Robot control based on qualitative representation of human trajectories

Bellotto, Nicola (2012) Robot control based on qualitative representation of human trajectories. In: AAAI Spring Symposium, "Designing Intelligent Robots: Reintegrating AI", 26-28 March 2012, Stanford University, CA, USA.

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Abstract

A major challenge for future social robots is the high-level interpretation of human motion, and the consequent generation of appropriate robot actions. This paper describes some fundamental steps towards the real-time implementation of a system that allows a mobile robot to transform quantitative information about human trajectories (i.e. coordinates and speed) into qualitative concepts, and from these to generate appropriate control commands. The problem is formulated using a simple version of qualitative trajectory calculus, then solved using an inference engine based on fuzzy temporal logic and situation graph trees. Preliminary results are discussed and future directions of the current research are drawn.

Item Type:Conference or Workshop Item (Paper)
Additional Information:A major challenge for future social robots is the high-level interpretation of human motion, and the consequent generation of appropriate robot actions. This paper describes some fundamental steps towards the real-time implementation of a system that allows a mobile robot to transform quantitative information about human trajectories (i.e. coordinates and speed) into qualitative concepts, and from these to generate appropriate control commands. The problem is formulated using a simple version of qualitative trajectory calculus, then solved using an inference engine based on fuzzy temporal logic and situation graph trees. Preliminary results are discussed and future directions of the current research are drawn.
Keywords:mobile robotics, artificial intelligence, qualitative spatial reasoning, human-robot interaction
Subjects:H Engineering > H670 Robotics and Cybernetics
G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Computer Science
ID Code:4780
Deposited By: Nicola Bellotto
Deposited On:13 Nov 2011 11:02
Last Modified:13 Mar 2013 09:03

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