Mass and friction optimization for natural motion in hands-on robotic surgery
Author(s)
Petersen, J
Bowyer, S
Rodriguez y Baena, F
Type
Journal Article
Abstract
In hands-on robotic surgery, the surgical tool is mounted on the end-effector of a robot and is directly manipulated by the surgeon. This simultaneously exploits the strengths of both humans and robots, such that the surgeon directly feels tool-tissue interactions and remains in control of the procedure, while taking advantage of the robot's higher precision and accuracy. A crucial challenge in hands-on robotics for delicate manipulation tasks, such as surgery, is that the user must interact with the dynamics of the robot at the end-effector, which can reduce dexterity and increase fatigue. This paper presents a null-space-based optimization technique for simultaneously minimizing the mass and friction of the robot that is experienced by the surgeon. By defining a novel optimization technique for minimizing the projection of the joint friction onto the end-effector, and integrating this with our previous techniques for minimizing the belted mass/inertia as perceived by the hand, a significant reduction in dynamics felt by the user is achieved. Experimental analyses in both simulation and human user trials demonstrate that the presented method can reduce the user-experienced dynamic mass and friction by, on average, 44% and 41%, respectively. The results presented robustly demonstrate that optimizing a robots pose can result in a more natural tool motion, potentially allowing future surgical robots to operate with increased usability, improved surgical outcomes, and wider clinical uptake.
Date Issued
2016-02-01
Date Acceptance
2015-11-30
Citation
IEEE Transactions on Robotics, 2016, 32 (1), pp.201-213
ISSN
1552-3098
Publisher
Institute of Electrical and Electronics Engineers
Start Page
201
End Page
213
Journal / Book Title
IEEE Transactions on Robotics
Volume
32
Issue
1
Copyright Statement
© 2015 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
Commission of the European Communities
The Leverhulme Trust
Identifier
https://ieeexplore.ieee.org/document/7384515
Grant Number
270460
PLP-2013-100
Subjects
Science & Technology
Technology
Robotics
Cooperative manipulators
dynamics
medical robots and systems
physical human-robot interaction
redundant robots
COMPENSATION
IDENTIFICATION
MANIPULATORS
EXOSKELETON
ASSISTANCE
AVOIDANCE
STABILITY
COMPLIANT
TASK
Industrial Engineering & Automation
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Publication Status
Published
Date Publish Online
2016-01-18