摘要
针对工业机器人打磨蜗轮齿面刀痕时末端力感知信息采集不准确的问题,文章提出一种力感知信息预处理方法.首先,建立卡尔曼滤波模型以减少外界环境因素带来的误差影响;其次,建立工业机器人末端坐标系与基坐标系之间的关系,对工业机器人进行重力补偿,以消除自身误差对六维力传感器采集力感知信息的影响;最后,建立基于位置的柔顺阻抗控制策略,以减少工业机器人末端冲击对蜗轮齿面表面质量的影响.实验结果显示,经过力感知信息预处理方法后,六维力传感器力的读数误差维持在±0.4 N之间,力矩误差维持在±0.16 N·m之间,力、力矩误差均接近于零,并且打磨后的蜗轮齿面表面粗糙度由0.902μm提高到了0.801μm.这表明力感知信息预处理方法能够有效减少外界因素和自身误差的影响,提高六维力传感器采集力感知信息的准确度,为实现工业机器人柔顺打磨蜗轮齿面刀痕奠定基础.
Aiming at the problem that the collection of end force sensing information is not accurate when the industrial robot is grinding the knife mark on the worm gear tooth surface,a force sensing information preprocessing method is proposed.Firstly,the Kalman filter model is established to reduce the error caused by external environmental factors.Then,the relationship between the terminal coordinate system and the base coordinate system of the industrial robot is established,so as to compensate the tilt Angle of the industrial robot installation,the gravity of the grinding tool and the zero point of the six-dimensional force sensor,and eliminate the influence of its own error on the force perception information collected by the six-dimensional force sensor.Finally,a position-based compliant impedance control strategy is established to reduce the impact of industrial robot end impact on the surface quality of worm gear tooth surface.The experimental results show that after the force sensing information preprocessing method,the force reading error of the six-dimensional force sensor is maintained between±0.4 N,and the torque error is maintained between±0.16 N·m.The force and torque errors are close to zero,and the surface roughness of the worm gear tooth surface after grinding is increased from 0.902μm to 0.801μm.The results show that the proposed force sensing information preprocessing method can effectively reduce the influence of external factors and own errors,improve the accuracy of the force sensing information collected by the six-dimensional force sensor,and lay a foundation for the realization of industrial robot to smooth grinding wormgear tooth surface knife mark.
作者
常旭
赵康
陈家荣
CHANG Xu;ZHAO Kang;CHEN Jiarong(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Songjiang 201600,China)
出处
《河南科技学院学报(自然科学版)》
2023年第5期74-84,共11页
Journal of Henan Institute of Science and Technology(Natural Science Edition)
基金
国家自然科学基金(52005317)。
关键词
蜗轮齿面刀痕
工业机器人
卡尔曼滤波
阻抗控制
重力补偿
knife mark of worm gear tooth surface
industrial robots
Kalman filter
impedance control
gravity compensation