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.

We introduce a novel framework for modeling articulated objects based on the aspects of their components. By decomposing the object into components, we divide the problem in smaller modeling tasks. After obtaining 3D models for each component aspect by employing a shape deformation paradigm, we merge them together, forming the object components. The final model is obtained by assembling the components using an optimization scheme which fits the respective 3D models to the corresponding apparent contours in a reference pose. The results suggest that our approach can produce realistic 3D models of articulated objects in reasonable time.