The use of collaborative robots (or cobots) in rehabilitation therapies is aimed at assisting and shortening the patient's recovery after neurological injuries. Cobots are inherently safe when interacting with humans and can be programmed in different working modalities based on the patient's needs and the level of the injury. This study presents a design optimization of a robotic system for upper limb rehabilitation based on the manipulability ellipsoid method. The human-robot system is modeled as a closed kinematic chain in which the human hand grasps a handle attached to the robot's end effector. The manipulability ellipsoids are determined for both the human and the robotic arm and compared by calculating an index that quantifies the alignment of the principal axes. The optimal position of the robot base with respect to the patient is identified by a first global optimization and by a further local refinement, seeking the best alignment of the manipulability ellipsoids in a series of points uniformly distributed within the shared workspace.

Manipulability Optimization of a Rehabilitative Collaborative Robotic System / Chiriatti, G; Bottiglione, A; Palmieri, G. - In: MACHINES. - ISSN 2075-1702. - 10:6(2022), p. 452. [10.3390/machines10060452]

Manipulability Optimization of a Rehabilitative Collaborative Robotic System

Chiriatti, G
;
Palmieri, G
2022-01-01

Abstract

The use of collaborative robots (or cobots) in rehabilitation therapies is aimed at assisting and shortening the patient's recovery after neurological injuries. Cobots are inherently safe when interacting with humans and can be programmed in different working modalities based on the patient's needs and the level of the injury. This study presents a design optimization of a robotic system for upper limb rehabilitation based on the manipulability ellipsoid method. The human-robot system is modeled as a closed kinematic chain in which the human hand grasps a handle attached to the robot's end effector. The manipulability ellipsoids are determined for both the human and the robotic arm and compared by calculating an index that quantifies the alignment of the principal axes. The optimal position of the robot base with respect to the patient is identified by a first global optimization and by a further local refinement, seeking the best alignment of the manipulability ellipsoids in a series of points uniformly distributed within the shared workspace.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/308474
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