[1]PU Xingcheng,LI Junjie,WU Huichao,et al.Mobile robot multi-goal path planning using improved particle swarm optimization[J].CAAI Transactions on Intelligent Systems,2017,12(3):301-309.[doi:10.11992/tis.201606046]
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Mobile robot multi-goal path planning using improved particle swarm optimization

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 12 Number of periods: 2017 3 Page number: 301-309 Column: 学术论文—智能系统 Public date: 2017-06-25
Title:
Mobile robot multi-goal path planning using improved particle swarm optimization
Author(s):
PU Xingcheng1;  LI Junjie2;  WU Huichao2;  ZHANG Yi3
1. School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2. Research Center of Intelligent System and Robot, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
3. Advanced Manufacturing Engineering School, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Keywords:
mobile robot; multi-goal path planning; ACO; improved PSO; opposition-based learning; inertia weight; learning factors
CLC:
TP242.6
DOI:
10.11992/tis.201606046
Abstract:
To solve the problem of multi-goal path planning for mobile robots that pass multiple goals, a new path planning method, based on improved particle swarm optimization (PSO) and ant colony optimization (ACO), is proposed. In this new method, the first step is to use an improved PSO, which has high convergence, to optimize the path between two goals among a sequence of goals. The second step is to use the ACO to obtain the shortest path for all target points. The performance experimental result demonstrates that the improved PSO algorithm can effectively avoid premature convergence and enhances search ability and stability. Simulation results show that the improved PSO algorithm can make a mobile robot realize collision-free multi-goal path planning effectively . Experiments in a real environment demonstrate that this algorithm has practical application for multi-goal path planning.
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