Learning slip behavior using automatic mechanical supervision

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2007, Pages 1741-1748

  Angelova, Anelia ^a   Matthies, Larry ^b   Helmick, Daniel ^b   Perona, Pietro ^c  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^c California Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMOUS VEHICLES; SLIP CHARACTERISTICS; VISUAL INFORMATION;

AUTOMATION; IMAGE ANALYSIS; IMAGE RETRIEVAL; ROBOTS; VISUAL SERVOING;

SUPERVISED LEARNING;

EID: 36349022657     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2007.363574     Document Type: Conference Paper

References (26)

1. A. Angelova, L. Matthies, D. Heimick, and P. Perona. Slip prediction using visual information. Robotics: Science and Systems Conference, 2006.
2. A. Angelova, L. Matthies, D. Helmick, G. Sibley, and P. Perona, Learning to predict slip for ground robots. International Conference on Robotics and Automation, 2006.
3. J. Biesiadecki, E. Baumgartner, R. Bonitz, B. Cooper, F. Hartman, P. Leger, M. Maimone, S. Maxwell, A. Trebi-OUennu, E. Tunstel, and J. Wright. Mars Exploration Rover surface operations: Driving Opportunity at Meridiani planum. IEEE Conference on Systems, Man, and Cybernetics, October 2005.
4. A. Blum and T. Mitchell. Combining labeled and unlabeled data with co-training. Conf. on Computational Learning Theory, 1998.
5. C. Brooks, K. Iagnemma, and S. Dubowsky, Vibration-based terrain analysis for mobile robots. International Conference on Robotics and Automation, 2005.
6. H. Dahlkamp, A. Kaehler, D. Stavens, S. Thrun, and G. Bradski. Self-supervised monocular road detection in desert terrain. Robotics: Science and Systems Conference, 2006.
7. A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B, 39(1):1-37, 1977.
8. E. DuPont, R. Roberts, C. Moore, M. Selekwa, and E. Collins. Online terrain classification for mobile robots. International Mechanical Engineering Congress and Exposition Conference, 2005.
9. D. Grollman, O. Jenkins, and F. Wood. Discovering natural kinds of robot sensoty experiences in unstructured environments. Journal of field robotics, 2006.
10. G. Grudic and J. Mulligan. Topological mapping with multiple visual manifolds. Robotics: Science and Systems Conference, 2005.
11. M. Happold, M. Ollis, and N. Johnson. Enhancing supervised terrain classification with predictive unsupervised learning. Robotics: Science and Systems Conference, 2006.
12. M. Jordan and R. Jacobs. Hierarchical mixtures of experts and the EM algorithm. Neural Computation, 6(2):181-214, 1994.
13. A. Julosky, S. Weiland, and W. Heemels. A Bayesian approach to identification of hybrid systems. IEEE Trans. on Automatic Control, 50(10):1520-1533, 2005.
14. D. Kim, J. Sun, S. Oh, J. Rehg, and A. Bobick. Traversability classification using unsupervised on-line visual learning for outdoor robot navigation. International Conference on Robotics and Automation, 2006.
15. Y. LeCun, U. Muller, J. Ben, E. Cosatto, and B. Flepp. Off-road obstacle avoidance through end-to-end learning. Advances in Neural Information Processing Systems, 2005.
16. C. Leger, A. Trebi-Ollennu, J. Wright, S. Maxwell, R. Bonitz, J. Biesiadecki, F. Hartman, B. Cooper, E. Baumgartner, and M. Maimone. Mars Exploration Rover surface operations: Driving Spirit at Gusev crater. IEEE Conference on Systems, Man, and Cybernetics, October 2005.
17. D. Lieb, A. Lookingbill, and S. Thrun. Adaptive road following using self-supervised learning and reverse optical flow. Robotics: Science and Systems Conference, 2005.
18. R. Lindemann and C. Voorhees. Mars Exploration Rover mobility assembly design, test and performance. IEEE International Conference on Systems, Man and Cybernetics, 2005.
19. L. Matthies and S. Schafer. Error modeling in stereo navigation. IEEE Journal of Robotics and Automation, RA-3(3):239-250, June 1987.
20. L. Matthies, M. Turmon, A. Howard, A. Angelova, B. Tang, and E. Mjolsness. Learning for autonomous navigation: Extrapolating from underfoot to the far field. NIPS, Workshop on Machine Learning Based Robotics in Unstructured Environments, 2005.
21. G. Seber and C. Wild. Nonlinear Regression. John Wiley & Sons, New York, 1989.
22. B. Sofman, E. Lin, J. Bagnell, N. Vandapel, and A. Stentz. Improving robot navigation through self-supervised online learning. Robotics: Science and Systems Conference, 2006.
23. J. Tenenbaum, V. de Silva, and J. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, December 2000.
24. M. Varma and A. Zisserman. Texture classification: Are filter banks necessary? IEEE Conf. on Computer Vision and Pattern Recognition, 2003.
25. K. Wagstaff, C. Cardie, S. Rogers, and S. Schroedl. Constrained k-means clustering with background knowledge. International Conference on Machine learning, pages 577-584, 2001.
26. C. Wellington and A. Stentz. Online adaptive rough-terrain navigation in vegetation. International Conference on Robotics and Automation, 2004.