基于Q-learning算法的煤矿井下移动机器人路径算法研究与展望

Coal Mine Underground Based on Q-learning Algorithm of Mobile Robot Path Planning

文章研究了Q-learning算法,并且基于该算法,对煤矿井下机器人的移动路径进行了规划,并且对规划方案进行了仿真分析,通过研究发现Q-learning算法的路径规划能力优越,特别是对于条件极为恶劣、工况十分复杂的煤矿井下作业环境而言,能够较好地获取满意的规划结果。

This paper studies the Q-learning algorithm, and based .on this algorithm, the coal mine underground robot moving path for the planning, and to plan a simulation analysis was carried out, through the study found that the Q-learning algorithm path planning ability is superior, especially for condition is very bad, very complex conditions of coal mine underground work environment is concerned, to better obtain satisfactory planning results.