Title: Ergodic Exploration of Distributed Information,
Abstract: This paper presents an active search trajectory synthesis technique for
autonomous mobile robots with nonlinear measurements and dynamics. The
presented approach uses the ergodicity of a planned trajectory with respect to
an expected information density map to close the loop during search. The
ergodic control algorithm does not rely on discretization of the search or
action spaces, and is well posed for coverage with respect to the expected
information density whether the information is diffuse or localized, thus
trading off between exploration and exploitation in a single objective
function. As a demonstration, we use a robotic electrolocation platform to
estimate location and size parameters describing static targets in an
underwater environment. Our results demonstrate that the ergodic exploration of
distributed information (EEDI) algorithm outperforms commonly used
information-oriented controllers, particularly when distractions are present.