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Terrain traversability analysis methods for unmanned ground vehicles: A survey

Abstract : Motion planning for unmanned ground vehicles (UGV) constitutes a domain of research where several disciplines meet, ranging from artificial intelligence and machine learning to robot perception and computer vision. In view of the plurality of related applications such as planetary exploration, search and rescue, agriculture, mining and off-road exploration, the aim of the present survey is to review the field of 3D terrain traversability analysis that is employed at a preceding stage as a means to effectively and efficiently guide the task of motion planning. We identify that in the epicenter of all related methodologies, 3D terrain information is used which is acquired from LIDAR, stereo range data, color or other sensory data and occasionally combined with static or dynamic vehicle models expressing the interaction of the vehicle with the terrain. By taxonomizing the various directions that have been explored in terrain perception and analysis, this review takes a step toward agglomerating the dispersed contributions from individual domains by elaborating on a number of key similarities as well as differences, in order to stimulate research in addressing the open challenges and inspire future developments.
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https://hal.inria.fr/hal-00801220
Contributor : Panagiotis Papadakis <>
Submitted on : Friday, March 15, 2013 - 12:44:43 PM
Last modification on : Wednesday, September 26, 2018 - 4:32:03 PM
Long-term archiving on: : Sunday, June 16, 2013 - 6:10:08 AM

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Panagiotis Papadakis. Terrain traversability analysis methods for unmanned ground vehicles: A survey. Engineering Applications of Artificial Intelligence, Elsevier, 2013, 26 (4), pp.1373 - 1385. ⟨10.1016/j.engappai.2013.01.006⟩. ⟨hal-00801220⟩

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