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Auteurs principaux: Morasso, Cristian, Meli, Daniele, Divet, Yann, Sessa, Salvatore, Farinelli, Alessandro
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:https://arxiv.org/abs/2403.05399
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author Morasso, Cristian
Meli, Daniele
Divet, Yann
Sessa, Salvatore
Farinelli, Alessandro
author_facet Morasso, Cristian
Meli, Daniele
Divet, Yann
Sessa, Salvatore
Farinelli, Alessandro
contents Hyper-redundant Robotic Manipulators (HRMs) offer great dexterity and flexibility of operation, but solving Inverse Kinematics (IK) is challenging. In this work, we introduce VO-FABRIK, an algorithm combining Forward and Backward Reaching Inverse Kinematics (FABRIK) for repeatable deterministic IK computation, and an approach inspired from velocity obstacles to perform path planning under collision and joint limits constraints. We show preliminary results on an industrial HRM with 19 actuated joints. Our algorithm achieves good performance where a state-of-the-art IK solver fails.
format Preprint
id arxiv_https___arxiv_org_abs_2403_05399
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Planning and Inverse Kinematics of Hyper-Redundant Manipulators with VO-FABRIK
Morasso, Cristian
Meli, Daniele
Divet, Yann
Sessa, Salvatore
Farinelli, Alessandro
Robotics
Hyper-redundant Robotic Manipulators (HRMs) offer great dexterity and flexibility of operation, but solving Inverse Kinematics (IK) is challenging. In this work, we introduce VO-FABRIK, an algorithm combining Forward and Backward Reaching Inverse Kinematics (FABRIK) for repeatable deterministic IK computation, and an approach inspired from velocity obstacles to perform path planning under collision and joint limits constraints. We show preliminary results on an industrial HRM with 19 actuated joints. Our algorithm achieves good performance where a state-of-the-art IK solver fails.
title Planning and Inverse Kinematics of Hyper-Redundant Manipulators with VO-FABRIK
topic Robotics
url https://arxiv.org/abs/2403.05399