Home /Research /Multi-robot Localization and Mapping Based on Signed Distance Functions
SWARM

Multi-robot Localization and Mapping Based on Signed Distance Functions

Philipp Koch, Stefan May, Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martín, Andreas Nüchter

Year
2015
Citations
11

Abstract

This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data as well as two actual robots operating in a comparably large area.

Keywords

RobotComputer scienceMobile robotComputer visionSoftwareArtificial intelligenceRepresentation (politics)Signed distance functionSimultaneous localization and mapping

Related papers

Browse all SWARM papers