Situation-specific intention recognition for human-robot cooperation

Authors:
Peter Krauthausen;Uwe D. Hanebeck
Affiliations:
Intelligent Sensor-Actuator-Systems Laboratory, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany;Intelligent Sensor-Actuator-Systems Laboratory, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
Venue:
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Year:
2010

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Abstract

Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used computation time need to be balanced. This becomes challenging, if the number of sensors is high and measurement systems are complex. In this paper, a model predictive approach to this problem based on online switching of small, situation-specific Dynamic Bayesian Networks is proposed. The contributions are an efficient modeling and inference of situations and a greedy model predictive switching algorithm maximizing the mutual information of predicted situations. The achievable accuracy and computational savings are demonstrated for a household scenario by using an extended range telepresence system.