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Combined Intention, Activity, and Motion Recognition for a Humanoid Household Robot

Gehrig, Dirk; Krauthausen, Peter; Rybok, Lukas; Kühne, Hildegard; Schultz, Tanja; Hanebeck, Uwe D.; Stiefelhagen, Rainer

In this paper, a multi-level approach to intention, activity, and motion recognition for a humanoid robot is proposed. Our system processes images from a monocular camera and combines this information with domain knowledge. The recognition works on-line and in real-time, it is independent of the test person, but limited to predefined view-points. Main contributions of this paper are the extensible, multi-level modeling of the robot's vision system, the efficient activity and motion recognition, and the asynchronous information fusion based on generic processing of mid-level recognition results. The complementarity of the activity and motion recognition renders the approach robust against misclassifications. Experimental results on a real-world data set of complex kitchen tasks, e.g., Prepare Cereals or Lay Table, prove the performance and robustness of the multi-level recognition approach.

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Volltext §
DOI: 10.5445/IR/1000035124
DOI: 10.1109/IROS.2011.6095118
Zugehörige Institution(en) am KIT Institut für Anthropomatik (IFA)
Publikationstyp Proceedingsbeitrag
Jahr 2011
Sprache Englisch
Identifikator ISBN: 978-1-61284-454-1
KITopen-ID: 1000035124
Erschienen in Proceedings of the International Conference on Intelligent Robots and Systems (IROS11), San Francisco, CA, USA, September 2011
Verlag IEEE, Piscataway
Seiten 4819-4825
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