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http://dx.doi.org/10.9723/jksiis.2019.24.5.115

Statistical Analysis of Receding Horizon Particle Swarm Optimization for Multi-Robot Formation Control  

Lee, Seung-Mok (계명대학교 기계자동차공학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.24, no.5, 2019 , pp. 115-120 More about this Journal
Abstract
In this paper, we present the results of the performance statistical analysis of the multi-robot formation control based on receding horizon particle swarm optimization (RHPSO). The formation control problem of multi-robot system can be defined as a constrained nonlinear optimization problem when considering collision avoidance between robots. In general, the constrained nonlinear optimization problem has a problem that it takes a long time to find the optimal solution. The RHPSO algorithm was proposed to quickly find a suboptimal solution to the optimization problem of multi-robot formation control. The computational complexity of the RHPSO increases as the number of candidate solutions and generations increases. Therefore, it is important to find a suboptimal solution that can be used for real-time control with minimal candidate solutions and generations. In this paper, we compared the formation error according to the number of candidate solutions and the number of generations. Through numerical simulations under various conditions, the results are analyzed statistically and the minimum number of candidate solutions and the minimum number of generations of the RHPSO algorithm are derived within the allowable control error.
Keywords
Collision avoidance; Model predictive control; Multi-robot; Formation control; Receding horizon control; Particle swarm optimization;
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Times Cited By KSCI : 3  (Citation Analysis)
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