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arXiv · 2509.14967

Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery

Ana Davila·Jacinto Colan·Yasuhisa Hasegawa
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Abstract

Effective human-robot collaboration in surgery is affected by the inherent ambiguity of verbal communication. This paper presents a framework for a robotic surgical assistant that interprets and disambiguates verbal instructions from a surgeon by grounding them in the visual context of the operating field. The system employs a two-level affordance-based reasoning process that first analyzes the surgical scene using a multimodal vision-language model and then reasons about the instruction using a knowledge base of tool capabilities. To ensure patient safety, a dual-set conformal prediction method is used to provide a statistically rigorous confidence measure for robot decisions, allowing it to identify and flag ambiguous commands. We evaluated our framework on a curated dataset of ambiguous surgical requests from cholecystectomy videos, demonstrating a general disambiguation rate of 60% and presenting a method for safer human-robot interaction in the operating room.

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Ana Davila, Jacinto Colan, Yasuhisa Hasegawa. 2025-09-18. Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery. https://arxiv.org/abs/2509.14967

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