Mobile robot global path planning using hybrid modified simulated annealing optimization 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

Citing 2
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Abstract

Global path planning for mobile robot using 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 conjugate direction method is proposed. On each temperature, conjugate direction method is utilized for searching local optimal solution firstly, then the modified simulated annealing algorithm is employed to move off local optimal solution, and then the temperature is updated; these operations are repeated until a termination criterion is satisfied. Experimental results indicate that the proposed algorithm has better performance than simulated annealing algorithm and conjugate direction method in term of both solution quality and computational time, and thus it is a viable approach to mobile robot global path planning.