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ICRA
2003
IEEE

An atlas framework for scalable mapping

13 years 9 months ago
An atlas framework for scalable mapping
Abstract— This paper describes Atlas, a hybrid metrical/topological approach to SLAM that achieves efficient mapping of large-scale environments. The representation is a graph of coordinate frames, with each vertex in the graph representing a local frame, and each edge representing the transformation between adjacent frames. In each frame, we build a map that captures the local environment and the current robot pose along with the uncertainties of each. Each map’s uncertainties are modeled with respect to its own frame. Probabilities of entities with respect to arbitrary frames are generated by following a path formed by the edges between adjacent frames, computed via Dijkstra’s shortest path algorithm. Loop closing is achieved via an efficient map matching algorithm. We demonstrate the technique running in real-time in a large indoor structured environment (2.2 km path length) with multiple nested loops using laser or ultrasonic ranging sensors.
Michael Bosse, Paul M. Newman, John J. Leonard, Ma
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICRA
Authors Michael Bosse, Paul M. Newman, John J. Leonard, Martin Soika, Wendelin Feiten, Seth J. Teller
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