工矿自动化2024，Vol.50Issue(5)：6-13,8.DOI:10.13272/j.issn.1671-251x.2024030014
基于改进人工势场算法的煤矿井下机器人路径规划
Path planning of coal mine underground robot based on improved artificial potential field algorithm
摘要
Abstract
Path planning is one of the key technologies that urgently need to be solved in the application of coal mine robots in narrow underground roadways.A path planning method for coal mine robots based on improved APF algorithm is proposed to address the issues of traditional artificial potential field(APF)algorithms that planning paths in narrow roadway environments may be too close to the roadway boundary,as well as the possibility of unreachable targets and path oscillations near obstacles.Referring to the relevant provisions of the Coal Mine Safety Regulations,the boundary potential field between the two sides of the roadway is established.The robot's path is planned as much as possible in the middle of the roadway to improve the safety of robot travel.The method introduces regulatory factors into the repulsive potential field of obstacles to solve the problem of unreachable targets.The method introduces corner constraint coefficients to smooth the planned path,reduce oscillations,improve planning efficiency,and ensure the safety of the planned path.The simulation results show that when the target point is very close to the obstacle,the improved APF algorithm can successfully plan a path that can reach the target point.The improved APF algorithm reduces the planning cycle by an average of 14.48%compared to traditional algorithms.The cumulative value of steering angle reduces by an average of 87.41%,and the sum of absolute curvature values is reduced by an average of 78.09%.The results indicate that the improved APF algorithm plans smoother paths,shorter path lengths,and has higher planning efficiency and safety.关键词
煤矿机器人/路径规划/人工势场法/目标不可达/路径振荡/斥力势场修正/转角限制系数Key words
coal mine robots/path planning/artificial potential field method/target unreachable/path oscillation/correction of repulsive potential field/corner restriction coefficient分类
矿业与冶金引用本文复制引用
薛光辉,王梓杰,王一凡,李亚男,刘文海..基于改进人工势场算法的煤矿井下机器人路径规划[J].工矿自动化,2024,50(5):6-13,8.基金项目
国家自然科学基金项目面上项目(51874308) （51874308）
国家重点基础研究发展计划(973计划)项目(2014CB046306). （973计划）
