Simultaneous localization and map building for mobile robots

Map-merging in Multi-robot Simultaneous Localization and Mapping Process Using Two Heterogeneous Ground Robots

In this article, a fast and reliable map-merging algorithm is proposed to produce a global two dimensional map of an indoor environment in a multi-robot simultaneous localization and mapping (SLAM) process. In SLAM process, to find its way in this environment, a robot should be able to determine its position relative to a map formed from its observations. To solve this complex problem, simultan...

Autonomous map building by mobile robots

In this paper we introduce a novel self-localization and map building approach. The new part is that we do not assume to have a correct motion model of the mobile robot. Our approach will improve the incorrect motion model online. We tested our approach in a simulation experiment.

Safe Navigation for Indoor Mobile Robots - Part II: Exploration, Self Localization and Map Building

This paper is the second part of the author’s contribution on the topic of Safe Navigation for Indoor Mobile Robots. It presents a new solution to the exploration, self localization and map building problem taking advantage of the sensor-based navigation framework presented in the paper: Safe Navigation for Indoor Mobile Robots Part I: A Sensor-based Navigation Framework. The model of the indoo...

Map Building and Localization for Long-Term Operation of Mobile Robots in Dynamic Environments

Filter Design for Simultaneous Localization and Map Building (SLAM)

This paper deals with the fusion of random variables when cross covariances are unknown. This is a vital problem in nearly every real world application since cross covariances are often impossible to obtain but also cannot be ignored. We provide a rigorous derivation of the fusion equations which are also known as covariance intersection. This approach allows us to derive an iterative scheme fo...