摘要
针对因复杂地质环境障碍物较多,导致避障难度大的问题,以矿用自行走式掘进机器人为研究对象,提出基于人工势场的机器人自适应避障方法。以最快前进速度和目标方向统一保持度作为映射条件建立目标函数。利用蚁群算法获取掘进机器人与目标位置的最短距离。将复杂地质环境中的障碍物看作一个质点,并确定质点影响范围。计算质点坐标并查找距离其最近的目标点,添加子目标,使机器人到达质点影响范围内时快速以子目标为前进方向,实现自适应避障。实验结果表明,所提方法在复杂地质环境中的避障精准度较高、效果表现较佳。
In view of the difficulty of obstacle avoidance caused by many obstacles in a complex geological environment,a self-adaptive obstacle avoidance method based on artificial potential field is proposed by taking mine self-propelled tunneling robot as the research object.The objective function is established by taking the fastest forward speed and the unified retention degree of the target direction as the mapping conditions.The ant colony algorithm is used to obtain the shortest distance between the tunneling robot and the target position.The obstacle in the complex geological environment is regarded as a particle,and the influence range of the particle is determined.The particle coordinates is calculated and the nearest target point is found,sub targets are added,so that when the robot reaches the particle influence range,it can quickly take the sub target as the forward direction,and realize adaptive obstacle avoidance.The experimental results show that the proposed method has high accuracy and good performance in obstacle avoidance in complex geological environments.
作者
刘晓亮
任文清
马平
赵俊达
周立军
LIU Xiao-liang;REN Wen-qing;MA Ping;ZHAO Jun-da;ZHOU Li-jun(CHN Energy Shendong Coal Group Co.,Ltd.,Shenmu 719315,China;CCTEG Tangshan Research Institute Co.,Ltd.,Tangshan 063000,China)
出处
《煤炭工程》
北大核心
2022年第S01期210-214,共5页
Coal Engineering
关键词
复杂地质环境
矿用自行走式掘进机器人
自适应避障
蚁群算法
complex geological environment
mining self-propelled tunneling robot
adaptive obstacle avoidance
ant colony
