61 citations · 213 across the 26 of their papers we have counts for
26 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…
SDF-Pack: Towards Compact Bin Packing with Signed-Distance-Field Minimization
Jia-Hui Pan, Ka-Hei Hui, Xiaojie Gao +4
Robotic bin packing is very challenging, especially when considering practical needs such as object variety and packing compactness. This paper presents SDF-Pack, a new approach ba…
Modal-graph 3D shape servoing of deformable objects with raw point clouds
Bohan Yang, Congying Sui, Fangxun Zhong +1
Deformable object manipulation (DOM) with point clouds has great potential as non-rigid 3D shapes can be measured without detecting and tracking image features. However, robotic sh…
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,…
Two-Stage Grasping: A New Bin Picking Framework for Small Objects
Hanwen Cao, Jianshu Zhou, Junda Huang +5
This paper proposes a novel bin picking framework, two-stage grasping, aiming at precise grasping of cluttered small objects. Object density estimation and rough grasping are condu…
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…
StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS
Kai Chen, Stephen James, Congying Sui +3
Most existing methods for category-level pose estimation rely on object point clouds. However, when considering transparent objects, depth cameras are usually not able to capture m…
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…
FBG-Based Online Learning and 3-D Shape Control of Unmodeled Continuum and Soft Robots in Unstructured Environments
Yiang Lu, Wei Chen, Bo Lu +4
In this paper, we present a novel and generic data-driven method to servo-control the 3-D shape of continuum and soft robots embedded with fiber Bragg grating (FBG) sensors. Develo…
AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy
Ziyi Wang, Bo Lu, Yonghao Long +4
Computer-assisted minimally invasive surgery has great potential in benefiting modern operating theatres. The video data streamed from the endoscope provides rich information to su…
Model-Free 3D Shape Control of Deformable Objects Using Novel Features Based on Modal Analysis
Bohan Yang, Bo Lu, Wei Chen +2
Shape control of deformable objects is a challenging and important robotic problem. This paper proposes a model-free controller using novel 3D global deformation features based on…
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…
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking
Kai Chen, Rui Cao, Stephen James +4
In this paper, we propose an iterative self-training framework for sim-to-real 6D object pose estimation to facilitate cost-effective robotic grasping. Given a bin-picking scenario…
Towards Robust Part-aware Instance Segmentation for Industrial Bin Picking
Yidan Feng, Biqi Yang, Xianzhi Li +7
Industrial bin picking is a challenging task that requires accurate and robust segmentation of individual object instances. Particularly, industrial objects can have irregular shap…
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…
PlaTe: Visually-Grounded Planning with Transformers in Procedural Tasks
Jiankai Sun, De-An Huang, Bo Lu +3
In this work, we study the problem of how to leverage instructional videos to facilitate the understanding of human decision-making processes, focusing on training a model with the…
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…
One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video
Zixu Zhao, Yueming Jin, Bo Lu +4
Surgical instrument segmentation in robot-assisted surgery (RAS) - especially that using learning-based models - relies on the assumption that training and testing videos are sampl…
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…
Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery
Yonghao Long, Jie Ying Wu, Bo Lu +5
Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery. With recent advancement in robot-assisted minimally…
Self-supervised Video Representation Learning by Pace Prediction
Jiangliu Wang, Jianbo Jiao, Yun-Hui Liu
This paper addresses the problem of self-supervised video representation learning from a new perspective -- by video pace prediction. It stems from the observation that human visua…
Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics
Jiangliu Wang, Jianbo Jiao, Linchao Bao +3
This paper proposes a novel pretext task to address the self-supervised video representation learning problem. Specifically, given an unlabeled video clip, we compute a series of s…