An ant-based filtering random-finite-set approach to simultaneous localization and mapping - Li, Demeng; Zhu, Jihong; Xu, Benlian; Lu, Mingli; Li, Mingyue (Zielona Góra: Uniwersytet Zielonogórski)
Inspired by ant foraging, as well as modeling of the feature map and measurements as random finite sets, a novel formulation in an ant colony framework is proposed to jointly estimate the map and the vehicle trajectory so as to solve a feature-based simultaneous localization and mapping (SLAM) problem. This so-called ant-PHD-SLAM algorithm allows decomposing the recursion for the joint map-trajectory posterior density into a jointly propagated posterior density of the vehicle trajectory and the posterior density of the feature map conditioned on the vehicle trajectory.
Keywords: simultaneous localization and mapping (SLAM); random finite sets; probability hypothesis density; ant colony