A hierarchical genetic algorithm for path planning in a static environment with obstacles

Abstract

In this paper, a new hierarchical genetic algorithm for path planning in a static environment with obstacles is presented. The algorithm of path planning in this paper is inspired by the Dubins' theorem regarding shortest paths of bounded curvature in the absence of obstacles. The algorithm is based on the Dubins' theorem to simplify the problem model, the genetic algorithm to search the best path, a special hierarchical structure of chromosome to denote a possible path in the environment, the special genetic operators for each module, and a penalty strategy to punish the infeasible chromosomes during searching. The performance results presented have shown that the approach is able to produce high quality solutions in reasonable time.