Skip to main content
Log in

Traversable Region Modeling for Outdoor Navigation

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

This article presents a new methodology to build, in real-time, compact local and global maps for outdoor navigation. The environment information is obtained from a 3D laser range. The navigation model, called Traversable Regions Model (TRM), is based on Voronoi diagram technique but adapted to large outdoor environments, that is, the model is built from 3D data. In the manuscript we also present a novel contribution to the regions modeling field in robotics. The method allows to calculate the roughness degree of an unknown terrain based on the normal vector deviation. The parameter which measure the roughness degree is called spherical variance and it will be useful to determine the traversable areas. The model built allows defining safe trajectories depending on the robot's capabilities and the terrain properties and will represent, in a topo-geometric way, the environment as local and global maps. The methodology presented is validated in real outdoor environments with an outdoor robot developed in our lab, called \(\mathcal{G}\mathcal{O}\mathcal{L}\mathcal{I}\mathcal{A}\mathcal{T}\).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Fernández V., Balaguer C., Blanco D., and Salichs M. A.: Active human-mobile manipulator cooperation through intention recognition, in: Proc. of the IEEE International Conference on Robotics and Automation, Seoul, Korea, 2001, pp. 2668–2673.

  2. Salichs, M. A. and Moreno, L.: Navigation of mobile robots: Open questions, Robotica 18 (2000), 227–234.

    Article  Google Scholar 

  3. DeSouza, G. N. and Kak, A. C.: Vision for mobile robot navigation: A survey, IEEE Trans. Pattern Anal. Mach. Intell. 24(2) (February 2002), 237–267.

    Article  Google Scholar 

  4. Murray D. and Little J.: Using real-time stereo vision for mobile robot navigation, Auton. Robots 8(2) (April 2000), 161–171.

    Article  Google Scholar 

  5. Al Haddad H.: Contróle Par Vision Du Mouvement D'un Robot Mobile En Environnement Naturel. Ph.D. thesis, Université Paul Sabatier de Toulouse, Laboratoire d'Analyse et d'Architecture des Systèmes du CNRS, 1998.

  6. Moorehead S., Simmons R., Apostolopoulos D., and Whittaker W. R. L.: Autonomous navigation field results of a planetary analog robot in antarctica, in: International Symposium on Artificial Intelligence, Robotics and Automation in Space, June 1999.

  7. Castejón, C., Boada, B. L., Blanco, D., and Moreno, L.: Traversable regions model for outdoor robots, in: The 11th International Conference on Advanced Robotics, ICAR 2003, 2003.

  8. Seraji, H.: Traversability index: A new concept for planetary rovers, in: Proc. of the 1999 IEEE International Conference on Robotics & Automation, 1999.

  9. Langer, D., Rosenblatt, J. K., and Hebert, M.: A behavior-based system for off-road navigation, IEEE Trans. Robot. Autom. 10(6) (1994), 776–782.

    Article  Google Scholar 

  10. Yahja, A., Singh, S., and Stentz, A.: An efficient on-line path planner for outdoor mobile robots, Robot. Auton. Syst. 32 (2000), 129–143.

    Article  Google Scholar 

  11. Macri, M., De Suvranu, and Shepard, M. S.: Hierarchical tree-based discretization for the method of finite spheres, Comput. Struct. 81 (2003), 789–803.

    Article  Google Scholar 

  12. Kweon, I. S. and Kanade, T.: High resolution terrain map from multiple sensor data, in: IEEE International Workshop on Intelligent Robots and Systems, 1990.

  13. Gomes-Mota, J., and Ribeiro, M. I.: Mobile robot localization on reconstructed 3d models, Robot. Auton. Syst. 31 (2000), 17–30.

    Article  Google Scholar 

  14. Hähnel, D., Burgard, W., and Thrun, S.: Learning compact 3d models of indoor and outdoor environments with a mobile robot, Robot. Auton. Syst. 1(44) (2003), 15–27.

    Article  Google Scholar 

  15. Ranganathan, P., Hayet, J. B., Devy, M., Hutchinson, S., and Lerasle, F.: Topological navigation and qualitative localization for indoor environment using multi-sensory perception, Robot. Auton. Syst. 41 (2002), 137–144.

    Article  Google Scholar 

  16. Nehmzow U. and Owen C.: Robot navigation in the real world: Experiments with manchester's fortytwo in unmodified, large environments, Robot. Auton. Syst. 33 (2000), 223–242.

    Article  Google Scholar 

  17. Thrun, S.: Learning metric-topological maps for indoor mobile robot navigation, Artif. Intell. 99(1) (February 1998), 21–71.

    Article  MATH  Google Scholar 

  18. Betgé-Brezetz, S, Chatila, R., and Devi, M.: Natural scene understanding for mobile robot navigation, IEEE Int. Conf. Robot. Autom. 1 (1994), 730–736.

    Google Scholar 

  19. Simon S. and Dudeck G.: A global topological map formed by local metric maps, in: International Conference on Intelligent Robots and Systems, Victoria, Canada, 1998.

    Google Scholar 

  20. Choset, H., Walker, S., Eiamsa-Ard, K., and Burdick, J.: Sensor-based exploration: Incremental construction of the hierarchical generalized Voronoi graph, Int. J. Rob. Res. 19(2) (February 2000), 126–148.

    Article  Google Scholar 

  21. Blanco, D., Boada, B. L., Moreno, L., and Salichs, M. A.: Local mapping from on-line laser Voronoi extraction, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2000.

  22. Blanco, D., Boada, B. L., Castejón, C., Balaguer, C., and Moreno, L. E.: Sensor-based path planning for a mobile manipulator guided by the humans, in: The 11th International Conference on Advanced Robotics, ICAR 2003 1, (2003).

  23. Langer, D., Rosenblatt, J. K., and Hebert, M.: An integrated system for autonomous off-road navigation, IEEE Int. Conf. Robot. Autom. 1 (1994), 414–419.

    Google Scholar 

  24. Gennery, D. B.: Traversabilty analysis and path planing for a planetary rover, Auton. Robots 6 (1999), 131–146.

    Article  Google Scholar 

  25. Howard, A. and Seraji, H.: Real-time assessment of terrain traversability for autonomous rover navigation, in: Proc. of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2000.

  26. Howard, A. and Seraji, H.: Vision-based terrain characterization and traversability assessment, J. Robot. Syst. 18(10) (2001) 577–587.

    Article  MATH  Google Scholar 

  27. Nashashibi, F., Devy, M., and Fillatreau, P.: Indoor scene terrain modeling using multiple range images for autonomous mobile robots, IEEE Int. Conf. Robot. Autom. 1 (1992), 40–46.

    Article  Google Scholar 

  28. Betgé-Brezetz, S.: Modélisation Incrémentale et Localisation Pour la Navigation D'un Robot Mobile Autonome En Environnement Naturel. Ph.D. thesis, Laboratoir d'analyse et d'architecture des systèmes du CNRS. Université Paul Sabatier de Touluse, février, 1996.

  29. Seraji, H.: Fuzzy traversability index: A new concept for terrain-based navigation, J. Robot. Syst. 17(2) (2000), 75–91.

    Article  MATH  Google Scholar 

  30. Mardia, K. V. and Jupp, P. E.: Directional Statistics, Wiley Series in Probability and Statistics, 1999.

  31. Castejón, C., Blanco, D., Boada, B. L., and Moreno, L.: Traversability analysis technics in outdoor environments: A comparative study, in: The 11th International Conference on Advanced Robotics, ICAR 2003, 2003.

  32. Castejón, C., Boada, B. L., and Moreno, L.: Topographical analysis for Voronoi-based modelling, in: The 28th Annual Conference of the IEEE Industrial Electronics Society, 2002.

  33. Choset, H.: Sensor Based Motion Planning: The Hierarchical Generalizerd Voronoi Graph, PhD thesis, California Institute of Technology, Pasadena, California, March 1996.

  34. Latombe, J.-C.: Robot Motion Planning, Boston/Dordrecht/London: Kluwer, 1991.

    Google Scholar 

  35. Mahkovic, R. and Slivnik, T.: Generalized local Voronoi diagram of visible region, in: Proc. IEEE International Conference on Robotics and Automation, Leuven, Belgium, May 1998, pp. 349–355.

    Google Scholar 

  36. Sudha, N., Nandi, S., and Sridharan, K.: A parallel algorithm to construct Voronoi diagram and its VLSI architecture, in: Proc. of the 1999 IEEE Conference on Robotics and Automation, 1999, pp. 1683–1688.

  37. Blanco, D., Boada, B. L., and Moreno, L.: Localization by Voronoi diagrams correlation, IEEE Int. Conf. Robot. Autom. 4 (2001), 4232–4237.

    Google Scholar 

  38. Thrun, S. and Bücken, A.: Integrating grid-based and topological maps for mobile robot navigation, in: Proc. of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference, Vol. 2, 1996, pp. 944–950.

  39. Davison, A. J. and Kita, N.: Sequential localisation and map-building for real time computer vision and robotics, Robot. Auton. Syst. 36 (2001), 171–183.

    Article  Google Scholar 

  40. Castejón, C., Moreno, L., and Salichs, M. A.: Traversability modelling in 3d environments, in: 3rd International Conference on Field and Service Robotics FSR2001, Finland, June 2001.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cristina Castejón.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Castejón, C., Boada, B.L., Blanco, D. et al. Traversable Region Modeling for Outdoor Navigation. J Intell Robot Syst 43, 175–216 (2005). https://doi.org/10.1007/s10846-005-9005-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-005-9005-5

Key words

Navigation