Terrain traversability analysis methods for unmanned ground vehicles: A survey

Engineering Applications of Artificial Intelligence

Volumn 26, Issue 4, 2013, Pages 1373-1385

  Papadakis, Panagiotis ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Mobile robots; Survey; Terrain traversability; Unmanned ground vehicles

Indexed keywords

INTELLIGENT ROBOTS; INTERPLANETARY SPACECRAFT; LANDFORMS; LEARNING SYSTEMS; MOBILE ROBOTS; MOTION PLANNING; OFF ROAD VEHICLES; OPTICAL RADAR; ROBOT PROGRAMMING; STEREO IMAGE PROCESSING; SURVEYING; SURVEYS;

ANALYSIS METHOD; PLANETARY EXPLORATION; ROBOT PERCEPTION; SEARCH AND RESCUE; TERRAIN PERCEPTION; TRAVERSABILITY; UNMANNED GROUND VEHICLES; VEHICLE MODEL;

INTELLIGENT VEHICLE HIGHWAY SYSTEMS;

EID: 84875227934     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2013.01.006     Document Type: Short Survey

References (95)

1. J. Andersen, B. Christian, R. Morten, O. Ravn, N. Andersen, and M. Blanke Traversable terrain classification for outdoor autonomous robots using single 2D laser scans Integrated Comput. Aided Eng. 13 2006 223 232
2. A. Angelova, L. Matthies, D. Helmick, and P. Perona Learning and prediction of slip from visual information research articles J. Field Robotic. 24 3 2007 205 231
3. Angelova, A.; Matthies, L.; Helmick, D.M.; Perona, P.; 2007. Fast terrain classification using variable-length representation for autonomous navigation. In: CVPR.
4. M. Bajracharya, A. Howard, L.H. Matthies, B. Tang, and M. Turmon Autonomous off-road navigation with end-to-end learning for the LAGR program J. Field Robotic. 26 1 2009 3 25
5. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool Speeded-up robust features (SURF) Comput. Vision Image Understanding 110 3 2008 346 359
6. Bellutta, P.; Manduchi, R.; Matthies, L.; Owens, K.; Rankin, A.; 2000. Terrain perception for Demo III. In: Proceedings of the IEEE Intelligent Vehicles Symposium.
7. Bermudez, F.L.G.; Julian, R.C.; Haldane, D.W.; Abbeel, P.; Fearing, R.S.; 2012. Performance analysis and terrain classification for a legged robot over rough terrain. In: IEEE International Conference on Intelligent Robots and Systems.
8. Bonnafous, D.; Lacroix, S.; Simeon, T.; 2001. Motion generation for a rover on rough terrains. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 784-789.
9. BostonDynamics, Sandflea jumping robot 〈 Www.bostondynamics.com 〉.
10. J. Carsten, A. Rankin, D. Ferguson, and A. Stentz Global planning on the Mars exploration rovers software integration and surface testing J. Field Robotic. 26 4 2009 337 357
11. S. Chhaniyara, C. Brunskill, B. Yeomans, M. Matthews, C. Saaj, S. Ransom, and L. Richter Terrain trafficability analysis and soil mechanical property identification for planetary rovers a survey J. Terramech. 49 2 2012 115 128
12. Coyle, E.; Collins, E.; 2008. A comparison of classifier performance for vibration-based terrain classification. In: Army Science Conference.
13. C.D. Crane III, D.G. Armstrong II, R. Touchton, T. Galluzzo, S. Solanki, J. Lee, D. Kent, M. Ahmed, R. Montane, S. Ridgeway, S. Velat, G. Garcia, M. Griffis, S. Gray, J. Washburn, and G. Routson Team CIMAR's navigator an unmanned ground vehicle for the 2005 DARPA grand challenge J. Field Robotic. 23 8 2006 599 623
14. Daily, M.; Harris, J.; Keirsey, D.; Olin, D.; Payton, D.; Reiser, K.; Rosenblatt, J.; Tseng, D.; Wong, V.; 1988. Autonomous cross-country navigation with the ALV. In: IEEE International Conference on Robotics and Automation.
15. G. DeSouza, and K. Avinash Vision for mobile robot navigation a survey IEEE Trans. Pattern Anal. Mach. Intell. 24 2002 237 267
16. Dima, C.; Vandapel, N.; Hebert, M.; 2004. Classifier fusion for outdoor obstacle detection. In: International Conference on Robotics and Automation.
17. Dongshin, K.; Oh, S.; Rehg, J.; 2007. Traversability classification for UGV navigation: a comparison of patch and superpixel representations. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
18. Dubbelmanand, G.; van der Mark, W.; van den Heuvel, J.; Groen, F.C.A.; 2007. Obstacle detection during day and night conditions using stereo vision. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
19. A. Elfes Using occupancy grids for mobile robot perception and navigation IEEE Comput. Mag. 22 6 1989 46 57
20. Ferguson, D.; Morris, A.C.; Haehnel, D.; Baker, C.R.; Omohundro, Z.; Reverte, C.; Thayer, S.; Whittaker, W.L.; Whittaker, C.; Burgard, W.; Thrun, S.; 2003. An autonomous robotic system for mapping abandoned mines. In: Advances in Neural Information Processing Systems.
21. Filitchkin, P.; Byl, K.; 2012. Feature-based terrain classification for littledog. In: IEEE International Conference on Intelligent Robots and Systems.
22. G. Freitas, G. Gleizer, F. Lizarralde, L. Hsu, and N.R.S. dos Reis Kinematic reconfigurability control for an environmental mobile robot operating in the Amazon rain forest J. Field Robotic. 27 2 2010 197 216
23. D. Gennery Traversability analysis and path planning for a planetary rover Auton. Robot. 6 1999 131 146
24. Gibson, J.; 1979. The Ecological Approach to Visual Perception. Laurence Erlbaum Associates.
25. Goldberg, S.; Maimone, M.; Matthies, L.; 2002. Stereo vision and rover navigation software for planetary exploration. In: IEEE Aerospace Conference Proceedings, pp. 2025-2036.
26. Guizzo, E.; Ackerman, E.; Waibel, M.; Taylor, M.; Bouchard, S.; August 2011. Fukushima robot operator writes tell-all blog 〈 http://spectrum.ieee. org/automaton/robotics/industrial-robots/fukushima-robot-operator-diaries 〉.
27. Guo, Y.; Song, A.; Bao, J.; Zhang, H.; 2011. Optimal path planning in field based on traversability prediction for mobile robot. In: International Conference on Electric Information and Control Engineering (ICEICE), pp. 563-566.
28. Halatci, I.; Brooks, C.; Iagnemma, K.; 2007. Terrain classification and classifier fusion for planetary exploration rovers. In: IEEE Aerospace Conference, pp. 1-11.
29. Happold, M.; Ollis, M.; Johnson, N.; 2006. Enhancing supervised terrain classification with predictive unsupervised learning. In: Robotics Science and Systems.
30. R. Hartley, and A. Zisserman Multiple View Geometry in Computer Vision 2004 Cambridge University Press
31. Heckman, N.; Lalonde, J.-F.; Vandapel, N.; Hebert, M.; 2007. Potential negative obstacle detection by occlusion labeling. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2168-2173.
32. D. Helmick, A. Angelova, and L. Matthies Terrain adaptive navigation for planetary rovers J. Field Robotics 26 2009 391 410
33. R. Hoffman, and E. Krotkov Terrain roughness measurement from elevation maps Mobile Robots 1195 1989 104 114
34. A. Howard, and H. Seraji Vision-based terrain characterization and traversability assessment J. Robotic Syst. 18 10 2001 577 587
35. Howard, A.; Seraji, H.; Tunstel, E.; 2001. A rule-based fuzzy traversability index for mobile robot navigation. In: IEEE International Conference on Robotics and Automation.
36. A. Howard, M. Turmon, L. Matthies, B. Tang, A. Angelova, and E. Mjolsness Towards learned traversability for robot navigation from underfoot to the far field J. Field Robotics 23 11-12 2006 1005 1017
37. T. Howard, C. Green, A. Kelly, and D. Ferguson State space sampling of feasible motions for high-performance mobile robot navigation in complex environments J. Field Robotics 25 6-7 2008 325 345
38. Huntsberger, T.; Jain, A.; Cameron, J.; Woodward, G.; Myers, D.; Sohl, G.; 2008. Characterization of the ROAMS simulation environment for testing rover mobility on sloped terrain. In: International Symposium on Artificial Intelligence, Robotics, and Automation in Space.
39. Iagnemma, K.; Shibly, H.; Dubowsky, S.; 2002. On-line terrain parameter estimation for planetary rovers. In: IEEE International Conference on Robotics and Automation, vol. 3, pp. 3142-3147.
40. iRobot, 110 first look 〈 Www.irobot.com 〉.
41. Ishigami, G.; Nagatani, K.; Yoshida, K.; 2011. Path planning and evaluation for planetary rovers based on dynamic mobility index. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
42. L. Jaillet, J. Cortes, and T. Simeon Sampling-based path planning on configuration-space costmaps IEEE Trans. Robotics 26 4 2010 635 646
43. Joho, D.; Stachniss, C.; Pfaff, P.; Burgard, W.; 2007. Autonomous exploration for 3D map learning. In: Autonome Mobile Systeme, pp. 22-28.
44. L. Kavraki, P. Svestka, J. Latombe, and M. Overmars Probabilistic roadmaps for path planning in high-dimensional configuration spaces IEEE Trans. Robotics Autom. 12 4 1996 566 580
45. Kelly, A.; 1995. An Intelligent Predictive Control Approach to the High Speed Cross Country Autonomous Navigation Problem. Ph.D. Thesis, Carnegie Mellon University.
46. A. Kelly, A. Stentz, O. Amidi, M. Bode, D. Bradley, A. Diaz-Calderon, M. Happold, H. Herman, R. Mandelbaum, T. Pilarski, P. Rander, S. Thayer, N. Vallidis, and R. Warner Toward reliable off road autonomous vehicles operating in challenging environments Int. J. Robotics Res. 25 5-6 2006 449 483
47. Khan, Y.; Komma, P.; Zell, A.; 2011. High resolution visual terrain classification for outdoor robots. In: IEEE International Conference on Computer Vision Workshops, pp. 1014-1021.
48. Kruijff, G.-J.M.; Pirri, F.; Gianni, M.; Papadakis, P.; Pizzoli, M.; Sinha, A.; Pianese, E.; Corrao, S.; Priori, F.; Febrini, S.; Angeletti, S.; Tretyakov, V.; Linder, T.; 2012. Rescue robots at earthquake-hit Mirandola, Italy: a field report. In: IEEE International Symposium on Safety, Security and Rescue Robotics.
49. Kubota, T.; Kuroda, Y.; Kunii, Y.; Yoshimitsu, T.; 2001. Path planning for newly developed microrover. In: IEEE International Conference on Robotics and Automation, pp. 3710-3715.
50. Kuthirummal, S.; Das, A.; Samarasekera, S.; 2011. A graph traversal based algorithm for obstacle detection using lidar or stereo. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
51. I.S. Kweon, and T. Kanade High-resolution terrain map from multiple sensor data IEEE Trans. Pattern Anal. Mach. Intell. 14 1 1992 278 292
52. J. Lalonde, N. Vandapel, D. Huber, and M. Hebert Natural terrain classification using three-dimensional ladar data for ground robot mobility J. Field Robotics 23 1 2006 839 861
53. D. Langer, J. Rosenblatt, and M. Hebert A behavior-based system for off-road navigation IEEE Trans. Robotics Autom. 10 6 1994 776 783
54. Larson, J.; Trivedi, M.; 2011. Lidar based off-road negative obstacle detection and analysis. In: IEEE International Conference on Intelligent Transportation Systems.
55. Larson, J.; Trivedi, M.; Bruch, M.; 2011. Off-road terrain traversability analysis and hazard avoidance for UGVs. In: IEEE Intelligent Vehicles Symposium.
56. Leppanen, I.; Virekoski, P.; Halme, A.; 2008. Sensing terrain parameters and the characteristics of vehicle-terrain interaction using the multimode locomotion system of a robot. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 500-505.
57. Lu, L.; Ordonez, C.; Collins, E.; DuPont, E.; 2009. Terrain surface classification for autonomous ground vehicles using a 2D laser stripe-based structured light sensor. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2174-2181.
58. L. Lu, C. Ordonez, E. Collins, and C. Palejiya Terrain surface classification with a control mode update rule using a 2D laser stripe-based structured light sensor Robotics Autonomous Syst. 59 11 2011 954 965
59. R. Manduchi, A. Castano, A. Talukder, and L. Matthies Obstacle detection and terrain classification for autonomous off-road navigation Autonomous Robots 18 2005 81 102
60. Matthies, L.; Rankin, A.; 2003. Negative obstacle detection by thermal signature. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
61. R. McGhee, and A. Frank On the stability properties of quadruped creeping gaits Math. Biosci. 3 0 1968 331 351
62. Melchior, N.; Simmons, R.; 2007. Particle RRT for path planning with uncertainty. In: IEEE International Conference on Robotics and Automation, pp. 1617-1624.
63. Molino, V.; Madhavan, R.; Messina, E.; Downs, A.; Jacoff, A.S.; Balakirsky, S.B.; 2007. Traversability metrics for urban search and rescue robots on rough terrain. In: Performance Metrics for Intelligent Systems (PerMIS).
64. Montemerlo, M.; Thrun, S.; 2004. A multi-resolution pyramid for outdoor robot terrain perception. In: AAAI, pp. 464-469.
65. Moravec, H.; Elfes, A.; 1985. High resolution maps from wide angle sonar. In: IEEE International Conference on Robotics and Automation, pp. 116-121.
66. Murarka, A.; Sridharan, M.; Kuipers, B.; 2008. Detecting obstacles and drop-offs using stereo and motion cues for safe local motion. In: IEEE/RSJ International Conference on Intelligent Robots and Systems.
67. NASA, Mars exploration rovers 〈 Http://marsrovers.jpl.nasa.gov/home/ index.html 〉.
68. Norouzi, M.; Miro, J.V.; Dissanayke, G.; 2012. Planning high-visibility stable paths for reconfigurable robots on uneven terrain. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2844-2849.
69. L. Ojeda, J. Borenstein, G. Witus, and R. Karlsen Terrain characterization and classification with a mobile robot J. Field Robotics 23 2 2006 103 122
70. K. Olin, and D. Tseng Autonomous cross-country navigation an integrated perception and planning system IEEE Expert 6 4 1991 16 30
71. D. Pai, and L. Reissell Multiresolution rough terrain motion planning IEEE Trans. Robotics Autom. 14 1 1998 19 33
72. Papadakis, P.; Pirri, F.; 2012. 3D mobility learning and regression of articulated, tracked robotic vehicles by physics-based optimization. In: Virtual Reality Interaction and Physical Simulation, pp. 147-156.
73. Papadopoulos, E.; Rey, D.; 1996. A new measure of tipover stability margin for mobile manipulators. In: IEEE International Conference on Robotics and Automation.
74. Pivtoraiko, M.; Kelly, A.; 2005. Generating near minimal spanning control sets for constrained motion planning in discrete state spaces. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3231-3237.
75. Quigley, M.; Conley, K.; Gerkey, B.; Faust, J.; Foote, T.; Leibs, J.; Wheeler, R.; Ng, A.; 2009. ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software.
76. Roan, P.; Burmeister, A.; Rahimi, A.; Holz, K.; Hooper, D.; 2010. Real-world validation of three tipover algorithms for mobile robots. In: IEEE International Conference on Robotics and Automation, pp. 4431-4436.
77. Rosenblum, M.; Gothard, B.; 2000. A high fidelity multi-sensor scene understanding system for autonomous navigation. In: IEEE Intelligent Vehicles Symposium, pp. 637-643.
78. Sheh, R.; Kadous, M.; Sammut, C.; Hengst, B.; 2007. Extracting terrain features from range images for autonomous random stepfield traversal. In: IEEE International Workshop on Safety, Security and Rescue Robotics, pp. 1-6.
79. M. Shneier, T. Chang, T. Hong, W. Shackleford, R. Bostelman, and J. Albus Learning traversability models for autonomous mobile vehicles Auton. Robot. 24 2008 69 86
80. Silver, D.; Sofman, B.; Vandapel, N.; Bagnell, J.A.; Stentz, A.; 2006. Experimental analysis of overhead data processing to support long range navigation. In: IEEE International Conference on Intelligent Robots and Systems.
81. Simeon, T.; 1991. Motion planning for a non-holonomic mobile robot on 3-dimensional terrains. In: IEEE/RSJ International Workshop on Intelligence for Mechanical Systems, Intelligent Robots and Systems, pp. 1455-1460.
82. Simeon, T.; Wright, B.; 1993. A practical motion planner for all-terrain mobile robots. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1357-1363.
83. Singh, S.; Simmons, R.; Smith, T.; Stentz, A.; Verma, V.; Yahja, A.; Schwehr, K.; 2000. Recent progress in local and global traversability for planetary rovers. In: IEEE International Conference on Robotics and Automation.
84. Stentz, A.; 1995. The focussed d algorithm for real-time replanning. In: International Joint Conference on Artificial Intelligence, pp. 1652-1659.
85. Stentz, A.; Kelly, A.; Rander, P.; Herman, H.; Amidi, O.; Mandelbaum, R.; Salgian, G.; Pedersen, J.; 2003. Real-time, multi-perspective perception for unmanned ground vehicles. In: AUVSI Unmanned Systems Symposium.
86. Thrun, S.; Montemerlo, M.; Aron, A.; 2006a. Probabilistic terrain analysis for high-speed desert driving. In: Proceedings of Robotics: Science and Systems, Philadelphia, USA.
87. S. Thrun, M. Montemerlo, H. Dahlkamp, D. Stavens, A. Aron, J. Diebel, P. Fong, J. Gale, M. Halpenny, G. Hoffmann, K. Lau, C. Oakley, M. Palatucci, V. Pratt, P. Stang, S. Strohband, C. Dupont, L.-E. Jendrossek, C. Koelen, and C. Markey Stanley the robot that won the DARPA grand challenge J. Field Robotics 23 9 2006 661 692
88. Thuer, T.; 2009. Mobility Evaluation of Wheeled All-terrain Robots Metrics and Application. Ph.D. Thesis, ETH.
89. E. Ugur, and E. Sahin Traversability a case study for learning and perceiving affordances in robots Adaptive Behav. 18 3-4 2010 258 284
90. N. Vandapel, R.R. Donamukkala, and M. Hebert Unmanned ground vehicle navigation using aerial ladar data Int. J. Robotics Res. 25 1 2006 31 51
91. M. Vukobratovic, and N. Borovac Zero-moment point - thirty five years of its life Int. J. Humanoid Robotics 1 1 2004 157 173
92. Wellington, C.; Stentz, A.; 2004. Online adaptive rough-terrain navigation in vegetation. In: IEEE International Conference on Robotics and Automation, pp. 96-101.
93. D. Wettergreen, P. Tompkins, C. Urmson, M.D. Wagner, and W. Whittaker Sun-synchronous robotic exploration technical description and field experimentation Int. J. Robotics Res. 24 January (1) 2005 3 30
94. Wright, B.; Simeon, T.; 1993. Free space representation for a mobile robot moving on a rough terrain. In: IEEE International Conference on Robotics and Automation, pp. 37-43.
95. C. Ye Navigating a mobile robot by a traversability field histogram IEEE Trans. Syst. Man Cybern. Part B: Cybern. 37 2 2007 361 372