of novel processors architectures, to obtain a flexible path planning navigation method that takes all the advantages of using the APF and the EAPF, strongly reducing their disadvantages.
Abstract: In this paper, we introduce the concept of Parallel Evolutionary Artificial Potential Field (PEAPF) as a new method for path planning in mobile robot navigation. The main contribution of this proposal is that it makes possible controllability in complex real-world sceneries with dynamic obstacles if a reachable configuration set exists. The PEAPF outperforms the Evolutionary Artificial Potential Field (EAPF) proposal, which can also obtain optimal solutions but its processing times might be prohibitive in complex real-world situations. Contrary to the original Artificial Potential Field (APF) method, which cannot guarantee controllability in dynamic environments, this innovative proposal integrates the original APF, evolutionary computation and parallel computation for taking advantages of novel processors architectures, to obtain a flexible path planning navigation method that takes all the advantages of using the APF and the EAPF, strongly reducing their disadvantages. We show comparative experiments of the PEAPF against the APF and the EAPF original methods. The results demonstrate that this proposal overcomes both methods of implementation; making the PEAPF suitable to be used in real-time applications.

100 citations


Cites background or methods from "An Evolutionary Artificial Potentia..."

  • ...In [36] the simulation results show that the proposed EAPF methodology is efficient and robust for robot path planning with non-stationary goals and obstacles, also in [32] a new EAPF method for MR path planning in a dynamic environment is proposed, in that work the target and the obstacles are mov-...

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  • ...Figure 5a shows the case of having a local minima trap regardless it might exist a valid path to the target; in [32, 36, 38, 44], this problem was illustrated for different situations....

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  • ...The interaction with the real world requires the ability to respond and taking decisions over the changes in the environment, in [12, 32, 35, 36] some implementations with changing environments (world configuration) are presented....

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Journal ArticleDOI
TL;DR: These path planning algorithms that deal with constraints and characteristics of AUV and the influence of marine environments are described and some potential future research directions that are worthy to investigate in this field are proposed.

78 citations

Proceedings ArticleDOI
01 Dec 2008
TL;DR: The contributions of the work include the employment of the simulated annealing algorithm for robot path planning in dynamic environments, and the development of a new algorithm planner for enhancement of the efficiency of the path planning algorithm.
Abstract: This paper proposes a simulated annealing based approach to determine the optimal or near-optimal path quickly for a mobile robot in dynamic environments with static and dynamic obstacles. The approach uses vertices of the obstacles to define the search space. It processes off-line computation based on known static obstacles, and re-computes the route online if a moving obstacle is detected. The contributions of the work include the employment of the simulated annealing algorithm for robot path planning in dynamic environments, and the development of a new algorithm planner for enhancement of the efficiency of the path planning algorithm. The effectiveness of the proposed approach is demonstrated through simulations under typical dynamic environments and comparisons with existing methods.

71 citations


Cites methods from "An Evolutionary Artificial Potentia..."

  • ...We will discuss in detail the modelling of the environment, structure of the approach/algorithm, the generation of the initial feasible path, the new planner for generating the random path, and the procedure of the online computation....

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  • ...Traditionally, the path length Ef is the evaluation criterion for the quality of the path solution derived from the algorithm....

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  • ...The pseudo-code of the algorithm is as following: T = Tinitial; while (T > Tterminate) randomly generate one feasible solution Xs; evaluate Xs, Ef = f(Xs); count = 1; while (count < Threshold) generate a new feasible solution Xn base on Xs; evaluate Xn, En = f(Xn); if f(Xn) < f(Xs) Xs = Xn; else if…...

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References
More filters
Journal ArticleDOI
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Abstract: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to move in a straight line with an...

6,515 citations

Book
01 Jan 1990
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Abstract: 1 Introduction and Overview.- 2 Configuration Space of a Rigid Object.- 3 Obstacles in Configuration Space.- 4 Roadmap Methods.- 5 Exact Cell Decomposition.- 6 Approximate Cell Decomposition.- 7 Potential Field Methods.- 8 Multiple Moving Objects.- 9 Kinematic Constraints.- 10 Dealing with Uncertainty.- 11 Movable Objects.- Prospects.- Appendix A Basic Mathematics.- Appendix B Computational Complexity.- Appendix C Graph Searching.- Appendix D Sweep-Line Algorithm.- References.

6,186 citations

Book
01 Jul 1990
TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Abstract: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to move in a straight line with an...

3,063 citations

Journal ArticleDOI
TL;DR: A new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving is proposed and the problem of local minima is discussed.
Abstract: The potential field method is widely used for autonomous mobile robot path planning due to its elegant mathematical analysis and simplicity. However, most researches have been focused on solving the motion planning problem in a stationary environment where both targets and obstacles are stationary. This paper proposes a new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving. Firstly, the new potential function and the corresponding virtual force are defined. Then, the problem of local minima is discussed. Finally, extensive computer simulations and hardware experiments are carried out to demonstrate the effectiveness of the dynamic motion planning schemes based on the new potential field method.

808 citations

Journal ArticleDOI
01 Oct 2000
TL;DR: New repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.
Abstract: The paper first describes the problem of goals unreachable with obstacles nearby when using potential field methods for mobile robot path planning. Then, new repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.

773 citations