An implementation of evolutionary computation for path planning of cooperative mobile robots

摘要

This article describes how to apply a genetic algorithm in finding a globally sub-optimal path for the robot group working under certain tasks. Path planning is an important problem in robotics. With the development of cooperative robotics in recent years, the problem of path planning for a robot group is receiving more and more attention and interest. In this paper, the problem of path planning for a robot group is formalized as a multiple travelling salesman problem (MTSP) that employed either total-path-shortest or longest-path-shortest as the evaluating criterion. Longest-path-shortest MTSP has never been studied before. The formalized models of the two kinds of multiple travelling salesman problem are presented in this paper, and the main idea and specific way of applying the genetic algorithm in solving the two kinds of travelling salesman problem or their admixture are also amply discussed in this paper. At the end the convergence analysis and the simulation are discussed, as the simulation result shows, it is an effective and robust way of solving the problem of path planning for a robot group.