@inproceedings{b694dc41a4104a139bde5f40faf014d1,
title = "GESRsim: Gastrointestinal Endoscopic Surgical Robot Simulator",
abstract = "Robot-assisted gastrointestinal endoscopic surgery (GES) as a kind of natural orifice transluminal endoscopic surgery (NOTES) is the next-generation minimally invasive surgery (MIS). Besides, rendering certain autonomy to a Gas-trointestinal Endoscopic Surgical Robot (GESR) is promising but highly challenging. Therefore, to accelerate the development and augment the autonomy of GESR, we use CoppeliaSim to develop the first robotic simulator for the GESR system (GESRsim) based on our previous design. The GESRsim provides several 3D models and kinematics of our designed manipulators and endoscopic snake bone. Additionally, we build several scenes for robotic GES training and then utilize different programming interfaces to perform teleoperation. Furthermore, several advanced control algorithms, including visual servoing (VS) and deep reinforcement learning (DRL), are implemented to verify the performance of the GESRsim.",
keywords = "Autonomy, Gastrointestinal endoscopic surgical robot, NOTES, Reinforcement learning, Robotic simulation, Robotic simulator, Visual servoing",
author = "Huxin Gao and Zedong Zhang and Changsheng Li and Xiao Xiao and Liang Qiu and Xiaoxiao Yang and Ruoyi Hao and Xiuli Zuo and Yanqing Li and Hongliang Ren",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 ; Conference date: 23-10-2022 Through 27-10-2022",
year = "2022",
doi = "10.1109/IROS47612.2022.9982138",
language = "English",
series = "IEEE International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9542--9549",
booktitle = "IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022",
address = "United States",
}