External Force Estimation for Industrial Robots With Flexible Joints

被引:16
|
作者
Lin, Yang [1 ]
Zhao, Huan [1 ]
Ding, Han [1 ]
机构
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Sch Mech Sci & Engn, Wuhan 430074, Hubei, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Force and tactile sensing; model learning for control; compliant joint; dynamics; industrial robots;
D O I
10.1109/LRA.2020.2968058
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
With no force sensors, estimating forces for robotic manipulation has gained a lot of attention. However, for industrial robots with harmonic drives (flexible joints), deviations between joint and motor positions inevitably deteriorate the force estimation performance due to the lack of encoders on the joint side. To this end, this letter presents a method to estimate not only joint states but also external forces. The method includes an extended disturbance state observer (DSO) and a proposed task-oriented disturbance modeling (TDM). First, a robust DSO is extended to robots with flexible joints aiming to estimate joint states and disturbances. Then, due to the observed disturbances including (possibly) external forces and also uncertainties such as measurement noises and model errors of the robot dynamics, a learning part is proposed to model the task-oriented disturbances during no-contact motion aiming to improve the effect of uncertainties on the force estimation performance. Finally, when the robot comes in contact with the environment, external forces are estimated as the differences between the modeled (no-contact) disturbances and the real-time observed disturbances. Experimental results, obtained on a six-degrees-of-freedom (6-DOF) industrial robot with flexible joints, show the feasibility and effectiveness of the proposed method.
引用
收藏
页码:1311 / 1318
页数:8
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