52 citations · 59 across the 13 of their papers we have counts for
13 papers
Phase-and-First-Arrival VLM Feedback for Sparse-Reward Reinforcement Learning in Surgical Manipulation
Wanli Liuchen, Fangyuan Wang, Bin Li +4
Sparse outcome feedback limits what robots can learn from unsuccessful attempts at complex manipulation. Failed multi-stage surgical attempts can contain grasps, lifts, or transfer…
A Unified Calibration Framework for Coordinate and Kinematic Parameters in Dual-Arm Robots
Tianyu Huang, Bohan Yang, Bin Li +4
Precise collaboration in vision-based dual-arm robot systems requires accurate system calibration. Recent dual-robot calibration methods have achieved strong performance by simulta…
Enhanced Scale-aware Depth Estimation for Monocular Endoscopic Scenes with Geometric Modeling
Ruofeng Wei, Bin Li, Kai Chen +3
Scale-aware monocular depth estimation poses a significant challenge in computer-aided endoscopic navigation. However, existing depth estimation methods that do not consider the ge…
Simultaneous Estimation of Shape and Force along Highly Deformable Surgical Manipulators Using Sparse FBG Measurement
Yiang Lu, Bin Li, Wei Chen +6
Recently, fiber optic sensors such as fiber Bragg gratings (FBGs) have been widely investigated for shape reconstruction and force estimation of flexible surgical robots. However,…
End-to-End Learning of Deep Visuomotor Policy for Needle Picking
Hongbin Lin, Bin Li, Xiangyu Chu +3
Needle picking is a challenging manipulation task in robot-assisted surgery due to the characteristics of small slender shapes of needles, needles' variations in shapes and sizes,…
Autonomous Intelligent Navigation for Flexible Endoscopy Using Monocular Depth Guidance and 3-D Shape Planning
Yiang Lu, Ruofeng Wei, Bin Li +5
Recent advancements toward perception and decision-making of flexible endoscopes have shown great potential in computer-aided surgical interventions. However, owing to modeling unc…
Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot
Tao Huang, Kai Chen, Bin Li +2
Task automation of surgical robot has the potentials to improve surgical efficiency. Recent reinforcement learning (RL) based approaches provide scalable solutions to surgical auto…
Distilled Visual and Robot Kinematics Embeddings for Metric Depth Estimation in Monocular Scene Reconstruction
Ruofeng Wei, Bin Li, Hangjie Mo +5
Estimating precise metric depth and scene reconstruction from monocular endoscopy is a fundamental task for surgical navigation in robotic surgery. However, traditional stereo matc…
Open-source High-precision Autonomous Suturing Framework With Visual Guidance
Hongbin Lin, Bin Li, Yunhui Liu +1
Autonomous surgery has attracted increasing attention for revolutionizing robotic patient care, yet remains a distant and challenging goal. In this paper, we propose an image-based…
3D Perception based Imitation Learning under Limited Demonstration for Laparoscope Control in Robotic Surgery
Bin Li, Ruofeng Wei, Jiaqi Xu +6
Automatic laparoscope motion control is fundamentally important for surgeons to efficiently perform operations. However, its traditional control methods based on tool tracking with…
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Ruofeng Wei, Bin Li, Hangjie Mo +6
Objective: The computation of anatomical information and laparoscope position is a fundamental block of surgical navigation in Minimally Invasive Surgery (MIS). Recovering a dense…
SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning
Jiaqi Xu, Bin Li, Bo Lu +3
Autonomous surgical execution relieves tedious routines and surgeon's fatigue. Recent learning-based methods, especially reinforcement learning (RL) based methods, achieve promisin…
Data-driven Holistic Framework for Automated Laparoscope Optimal View Control with Learning-based Depth Perception
Bin Li, Bo Lu, Yiang Lu +2
Laparoscopic Field of View (FOV) control is one of the most fundamental and important components in Minimally Invasive Surgery (MIS), nevertheless, the traditional manual holding p…