Title: Visual estimation of wheel sinkage for rough-terrain mobile robots

Authors: Giulio Reina, Annalisa Milella, Angelo Gentile

Addresses: Department of Engineering for Innovation, University of Salento, Via Arnesano, Lecce 73100, Italy. ' Institute of Intelligent Systems for Automation, Italian National Research Council, Via Amendola 122/D, Bari 70126, Italy; Department of Mechanical and Management Engineering, Politecnico of Bari, Viale Japigia 182, Bari 70126, Italy. ' Institute of Intelligent Systems for Automation, Italian National Research Council, Via Amendola 122/D, Bari 70126, Italy; Department of Mechanical and Management Engineering, Politecnico of Bari, Viale Japigia 182, Bari 70126, Italy

Abstract: For mobile robots driving across natural terrains, it is critical that the dynamic effects occurring at the wheel-terrain interface be taken into account. One of the most prevalent of these effects is wheel sinkage. Wheels can sink to depths sufficient to prevent further motion, possibly leading to danger of entrapment. This paper presents an algorithm for visual estimation of sinkage. We call it the visual sinkage estimation (VSE) method. It assumes the presence of a monocular camera and an artificial pattern, attached to the wheel side, to determine the terrain contact angle. This paper also introduces an analytical model for wheel sinkage in deformable terrain based on terramechanics. To validate the VSE module, firstly, several tests are performed on a single-wheel test bed, under different operating conditions. Secondly, the effectiveness of the proposed approach is proved in real contexts, employing an all-terrain rover travelling on a sandy beach.

Keywords: rough terrain robots; mobile robots; wheel sinkage estimation; machine vision; intelligent systems; visual estimation; robot vision; deformable terrain; terramechanics; sandy beaches; all-terrain rover.

DOI: 10.1504/IJISTA.2010.030203

International Journal of Intelligent Systems Technologies and Applications, 2010 Vol.8 No.1/2/3/4, pp.247 - 260

Available online: 11 Dec 2009 *

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