IROS 2015 Paper Abstract


Paper ThAP.21

Mao, Yichao (Zhejiang University), Zhu, Qiuguo (Zhejiang University), Xiong, Rong (Zhejiang University)

Dynamic Estimator Module for Multi-Link System

Scheduled for presentation during the Poster session "Late Breaking Posters" (ThAP), Thursday, October 1, 2015, 09:45−10:00, Saal G1

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 19, 2019

Keywords Calibration and Identification, Learning Control, Legged Robots


For a multi-link system, identification of dynamics model for each joint is of essential importance in position tracking and disturbance monitoring problems. However, traditional identification methods lack adaptability and need manual adjustment or reprogramming for each specific system or different operation states. Inspired by the thought of modularization, this paper proposes to introduce the recursive form of multi-link dynamics to construct a general dynamics estimator module, which has the ability to automatically generate dynamics estimator for various open-multi-link systems through module interconnection. To use the idea of recursive dynamics, a base parameter set as a minimum set of inertial parameters whose value can determine dynamics of multi-link system uniquely is investigated. Then, to adapt different requirement in different applications, both offline and online estimator for parameters are designed, where the former has an original form that employs least square algorithm, and the latter is achieved by introducing the geometric property of Kalman estimator. This method is validated through simulation results of a 6-link bifurcate system and a 5-link series system, as well as experimental results of a 2-link SEA (Serial Elastic Actuator) system.



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