Hybrid Vision-Force Control for Human Robot Co-Carrying on Ball and Board Systems

Gaochen Min, Yifan Wu, Nan Feng, Xinbo Yu, Guang Li, Wei He*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

We propose a hybrid vision-force control that combines vision servo control with force control to perform a robot collaborative by human carrying task on a ball-and-board systems. The proposed control allows the robot to effectively cooperate with human by successfully moving the board to the desired target position, while actively avoiding the ball from falling off the board. A RBFNN-based force control is designed to ensure the robot is able of complying with human motion under uncertain robot dynamics. Visual servo control based on image recognition and location is used to generate reference height and angle to adjust the position and posture of the board to keep the ball on the board. The experiment illustrates that the proposed technique is practical and effective to perform human-robot co-carrying on a ball-and-board systems.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Development and Learning, ICDL 2023
PublisherIEEE
Pages220-224
Number of pages5
ISBN (Electronic)9781665470759
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Development and Learning, ICDL 2023 - Macau, China
Duration: 9 Nov 202311 Nov 2023

Publication series

Name2023 IEEE International Conference on Development and Learning, ICDL 2023

Conference

Conference2023 IEEE International Conference on Development and Learning, ICDL 2023
Country/TerritoryChina
CityMacau
Period9/11/2311/11/23

Keywords

  • admittance control
  • human-robot collaborative carrying tasks
  • visual servoing

Fingerprint

Dive into the research topics of 'Hybrid Vision-Force Control for Human Robot Co-Carrying on Ball and Board Systems'. Together they form a unique fingerprint.

Cite this