Experiences with CiceRobot, a Museum Guide Cognitive Robot

The paper describes CiceRobot, a robot based on a cognitive architecture for robot vision and action. The aim of the architecture is to integrate visual perception and actions with knowledge representation, in order to let the robot to generate a deep inner understanding of its environment. The principled integration of perception, action and of symbolic knowledge is based on the introduction of an intermediate representation based on Gardenfors conceptual spaces. The architecture has been tested on a RWI B21 autonomous robot on tasks related with guided tours in the Archaeological Museum of Agrigento. Experimental results are presented.

[1]  Roberto Pirrone,et al.  Modeling ontologies for robotic environments , 2002, SEKE '02.

[2]  Gideon P. Stein,et al.  Lens distortion calibration using point correspondences , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Salvatore Gaglio,et al.  A Cognitive Architecture for Artificial Vision , 1997, Artif. Intell..

[4]  Wolfram Burgard,et al.  Experiences with an Interactive Museum Tour-Guide Robot , 1999, Artif. Intell..

[5]  Salvatore Gaglio,et al.  Understanding dynamic scenes , 2000, Artif. Intell..

[6]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[7]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..