A new potential field method for mobile robot path planning in the dynamic environments

2009 ◽  
Vol 11 (2) ◽  
pp. 214-225 ◽  
Author(s):  
Lu Yin ◽  
Yixin Yin ◽  
Cheng-Jian Lin
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Potential Field ◽  
Dynamic Environments ◽  
Field Method ◽  
Robot Path Planning ◽  
Potential Field Method ◽  
Robot Path

scholarly journals An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot

2015 ◽  
Vol 15 (2) ◽  
pp. 181-191 ◽  
Author(s):  
Wenbai Chen ◽  
Xibao Wu ◽  
Yang Lu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Potential Field ◽  
Field Method ◽  
Artificial Potential Field ◽  
Improved Method ◽  
Chaos Optimization ◽  
Potential Field Method ◽  
Artificial Potential Field Method ◽  
Robot Path

Abstract To solve the problem of local minima and unreachable destination of the traditional artificial potential field method in mobile robot path planning, chaos optimization is introduced to improve the artificial potential field method. The potential field function was adopted as a target function of chaos optimization, and a kind of “two-stage” chaos optimization was used. The corresponding movement step and direction of the robot were achieved by chaos search. Comparison of the improved method proposed in this paper and the traditional artificial potential field method is performed by simulation. The simulation results show that the improved method gets rid of the drawbacks, such as local minima and unreachable goal. Furthermore, the improved method is also verified by building up a physical platform based on “Future Star” robot. The success of the physical experiment indicates that the improved algorithm is feasible and efficient for mobile robot path planning.

A Potential Field Method for Path Planning Into Cavities Defined by B-Splines

1998 ◽  
Author(s):  
Alley C. Butler ◽  
Steven R. LeClair
Keyword(s):  
Path Planning ◽  
Potential Function ◽  
Potential Field ◽  
Robot Manipulator ◽  
Field Method ◽  
Robot Path Planning ◽  
B Splines ◽  
Field Approach ◽  
Potential Field Method ◽  
Robot Path

Abstract This paper describes a potential field approach to robot path planning into cavities defined by B-splines. It discusses existing methods, and describes the development of a Voronoi tree using intersecting hodographs. The Voronoi tree is similar to the Voronoi diagram in that it is maximally distant from all objects in the robot’s environment, but the Voronoi tree is developed for cavities modeled by splines. By adding a potential field to the robot manipulator, a robot path can be found by seeking the manipulator position with the minimum value of the potential function. This position as defined by the potential field is also maximally distant from cavity walls. Results with the potential field method are discussed and conclusions are drawn.

The Study of Soccer Robot Path Planning Based on Grid-Based Potential Field Method Improvements

2010 ◽  
Vol 139-141 ◽  
pp. 1798-1802 ◽  
Author(s):  
Xiao Jun Zhao ◽  
Jia Bi ◽  
Meng Zhe Liu ◽  
Lei Chen
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Grid Method ◽  
Field Method ◽  
Robot Path Planning ◽  
Soccer Robot ◽  
Potential Field Method ◽  
Dynamic Potential ◽  
Grid Based ◽  
Robot Path

An improved dynamic Grid-based potential field method was proposed based on the consideration that the goal, robot and obstacles in robot soccer compete are all dynamic. We combined the advantages of potential field method and the grid method, set the grid method to represent the environment, and got dynamic potential function in the potential field method. We used dynamic potential function to form the inspire function of the search algorithm A* which is used for the search of adjacent nodes. The dynamic Grid-based potential field method meets the real-time planning requirements in the complex and dynamic environment. And it has received very good results in solving the local minima problem of the traditional potential field and improving the planning efficiency. It is better in security and reliability. Simulation results show that the method is feasible and effective in soccer robot path planning.

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