Location and orientation estimation with an electrosense robot

We have designed an underwater robot that uses perturbations of an emitted electric field to sense, localize, and map its environment. This system is inspired by weakly electric fish, which emit an electric field to sense objects, localize prey, and communicate. When nearby objects distort the electric field, electroreceptors (fish) or voltage sensors (robot) detect these perturbations. Further analysis of the perturbations can reveal information about the associated target, such as size, shape, and distance. One difficulty with extracting distance-to-target for our robotic electrosense platform is that the measurements are dependent on orientation of the robot with respect to the object. We solve this problem by applying techniques from range-only SLAM, with modifications for some of the ways in which electrosense differs from the sensors typically used. We use two different Bayesian filters to estimate the orientation and position separately. Using this approach, we show that our electrosense robot can accurately localize and orient itself, and improve its estimate of position and orientation using motion.