Multi-objective optimization path planning with moving target

Path planning or finding a collision-free path for mobile robots between starting position and its destination is a critical problem in robotics. This study is concerned with the multi objective optimization path planning problem of autonomous mobile robots with moving targets in dynamic environment, with three objectives considered: path security, length and smoothness. Three modules are presented in the study. The first module is to combine particle swarm optimization algorithm (PSO) with bat algorithm (BA). The purpose of PSO is to optimize two important parameters of BA algorithm to minimize distance and smooth the path. The second module is to convert the generated infeasible points into feasible ones using a new local search algorithm (LS). The third module obstacle detection and avoidance (ODA) algorithm is proposed to complete the path, which is triggered when the mobile robot detects obstacles in its field of vision. ODA algorithm based on simulating human walking in a dark room. Several simulations with varying scenarios are run to test the validity of the proposed solution. The results show that the mobile robots are able to travel clearly and completely safe with short path, and smoothly proving the effectiveness of this method.