A PSO method for time-optimal motion planning of a mobile robot

Based on a particle swarm optimization (PSO) algorithm for time-optimal control problem of a two-wheeled mobile robot is addressed in this paper. The PSO algorithm is that it is easier to implement and there are fewer parameters to be adjusted. Different from usual cases, in which the Pontryagin's Minimum Principle (PMP) is used, an iterative procedure is proposed to transform the time-optimal problem into a nonlinear programming (NLP) one. Motion planning of a mobile robot is a NLP problem. In the NLP problem, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. Because the NLP has a initial feasible solutions problem that is not easier to find. In this paper, The PSO algorithm and fitness function to solve initial feasible solutions problem and optimal problem. To show the feasibility of the proposed method, simulation results are included for illustration.