Self-learning classification of radar features for scene understanding

Robotics and Autonomous Systems

Volumn 60, Issue 11, 2012, Pages 1377-1388

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

^a UNIVERSITY OF SALENTO   (Italy)

^b INSTITUTE OF INTELLIGENT SYSTEMS FOR AUTOMATION   (Italy)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Field robotics; Radar based perception; Self learning classifier

Indexed keywords

ADAPTIVE TRAINING; AUTONOMOUS DRIVING; AUTONOMOUS NAVIGATION; CHANGING ENVIRONMENT; CLASS LABELS; DUST CLOUDS; FIELD ROBOTICS; LASER DATA; LIGHTING CONDITIONS; LONG DURATION; LONG RANGE; LOW VISIBILITY; MILLIMETER WAVE RADAR; MOBILE ROBOTIC; NATURAL STRUCTURES; PERCEPTION SYSTEMS; QUANTITATIVE COMPARISON; RADAR DATA; RADAR IMAGE; ROBOTIC SENSOR; RURAL ENVIRONMENT; SCENE UNDERSTANDING; SELF-LEARNING; TRAINING SETS; UNMANNED GROUND VEHICLES; WEATHER PHENOMENA;

INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MILLIMETER WAVES; PRECIPITATION (METEOROLOGY); ROADS AND STREETS; ROBOTICS; VISIBILITY;

RADAR;

EID: 84867863058     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.robot.2012.03.002     Document Type: Article

References (39)

1. C. Leger, R. Deen, R. Bonitz, Remote image analysis for Mars exploration rover mobility and manipulation operations, in: Proceedings of IEEE Conference on Systems, Man, and Cybernetics, 2005.
2. S. Thrun, M. Montemerlo, and H. Dahlkamp Stanley: the robot that won the DARPA Grand Challenge Journal of Field Robotics 23 9 2006 661 692
3. N. Vandapel, S. Moorehead, W. Whittaker, R. Chatila, R. Murrieta-Cid, Preliminary results on the use of stereo, color cameras and laser sensors in Antarctica, in: Proceedings of the International Symposium on Experimental Robotics, 1999.
4. T. Hastie, R. Tibshirani, and J. Friedman The Elements of Statistical Learning 2003 Springer
5. 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 23 10 2006 891 912
6. M. Buehler, K. Iagnemma, and S. Singh The 2005 DARPA Grand Challenge 2007 Springer
7. B. Douillard, J. Underwood, K. Kuntz, V. Vlaskine, A. Quadros, P. Morton, A. Frenkel, On the segmentation of 3-D lidar point clouds, in: IEEE International Conference on Robotics and Automation, 2011.
8. G. Reina, G. Ishigami, K. Nagatani, and K. Yoshida Odometry correction using visual slip-angle estimation for planetary exploration rovers Advanced Robotics 24 3 2010 359 385
9. A. Huertas, L. Matthies, A. Rankin, Stereo-based tree traversability analysis for autonomous off-road navigation, in: Workshop of Applications of Computer Vision, 2005.
10. R. Pagnot, P. Grandjea, Fast cross country navigation on fair terrains, in: IEEE International Conference on Robotics and Automation, 1995, pp. 2593-2598.
11. S. Singh, R. Simmons, T. Smith, A. Stentz, V. Verma, A. Yahja, K. Schwehr, Recent progress in local and global traversability for planetary rovers, in: IEEE International Conference on Robotics and Automation, 2000, pp. 1194-1200.
12. G. DeSouza, and A. Kak Vision for mobile robot navigation: a survey IEEE Transactions on Pattern Analysis and Machine Intelligence 24 2 2002 237 267
13. T. Jocherm, T. Pomerleau, C. Thorpe, Vision-based neural network road and intersection detection and traversal, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 1995.
14. D. Pomerleau ALVINN: an autonomous land vehicle in a neural network Advances in Neural Information Processing Systems 1989 Morgan Kaufmann
15. Y. LeCun, F.J. Huang, L. Bottou, Learning methods for generic object recognition with invariance to pose and lighting, in: Conference on Computer Vision and Pattern Recognition, vol. 2, 2004, pp. 97-104.
16. R. Manduchi, A. Castano, A. Talukder, and L. Matthies Obstacle detection and terrain classification for autonomous off-road navigation Autonomous Robot 18 2003 81 102
17. T. Hong, T. Chang, C. Rasmussen, M. Shneier, Road detection and tracking for autonomous mobile robots, in: Proceedings of SPIE Aerosense Conference, 2002, pp. 1194-1200.
18. N. Dima, N. Vandapel, M. Hebert, Classifier fusion for outdoor obstacle detection, in: International Conference on Robotics and Automation (ICRA), 2004.
19. A. Milella, G. Reina, J. Underwood, B. Douillard, Combining radar and vision for self-supervised ground segmentation in outdoor environments, in: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, 2011, pp. 255-260.
20. C. Brooks, K. Iagnemma, Self-supervised terrain classification for planetary rovers, in: Proceedings of NASA Science Technology Conference, 2007.
21. D. Stavens, S. Thrun, A self-supervised terrain roughness estimator for offroad autonomous driving, in: Proceedings of Conference on Uncertainty in AI (UAI), 2006, pp. 255-260.
22. C. Wellington, A. Stentz, Online adaptive rough-terrain navigation in vegetation, in: Proceedings of International Conference on Robotics and Automation, 2004.
23. D. Kim, J. Sun, S.M. Oh, J.M. Rehg, A. Bobick, Traversibility classification using unsupervised on-line visual learning for outdoor robot navigation, in: Proceedings of International Conference on Robotics and Automation, 2006.
24. S. Clark, H.F. Durrant-Whyte, The design of a high performance mm w radar system for autonomous land vehicle navigation, in: International Conference Field and Service Robotics, Sydney, Australia, 1997.
25. S. Boehmke, J. Bares, E. Mutschler, and K. Lay A high speed 3D radar scanner for automation IEEE International Conference on Robotics and Automation 1998 Leuven Belgium
26. H. Durrant-Whyte An autonomous guided vehicle for cargo handling applications International Journal on Robotics Research 15 5 2002 407 441
27. A. Foessel-Bunting, S. Chheda, and D. Apostolopoulos Short-range millimeter-wave radar perception in a polar environment International Conference on Field and Service Robotics 1999 Leuven Belgium
28. G. Brooker, R. Hennessey, M. Bishop, C. Lobsey, and E. Widzyk-Capehart Seeing through dust and water vapor: millimeter wave radar sensors for mining applications Journal of Field Robotics 24 7 2007 527 557
29. J. Mullane, D.M. Adams, and W.S. Wijesoma Robotic mapping using measurement likelihood filtering Journal of Hydrology 10 3 2006 282 290
30. T. Peynot, J. Underwood, and S. Scheding Towards reliable perception for unmanned ground vehicles in challenging conditions IEEE/RSJ International Conference on Intelligent Robots and Systems 2009 St Louis MO, USA
31. G. Reina, J. Underwood, G. Brooker, and H. Durrant-Whyte Radar-based perception for autonomous outdoor vehicles Journal of Field Robotics 28 6 2011 894 913
32. J. Nash, and J. Sutcliffe River flow forecasting through conceptual models part 1: a discussion of principles International Journal on Robotics Research 28 2 2009 172 190
33. G. Reina, J. Underwood, G. Brooker, Short-range radar perception in outdoor environments, in: Towards Autonomous Robotics Systems (TAROS), 2011, pp. 265-276.
34. D. Tax, One-class classification, concept learning in the absence of counter examples, Ph.D. Thesis, Delft University of Technology, Delft, Netherlands, 2001.
35. E. Duda, P. Hart, and D. Stork Pattern Classification second ed. 2001 Wiley
36. J.P. Underwood, A. Hill, T. Peynot, and S.J. Scheding Error modeling and calibration of exteroceptive sensors for accurate mapping applications Journal of Field Robotics 27 1 2010 2 20
37. 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) 29 13 2010 1602 1607
38. J.A. Hanley, and B.J. McNeil The meaning and use of the area under a receiver operating characteristic (ROC) curve Radiology 143 1982 29 36
39. M. Sokolova, N. Japkowicz, and S. Szpakowicz Beyond accuracy, F-score and ROC: a family of discriminant measures for performance evaluation AI 2006: Advances in Artificial Intelligence 2006 1015 1021