A Modified Membrane-Inspired Algorithm Based on Particle Swarm Optimization for Mobile Robot Path Planning

Xueyuan Wang, Gexiang Zhang, Junbo Zhao, Haina Rong, Florentin Ipate, Raluca Lefticaru

Abstract


To solve the multi-objective mobile robot path planning in a dangerous environment with dynamic obstacles, this paper proposes a modified membraneinspired algorithm based on particle swarm optimization (mMPSO), which combines membrane systems with particle swarm optimization. In mMPSO, a dynamic double one-level membrane structure is introduced to arrange the particles with various dimensions and perform the communications between particles in different membranes; a point repair algorithm is presented to change an infeasible path into a feasible path; a smoothness algorithm is proposed to remove the redundant information of a feasible path; inspired by the idea of tightening the fishing line, a moving direction adjustment for each node of a path is introduced to enhance the algorithm performance. Extensive experiments conducted in different environments with three kinds of grid models and five kinds of obstacles show the effectiveness and practicality of mMPSO.

Keywords


Membrane computing, evolutionary membrane computing, particle swarm optimization, variable dimensions, mobile robot path planning, membrane systems

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DOI: https://doi.org/10.15837/ijccc.2015.5.2030



Copyright (c) 2017 Xueyuan Wang, Gexiang Zhang, Junbo Zhao, Haina Rong, Florentin Ipate, Raluca Lefticaru

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