Radar sensing for intelligent vehicles in urban environments

Sensors (Switzerland)

Volumn 15, Issue 6, 2015, Pages 14661-14678

  Reina, Giulio ^a   Johnson, David ^b   Underwood, James ^b  

^a UNIVERSITY OF SALENTO   (Italy)

^b UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Navigation systems; Perception in urban environment; Radar sensing; Robotic intelligent vehicles; Unmanned ground vehicles

Indexed keywords

ADVANCED DRIVER ASSISTANCE SYSTEMS; AIRSHIPS; AUTOMOBILE FRAMES; GROUND VEHICLES; INTELLIGENT ROBOTS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; RADAR; RESEARCH AIRCRAFT; ROBOTICS; STORMS; URBAN PLANNING; VEHICLES;

AUTONOMOUS VEHICLES; CALIBRATION PARAMETERS; DRIVING ASSISTANCE SYSTEMS; OBSTACLE SEGMENTATION; RADAR SENSING; UNMANNED GROUND VEHICLES; URBAN ENVIRONMENTS; URBAN SCENARIOS;

NAVIGATION SYSTEMS;

EID: 84933557866     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s150614661     Document Type: Article

References (24)

1. Pascoal, J.; Marques, L.; de Almeida, A.T. Assessment of laser range finders in risky environments. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008 (IROS 2008), Nice, France, 22–26 September 2008; pp. 3533–3538
2. Peynot, T.; Underwood, J.; Scheding, S. Towards reliable perception for unmanned ground vehicles in challenging conditions. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009 (IROS 2009), St. Louis, MO, USA, 10–15 October 2009
3. Reina, G.; Milella, A.; Underwood, J. Self-learning classification of radar features for scene understanding. Robot. Auton. Syst. 2012, 60, 1377–1388
4. Currie, N.C.; Hayes, R.D.; Trebits, R.N. Millimeter-Wave Radar Clutter; Artech House: Norwood, MA, USA, 1992
5. Lakshmanan, V.; Zhang, J.; Hondl, K.; Langston, C. A Statistical Approach to Mitigating Persistent Clutter in Radar Reflectivity Data. Sel. Top. Appl. Earth Obs. Remote Sens. IEEE J. 2012, 5, 652–662
6. Papadakis, P. Terrain traversability analysis methods for unmanned ground vehicles: A survey. Eng. Appl. Artif. Intell. 2013, 26, 1373–1385
7. Lalonde, J.; Vandapel, N.; Huber, D.; Hebert, M. Natural terrain classification using three-dimensional ladar data for ground robot mobility. J. Field Robot. 2006, 23, 839–861
8. Cherubini, A.; Spindler, F.; Chaumette, F. Autonomous Visual Navigation and Laser-Based Moving Obstacle Avoidance. IEEE Trans. Intell. Transp. Syst. 2012, 15, 2101–2110
9. Reina, G.; Ishigami, G.; Nagatani, K.; Yoshida, K. Vision-based estimation of slip angle for mobile robots and planetary rovers. In Proceedings of IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, 19–23 May 2008; pp. 486–491
10. Reina, G.; Milella, A. Towards Autonomous Agriculture: Automatic Ground Detection Using Trinocular Stereovision. Sensors 2012, 12, 12405–12423
11. Hadsell, R.; Sermanet, P.; Ben, J.; Erkan, A.; Scoffier, M.; Kavukcuoglu, K.; Muller, U.; LeCun, Y. Learning long-range vision for autonomous off-road driving. J. Field Robot. 2009, 26, 120–144
12. Brooker, G.; Hennesy, R.; Lobsey, C.; Bishop, M.; Widzyk-Capehart, E. Seeing through dust and water vapor: Millimeter wave radar sensors for mining applications. J. Field Robot. 2007, 24, 527–557
13. Peynot, T.; Scheding, S.; Terho, S. The Marulan Data Sets: Multi-sensor Perception in a Natural Environment with Challenging Conditions. Int. J. Robot. Res. 2010, 29, 1602–1607
14. Foessel-Bunting, A.; Chheda, S.; Apostolopoulos, D. Short-range millimeter-wave radar perception in a polar environment. In Proceedings of the 5th International Conference on Field and Service Robotics, Port Douglas, Australia, 29–31 July 1999; pp. 133–138
15. Durrant-Whyte, H.F. An autonomous guided vehicle for cargo handling applications. Int. J. Robot. Res. 2002, 15, 407–441
16. Mullane, J.; Adams, D.M.; Wijesoma, W.S. Robotic Mapping Using Measurement Likelihood Filtering. Int. J. Robot. Res. 2009, 28, 172–190
17. Milella, A.; Reina, G.; Underwood, J. A Self-learning Framework for Statistical Ground Classification using Radar and Monocular Vision. J. Field Robot. 2015, 32, 20–41
18. Kaliyaperumal, K.; Lakshmanan, S.; Kluge, K. An Algorithm for Detecting Roads and Obstacles in Radar Images. IEEE Trans. Veh. Technol. 2001, 50, 170–182
19. Alessandretti, G.; Broggi, A.; Cerri, P. Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion. IEEE Trans. Intell. Trans. Syst. 2007, 8, 95–105
20. Wu, S.; Decker, S.; Chang, P.; Camus, T.; Eledath, J. Collision Sensing by Stereo Vision and Radar Sensor Fusion. IEEE Trans. Intell. Trans. Syst. 2009, 10, 606–614
21. Reina, G.; Underwood, J.; Brooker, G.; Durrant-Whyte, H. Radar-based Perception for Autonomous Outdoor Vehicles. J. Field Robot. 2011, 28, 894–913
22. Brooker, G. Introduction to Sensors; SciTech Publishing: New Dehli, India, 2005
23. Hastie, T.; Tibshirani, R.; Friedman, J. The Elements of Statistical Learning; Springer-Verlag: New York, NY, USA, 2003
24. Johnson, D.; Calleija, M.; Brooker, G.; Nettleton, E. Development of a Dual-Mirror-Scan Elevation-Monopulse Antenna System. In Proceedings of the 2011 European Radar Conference (EuRAD), Manchester, UK, 12–14 October 2011.