Improving the Mobility Performance of Autonomous Unmanned Ground Vehicles by Adding the Ability to ‘Sense/Feel‘ Their Local Environment

  • Siddharth Odedra
  • Stephen D. Prior
  • Mehmet Karamanoglu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4563)

Abstract

This paper explores how a ‘learning‘ algorithm can be added to UGV’s by giving it the ability to test the terrain through ‘feeling‘ using incorporated sensors, which would in turn increase its situational awareness. Once the conditions are measured the system will log the results and a database can be built up of terrain types and their properties (terrain classification), therefore when it comes to operating autonomously in an unknown, unpredictable environment, the vehicle will be able to cope by identifying the terrain and situation and then decide on the best and most efficient way to travel over it by making adjustments, which would greatly improve the vehicles ability to operate autonomously.

Keywords

Unmanned Autonomous Mobility Situational Awareness Way Finding Terrain Reconfigurable Intelligent Wheels 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Vance, A.: DARPA’s Grand Challenge proves to be too grand (2004) cited, Available from: http://www.theregister.co.uk/2004/03/13/darpas_grand_challenge_proves/
  2. 2.
    Vanderwerp, D.: What Does Terrain Response Do? (2005) cited; Available from: http://www.caranddriver.com/features/9026/what-does-terrain-response-do.html
  3. 3.
    Shachtman, N.: Undead Warrior (2006), cited, Available from: http://www.defensetech.org/archives/cat_fcs_watch.html
  4. 4.
    Lacroix, S., Chatila, R., Fleury, S., Herrb, M., Simeon, T.: Autonomous Navigation in Outdoor Environments: Adaptive Approach and Experiment. In: IEEE International Conference on Robotics and Automation 1994 (1994)Google Scholar
  5. 5.
    DuPont, E.M., Moore, C.A., Roberts, R.G., Collins, E.G., Selekwa, M.F.: Online Terrain Classification for Mobile Robots. In: ASME International Mechanical Engineering Congress and Exposition Conference (2005)Google Scholar
  6. 6.
    Sadhukhan, D.: Autonomous ground vehicle terrain classification using internal sensors, in Department of Mechanical Engineering. The Florida State University (2004)Google Scholar
  7. 7.
    Iagnemma, K., Dubowsky, S.: Terrain Estimation for High-Speed Rough-Terrain Autonomous Vehicle Navigation. In: SPIE Conference on Unmanned Ground Vehicle Technology IV 2002 (2002)Google Scholar
  8. 8.
    Iagnemma, K., Shibly, H., Dubowsky, S.: On-Line Terrain Parameter Estimation for Planetary Rovers. In: IEEE International Conference on Robotics and Automation (2002)Google Scholar
  9. 9.
    Seraji, H.: Safety measures for terrain classification and safest site selection. Autonomous Robots, (21), 211–225 (2006)Google Scholar
  10. 10.
    Howard, A., Seraji, H.: Vision-based terrain characterization and traversability assessment. Journal of Robotic Systems 18(10), 577–587 (2001)MATHCrossRefGoogle Scholar
  11. 11.
    Manduchi, R., Castano, A., Talukder, A., Matthies, L.: Obstacle Detection and Terrain Classification for Autonomous Off-Road Navigation. Autonomous Robots 18(1), 81–102 (2005)CrossRefGoogle Scholar
  12. 12.
    Thrun, S., Montemerlo, M.: DARPA Grand Challenge 2005 Technical Paper 2005 Stanford Racing Team (2005)Google Scholar
  13. 13.
    Orenstein, D.: Stanford team’s win in robot car race nets $2 million prize (2005), cited Available from: http://news-service.stanford.edu/news/2005/october12/stanleyfinish-100905.html
  14. 14.
    Maheshwari, V., Saraf, R.F.: High-Resolution Thin-Film Device to Sense Texture by Touch in Science 2006, pp. 1501–1504 (2006)Google Scholar
  15. 15.
    Saraf, R.F., Maheshwari, V.: Nanodevice for Imaging Normal Stress Distribution With Application in Sensing Texture and Feel’ by Touching, Nebraska Univ Lincoln (2004)Google Scholar
  16. 16.
    Schultz, A.E., Solomon, J.H., Peshkin, M.A., Hartmann, M.J.: Multifunctional Whisker Arrays for Distance Detection, Terrain Mapping, and Object Feature Extraction. In: 2005 IEEE International Conference on Robotics and Automation (2005)Google Scholar
  17. 17.
    Gaspar, T., Rodrigues, H., Odedra, S., Costa, M., Metrolho, J.C., Prior, S.: Handheld devices as actors in domotic monitoring system. In: IEEE International Conference on Industrial Informatics, INDIN 2004, pp. 547–551 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Siddharth Odedra
    • 1
  • Stephen D. Prior
    • 1
  • Mehmet Karamanoglu
    • 1
  1. 1.Department of Product Design and Engineering, Middlesex University, London, N14 4YZUnited Kingdom

Personalised recommendations