Terrain Classification for Outdoor Autonomous Robots using 2D Laser Scans. Robot perception for dirt road navigation

Morten Rufus Blas, Søren Riisgaard, Ole Ravn, Nils Axel Andersen, Mogens Blanke, Jens Christian Andersen

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Abstract

Interpreting laser data to allow autonomous robot navigation on paved as well as dirt roads using a fixed angle 2D laser scanner is a daunting task. This paper introduces an algorithm for terrain classification that fuses four distinctly different classifiers: raw height, step size, slope, and roughness. Input is a single 2D laser scan and output is a classification of each laser scan range reading. The range readings are classified as either returning from an obstacle (not traversable) or from traversable ground. Experimental results are shown and discussed from the implementation done with a department developed Medium Mobile Robot and tests conducted in a national park environment
Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Informatics in Control, Automation and Robotics.
Publication date2005
Pages347-351
ISBN (Print)972-8865-30-9
Publication statusPublished - 2005
Event2nd International Conference on Informatics in Control, Automation and Robotics : 14-17 September - Barcelona, Spain
Duration: 1 Jan 2005 → …
Conference number: 2

Conference

Conference2nd International Conference on Informatics in Control, Automation and Robotics : 14-17 September
Number2
CityBarcelona, Spain
Period01/01/2005 → …

Keywords

  • Terrain classification
  • Obstacle detection
  • Road following
  • Laser scanner
  • Classifier fusion

Cite this

Rufus Blas, M., Riisgaard, S., Ravn, O., Andersen, N. A., Blanke, M., & Andersen, J. C. (2005). Terrain Classification for Outdoor Autonomous Robots using 2D Laser Scans. Robot perception for dirt road navigation. In Proceedings of the 2nd International Conference on Informatics in Control, Automation and Robotics. (pp. 347-351)