Event-based signaling for reducing required data rates and processing power in a large-scale artificial robotic skin

Abstract

In this paper we propose event-based signaling for large-scale artificial robotic skin to reduce bandwidth requirements on data transmission and processing power. We use the send-on-delta principle to trigger the event generation only when tactile sensors are stimulated and transduce novel information. To compare the standard non-event based method with the proposed event-based method we present a comprehensive analysis of large-scale artificial skin systems for different test applications. For this purpose we collect data of 260 CellulARSkin cells on an UR-5 arm and calculate the events off-line. We determine the optimal packet size for event-based signaling and we show that the event-based system reduces the data rate with respect to the non-event based system for an unstimulated skin cell network to 16.45% and for a heavily stimulated skin cell network to 47.69%. The obtained results show that the event-based system reduces the data redundancy and the required transmission rates without loosing information.