Sim-to-Real Surgical Robot Learning and Autonomous Planning for Internal Tissue Points Manipulation Using Reinforcement Learning-Reference-Cited by-同舟云学术

Sim-to-Real Surgical Robot Learning and Autonomous Planning for Internal Tissue Points Manipulation Using Reinforcement Learning

Published:2023-05 Issue:5 Volume:8 Page:2502-2509
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Ou Yafei¹^ORCID,Tavakoli Mahdi¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10073596/10065553.pdf?arnumber=10065553

Reference26 articles.

1. Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning

2. Domain randomization for transferring deep neural networks from simulation to the real world

3. Real-to-Sim Registration of Deformable Soft Tissue with Position-Based Dynamics for Surgical Robot Autonomy

4. Soft Tissue Simulation Environment to Learn Manipulation Tasks in Autonomous Robotic Surgery*

5. Autonomous Tissue Manipulation via Surgical Robot Using Learning Based Model Predictive Control

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