An improved path planning approach based on Particle Swarm Optimization

Abstract

In this paper, an improved path planning scheme based on Particle Swarm Optimization and Ferguson Splines is proposed. Firstly, a string of Ferguson Splines are used to describe a path for a mobile robot, and the path planning problem is then equivalent to the optimization of parameters of particular cubic Ferguson splines. Secondly, an improved Particle Swarm Optimization Algorithm, which performs well in avoiding the premature convergence problem, is introduced to optimize the path. The experimental results illustrate the reasonability and great practical value of the proposed path planning scheme. A collision-avoiding smooth optimal path can be planned automatically within 60 iterations.