Cooperative Localization and SLAM Based on the Extended Information Filter

Abstract

Simultaneous Localization and Mapping (SLAM) requires a mobile robot to autonomously explore the environment with its on-board sensors, gain knowledge about it, interpret the scene, build an appropriate map and localize itself relative to this map. Many approaches have been proposed both in the framework of metric and topological navigation. A very successful metric method is the stochastic map (26) where early experiments (4) (16) have shown the quality of fully metric SLAM. Currently, the SLAM has two contrasting problems to be solved, which are often faced with a trade-off: