首页> 外文会议>Proceedings of the First ACM/SIGEVO Summit on Genetic and Evolutionary Computation >Mobile robot global path planning using hybrid modified simulated annealing optimization algorithm
【24h】

Mobile robot global path planning using hybrid modified simulated annealing optimization algorithm

机译:基于混合改进模拟退火优化算法的移动机器人全局路径规划

获取原文
获取原文并翻译 | 示例

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.
机译:研究了基于模拟退火算法的移动机器人全局路径规划。针对传统模拟退火算法收敛速度慢的问题,提出了一种改进的模拟退火算法,并提出了一种基于改进的模拟退火算法和共轭方向法的混合算法。在每种温度下,首先采用共轭方向法搜索局部最优解,然后采用改进的模拟退火算法移出局部最优解,然后对温度进行更新。重复这些操作,直到满足终止条件为止。实验结果表明,该算法在求解质量和计算时间上均优于模拟退火算法和共轭方向法,是一种可行的移动机器人全局路径规划方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号