基于凯恩动力学的协作机器人力补偿研究

Research on Collaborative Robot Force Compensation Based on Kane’s Dynamics

摘要:

针对现有利用六维力传感器对机器人力补偿算法不足的问题,提出一种基于凯恩动力学的力补偿算法,该方法将动态力转化为所需补偿的广义合力,统一进行力补偿推导,实时补偿机器人在不受外力的情况下传感器的零位值。首先,建立关节型协作机器人的凯恩动力学方程,并推导各关节间的速度递推算法;然后,建立关节型协作机器人力补偿模型,推导得到力补偿算法,进而得到力补偿的表达式;最后,利用AUBO-I5关节型协作机器人分别进行仿真和实验验证,将仿真、实验和理论结果进行对比验证和误差分析,得到机器人运动过程中对于基座六维力传感器力补偿对比曲线和误差分析结果。结果表明,3个方向力/力矩的对比曲线一致,且相对误差在5.6%以下,验证了该力补偿算法理论分析的正确性。结果可为人机协作和碰撞检测研究提供理论基础。

Abstract:

A force compensation algorithm based on Kane dynamics was proposed to address the problem of insufficient use of six-dimensional force sensors for robot force compensation algorithms. This method converted dynamic forces into generalized resultant forces that required compensation, and derived force compensation in a unified manner to compensate for the zero position value of the robot sensor in real-time without external forces. Firstly, the Kane’ s dynamic equation of the articulated collaborative robot was established and the velocity recursive algorithm between each joint was derived. Then, a joint type collaborative robot force compensation model was established, the force compensation algorithm was derived, and the expression for force compensation was obtained. Finally, the AUBO-I5 articulated collaborative robot was used for simulation and experimental verification, and the simulation, experimental, and theoretical results were compared, verified, and error were analyzed to obtain the force compensation comparison curve and error analysis results of the base six-dimensional force sensor during the robot??s motion process. The results showed that the comparison curves of the three directions of force / torque were consistent, and the relative error was below 5. 6% , which verified the correctness of the theoretical analysis of the force compensation algorithm. The results can provide a solid theoretical basis and valuable reference for future research in the fields of human-machine collaboration and collision detection.