Imperial College London
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DrBennyLo

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

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Contact

 

+44 (0)20 7594 0806benny.lo Website

 
 
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Location

 

Bessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Zhang:2022:10.1109/icra46639.2022.9812379,
author = {Zhang, D and Wu, Z and Chen, J and Zhu, R and Munawar, A and Xiao, B and Guan, Y and Su, H and Hong, W and Guo, Y and Fischer, GS and Lo, B and Yang, G-Z},
doi = {10.1109/icra46639.2022.9812379},
pages = {7701--7707},
publisher = {IEEE},
title = {Human-robot shared control for surgical robot based on context-aware sim-to-real adaptation},
url = {http://dx.doi.org/10.1109/icra46639.2022.9812379},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Human-robot shared control, which integrates the advantages of both humans and robots, is an effective approach to facilitate efficient surgical operation. Learning from demonstration (LfD) techniques can be used to automate some of the surgical sub tasks for the construction of the shared control mechanism. However, a sufficient amount of data is required for the robot to learn the manoeuvres. Using a surgical simulator to collect data is a less resource-demanding approach. With sim-to-real adaptation, the manoeuvres learned from a simulator can be transferred to a physical robot. To this end, we propose a sim-to-real adaptation method to construct a human-robot shared control framework for robotic surgery. In this paper, a desired trajectory is generated from a simulator using LfD method, while dynamic motion primitives (DMP) is used to transfer the desired trajectory from the simulator to the physical robotic platform. Moreover, a role adaptation mechanism is developed such that the robot can adjust its role according to the surgical operation contexts predicted by a neural network model. The effectiveness of the proposed framework is validated on the da Vinci Research Kit (dVRK). Results of the user studies indicated that with the adaptive human-robot shared control framework, the path length of the remote controller, the total clutching number and the task completion time can be reduced significantly. The proposed method outperformed the traditional manual control via teleoperation.
AU  - Zhang,D
AU  - Wu,Z
AU  - Chen,J
AU  - Zhu,R
AU  - Munawar,A
AU  - Xiao,B
AU  - Guan,Y
AU  - Su,H
AU  - Hong,W
AU  - Guo,Y
AU  - Fischer,GS
AU  - Lo,B
AU  - Yang,G-Z
DO  - 10.1109/icra46639.2022.9812379
EP  - 7707
PB  - IEEE
PY  - 2022///
SP  - 7701
TI  - Human-robot shared control for surgical robot based on context-aware sim-to-real adaptation
UR  - http://dx.doi.org/10.1109/icra46639.2022.9812379
UR  - https://ieeexplore.ieee.org/document/9812379
UR  - http://hdl.handle.net/10044/1/99373
ER  -
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