Global path planning for mobile robot based genetic algorithm and modified simulated annealing algorithm

Authors:
Yuming Liang;Lihong Xu
Affiliations:
School of Electronics and Information Engineering, Tongji University, Shanghai, China;School of Electronics and Information Engineering, Tongji University, Shanghai, China
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

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Abstract

Global path planning for mobile robot using genetic algorithm and simulated annealing algorithm is investigated in this paper. In view of the slow convergence speed of the conventional simulated annealing algorithm, a modified simulated annealing algorithm is presented, and a hybrid algorithm based on the modified simulated annealing algorithm and genetic algorithm is proposed. The proposed algorithm includes three steps: the MAKLINK graph theory is adopted to establish the free space model of mobile robots firstly, then Dijkstra algorithm is utilized for finding a feasible collision-free path and fixing on the sub-search-space where the global optimal path inside, finally the global optimal path of mobile robots is obtained based on the hybrid algorithm of modified simulated annealing algorithm and genetic algorithm. Experimental results indicate that the proposed algorithm has better performance than simulated annealing algorithm and ant system algorithm in term of both solution quality and computational time, and thus it is a viable approach to mobile robot global path planning.