Terrain contact modeling and classification for ATVs

We present a method for estimating the contact event between sensor-free active subtracks, named flippers, of an articulated tracked vehicle (ATV) and the terrain surface. The main idea is to consider both the moving base link and unexpected collisions dynamics as disturbances of the flipper dynamics. On this basis we extend the generalized momenta fault detection and isolation (FDI) method to compute the residual dynamics of the flippers, without resorting to additional sensory information. Under the hypothesis that the residual signal presents disturbance patterns that can be discriminated by those generated by unexpected collisions of the flippers with the ground, we apply a classification method to recover the contact event. The wavelet packet transform is used to decompose the signal and to generate a feature space for the residual, from the different subbands. Finally, sparse SVM, based on feature selection discriminates the contact signal.