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Learning Human Body Motions from Skeleton-Based Observations for Robot-Assisted Therapy

  • Robots applied in therapeutic scenarios, for instance in the therapy of individuals with Autism Spectrum Disorder, are sometimes used for imitation learning activities in which a person needs to repeat motions by the robot. To simplify the task of incorporating new types of motions that a robot can perform, it is desirable that the robot has the ability to learn motions by observing demonstrations from a human, such as a therapist. In this paper, we investigate an approach for acquiring motions from skeleton observations of a human, which are collected by a robot-centric RGB-D camera. Given a sequence of observations of various joints, the joint positions are mapped to match the configuration of a robot before being executed by a PID position controller. We evaluate the method, in particular the reproduction error, by performing a study with QTrobot in which the robot acquired different upper-body dance moves from multiple participants. The results indicate the method's overall feasibility, but also indicate that the reproduction quality is affected by noise in the skeleton observations.

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Document Type:Preprint
Author:Natalia Quiroga, Alex Mitrevski, Paul G. Plöger
Number of pages:6
ArXiv Id:http://arxiv.org/abs/2207.12224
Date of first publication:2022/07/25
Publication status:Accepted for presentation at the 6th Workshop on Behavior Adaptation and Learning for Assistive Robotics (BAILAR) at RO-MAN 2022
Funding:This work is conducted in the context of the MigrAVE project, which is funded by the German Ministry of Education and Research (BMBF).
Departments, institutes and facilities:Fachbereich Informatik
Projects:FH-Sozial 2018: MigrAVE - Multilinguales Online-Lernportal und transkultureller Roboter-Lernassistent für Autismus-Spektrum-Störungen (DE/BMBF/13FH090SB8)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2023/06/13