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Enhanced Particle Swarm Optimisation for Multi-Robot Path Planning with Bezier Curve Smoothing

Yi-Ler Poy, Zhi-Yu Loke, Shalini Darmaraju, Choon‐Hian Goh, Ban-Hoe Kwan, Haipeng Liu, Danny Wee-Kiat Ng

发表年份
2024
引用次数
13
访问权限
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摘要

This paper presents an Enhanced Particle Swarm Optimisation (EPSO) algorithm to improve multi-robot path planning by integrating a new path planning scheme with a cubic Bezier curve trajectory smoothing algorithm. Traditional PSO algorithms often result in suboptimal paths with numerous turns, necessitating frequent stops and higher energy consumption. The proposed EPSO algorithm addresses these issues by generating smoother paths that reduce the number of turns and enhance the efficiency of multi-robot systems. The proposed algorithm was evaluated through simulations in two scenarios, and its performance was compared against the basic PSO algorithm. The results demonstrated that EPSO consistently produced shorter, smoother paths with fewer directional changes, albeit with slightly longer execution times. This improvement translates to more efficient navigation, reduced energy consumption, and enhanced overall performance of multi-robot systems. The findings underscore the potential of EPSO in applications requiring precise and efficient path planning, highlighting its contribution to advancing the field of robotics.

关键词

Bézier curveSmoothingMotion planningParticle swarm optimizationPath (computing)RobotComputer scienceParticle (ecology)SimulationMathematical optimization

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