基于环境点云的矿用挖掘机器人自主作业规划

Autonomous Operation Planning of Mining Robot Based on Environmental Point Cloud

针对传统矿用挖掘机难以在复杂矿岩环境下高效开采的问题,基于环境的雷达点云信息提出一种在面对复杂堆料时挖掘机器人的自主作业规划方法,以实现其连续、高效的自主化采掘任务。该方法首先利用挖掘机器人的激光雷达对复杂未知的物料环境形貌进行建模分析,通过点云信息的特点识别并筛选不同的物料堆面,然后采用多项式插值的方法对不同物料堆面的挖掘轨迹进行在线规划。结果表明,基于环境点云的自主规划方法能够使挖掘机器人在满足满斗率的条件下对不同的物料堆面实现快速有效的自主作业规划,并保证挖掘机器人连续高效的挖掘作业,对复杂工况环境下矿用挖掘机自主化的高效开采方面的研究有很大的指导意义。

Aiming at the problem that traditional excavators are difficult to mine efficiently in complex rock environments,an autonomous operation planning method is designed for mining robots in the face of complex piles to achieve its continuous and efficient autonomous operation task based on the radar point cloud information of environment.This method firstly used the radar of the robot to model and analyze the complex and unknown material environment morphology.The point cloud information is used to identify and filter different material stacking surfaces,and the mining trajectories of different material stacking surfaces are planned online by polynomial interpolation.The results show that the autonomous planning method based on environmental point cloud can enable the mining robot to realize fast and effective autonomous operation planning for different material stacking surfaces under the condition of satisfying the full bucket rate,which has great guiding significance for the research on intelligent and efficient mining of excavators under complex woking conditions.