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Bo Lu

21 accepted papers

2026

Endo-GSG: Endoscopic Gaussian Splatting with Geometry-Awareness for Dynamic Tissue Reconstruction via Single-View Monocular Knowledge

IJCAI 2026

Dynamic 3D reconstruction of surgical scenes plays a critical role in robotic-assisted surgery. Gaussian Splatting (GS), while effective for novel view synthesis, struggles to recover accurate surface from a monocular view due to the implicit multi-Gaussian representation of the surface. Specificall

Cited by 0Scholar
2026

Gracefully Air-Written: Enhancing the Legibility and Style Consistency of In-Air Handwriting

AAAI 2026technical

Space computing devices expand handwritten input from two-dimensional screens into three-dimensional space, providing an unrestricted interactive experience. Due to the high degree of freedom and lack of tactile feedback in in-air handwriting, handwritten characters not only become less legible but

Cited by 0SourcePDFScholar
2026

Sample-Efficient Learning with Online Expert Correction for Autonomous Catheter Steering in Endovascular Bifurcation Navigation

ICRA 2026poster

Robot-assisted endovascular intervention offers a safe and effective solution for remote catheter manipulation, reducing radiation exposure while enabling precise navigation. Reinforcement learning (RL) has recently emerged as a promising approach for autonomous catheter steering; however, conventio…

2025

Igniting Creative Writing in Small Language Models: LLM-as-a-Judge versus Multi-Agent Refined Rewards

EMNLP 2025

Large Language Models (LLMs) have demonstrated remarkable creative writing capabilities, yet their substantial computational demands hinder widespread use. Enhancing Small Language Models (SLMs) offers a promising alternative, but current methods like Supervised Fine-Tuning (SFT) struggle with novel

Cited by 0SourcePDFScholar
2025

Real-Time 3D Guidewire Reconstruction from Intraoperative DSA Images for Robot-Assisted Endovascular Interventions

IROS 2025

Accurate three-dimensional (3D) reconstruction of guidewire shapes is crucial for precise navigation in robot-assisted endovascular interventions. Conventional 2D Digital Subtraction Angiography (DSA) is limited by the absence of depth information, leading to spatial ambiguities that hinder reliable

Cited by 0SourceScholar
2025

Sim4EndoR: A Reinforcement Learning Centered Simulation Platform for Task Automation of Endovascular Robotics

ICRA 2025

Robotic-assisted percutaneous coronary intervention (PCI) holds considerable promise for elevating precision and safety in cardiovascular procedures. Nevertheless, current systems heavily depend on human operators, resulting in variability and the potential for human error. To tackle these challenge

Cited by 6SourceScholar
2024

GMM-Based Heuristic Decision Framework for Safe Automated Laparoscope Control

RA-L 2024

Automated laparoscope field of view (FoV) control in minimal invasive surgery (MIS) poses challenges, as existing solutions failed to address dynamic surgical FoV requirements across different phases and they neglected the misorientation effect or potential obstacles during the control process which

Cited by 11SourceScholar
2022

3D Perception based Imitation Learning under Limited Demonstration for Laparoscope Control in Robotic Surgery

ICRA 2022poster

Automatic laparoscope motion control is fundamentally important for surgeons to efficiently perform operations. However, its traditional control methods based on tool tracking without considering information hidden in surgical scenes are not intelligent enough, while the latest supervised imitation…

Cited by 15SourceScholar
2022

Constrained Motion Planning of a Cable-Driven Soft Robot With Compressible Curvature Modeling

RA-L 2022

A cable-driven soft robot with redundancy can perform the tip trajectory tracking task and in the meanwhile fulfill some extra constraints, such as tracking with a designated tip orientation, or avoiding obstacles in the environment. These constraints require proper motion planning of the soft mater

Cited by 49SourcecodeScholar
2022

Learning Laparoscope Actions via Video Features for Proactive Robotic Field-of-View Control

RA-L 2022

Smart laparoscope motion control for adjusting surgical field-of-view is an increasingly hot topic in robot-assisted surgery. Previous off-the-shelf methods have been conducted in reactive ways which heavily rely on human input signals, e.g., gaze or voice, thus cannot avoid cognitive burdens to sur

Cited by 18SourceScholar
2022

PlaTe: Visually-Grounded Planning With Transformers in Procedural Tasks

RA-L 2022

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 ability to plan a goal-directed procedure from real-world videos. Learning structured and plannable state and action sp

Cited by 67SourceScholar
2021

Adversarial Inverse Reinforcement Learning With Self-Attention Dynamics Model

RA-L 2021

In many real-world applications where specifying a proper reward function is difficult, it is desirable to learn policies from expert demonstrations. Adversarial Inverse Reinforcement Learning (AIRL) is one of the most common approaches for learning from demonstrations. However, due to the stochasti

Cited by 32SourcecodeScholar
2021

Data-driven Holistic Framework for Automated Laparoscope Optimal View Control with Learning-based Depth Perception

ICRA 2021poster

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 paradigm may easily bring fatigue to surgical assistants, and misunderstanding between surgeons also hinders assistants to…

Cited by 28SourceScholar
2021

One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video

ICRA 2021poster

Surgical instrument segmentation in robot-assisted surgery (RAS) - especially that using learning-based models - relies on the assumption that training and testing videos are sampled from the same domain. However, it is impractical and expensive to collect and annotate sufficient data from every new…

Cited by 26SourceScholar
2021

Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery

ICRA 2021poster

Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery. With recent advancement in robot-assisted minimally invasive surgery, rich information including surgical videos and robotic kinematics can be recorded, which provide comp…

Cited by 47SourceScholar
2021

Robust Three-Dimensional Shape Sensing for Flexible Endoscopic Surgery Using Multi-Core FBG Sensors

RA-L 2021

In this letter, we propose a novel 3D shape sensing algorithm for flexible endoscopic surgery using multi-core fiber Bragg grating (FBG) sensors. Considering the signal noises and environmental perturbations, the direct use of FBG measurements for shape sensing and position estimation is regarded as

Cited by 55SourceScholar
2021

SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning

IROS 2021poster

Autonomous surgical execution relieves tedious routines and surgeon’s fatigue. Recent learning-based methods, especially reinforcement learning (RL) based methods, achieve promising performance for dexterous manipulation, which usually requires the simulation to collect data efficiently and reduce t…

Cited by 95SourcecodeScholar
2020

A Learning-Driven Framework with Spatial Optimization For Surgical Suture Thread Reconstruction and Autonomous Grasping Under Multiple Topologies and Environmental Noises

IROS 2020poster

Surgical knot tying is one of the most fundamental and important procedures in surgery, and a high-quality knot can significantly benefit the postoperative recovery of the patient. However, a longtime operation may easily cause fatigue to surgeons, especially during the tedious wound closure task. I…

Cited by 17SourceScholar
2020

Automated Folding of a Deformable Thin Object through Robot Manipulators

IROS 2020poster

This paper presents a model-free approach to automate folding of a deformable object with robot manipulators, where its surface was labelled with markers to facilitate vision-based control and alignment. While performing the task involves solving nonconvex or nonlinear terms, in this paper, lineariz…

Cited by 2SourceScholar
2019

Automated Cell Patterning System with a Microchip using Dielectrophoresis

ICRA 2019poster

The ability to patterning cells is an important technique to facilitate cell-based assay and characterization. In this paper, an automated cell patterning system was developed for the fabrication of large-scale cell patterns. To resolve the challenge of the limited printable area, the cell-printing…

Cited by 7SourceScholar