Multi-robot Path Planning Based on Cooperative Co-evolution and Adaptive CGA

2006 ◽  
Author(s):  
Jinyin Chen ◽  
Dongyong Yang ◽  
Naofumi Matsumoto ◽  
Yuzo Yamane
Keyword(s):  
Path Planning ◽  
Robot Path Planning ◽  
Robot Path ◽  
Multi Robot

Research and Implementation of Multi-robot Path Planning Based on Genetic Algorithm

2021 ◽  
Author(s):  
Mengqing Fan ◽  
Jiawang He ◽  
Susheng Ding ◽  
Yuanhao Ding ◽  
Meng Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Robot Path Planning ◽  
Robot Path ◽  
Multi Robot

scholarly journals Multi-robot path planning using an improved self-adaptive particle swarm optimization

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142093615
Author(s):  
Biwei Tang ◽  
Kui Xiang ◽  
Muye Pang ◽  
Zhu Zhanxia
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Evolutionary Game ◽  
Particle Swarm ◽  
Computation Time ◽  
Robot Path Planning ◽  
Swarm Optimization ◽  
Robot Path ◽  
Self Adaptive ◽  
Multi Robot

Path planning is of great significance in motion planning and cooperative navigation of multiple robots. Nevertheless, because of its high complexity and nondeterministic polynomial time hard nature, efficiently tackling with the issue of multi-robot path planning remains greatly challenging. To this end, enhancing a coevolution mechanism and an improved particle swarm optimization (PSO) algorithm, this article presents a coevolution-based particle swarm optimization method to cope with the multi-robot path planning issue. Attempting to well adjust the global and local search abilities and address the stagnation issue of particle swarm optimization, the proposed particle swarm optimization enhances a widely used standard particle swarm optimization algorithm with the evolutionary game theory, in which a novel self-adaptive strategy is proposed to update the three main control parameters of particles. Since the convergence of particle swarm optimization significantly influences its optimization efficiency, the convergence of the proposed particle swarm optimization is analytically investigated and a parameter selection rule, sufficiently guaranteeing the convergence of this particle swarm optimization, is provided in this article. The performance of the proposed planning method is verified through different scenarios both in single-robot and in multi-robot path planning problems. The numerical simulation results reveal that, compared to its contenders, the proposed method is highly promising with respect to the path optimality. Also, the computation time of the proposed method is comparable with those of its peers.

Multi-robot path planning for smart access of distributed charging points in map

2020 ◽  
Author(s):  
Abhijeet Ravankar ◽  
Ankit A. Ravankar ◽  
Michiko Watanabe ◽  
Yohei Hoshino ◽  
Arpit Rawankar
Keyword(s):  
Path Planning ◽  
Robot Path Planning ◽  
Robot Path ◽  
Multi Robot
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