Enhanced detection performance in electrosense through capacitive sensing

Weakly electric fish emit an AC electric field into the water and use thousands of sensors on the skin to detect field perturbations due to surrounding objects. The fish’s active electrosensory system allows them to navigate and hunt, using separate neural pathways and receptors for resistive and capacitive perturbations. We have previously developed a sensing method inspired by the weakly electric fish to detect resistive perturbations and now report on an extension of this system to detect capacitive perturbations as well. In our method, an external object is probed by an AC field over multiple frequencies. We present a quantitative framework that relates the response of a capacitive object at multiple frequencies to the object’s composition and internal structure, and we validate this framework with an electrosense robot that implements our capacitive sensing method. We define a metric for comparing the electrosensory range of different underwater electrosense systems. For detecting non-conductive objects, we show that capacitive sensing performs better than resistive sensing by almost an order of magnitude using this measure, while for conductive objects there is a four-fold increase in performance. Capacitive sensing could therefore provide electric fish with extended sensing range for capacitive objects such as prey, and gives artificial electrolocation systems enhanced range for targets that are capacitive.