摘要
为避免机器人碰撞对施工进程与安全带来的威胁,激发机器人在装配式建筑中的巨大潜力,提出一种激光传感自适应装配式建筑机器人轨迹规划方法。构建某装配式建筑网格地图,并由激光传感器获取机器人外围环境数据,利用改进A*算法去除冗余节点,使路径只包括起、终和关键点;结合动态窗口和蚁群算法进行局部轨迹规划,并计算目标速度完成全局规划。在某装配式建筑网格地图中完成实验验证,在静态网格环境中,本方法可在165次迭代和3.16s内,规划出38.6m的路径;在动态网格环境中,本方法则可在248次迭代和3.81s内,躲避动态障碍物。结果表明本方法的路径比文献方法[5,6]更平滑,可在较少的时长和迭代数目内规划出较短的路径。
In order to avoid the threat of robot collision to construction process and safety, and stimulate the great potential of robots in prefabricated buildings, a laser sensing adaptive trajectory planning method for prefabricated building robots is proposed. The grid map of a prefabricated building is constructed, and the peripheral environment data of the robot is obtained by the laser sensor. The improved A~* algorithm is used to remove redundant nodes, so that the path only includes the beginning, end and key points. The dynamic window and ant colony algorithm are used for local trajectory planning, and the target velocity is calculated to complete the global planning. The experimental results are verified in the grid map of a prefabricated building. In the static grid environment, the proposed method can plan a 38.6m path in 165 iterations and 3.16s. In a dynamic grid environment, this method can avoid dynamic obstacles in 248 iterations and 3.81s. The results show that the path of this method is smoother than that of the literature method[5,6], and a shorter path can be planned in less time and number of iterations.
作者
张茜
王平
ZHANG Qian;WANG Ping(Mianyang Vocational and Technical College,Mianyang 621000,China;College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou University of Technology,Lanzhou 730050,China)
出处
《光学技术》
CAS
CSCD
北大核心
2024年第5期598-605,共8页
Optical Technique
基金
国家自然科学基金(62361039)
甘肃省工业过程先进控制重点实验室开放基金(2022KX02)。
关键词
装配式建筑
激光传感
轨迹规划
蚁群
动态窗口
prefabricated building
laser sensing
trajectory planning
ant colony
dynamic window
作者简介
张茜(1985-),女,讲师,本科,从事建筑施工机器人技术研究。zhangqianmyzy@163.com;通讯作者:王平(1989-),男,副教授,博士,硕士生导师,从事深度学习、机器人控制研究。zhangqianmyzy@163.com。
