基于人机协作的机器人防撞控制研究

Collision Avoidance Control for Robots Based on Human-Robot Collaboration

摘要:

针对人机协作环境下人与机器人末端之间不可预测的碰撞问题，本文提出一种由自适应导纳控制和鲁棒控制组成的双环人机协作防撞控制算法。在对导纳参数分析的基础上建立外环自适应导纳控制器，根据碰撞力信息实时更新阻尼系数和刚度以产生避让轨迹。根据鲁棒控制理论建立内环鲁棒跟踪控制器，用于克服动力学误差对轨迹跟踪精度产生的影响。对该算法进行可视化仿真与实验验证，仿真结果表明，该算法与变刚度导纳控制相比，末端在x、y、z轴方向上最大位置偏移量分别提高17.46%、8.89%、13.09%，响应时间分别降低7.94%、14.89%、8.21%，显著提高了机器人末端碰撞响应的柔顺性与灵活性；碰撞实验中机器人末端在x、y、z轴方向上受到的最大碰撞力分别为1.12、4.06、-0.44N，末端在碰撞力方向上产生的最大位置偏移分别为6.94、98.75、5.43mm，结果表明在较小碰撞力作用下，机器人末端可以表现出良好的柔顺性，满足人机协作安全需求。

Abstract:

Aiming at the unpredictable collision problem between human and robot end in human-robot cooperative environment, a double-loop human-robot cooperative anti-collision control algorithm composed of adaptive admittance control and robust control was proposed. Firstly, based on the analysis of admittance parameters, an outer loop adaptive admittance controller was established, and the damping and stiffness parameters were updated in real time according to the collision force information to generate the avoidance trajectory. Then, according to the robust control theory, the inner loop robust tracking controller was established to overcome the influence of dynamics error on the trajectory tracking accuracy. Finally, the visual simulation and experimental verification of the algorithm were carried out. The simulation results showed that compared with the variable stiffness admittance control, the maximum offset of the end position on the x, y and z axes was increased by 17.46%, 8.89% and 13.09%, respectively, and the response time was reduced by 7.94%, 14.89% and 8.21%, respectively, which significantly improved the flexibility of the robot end collision response. In the collision experiment, the maximum collision forces on the x, y and z axes of the robot end were 1.12N, 4.06N and -0.44N, respectively. The maximum position offsets of the robot end in the direction of collision force were 6.94mm,98.75mm and 5.43mm, respectively. The results showed that the robot end could show good flexibility under the action of small collision force, which met the safety requirements of human-robot cooperation.