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Guankun Wang

7 accepted papers

2026

GeoLanG: Geometry-Aware Language-Guided Grasping with Unified RGB-D Multimodal Learning

ICRA 2026poster

Language-guided grasping has emerged as a promising paradigm for enabling robots to identify and manipulate target objects through natural language instructions, yet it remains highly challenging in cluttered or occluded scenes. Existing methods often rely on multi-stage pipelines that separate obje…

2026

MedScope: Incentivizing "Think with Videos" for Clinical Reasoning via Coarse-to-Fine Tool Calling

ICML 2026poster

Long-form clinical videos are central to visual evidence-based decision-making, with growing importance for applications such as surgical robotics and related settings. However, current multimodal large language models typically process videos with passive sampling or weakly grounded inspection, whi…

Cited by 0SourceScholar
2026

TMR-VLA: Vision-Language-Action Model for Magnetic Motion Control of Tri-Leg Silicone-Based Soft Robot

ICRA 2026poster

In-vivo environments, magnetically actuated soft robots offer advantages such as wireless operation and precise control, showing promising potential for painless detection and therapeutic procedures. We developed a trileg magnetically driven soft robot (TMR) whose multi-legged design enables more fl…

Cited by 0Scholar
2025

ETSM: Automating Dissection Trajectory Suggestion and Confidence Map-Based Safety Margin Prediction for Robot-Assisted Endoscopic Submucosal Dissection

ICRA 2025

Robot-assisted Endoscopic Submucosal Dissection (ESD) improves the surgical procedure by providing a more comprehensive view through advanced robotic instruments and bimanual operation, thereby enhancing dissection efficiency and accuracy. Accurate prediction of dissection trajectories is crucial fo

Cited by 3SourcecodeScholar
2025

EndoVLA: Dual-Phase Vision-Language-Action for Precise Autonomous Tracking in Endoscopy

CoRL 2025poster

In endoscopic procedures, autonomous tracking of abnormal regions and following of circumferential cutting markers can significantly reduce the cognitive burden on endoscopists. However, conventional model-based pipelines are fragile—each component (e.g., detection, motion planning) requires manual…

Cited by 0SourceScholar
2024

OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery

ICRA 2024poster

In the realm of automated robotic surgery and computer-assisted interventions, understanding robotic surgical activities stands paramount. Existing algorithms dedicated to surgical activity recognition predominantly cater to pre-defined closed-set paradigms, ignoring the challenges of real-world ope…

Cited by 7SourcecodeScholar