Paper presented at the 16th European-African Regional Conference of the ISTVS
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Title: Real-time measurement of tire sinkage using stereo cameras
Authors: Hannah White, Corina Sandu, Jyotirmoy Mukherjee, Andrea L'Afflitto, David Gorsich, and Michael Cole
Abstract: There is a need for autonomous vehicles operating off-road, such as in military operations and farming. However, most established models, planning, and control algorithms for autonomous vehicles are created assuming on-road conditions only and, hence, underperform when employed otherwise. An approach to overcome this limitation is to feed these algorithms with real-time data on the terrain parameters and the terrain-vehicle interaction parameters. One of the key parameters to estimate for reliable off-road operations is is tire sinkage. This parameter affects the slip-sinkage relationship, which, in turn, has a significant influence on the tractive performance of the vehicle. This paper presents a method for real-time sensing and estimation of the sinkage of off-road vehicles under the assumption that the rut left behind has the same value as the sinkage; this assumption is driven by the need for low computational times and is proven experimentally to be sufficiently accurate in problems of practical interest. Specifically, we are using image processing techniques to assess the sinkage of a tire on a deformable surface. To this goal, we collect the depth data of a tire rut in real-time using two stereo cameras. The first camera measures the profile of the undisturbed terrain in front of the tire. The second camera measures the depth profile of the tire rut depth. These profiles are compared to estimate the final rut depth. The measurements from the two cameras are also used to compute the tire’s entry and exit angles; these parameters can further be employed in the computation of the shear stresses along the contact patch of the tire.
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