Mobile Robot Global Path Planning Using Hybrid Modified Simulated Annealing Optimization Algorithm

被引：0
|
作者：
Liang, Yuming [1 ]
Xu, Lihong [1 ]
机构：
[1] Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China
来源：
WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) | 2009年
关键词：
Modified Simulated Annealing Algorithm; Conjugate Direction Method; Mobile Robot; Global Path Planning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：309 / +
页数：5
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