李龙, 陈禾炜, 汪田鸿, 张泉, 王国鹏, 田应仲, 彭艳, 罗均. 基于接近觉的机械臂避障路径规划[J]. 机器人, 2022, 44(5): 601-612. DOI: 10.13973/j.cnki.robot.210302
引用本文: 李龙, 陈禾炜, 汪田鸿, 张泉, 王国鹏, 田应仲, 彭艳, 罗均. 基于接近觉的机械臂避障路径规划[J]. 机器人, 2022, 44(5): 601-612. DOI: 10.13973/j.cnki.robot.210302
LI Long, CHEN Hewei, WANG Tianhong, ZHANG Quan, WANG Guopeng, TIAN Yingzhong, PENG Yan, LUO Jun. Obstacle Avoidance Path Planning of Manipulator Based on Proximity[J]. ROBOT, 2022, 44(5): 601-612. DOI: 10.13973/j.cnki.robot.210302
Citation: LI Long, CHEN Hewei, WANG Tianhong, ZHANG Quan, WANG Guopeng, TIAN Yingzhong, PENG Yan, LUO Jun. Obstacle Avoidance Path Planning of Manipulator Based on Proximity[J]. ROBOT, 2022, 44(5): 601-612. DOI: 10.13973/j.cnki.robot.210302

基于接近觉的机械臂避障路径规划

Obstacle Avoidance Path Planning of Manipulator Based on Proximity

  • 摘要: 提出了一种基于接近觉的机械臂避障路径规划方法。首先,针对排列稀疏的接近觉传感器阵列的障碍物感知问题,定义连杆“运动方向”的概念,优先读取连杆运动方向上的传感器以缩短读取周期的长度,并将距离传感器最近的障碍物表面建模为“假想圆锥”,过其顶点作“安全平面”,连杆在运动过程中不能与其发生碰撞。其次,针对避障路径规划问题,采用基于势函数与关节空间的人工势场法,并根据所提出的障碍物感知方法提出了基于“绕行”的改进方法以解决人工势场法的局部最优问题。最后,在UR10机器人的小臂连杆上验证本文方法,实验结果证明了本文方法的有效性、鲁棒性与实时性。

     

    Abstract: An obstacle avoidance path planning method of manipulator based on proximity is proposed. Firstly, the concept of "movement direction" of link is defined for the obstacle perception problem based on sparse distance information of proximity sensor array. The sensors in the movement direction of link are read preferentially to reduce the read period. The nearest obstacle surface is modeled as the "imaginary cone", through whose vertex a "safety plane" is made. The link can't collide with the safety plane in the movement process. Secondly, an artificial potential field method based on potential function and joint space is applied to the obstacle avoidance path planning problem. According to the proposed obstacle perception method, an improved method based on "detour" is proposed to solve the local optimum problem of the artificial potential field method. Finally, the proposed method is verified on the forearm of a UR10 robot, and the experimental results show that the proposed method is effective, robust and real-time.

     

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