Robotics: Science and Systems II

Probabilistic Terrain Analysis For High-Speed Desert Driving

S. Thrun, M. Montemerlo, A. Aron

Abstract: The ability to perceive terrain is a key problem in mobile robot navigation. Terrain perception problems arise in planetary robotics, agriculture, mining, and, of course, selfdriving cars. Here, we introduce the PTA (probabilistic terrain analysis) algorithm for terrain classification with a fastmoving robot platform. The PTA algorithm uses probabilistic techniques to integrate range measurements over time, and relies on efficient statistical tests for distinguishing drivable from nondrivable terrain. By using probabilistic techniques, PTA is able to accommodate severe errors in sensing, and identify obstacles with nearly 100% accuracy at speeds of up to 35mph. The PTA algorithm was an essential component in the DARPA Grand Challenge, where it enabled a robot to traverse the entire course in record time.



    AUTHOR    = {S. Thrun and M. Montemerlo and A. Aron},
    TITLE     = {Probabilistic Terrain Analysis For High-Speed Desert Driving},
    BOOKTITLE = {Proceedings of Robotics: Science and Systems},
    YEAR      = {2006},
    ADDRESS   = {Philadelphia, USA},
    MONTH     = {August},
    DOI       = {10.15607/RSS.2006.II.021}