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

Author:

Min Kang,Ni Fenglei,Liu Hong

Abstract

Purpose The 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/approach This 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. Findings Experiments 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/value The 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.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Control and Systems Engineering

Reference21 articles.

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4. Compensation of load dynamics for admittance controlled interactive industrial robots using a quaternion-based Kalman filter;IEEE Robotics and Automation Letters,2017

5. Generalized contact force estimator for a robot manipulator,2006

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