首页 /研究 /Path Planning for Mobile Robot Based on Improved Simulated Annealing Artificial Neural Network
LEARNING

Path Planning for Mobile Robot Based on Improved Simulated Annealing Artificial Neural Network

Meijuan Gao, Jingwen Tian

发表年份
2007
引用次数
23

摘要

A mobile robot path planning method based on improved simulated annealing algorithm and artificial neural network is proposed. First the simulated annealing algorithm with the best reserve mechanism is introduced and it is combined with Powell algorithm to form improved simulated annealing mixed optimize algorithm which not only add the good solution protective measures but also improve the convergence rate of simulated annealing algorithm. Then we take the obstacle collision penalty function which expressed using neural network and the path length as the energy function of improved simulated annealing mixed optimize algorithm, thereby the solution which obtained by the improved simulated annealing mixed optimize algorithm can not only satisfy the path shortest but also effective avoid the collision with obstacle. The simulation result shows that the proposed method is feasible and valid.

关键词

Simulated annealingMotion planningAdaptive simulated annealingComputer scienceObstacleArtificial neural networkMathematical optimizationMobile robotShortest path problemObstacle avoidance

相关论文

查看 LEARNING 分类全部论文