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Anytime merging of appearance based maps

Gorkem Erinc, Stefano Carpin

Year
2012
Citations
5

Abstract

Appearance based maps are emerging as an important class of spatial representations for mobile robots. In this paper we tackle the problem of merging together two or more appearance based maps independently built by robots operating in the same environment. Noticing the lack of well accepted metrics to measure the performance of map merging algorithms, we propose to use algebraic connectivity as a metric to assess the advantage gained by merging multiple maps. Next, based on this criterion, we propose an anytime algorithm aiming to quickly identify the more advantageous parts to merge. The system we proposed has been fully implemented and tested in indoor scenarios and shows that our algorithm achieves a convenient tradeoff between accuracy and speed.

Keywords

Computer scienceMerge (version control)RobotMobile robotMetric (unit)Artificial intelligenceMetric mapData miningComputer visionMetric space

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