Robot Control Based on Qualitative Representation of Human Trajectories

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.

[1]  Hans-Hellmut Nagel,et al.  Steps toward a Cognitive Vision System , 2004, AI Mag..

[2]  Wolfram Burgard,et al.  Learning Motion Patterns of People for Compliant Robot Motion , 2005, Int. J. Robotics Res..

[3]  Anthony G. Cohn,et al.  Qualitative Spatial Representation and Reasoning , 2008, Handbook of Knowledge Representation.

[4]  Kai Oliver Arras,et al.  Place-Dependent People Tracking , 2009, ISRR.

[5]  Francesco Bullo,et al.  Smooth Nearness-Diagram Navigation , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Alessandro Saffiotti,et al.  Robots that Change Their World: Inferring Goals from Semantic Knowledge , 2011, ECMR.

[7]  Yasushi Nakauchi,et al.  A Social Robot that Stands in Line , 2002, Auton. Robots.

[8]  Hans-Hellmut Nagel,et al.  Cognitive visual tracking and camera control , 2012, Comput. Vis. Image Underst..

[9]  Nico Van de Weghe,et al.  A Qualitative Trajectory Calculus to Reason about Moving Point Objects , 2012 .

[10]  Huosheng Hu,et al.  Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters , 2010, Auton. Robots.

[11]  B. Duffy,et al.  What is a social robot , 1999 .

[12]  A. Cohn,et al.  A qualitative trajectory calculus as a basis for representing moving objects in Geographical Information Systems , 2006 .

[13]  H.-H. Nagel,et al.  Representation of occurrences for road vehicle traffic , 2008, Artif. Intell..

[14]  Han-Pang Huang,et al.  A mobile robot that understands pedestrian spatial behaviors , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Takayuki Kanda,et al.  Abstracting People's Trajectories for Social Robots to Proactively Approach Customers , 2009, IEEE Transactions on Robotics.

[16]  Luc Van Gool,et al.  A distributed camera system for multi-resolution surveillance , 2009, 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC).