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http://dx.doi.org/10.7746/jkros.2014.9.1.011

Exact External Torque Sensing System for Flexible-Joint Robot: Kalman Filter Estimation with Random-Walk Model  

Park, Young-Jin (Mechanical Engineering, POSTECH)
Chung, Wan-Kyun (Mechanical Engineering, POSTECH)
Publication Information
The Journal of Korea Robotics Society / v.9, no.1, 2014 , pp. 11-19 More about this Journal
Abstract
In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the joint-torque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.
Keywords
flexible-joint robot; external torque estimation; model-based estimation; Kalman filter; random-walk model;
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