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作 者:商德勇[1,2,3] 汪俊杰 樊虎 索双富 SHANG Deyong;WANG Junjie;FAN Hu;SUO Shuangfu(School of Mechanical,Electronic&Information Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China;Institute of intelligent Mining&Robotics,China University of Mining and Technology(Beijing),Beijing 100083,China;Key Laboratory of Intelligent Mining and Robotics,Ministry of Emergency Management,Beijing 100083,China;Department of Mechanical Engineering,Tsinghua University,Beijing 100081,China)
机构地区:[1]中国矿业大学(北京)机电与信息工程学院,北京100083 [2]中国矿业大学(北京)智慧矿山与机器人研究院,北京100083 [3]煤矿智能化与机器人创新应用应急管理部重点实验室,北京100083 [4]清华大学机械工程系,北京100081
出 处:《计算机集成制造系统》2024年第3期1149-1160,共12页Computer Integrated Manufacturing Systems
基 金:国家自然科学基金面上资助项目(52174154);国家自然基金创新研究群体资助项目(52121003);中央高校基本科研业务费专项资金资助项目(2022YQJD21)。
摘 要:为使机械臂在障碍物环境下快速规划较优路径,提出了一种基于动态区域采样的改进RRT^(*)-DR路径规划算法,将整个规划过程分为快速探索路径和优化初始路径两个步骤。首先利用半目标导向扩展快速探索,找到连接起始点和目标点的路径。随后利用动态区域采样方法,始终在当前最优路径的周边范围内采样,优先密化当前最优路径附近的节点树,节省计算资源,使初始路径经过迭代快速向渐进最优路径收敛。同时,提出一种近障碍节点变步长机制,有选择性地缩短靠近障碍节点的扩展步长,可有效减少碰撞检测失败次数,提高算法效率。最后,在MATLAB和ROS系统下进行路径规划算法仿真,结果表明RRT^(*)-DR算法可在更短时间内实现路径规划,同时有效缩小路径代价。进一步通过实体机器人路径规划避障实验,验证了该算法的实用性和有效性。To quickly plan a better path for the manipulator in the obstacles environment,a kind of improved RRT^(*)-DR path planning algorithm based on RRT^(*)was proposed.The entire planning process was divided into two steps:fast exploration of path and optimization of the initial path.A path connecting the starting point and target was found by exploring quickly with a half-goal-guiding expanding mechanism.Then,the dynamic region sampling method was used to always sample in the surrounding range of the current optimal path,and the node tree near the current optimal path was densified,which saved computing resources and made the initial path converge to the asymptotic optimal path quickly through iteration.At the same time,a variable step size mechanism for obstacle-nearing nodes was proposed,which selectively reduced the extended step size of the obstacle-nearing nodes,effectively reduced the number of collision detection failures,and improved the algorithm efficiency.The simulation results of MATLAB and the Robot Operating System(ROS)showed that the improved algorithm RRT^(*)-DR could optimize the path in a shorter time,and effectively reducing the path cost.Furthermore,the practicability and effectiveness of the algorithm were verified by the path planning and obstacle avoidance experiment of the real manipulator.
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
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