3D Recognition of Obstacles Using A Vibrissa-like Tactile Sensor

Many rodents are able to detect the shape and texture information of objects [1] - [2] by means of tactile hairs in their snout region (mystacial vibrissae) [3] - [6] . Since these hairs are made up of dead tissue, all sensing has to be performed in the support of each vibrissa, the so-called follicle-sinus complex (FSC) [7] . Guided by the natural paragon we set up a mechanical model, consisting of a cylindrical, one-sided clamped bending rod, which is swept along an object quasi-statically. Due to the contact force the rod undergoes (large) bending deflections in three dimensional space which are described using a non-linear bending theory. The scanning sweep is simulated using a Matlab algorithm in two steps: Firstly, the sweep is simulated to generate the support reactions, which might also be measured using an experimental setup. Secondly, the generated support reactions are used in order to determine a sequence of contact points reconstructing and approximating the object contour. The theoretically generated observables allow to reconstruct contact points on the object within numerical boundaries (error 5⋅10 -11 ). The object reconstruction reveals that it is useful to scan objects in various orientations, in order to avoid reconstruction gaps.