The improved potential grid method in robot path planning

This paper presents an improved ant colony algorithm to plan an optimal collision-free path for mobile robot in complicated static environment. Based on the work space model with grid method, simulated foraging behavior of ants and to serve the mobile robot path planning, update the conventional ant colony algorithm with some special functions. To avoid mobile robot path deadlock, a dead-corner table is established and the penalty function is used to update the trail intensity when an ant explores a dead—corner in the path searching. The simulation results show that the algorithm can improve performance of path planning obviously, and the algorithm is simple and effective.

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

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.139-141.1798 ◽

2010 ◽

Vol 139-141 ◽

pp. 1798-1802 ◽

Cited By ~ 1

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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A Biological Inspired Neural Network Approach to Robot Path Planning in Unknown Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.1399 ◽

2014 ◽

Vol 602-605 ◽

pp. 1399-1402 ◽

Cited By ~ 1

Author(s):

Bo Zhu ◽

Zhong Min Wang ◽

Zhao Lin Liu

Keyword(s):

Path Planning ◽

Mobile Robot ◽

Grid Method ◽

Robot Path Planning ◽

Simulation Experiments ◽

Neural Network Approach ◽

Environmental Models ◽

Whole Space ◽

Complete Path ◽

Robot Path

Aiming to solve the problem of mobile robot path planning, environmental models are established by using grid method at first, each grid is treated as a neuron, and then the whole space is changed into a topology-form one with all neutral net. Secondly, biological inspired neural networks (BINN) method towards neutral net is adopted to complete path planning of mobile robot. Furthermore, non-optimal solutions potentially produced in neutral net are modified in BINN. Simulation experiments show the feasibility and effectiveness of BINN method.

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