Abstract
This paper presents a scan-matching approach for online simultaneous localization and mapping. This approach combines a fast and efficient scan-matching algorithm for localization with dynamic and approximate likelihood fields to incrementally build a map. The achievable results of the approach are evaluated using an objective benchmark designed to compare SLAM solutions that use different methods. The result is a fast online SLAM approach suitable for real-time operations.
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Pedrosa, E., Lau, N., Pereira, A. (2013). Online SLAM Based on a Fast Scan-Matching Algorithm. In: Correia, L., Reis, L.P., Cascalho, J. (eds) Progress in Artificial Intelligence. EPIA 2013. Lecture Notes in Computer Science(), vol 8154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40669-0_26
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DOI: https://doi.org/10.1007/978-3-642-40669-0_26
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