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Humans display the remarkable ability to sense the world through tools andother held objects. For example, we are able to pinpoint impact locations on aheld rod and tell apart different textures using a rigid probe. In this work,we consider how we can enable robots to have a similar capacity, i.e., toembody tools and extend perception using standard grasped objects. We proposethat vibro-tactile sensing using dynamic tactile sensors on the robot fingers,along with machine learning models, enables robots to decipher contactinformation that is transmitted as vibrations along rigid objects. This paperreports on extensive experiments using the BioTac micro-vibration sensor and anew event dynamic sensor, the NUSkin, capable of multi-taxel sensing at 4~kHz.We demonstrate that fine localization on a held rod is possible using ourapproach (with errors less than 1 cm on a 20 cm rod). Next, we show thatvibro-tactile perception can lead to reasonable grasp stability predictionduring object handover, and accurate food identification using a standard fork.We find that multi-taxel vibro-tactile sensing at sufficiently high samplingrate led to the best performance across the various tasks and objects. Takentogether, our results provides both evidence and guidelines for usingvibro-tactile perception to extend tactile perception, which we believe willlead to enhanced competency with tools and better physicalhuman-robot-interaction.

Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects