Combining radar and vision for self-supervised ground segmentation in outdoor environments

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2011, Pages 255-260

  Milella, Annalisa ^a   Reina, Giulio ^b   Underwood, James ^c   Douillard, Bertrand ^c  

^a INSTITUTE OF INTELLIGENT SYSTEMS FOR AUTOMATION   (Italy)

^b UNIVERSITY OF SALENTO   (Italy)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMOUS VEHICLES; CAMERA IMAGES; CLASSIFICATION SYSTEM; EXPERIMENTAL TEST; GROUND MODELS; LONG DURATION; LONG RANGE; OUTDOOR ENVIRONMENT; SYSTEM FEATURES; TERRAIN CLASSIFICATION; TRAINING PHASE; VISUAL APPEARANCE; VISUAL MODEL;

IMAGE SEGMENTATION; INTELLIGENT ROBOTS; RADAR; ROBOTICS; UNMANNED VEHICLES; VISUALIZATION;

RADAR MEASUREMENT;

EID: 84455201706     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2011.6048156     Document Type: Conference Paper

References (15)

1. A. Sole, O. Mano, G.P. Stein, H. Kumon, Y. Tamatsu, and A. Shashua, "Solid or not solid: vision for radar target validation," in Proc. IEEE Intelligent Vehicles Symposium, Parma, Italy, 2004, pp. 819-824.
2. Z. Ji and D. Prokhorov, "Radar-vision fusion for object classification," in Proc. 11th International Conference on Information Fusion, Cologne, Germany, 2008, pp. 1-7.
3. G. Alessandretti, A. Broggi, and P. Cerri, "Vehicle and guard rail detection using radar and vision data fusion," IEEE Trans. on Intelligent Transportation Systems, vol. 8, no. 1, pp. 95-105, 2007. (Pubitemid 46376157)
4. R. Grover, G. Brooker, and H.F. Durrant-Whyte, "A low level fusion of millimeter wave radar and night-vision imaging for enhanced characterization of a cluttered environment," in Proc. Australian Conference on Robotics and Automation, Sydney, Australia, 2001, pp. 98-103.
5. U. Hofmann, A. Rieder, and E.D. Dickmanns, "Radar and vision data fusion for hybrid adaptive cruise control on highways," in Proc. International Conference on Computer Vision Systems (ICVS), Vancouver, Canada, 2001, pp. 125-138.
6. B. Steux, C. Laurgeau, L. Salesse, and D. Wautier, "Fade: a vehicle detection and tracking system featuring monocular color vision and radar data fusion," in Proc. IEEE Intelligent Vehicles Symposium (IV2002), Versailles, France, 2002, pp. 632-639.
7. S. Wu, S. Decker, P. Chang, T. Camus, and J. Eledath, "Collision sensing by stereo vision and radar sensor fusion," IEEE Trans. on Intelligent Transportation Systems, vol. 10, no. 4, pp. 606-614, December 2009.
8. C.A. Brooks and K. Iagnemma, "Self-supervised terrain classification for planetary rovers," in Proc. of NASA Science Technology Conference, Adelphi, Maryland, USA, 2007.
9. P. Vernaza, B. Taskar, and D.D. Lee, "Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields," in Proc. IEEE International Conference on Robotics and Automation, Pasadena, California, 2008, pp. 2750-2757.
10. H. Dahlkamp, A. Kaehler, D. Stavens, S. Thrun, and G. Bradski, "Self-supervised monocular road detection in desert terrain," in Proc. of Robotics: Science and Systems, Philadelphia, USA, 2006.
11. G. Brooker, R. Hennessey, M. Bishop, C. Lobsey, H. Durrant-Whyte, and D. Birch, "High-resolution millimeter-wave radar systems for visualization of unstructured outdoor environments," Journal of Field Robotics, vol. 23, no. 10, pp. 891-912, 2006. (Pubitemid 44782742)
12. G. Reina, J. Underwood, G. Brooker, and H. Durrant-Whyte, "Radar-based perception for autonomous outdoor vehicles," Journal of Field Robotics, vol. 28: n/a, doi: 10.1002/rob.20393, 2011.
13. D.M.J. Tax, "One-Class Classification. Concept Learning in the Absence of Counter Examples," PhD Thesis, Delft University of Technology, Delft, Netherlands, 2001.
14. nd Ed., Wiley.
15. T. Peynot, S. Scheding and S. Terho, "The Marulan Data Sets: Multi-Sensor Perception in Natural Environment with Challenging Conditions," International Journal of Robotics Research (IJRR), vol. 29, no. 13, pp. 1602-1607, November 2010.