Research Of Path Planning For Mobile Robots Based On Chaos Genetic Optimization

Path planning for mobile robots is a complex problem that not only guarantees a collision-free path with minimum traveling distance but also requires smoothness and security. This dissertation presents a chaos genetic algorithm for solving the path planning problem in static mobile robot environments.Firstly, the paper summarizes and analyzes the current development and research method of path planning in several active areas. Secondly, the paper develops a chaos genetic algorithm, a hybrid of genetic and chaos algorithm, by analyzing and comparing the advantages and disadvantages of them. The new algorithm has better capability of searching globally and locally. Thirdly, according to the characteristic of path planning problem, every component of the algorithm is researched carefully, including environment representation, chromosome coding, fitness function design, genetic operators design and chaos genetic algorithm parameters selection etc. Finally, simulate experiment are finished in three static environment. drawing on the concept of quantitative analysis and evaluation in engineering optimization, the paper introduces two separate indicators, i.e., truncated generation and its distribution entropy, to evaluate the efficiency of optimization. In addition, the paper emphasizes that different parameters and the fitness function coefficients have a great effect on path planning, chaos genetic algorithm is compared and analyzed with other algorithms as well.It's proved that the algorithm can plan an approximate optimal path successfully in different static environment, and validate the effectiveness of the proposed approach.