Open AccessCombined intention, activity, and motion recognition for a humanoid household robot
Author(s) -
Dirk Gehrig,
Peter Krauthausen,
Lukas Rybok,
Hilde Kuehne,
Uwe D. Hanebeck,
Tanja Schultz,
Rainer Stiefelhagen
Publication year - 2011
Publication title -
2011 ieee/rsj international conference on intelligent robots and systems
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1109/iros.2011.6048716
Subject(s) - humanoid robot , computer science , robustness (evolution) , artificial intelligence , complementarity (molecular biology) , computer vision , activity recognition , robot , motion (physics) , asynchronous communication , computer network , biochemistry , chemistry , genetics , biology , gene
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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