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Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery

Su, Hang; Yang, Chenguang; Ferrigno, Giancarlo; De Momi, Elena

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Authors

Hang Su

Giancarlo Ferrigno

Elena De Momi



Abstract

© 2016 IEEE. An improved human-robot collaborative control scheme is proposed in a teleoperated minimally invasive surgery scenario, based on a hierarchical operational space formulation of a seven-degree-of-freedom redundant robot. Redundancy is exploited to guarantee a remote center of motion (RCM) constraint and to provide a compliant behavior for the medical staff. Based on the implemented hierarchical control framework, an RCM constraint and a safe constraint are applied to the null-space motion to achieve the surgical tasks with human-robot interaction. Due to the physical interactions, safety and accuracy of the surgery may be affected. The control framework integrates an adaptive compensator to enhance the accuracy of the surgical tip and to maintain the RCM constraint in a decoupled way avoiding any physical interactions. The system performance is verified on a patient phantom. Compared with the methods proposed in the literature, results show that the accuracy of both the RCM constraint and the surgical tip is improved. The compliant swivel motion of the robot arm is also constrained in a defined area, and the interaction force on the abdominal wall becomes smaller.

Citation

Su, H., Yang, C., Ferrigno, G., & De Momi, E. (2019). Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery. IEEE Robotics and Automation Letters, 4(2), 1447-1453. https://doi.org/10.1109/LRA.2019.2897145

Journal Article Type Article
Acceptance Date Dec 31, 2018
Online Publication Date Feb 4, 2019
Publication Date Apr 1, 2019
Deposit Date Feb 7, 2019
Publicly Available Date Feb 8, 2019
Journal IEEE Robotics and Automation Letters
Print ISSN 2377-3766
Electronic ISSN 2377-3766
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 4
Issue 2
Pages 1447-1453
DOI https://doi.org/10.1109/LRA.2019.2897145
Public URL https://uwe-repository.worktribe.com/output/847862
Publisher URL http://doi.org/10.1109/LRA.2019.2897145
Additional Information Additional Information : (c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

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