TY - GEN
T1 - Whole-Body Control for Velocity-Controlled Mobile Collaborative Robots Using Coupling Dynamic Movement Primitives
AU - Tu, Zhangjie
AU - Zhang, Tianwei
AU - Yan, Lei
AU - Lam, Tin Lun
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we propose a unified whole-body control framework for velocity-controlled mobile collaborative robots which can distribute task motion into the arm and mobile base according to specific task requirements by adjusting weighting factors. Our framework focuses on addressing two challenging issues in whole-body coordination: 1) different dynamic characteristics of the mobile base and the arm; 2) avoidance of violating both safety and configuration con-straints. In addition, our controller involves Coupling Dynamic Movement Primitive to enable the essential capabilities for collaboration and interaction applications, such as obstacle avoidance, human teaching, and compliance control. Based on these, we design an adaptive motion mode for intuitive physical human-robot interaction through adjusting the weighting factors. The proposed controller is in closed-form and thus quite computationally efficient. Several typical experiments carried out on a real mobile collaborative robot validate the effectiveness of the proposed controller.
AB - In this paper, we propose a unified whole-body control framework for velocity-controlled mobile collaborative robots which can distribute task motion into the arm and mobile base according to specific task requirements by adjusting weighting factors. Our framework focuses on addressing two challenging issues in whole-body coordination: 1) different dynamic characteristics of the mobile base and the arm; 2) avoidance of violating both safety and configuration con-straints. In addition, our controller involves Coupling Dynamic Movement Primitive to enable the essential capabilities for collaboration and interaction applications, such as obstacle avoidance, human teaching, and compliance control. Based on these, we design an adaptive motion mode for intuitive physical human-robot interaction through adjusting the weighting factors. The proposed controller is in closed-form and thus quite computationally efficient. Several typical experiments carried out on a real mobile collaborative robot validate the effectiveness of the proposed controller.
UR - https://www.scopus.com/pages/publications/85146359440
U2 - 10.1109/Humanoids53995.2022.10000097
DO - 10.1109/Humanoids53995.2022.10000097
M3 - 会议稿件
AN - SCOPUS:85146359440
T3 - IEEE-RAS International Conference on Humanoid Robots
SP - 119
EP - 126
BT - 2022 IEEE-RAS 21st International Conference on Humanoid Robots, Humanoids 2022
PB - IEEE Computer Society
T2 - 2022 IEEE-RAS 21st International Conference on Humanoid Robots, Humanoids 2022
Y2 - 28 November 2022 through 30 November 2022
ER -