Predicting Maximum Traction for Improving Traversability of Unmanned Robots on Rough Terrain

This paper proposes a method to predict maximum traction for unmanned robots on rough terrain in order to improve traversability. For a traction prediction, we use a friction-slip model based on modified Brixius model derived empirically in terramechanics which is a function of mobility number $B_n$ and slip ratio S. A friction-slip model includes characteristics of various rough terrains where robots are operated such as soil, sandy soil and grass-covered soil. Using a friction-slip model, we build a prediction model for terrain parameters on which we can know maximum static friction and optimal slip with respect to mobility number $B_n$. In this paper, Mobility number $B_n$ is estimated by modified Willoughby Sinkage model which is a function of sinkage z and slip ratio S. Therefore, if sinkage z and slip ratio are measured once by sensors such as a laser sensor and a velocity sensor, then mobility number $B_n$ is estimated and maximum traction is predicted through a prediction model for terrain parameters. Estimation results for maximum traction are shown on simulation using MATLAB. Prediction Performance for maximum traction of various terrains is evaluated as high accuracy by analyzing estimation errors.

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