Language-guided robot control for surgical tasks

Paper Title:

SuFIA: Language-Guided Augmented Dexterity for Robotic Surgical Assistants

Published on:

8 May 2024

Primary Category:

Robotics

Paper Authors:

Masoud Moghani,

Lars Doorenbos,

William Chung-Ho Panitch,

Sean Huver,

Mahdi Azizian,

Ken Goldberg,

Animesh Garg

Bullets

Key Details

•

Incorporates LLMs for surgical robot planning and control

•

Enables automation without learning from examples/primitives

•

Uses perception modules to ground objects

•

Has re-planning and human oversight for safety

•

Shown to work on multiple surgical tasks in simulation & physically

Explore the topics in this paper

human oversight

large language models

re-planning

robotic control

surgical automation

AI generated summary

Language-guided robot control for surgical tasks

This paper presents SuFIA, a framework that uses large language models (LLMs) and perception modules to plan and execute robotic control for surgical sub-tasks. This allows for a learning-free approach to surgical automation without needing motion primitives or examples. SuFIA incorporates re-planning and human oversight to mitigate errors. Experiments in simulation and on a physical robot platform demonstrate SuFIA's ability to autonomously perform common surgical tasks under challenging conditions.