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20232026
most citedDeep Reinforcement Learning in Surgical Robotics: Enhancing the Automation Level

7 citations · 7 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

Multimodal Progress-Residual Fusion for Anticipating Navigation Retreat in Robotic Flexible Endoscopy

Chi Kit Ng, Tianchun Wu, Jiatan Sun +3

Flexible robotic endoscopes provide access through tortuous anatomy, where friction, deformation, and wall interaction separate commanded insertion from useful distal progress. Ope…

cs.RO2026

StenoVLA-3D: 3D-Aware Reasoning VLA for Navigation Through Gastrointestinal Stenoses

Tamima Tabassum, Yiming Huang, Tianchun Wu +7

Autonomous endoscopic navigation requires the policy model to predict actions from texture-poor monocular observations, make safe control decisions, and retain evidence of lesions…

cs.RO2025

Jacobian Exploratory Dual-Phase Reinforcement Learning for Dynamic Endoluminal Navigation of Deformable Continuum Robots

Yu Tian, Chi Kit Ng, Hongliang Ren

Deformable continuum robots (DCRs) present unique planning challenges due to nonlinear deformation mechanics and partial state observability, violating the Markov assumptions of co…

cs.RO2025

Contact-Aided Navigation of Flexible Robotic Endoscope Using Deep Reinforcement Learning in Dynamic Stomach

Chi Kit Ng, Huxin Gao, Tian-Ao Ren +2

Navigating a flexible robotic endoscope (FRE) through the gastrointestinal tract is critical for surgical diagnosis and treatment. However, navigation in the dynamic stomach is par…

cs.RO2023★ 7 cited

Deep Reinforcement Learning in Surgical Robotics: Enhancing the Automation Level

Cheng Qian, Hongliang Ren

Surgical robotics is a rapidly evolving field that is transforming the landscape of surgeries. Surgical robots have been shown to enhance precision, minimize invasiveness, and alle…