An efficient robot payload identification method for industrial application
ISSN: 0143-991x
Article publication date: 27 July 2018
Issue publication date: 29 August 2018
Abstract
Purpose
This paper aims to improve the accuracy of robot payload identification and decrease the complexity in its industrial application by developing a new method based on the actuator current.
Design/methodology/approach
Instead of previous general robot dynamic modeling of the actuators, links, together with payload inertial parameters, the paper discovers that the difference of the actuator torque between the robot moving along the same trajectory with and without carrying payload can be described as a function of the payload inertial parameters directly. Then a direct dynamic identification model of payload is built, a set of specialized novel exciting trajectories are designed for accurate identification and the least square method is applied for the estimation of the load parameters.
Findings
The experiments confirm the effectiveness of the proposed method in robot payload identification. The identification accuracy is greatly improved compared with that of existing methods based on the actuator current and is close to the accuracy of the methods that direct use the wrist-mounted force-torque sensor.
Practical implications
As the provided experiments indicate, the proposed method expands the application range and greatly improves the accuracy, hence making payload identification fully operational in the industrial application.
Originality/value
The novelty of such an identification method is that it does not require the rotor inertias and inertial parameters of links as a prior knowledge, and the specially designed trajectories provide completed decoupling of the load parameters.
Keywords
Citation
Dong, Y., Ren, T., Chen, K. and Wu, D. (2019), "An efficient robot payload identification method for industrial application", Industrial Robot, Vol. 45 No. 4, pp. 505-515. https://doi.org/10.1108/IR-03-2018-0037
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited