摘要
针对煤矿灾害发生后复杂的矿井环境,提出一种用于救援机器人的分级扩展式快速扩展随机树(CERRT)算法。该方法利用快速扩展随机树(RRT)算法在未知环境中规划路径的优势,将分级扩展的思想融入到RRT算法中,具有在未知环境中避开障碍物快速找到目标的特点。仿真验证了该方法的有效性,与传统方法比较,路径规划速度和避障能力得到了提高,缩短了找到目标的时间。该方法也可为钼矿、铜矿等其他矿井的救援机器人寻找目标提供参考。
According to the complicated mine environment when a mine disaster occurred,a class expansion type rapid expanded random tree（CERRT） algorithm for the mine rescue robot was provided.With the planning route advantages of the rapid expanded random RRT tree algorithm in the unknown environment,the method could apply the class expansion idea into the RRT algorithm and could have the features to avoid obstacles and rapidly seek the target in the unknown environment.The simulation was applied to prove the affectivity of the method.In comparison with the conventional method,the route planning and the avoiding obstacle capacity of the method was improved and the time to seek the target was reduced.This method could provide the references for the rescue robot seeking the target in the molybdenum mine,the copper mine and other mines.
出处
《煤炭科学技术》
CAS
北大核心
2011年第10期90-92,21,共4页
Coal Science and Technology
