摘要 : The particle swarm optimization dynamic variable speed force field (PSO-DVSF~2) is a mobile robot motion planning approach that we have previously proposed for static and dynamic environments with a fixed target. In this paper, th... 展开 The particle swarm optimization dynamic variable speed force field (PSO-DVSF~2) 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-DVSF~2 are expanded to cover moving targets in known environments. We affect to the new motion planning approach the name "PSO-DVSF~2-mt" (PSO-DVSF~2 for moving targets). PSO-DVSF~2-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 DVSF~2-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-DVSF~2 to follow moving targets. Also, a comparative study with the famous artificial potential field and genetic algorithm (GA)-DVSF~2-mt motion planning approaches prove the quality of the solution delivered with PSO-DVSF~2-mt. We name GA-DVSF~2-mt a motion planning approach identical to PSO-DVSF~2-mt but optimized with GA instead of PSO. 收起