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Titel:

Humanoid robot learning and game playing using PC-based vision

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Darrin C Bentivegna, Ales Ude, Christopher G Atkeson, Gordon Cheng
Seitenangaben Beitrag:
2449-2454
Abstract:
This paper describes humanoid robot learning from observation and game playing using information provided by a real-time PC-based vision system. To cope with extremely fast motions that arise in the environment, a visual system capable of perceiving the motion of several objects at 60 fields per second was developed. We have designed a suitable error recovery scheme for our vision system to ensure successful game playing over longer periods of time. To increase the learning rate of the robot it...     »
Herausgeber:
IEEE
Kongress- / Buchtitel:
IEEE/RSJ international conference on intelligent robots and systems
Ausrichter der Konferenz:
IEEE
Datum der Konferenz:
30.9.2002-4.10.2002
Verlag / Institution:
IEEE
Jahr:
2002
Seiten:
2449-2454
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