TY - GEN
T1 - Real-time Contact State Estimation in Shape Control of Deformable Linear Objects under Small Environmental Constraints
AU - Chen, Kejia
AU - Bing, Zhenshan
AU - Wu, Yansong
AU - Wu, Fan
AU - Zhang, Liding
AU - Haddadin, Sami
AU - Knoll, Alois
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the contact state is essential for preventing and rectifying potential anomalies. However, this task is challenging due to the small sizes of fixtures, the requirement for real-time performances, and the infinite degrees of freedom of the deformable linear objects. In this paper, we propose a real-time approach for estimating both contact establishment and subsequent changes by leveraging the dependency between the applied and detected contact force on the deformable linear objects. We seamlessly integrate this method into the robot control loop and achieve an adaptive shape control framework which avoids, detects and corrects anomalies automatically. Real-world experiments validate the robustness and effectiveness of our contact estimation approach across various scenarios, significantly increasing the success rate of shape control processes.
AB - Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the contact state is essential for preventing and rectifying potential anomalies. However, this task is challenging due to the small sizes of fixtures, the requirement for real-time performances, and the infinite degrees of freedom of the deformable linear objects. In this paper, we propose a real-time approach for estimating both contact establishment and subsequent changes by leveraging the dependency between the applied and detected contact force on the deformable linear objects. We seamlessly integrate this method into the robot control loop and achieve an adaptive shape control framework which avoids, detects and corrects anomalies automatically. Real-world experiments validate the robustness and effectiveness of our contact estimation approach across various scenarios, significantly increasing the success rate of shape control processes.
UR - http://www.scopus.com/inward/record.url?scp=85202431769&partnerID=8YFLogxK
U2 - 10.1109/ICRA57147.2024.10611558
DO - 10.1109/ICRA57147.2024.10611558
M3 - Conference contribution
AN - SCOPUS:85202431769
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 13833
EP - 13839
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -