An efficient and accurate force/torque sensing method based on an excitation trajectory

被引:3
|
作者
Min, Kang [1 ]
Ni, Fenglei [1 ]
Liu, Hong [1 ]
机构
[1] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
Gravity compensation; Inertial force; torque compensation; Excitation trajectory; Robot manipulator; Contact force; torque sensing; INDUSTRIAL ROBOTS; SENSOR FUSION;
D O I
10.1108/IR-08-2022-0206
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
PurposeThe purpose of the paper is to propose an efficient and accurate force/torque (F/T) sensing method for the robotic wrist-mounted six-dimensional F/T sensor based on an excitation trajectory. Design/methodology/approachThis paper presents an efficient and accurate F/T sensing method based on an excitation trajectory. First, the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity. Therefore, the sensing accuracy is improved. Then, the excitation trajectory with optimized poses is used for robot following and data acquisition. The data acquisition is not limited by poses and its time can be significantly shortened. Finally, the least squares method is used to identify parameters and sense contact forces/torques. FindingsExperiments have been carried out on the self-developed robot manipulator. The results strongly demonstrate that the proposed approach is more efficient and accurate than the existing widely-adopted method. Furthermore, the data acquisition time can be shortened from more than 60 s to 3 s/20 s. Thus, the proposed approach is effective and suitable for fast-paced industrial applications. Originality/valueThe main contributions of this paper are as follows: the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity; and the excitation trajectory with optimized poses is used for robot following and data acquisition.
引用
收藏
页数:13
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