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Supervised semi-autonomous control for surgical robot based on Banoian optimization

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Title: Supervised semi-autonomous control for surgical robot based on Banoian optimization
Authors: Chen, J
Zhang, D
Munawar, A
Zhu, R
Lo, B
Fischer, GS
Yang, G-Z
Item Type: Conference Paper
Abstract: The recent development of Robot-Assisted Minimally Invasive Surgery (RAMIS) has brought much benefit to ease the performance of complex Minimally Invasive Surgery (MIS) tasks and lead to more clinical outcomes. Compared to direct master-slave manipulation, semi-autonomous control for the surgical robot can enhance the efficiency of the operation, particularly for repetitive tasks. However, operating in a highly dynamic in-vivo environment is complex. Supervisory control functions should be included to ensure flexibility and safety during the autonomous control phase. This paper presents a haptic rendering interface to enable supervised semi-autonomous control for a surgical robot. Bayesian optimization is used to tune user-specific parameters during the surgical training process. User studies were conducted on a customized simulator for validation. Detailed comparisons are made between with and without the supervised semi-autonomous control mode in terms of the number of clutching events, task completion time, master robot end-effector trajectory and average control speed of the slave robot. The effectiveness of the Bayesian optimization is also evaluated, demonstrating that the optimized parameters can significantly improve users' performance. Results indicate that the proposed control method can reduce the operator's workload and enhance operation efficiency.
Issue Date: 24-Oct-2020
Date of Acceptance: 2-Jul-2020
URI: http://hdl.handle.net/10044/1/89093
DOI: 10.1109/iros45743.2020.9341383
Publisher: IEEE
Start Page: 2943
End Page: 2949
Journal / Book Title: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Copyright Statement: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/L014149/1
Conference Name: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Publication Status: Published
Start Date: 2020-10-24
Finish Date: 2021-01-24
Conference Place: Las Vegas, NV, USA
Open Access location: https://ieeexplore.ieee.org/document/9341383
Online Publication Date: 2021-02-10
Appears in Collections:Department of Surgery and Cancer
Institute of Global Health Innovation