PSO-DVSF -mt: AN OPTIMIZED MOBILE ROBOT MOTION PLANNING APPROACH FOR TRACKING MOVING TARGETS

Safa Ziadi and Mohamed Njah

Keywords

PSO-DVSF2-mt, PSO-DVSF2, robot motion planning, moving tar-get, dynamic environments, APF and GA-DVSF2-mt

Abstract

The particle swarm optimization dynamic variable speed force field (PSO-DVSF2) is a mobile robot motion planning approach that we have previously proposed for static and dynamic environments with a fixed target. In this paper, the capacities of PSO-DVSF2 are expanded to cover moving targets in known environments. We affect to the new motion planning approach the name “PSO-DVSF2- mt”(PSO-DVSF2 for moving targets). PSO-DVSF2-mt designs an optimal path for a mobile robot to attain a moving target whatever the environment (static or dynamic). PSO continually changes the parameters of DVSF2-mt and the velocity of the robot to find a secure path that brings it closer to the moving target while avoiding static and dynamic obstacles. Simulation results prove the efficacy of this new version of PSO-DVSF2 to follow moving targets. Also, a comparative study with the famous artificial potential field and genetic algorithm (GA)-DVSF2-mt motion planning approaches prove the quality of the solution delivered with PSO-DVSF2-mt. We name GA-DVSF2-mt a motion planning approach identical to PSO-DVSF2-mt but optimized with GA instead of PSO.

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