A discrete computational model of sensorimotor contingencies for object perception and control of behavior

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2011, Pages 3810-3815

  Maye, Alexander ^a   Engel, Andreas K ^a  

^a UNIVERSITY MEDICAL CENTER HAMBURG EPPENDORF   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL AGENTS; COGNITIVE CONTROL ARCHITECTURE; COMPUTATIONAL MODEL; MODELING STUDIES; OBJECT PERCEPTION; REAL ROBOT; ROBOT CONTROLS; SENSORIMOTOR CONTINGENCIES; SENSORY MEASUREMENT; SENSORY SIGNALS; SENSORY STIMULATION; SENSORY SYSTEM; VALUE SYSTEMS; VISUAL AWARENESS;

BEHAVIORAL RESEARCH; COGNITIVE SYSTEMS; COMPUTER SIMULATION; OBJECT RECOGNITION; ROBOTICS; SENSORY PERCEPTION;

AUTONOMOUS AGENTS;

EID: 84865250048     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2011.5979919     Document Type: Conference Paper

References (14)

1. J.K. O'Regan and A. Noë. A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences, 24:939-973, 2001.
2. T.C. Kietzmann, S. Geuter, and P. König. The role of overt visual attention in the process of perceptual formation. In Rovereto Attention Workshop, 2009.
3. T. Asfour, A. Welke, P. Ude, P. Azad, J. Hoeft, and R. Dillmann. Perceiving objects and movements to generate actions on a humanoid robot. In IEEE International Conference on Robotics and Automation (ICRA'07). Workshop: From features to actions - Unifying perspectives in computational and robot vision, April 2007.
4. M. Lungarella and O. Sporns. Mapping information flow in sensorimotor networks. PLoS Computational Biology, 2 e144(10):1301-1312, 2006.
5. P. Fine, E. Di Paolo, and E. Izquierdo. Adapting to your body. In Ninth European Conference on Artificial Life, pages 203-212. Springer, 2007.
6. H. Hoffmann. Perception through visuomotor anticipation in a mobile robot. Neural Networks, 20:22-33, 2007.
7. S. Bovet and R. Pfeifer. Emergence of delayed reward learning from sensorimotor coordination. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2272 - 2277, August 2005.
8. M. Maillard, O. Gapenne, L. Hafemeister, and P. Gaussier. Perception as a dynamical sensori-motor attraction basin. In Advances in Artificial Life (8th European Conference, ECAL), pages 37-46, 2005.
9. Y. Choe, H.-F. Yang, and D.C.-Y. Eng. Autonomous learning of the semantics of internal sensory states based on motor exploration. International Journal of Humanoid Robotics, 4:211-243, 2007.
10. D.G. Lowe. Distinctive image features from scale-invariant key-points. International Journal of Computer Vision, 60:91-110, 2004.
11. A.C. Romea, D. Berenson, S. Srinivasa, and D. Ferguson. Object recognition and full pose registration from a single image for robotic manipulation. In IEEE International Conference on Robotics and Automation (ICRA '09), May 2009.
12. L. Wiskott, M. Franzius, P. Berkes, and H. Sprekeler. Is slowness a learning principle of the visual system? In Proc. 39th Annual European Brain and Behaviour Society, Triest, Italy, September 15-19, pages 14-15, 2007. Special issue of Neural Plasticity, Article ID 23250.
13. E. Di Paolo, M. Rohde, and H. De Jaegher. Enaction: Toward a New Paradigm for Cognitive Science, chapter Horizons for the enactive mind: Values, social interaction and play, pages 33-87. MIT Press, Cambridge, MA, USA, 2010.
14. F. Oudeyer P.-Y., Kaplan and V. Hafner. Intrinsic motivation systems for autonomous mental development. IEEE Transactions on Evolutionary Computation, 11(2):265-286, 2007.