Endoscopic bi-manual robotic instrument design using a genetic algorithm
File(s)
Accepted version
Author(s)
Schmitz, Andreas
Berthet-Rayne, Pierre
Yang, Guang-Zhong
Type
Conference Paper
Abstract
Over the last few years, there has been a significant rise in designing small, agile and flexible medical systems that can navigate through natural orifices. In the case of endoscopic surgery, existing systems vary significantly from each other which raises the question of the existence of a general design that can do it all. In this context, this paper proposes to use a genetic algorithm combined with recorded suturing and anatomical data to automatically design a pair of robotic instruments for the i 2 Snake under strict mechanical constraints. The resulting automatically generated instrument designs include a 6 degrees of freedom instrument that can follow a predefined trajectory accurately and a more simple 4 degrees of freedom instrument that can accomplish most of the task. The results also showed the importance of having a prismatic joint to gain the precision required for endoscopic surgery.
Date Issued
2020-01-27
Date Acceptance
2020-01-01
Citation
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, pp.2975-2982
ISSN
2153-0858
Publisher
IEEE
Start Page
2975
End Page
2982
Journal / Book Title
2019 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.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000544658402066&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
EP/P012779/1
Source
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science, Theory & Methods
Robotics
Computer Science
OPTIMIZATION
TASK
Publication Status
Published
Start Date
2019-11-04
Finish Date
2019-11-08
Coverage Spatial
Macau, PEOPLES R CHINA
Date Publish Online
2020-01-27