A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery

Fuente: arXiv
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Auteurs principaux: Colan, Jacinto, Davila, Ana, Fozilov, Khusniddin, Hasegawa, Yasuhisa
Format: Preprint
Publié: 2024
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author Colan, Jacinto
Davila, Ana
Fozilov, Khusniddin
Hasegawa, Yasuhisa
author_facet Colan, Jacinto
Davila, Ana
Fozilov, Khusniddin
Hasegawa, Yasuhisa
contents Minimally invasive surgery (MIS) procedures benefit significantly from robotic systems due to their improved precision and dexterity. However, ensuring safety in these dynamic and cluttered environments is an ongoing challenge. This paper proposes a novel hierarchical framework for collision avoidance in MIS. This framework integrates multiple tasks, including maintaining the Remote Center of Motion (RCM) constraint, tracking desired tool poses, avoiding collisions, optimizing manipulability, and adhering to joint limits. The proposed approach utilizes Hierarchical Quadratic Programming (HQP) to seamlessly manage these constraints while enabling smooth transitions between task priorities for collision avoidance. Experimental validation through simulated scenarios demonstrates the framework's robustness and effectiveness in handling diverse scenarios involving static and dynamic obstacles, as well as inter-tool collisions.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10135
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery
Colan, Jacinto
Davila, Ana
Fozilov, Khusniddin
Hasegawa, Yasuhisa
Robotics
Minimally invasive surgery (MIS) procedures benefit significantly from robotic systems due to their improved precision and dexterity. However, ensuring safety in these dynamic and cluttered environments is an ongoing challenge. This paper proposes a novel hierarchical framework for collision avoidance in MIS. This framework integrates multiple tasks, including maintaining the Remote Center of Motion (RCM) constraint, tracking desired tool poses, avoiding collisions, optimizing manipulability, and adhering to joint limits. The proposed approach utilizes Hierarchical Quadratic Programming (HQP) to seamlessly manage these constraints while enabling smooth transitions between task priorities for collision avoidance. Experimental validation through simulated scenarios demonstrates the framework's robustness and effectiveness in handling diverse scenarios involving static and dynamic obstacles, as well as inter-tool collisions.
title A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery
topic Robotics
url https://arxiv.org/abs/2409.10135