- AutorIn
- Heni Ben Amor
- Titel
- Imitation Learning of Motor Skills for Synthetic Humanoids
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:105-qucosa-62877
- Datum der Einreichung
- 01.06.2010
- Datum der Verteidigung
- 12.11.2010
- Abstract (EN)
- This thesis addresses the question of how to teach dynamic motor skills to synthetic humanoids. A general approach based on imitation learning is presented and evaluated on a number of synthetic humanoids, as well as a number of different motor skills. The approach allows for intuitive and natural specification of motor skills without the need for expert knowledge. Using this approach we show that various important problems in robotics and computer animation can be tackled, including the synthesis of natural grasping, the synthesis of locomotion behavior or the physical interaction between humans and robots.
- Freie Schlagwörter (DE)
- Imitation, Virtuelle Menschen, Bewegungssynthese, Künstliche Intelligenz, Machinelles Lernen
- Freie Schlagwörter (EN)
- Imitation, Machine Learning, Virtual Humans, Artificial Intelligence, Animation
- Klassifikation (DDC)
- 004
- Normschlagwörter (GND)
- Künstlicher Mensch, Motorik, Virtuelle Realität, Künstliche Intelligenz
- GutachterIn
- Prof. Dr. Bernhard Jung
- Prof. Dr. Ulrich Furbach
- BetreuerIn
- Prof. Dr. Bernhard Jung
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Bergakademie Freiberg, Freiberg
- URN Qucosa
- urn:nbn:de:bsz:105-qucosa-62877
- Veröffentlichungsdatum Qucosa
- 13.12.2010
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Englisch