Bayesian motion intention estimation-based impedance control of modular robot manipulator: theory and experimental verification

被引：0

作者：

Li, Shijie ^{[1
]}

An, Tianjiao ^{[1
]}

Ma, Bing ^{[1
]}

Gao, Yuhang ^{[1
]}

Dong, Bo ^{[1
]}

机构：

[1] Changchun Univ Technol, Dept Control Sci & Engn, Changchun, Peoples R China

来源：

2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年

基金：

中国国家自然科学基金;

关键词：

Modular robot manipulator; Human motion intention; Impedance control; Physical human robot interaction;

D O I：

10.1109/CCDC58219.2023.10326701

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article proposes an impedance control method of modular robot manipulator (MRM) system for physical human-robot interaction (pHRI). Bayesian parameter estimation is employed to identify human motion intention, which is considered as the desired trajectory in impedance control that allows the MRM easily to track the target impedance model. The uniformly ultimately bounded (UUB) of the tracking error is proved based on Lyapunov theory, and the experimental results demonstrate the effectiveness of the proposed control method in pHRI.

引用

页码：3477 / 3481

页数：5

共 30 条

[21] Wrench Estimation and Impedance-based Control applied to a Flying Parallel Robot Interacting with the Environment
Liu, Shiyu
Fantoni, Isabelle
Chriette, Abdelhamid
Six, Damien
IFAC PAPERSONLINE, 2022, 55 (14): : 151 - 157
[22] Variable-parameter impedance control of robot manipulator based on a super-twisting sliding mode with uncertain environment interaction
Li, Yan
Tang, Budong
Bi, Jiabin
Lu, Jiacheng
Sheng, Mingzhe
Lu, Zengpeng
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2024, 38 (11) : 6297 - 6307
[23] Research on Trajectory Tracking Control of Traction upper Limb Rehabilitation Robot Based on Feedforward Impedance Theory
Zhang, Yan
Xu, Linsen
Jin, Haihong
Xincan, Liang
Liu, Jinfu
Yan, Wenjun
Zhang, Wenxiang
Zhou, Jian
2022 INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2022), 2022, : 1035 - 1039
[24] Design of an Assistive Controller for Physical Human-Robot Interaction Based on Cooperative Game Theory and Human Intention Estimation
Franceschi, Paolo
Cassinelli, Davide
Pedrocchi, Nicola
Beschi, Manuel
Rocco, Paolo
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 5741 - 5756
[25] Experimental study on fuzzy-logic-based impedance control for upper-limb rehabilitation robot
Xu G.
Song A.
Li H.
Jiqiren/Robot, 2010, 32 (06): : 792 - 798
[26] Robotic Assistance for Physical Human-Robot Interaction Using a Fuzzy RBF Hand Impedance Compensator and a Neural Network Based Human Motion Intention Estimator
Chien, Shih-Hsuan
Wang, Jyun-Hsiang
Cheng, Ming-Yang
IEEE ACCESS, 2021, 9 : 126048 - 126057
[27] Decentralized robust control of modular robot manipulators with harmonic drive transmission using RARKF-based joint torque estimation
Wang, Tianhe
An, Tianjiao
Wei, Chongyang
Li, Yuachun
Dong, Bo
2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2022, : 5496 - 5501
[28] Biomechanics-Based User-Adaptive Variable Impedance Control for Enhanced Physical Human-Robot Interaction Using Bayesian Optimization
Zahedi, Fatemeh
Lee, Hyunglae
ADVANCED INTELLIGENT SYSTEMS, 2025, 7 (02)
[29] Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction
Omrani, Javad
Moghaddam, Majid M.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE, 2022, 236 (03) : 385 - 398
[30] Adaptive torque estimation-based nonlinear H∞\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\infty $$\end{document} control of modular robot manipulators with uncertain environments
Bo Dong
Yuge Wang
Tianjiao An
Yiming Cui
Xinye Zhu
Neural Computing and Applications, 2025, 37 (3) : 1617 - 1631

← 1 2 3 →