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On rough terrain, there are a variety of soil types having different soil strength. It means that it is needed for outdoor robots to change wheel control strategies since optimal slip and maximum traction levels on wheels differ depending on soil strength. Therefore this paper proposes an algorithm for acquiring optimal control parameters, such as maximum traction coefficient and optimal slip ratio to maximize traction or minimize energy consumption, based on estimating strength of soils. In this paper the optimal models of wheel traction and slip are derived through indoor experiments by a testbed for analysis of wheel-terrain interactions on three types of soil; grass, gravel and sand. For estimating soil strength, actual traction coefficient, including information of motion resistance, is observed by a state estimator related to wheeled robot dynamics. The actual traction coefficient and slip ratio on wheels are employed to estimate soil strength by a numerical method on the basis of derived optimal models. The proposed algorithm was verified through real driving experiments of a wheeled robot on various types of soil.

Soil Strength-based Estimation of Optimal Control Parameters for Wheeled Robots on Rough Terrain