6 páginas, 6 figuras.-- Presentado al Workshop on Agents Learning Interactively from Human Teachers(ALIHT) celebrado en Barcelona del 16 al 22 de julio de 2011. ; Researchers are becoming aware of the importance of other information sources besides visual data in robot learning by demonstration (LbD). Force-based 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. ; This research is partially sponsored by the European projects GARNICS (FP7-247947) and IntellAct (FP7-269959), the Spanish projects MIPRCV (Consolider Ingenio 2010 project CSD2007-00018) and PAU (DPI2008-06022). L. Rozo was supported by the CSIC under a JAE-PREDOC scholarship. ; Peer reviewed
Robot learning from demonstration in the force domain
2011-01-01
Conference paper
Electronic Resource
English
DDC: | 629 |