Abstract-We developed a novel whisker-follicle sensor that measures three mechanical signals at the whisker base. The first two signals are closely related to the two bending moments, and the third is an approximation to the axial force. Previous simulation studies have shown that these three signals are sufficient to determine the three-dimensional (3D) location at which the whisker makes contact with an object. Here we demonstrate hardware implementation of 3D contact point determination and then use continuous sweeps of the whisker to show proof-of principle 3D contour extraction. We begin by using simulations to confirm the uniqueness of the mapping between the mechanical signals at the whisker base and the 3D contact point location for the specific dimensions of the hardware whisker. Multi-output random forest regression is then used to predict the contact point locations of objects based on observed mechanical signals. When calibrated to the simulated data, signals from the hardware whisker can correctly predict contact point locations to within 1.5 cm about 74% of the time. However, if normalized output voltages from the hardware whiskers are used to train the algorithm (without calibrating to simulation), predictions improve to within 1.5 cm for about 96% of contact points and to within 0.6 cm for about 78% of contact points. This improvement suggests that as long as three appropriate predictor signals are chosen, calibrating to simulations may not be required. The sensor was next used to perform contour extraction on a cylinder and a cone. We show that basic contour extraction can be obtained with just two sweeps of the sensor. With further sweeps, it is expected that full 3D shape reconstruction could be achieved.

The rodent vibrissal (whisker) system has been studied for decades as a model of active touch sensing. There are no sensors along the length of a whisker; all sensing occurs at the whisker base. Therefore, a large open question in many neuroscience studies is how an animal could estimate the three-dimensional (3D) location at which a whisker makes contact with an object. In the present work we simulated the shape of a real rat whisker to demonstrate the existence of several unique mappings from triplets of mechanical signals at the whisker base to the three-dimensional whisker-object contact point. We then used high speed video to record whisker deflections as an awake rat whisked against a peg, and used the mechanics resulting from those deflections to extract the contact points along the peg surface. These results demonstrate that measurement of specific mechanical triplets at the base of a biological whisker can enable 3D contact point determination during natural whisking behavior. The approach is viable even though the biological whisker has non-ideal, non-planar curvature, and even given the rat’s real-world choices of whisking parameters. Visual intuition for the quality of the approach is provided in a video that shows the contour of the peg gradually emerging during active whisking behavior.

No abstract

The rodent vibrissal (whisker) system has been studied for decades as a model of active touch sensing. There are no sensors along the length of a whisker; all sensing occurs at the whisker base. Therefore, a large open question in many neuroscience studies is how an animal could estimate the three-dimensional location at which a whisker makes contact with an object. In the present work we simulated the exact shape of a real rat whisker to demonstrate the existence of a unique mapping from triplets of mechanical signals at the whisker base to the three-dimensional whisker-object contact point. We then used high speed video to record whisker deflections as an awake rat whisked against a peg and used the mechanics resulting from those deflections to extract the contact points along the peg surface. A video shows the contour of the peg gradually emerging during active whisking behavior.

No abstract