Global action selection for illumination invariant color modeling

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2007, Pages 1671-1676

  Sridharan, Mohan ^a   Stone, Peter ^b  

^a The University of Texas at Austin   (United States)

^b University of Texas at Austin   (United States)

Author keywords

Action sequence learning; Color segmentation; Illumination invariance; Legged robots

Indexed keywords

COLOR; INTELLIGENT ROBOTS; INTELLIGENT SYSTEMS; MOBILE ROBOTS; OPTICAL PROPERTIES;

ACTION SEQUENCE LEARNING; COLOR SEGMENTATION; ILLUMINATION INVARIANCE; LEGGED ROBOTS;

ROBOTS;

EID: 51349154674     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2007.4399203     Document Type: Conference Paper

References (24)

1. J. Pineau, M. Montemerlo, M. Pollack, N. Roy, and S. Thrun, "Towards robotic assistants in nursing homes: Challenges and results," RAS Special Issue on Socially Interactive Robots, 2003.
2. B. W. Minten, R.R. Murphy, J. Hyams, and M. Micire, "Low-order- complexity vision-based docking," IEEE Transactions on Robotics and Automation, vol. 17, no. 6, pp. 922-930, 2001.
3. S. Thrun, "Stanley: The Robot that Won the DARPA Grand Challenge," Journal of Field Robotics, vol. 23, no. 9, pp. 661-692, 2006.
4. D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," PAMI, 2002.
5. J. Shi and J. Malik, "Normalized cuts and image segmentation," In IEEE Transactions on PAMI, 2000.
6. A. Elgammal, D. Harwood, and L. Davis, "Non-parametric Model for Background Subtraction," in The European Conference on Computer Vision (ECCV), 2000.
7. M. Sridharan and P. Stone, "Color learning on a mobile robot: Towards full autonomy under changing illumination," in The International Joint Conference on Artificial Intelligence, 2007.
8. D. Cohen, Y. H. Ooi, P. Vernaza, and D. D. Lee, UPenn TDP, RoboCup-2003: RoboCup Competitions and Conferences, 2004.
9. L. T. Maloney and B. A. Wandell, "Color Constancy: A Method for Recovering Surface Spectral Reflectance," Journal of Optical Soceity of America A, vol. 3, no. 1, pp. 29-33, 1986.
10. C. Rosenberg, M. Hebert, and S. Thrun, "Color constancy using kl-divergence," in The IEEE International Conference on Computer Vision (ICCV), 2001.
11. Y. B. Lauziere, D. Gingras, and F. P. Ferrie, "Autonomous physics-based color learning under daylight," in Conf. on Color Techniques and Polarization in Industrial Inspection, 1999.
12. T Gevers and A. W. M. Smeulders, "Color based object recognition," In Pattern Recognition, 1999.
13. D. Cameron and N. Barnes, "Knowledge-based autonomous dynamic color calibration," in The International RoboCup Symposium, 2003.
14. M. Jungel, "Using layered color precision for a self-calibrating vision system," in The International RoboCup Symposium, 2004.
15. D. Schulz and D. Fox, "Bayesian color estimation for adaptive vision-based robot localization," in IROS, 2004.
16. F. Anzani, D. Bosisio, M. Matteucci, and D. Sorrenti, "On-line color calibration in non-stationary environments," in The International RoboCup Symposium, 2005.
17. "The DARPA Learning Applied to Ground Robots Challenge," 2005, www.darpa.mil/ipto/programs/lagr/.
18. H. Kitano, M. Asada, I. Noda, and H. Matsubara, "Robot world cup," Robotics and Automation, 1998.
19. B. Efron and R. J. Tibshirani, An Introduction to Bootstrap. Chapman and Hall Publishers, 1993.
20. P. S. Maybeck, Stochastic Models, Estimation and Control, 1979.
21. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford University Press, 1995.
22. "Matlab Neural Network Toolbox," http://www.mathworks.com/ access/helpdesk/help/toolbox/nnet/.
23. "The Four-Legged League," 2007, http://www.tzi.de/4legged/.
24. P. Jensfelt, J. Folkesson, D. Kragic, and H. I. Christensen, "Exploiting distinguishable image features in robotic mapping and localization," in The European Robotics Symposium (EUROS), 2006.