Virtual-Fixtures for Robotic-Assisted Bi-manual Cutting using Vector-Field Inequalities

Hisashi Ishida, Murilo M. Marinho*, Kanako Harada, Jian Gao, Mamoru Mitsuishi

*Corresponding author for this work

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

Abstract

Master - slave robotic systems have enabled operators to perform complex tasks with high precision. Some tasks can be further enhanced by adding virtual fixtures, which can guide user motion or constrain it within a safety envelope. In this study, the focus is on the generation of virtual fixtures for robotic-assisted bi-manual cutting, with possible applications in medicine and industry. Two control methods are proposed: forbidden-plane constraints (for increased safety) and an angle-ellipsoid constraint (for increased performance) which guide the user to safe and efficient bi-manual cutting. The proposed methods were evaluated in a user experiment using a pathology grossing master-slave robotic system. The results show that the forbidden-plane constraints enhanced the safety of the task, while the angle-ellipsoid constraint reduced cutting error by more than 58% (p<0.05).

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
PublisherIEEE
Pages395-400
Number of pages6
ISBN (Electronic)9781728166674
DOIs
Publication statusPublished - Jan 2020
Event2020 IEEE/SICE International Symposium on System Integration, SII 2020 - Honolulu, United States
Duration: 12 Jan 202015 Jan 2020

Publication series

NameProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020

Conference

Conference2020 IEEE/SICE International Symposium on System Integration, SII 2020
Country/TerritoryUnited States
CityHonolulu
Period12/01/2015/01/20

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