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Robot learning from demonstration in the force domain
Rozo Castañeda, Leonel; Jimenez Schlegl, Pablo; Torras, Carme
Universitat Politècnica de Catalunya. Departament d'Urbanisme i Ordenació del Territori; Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
Researchers are becoming aware of the importance of other information sources besides visual data in robot learning by demonstration (LbD). Forcebased perceptions are shown to convey very relevant information – missed by visual and position sensors – for learning specific tasks. In this paper, we review some recent works using forces as input data in LbD and Human-Robot interaction (HRI) scenarios, and propose a complete learning framework for teaching force-based manipulation skills to a robot through a haptic device. We suggest to use haptic interfaces not only as a demonstration tool but also as a communication channel between the human and the robot, getting the teacher more involved in the teaching process by experiencing the force signals sensed by the robot. Within the proposed framework, we provide solutions for treating force signals, extracting relevant information about the task, encoding the training data and generalizing to perform successfully under unknown conditions.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Robòtica
Human-robot interaction
Robot learning
learning (artificial intelligence) robot programming telerobotics PARAULES AUTOR: robot learning
human-robot interaction
haptic Inputs
HMM
GMR
Interacció persona-robot
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