Robot-aided rehabilitation enables to assist the patient in executing task-oriented exercises and typically takes advantage of virtual environments in which motor tasks are performed. However, a mismatch between the visual and the proprioceptive stimuli can occurr. The use of real tools to perform rehabilitation tasks could overcome this drawback. Nevertheless, several issues arise, such as the estimation of the pose of the real objects in the workspace and the planning of the trajectories the robot has to execute to guide the patient’s limb to reach the objects. In this paper, a robot-aided upper-limb rehabilitation system able to recognize the objects the patient has to interact with and to dynamically plan the robot trajectories is presented. The performance of the DMP-based Motion Planner is assessed to evaluate its capability i) to reproduce the motion style of an healthy subject and ii) to reach the target position with small residual errors. https://youtu.be/4TgRGg6sVTM

Combined use of DMP and real objects in robot-aided rehabilitation

Tamantini, Christian
Primo
;
2020

Abstract

Robot-aided rehabilitation enables to assist the patient in executing task-oriented exercises and typically takes advantage of virtual environments in which motor tasks are performed. However, a mismatch between the visual and the proprioceptive stimuli can occurr. The use of real tools to perform rehabilitation tasks could overcome this drawback. Nevertheless, several issues arise, such as the estimation of the pose of the real objects in the workspace and the planning of the trajectories the robot has to execute to guide the patient’s limb to reach the objects. In this paper, a robot-aided upper-limb rehabilitation system able to recognize the objects the patient has to interact with and to dynamically plan the robot trajectories is presented. The performance of the DMP-based Motion Planner is assessed to evaluate its capability i) to reproduce the motion style of an healthy subject and ii) to reach the target position with small residual errors. https://youtu.be/4TgRGg6sVTM
2020
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Robot-aided Rehabilitation, Vision-based Pose Estimation, Dynamical Movement Primitives
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/551006
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