运动规划
强化学习
机器人
路径(计算)
搜救
计算机科学
启发式
人工智能
国家(计算机科学)
救援机器人
搜索算法
移动机器人
数学优化
算法
数学
计算机网络
作者
Tao Pang,Xiao Gang Ruan,Er Shen Wang,Rui Yuan Fan
出处
期刊:Applied Mechanics and Materials
[Trans Tech Publications, Ltd.]
日期:2012-12-01
卷期号:241-244: 1682-1687
被引量:1
标识
DOI:10.4028/www.scientific.net/amm.241-244.1682
摘要
For the path planning problem of search and rescue robot in unknown environment, a bionic learning algorithm was proposed. The GSOM (Growing Self-organizing Map) algorithm was used to build the environment cognitive map. The heuristic search A* algorithm was used to find the global optimal path from initial state to target state. When the local environment was changed, reinforcement learning algorithm based on sensor information was used to guide the search and rescue robot behavior of local path planning. Simulation results show the method effectiveness.
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