Abstract
This paper presents a method for fusing two maps of an environment: one estimated with an application of the Simultaneous Localization and Mapping (SLAM) concept and the other one known a priori by a vehicle. The goal of such an application is double: first, to estimate the vehicle pose in this known map and, second, to constrain the map estimate with the known map using an implementation of the local maps fusion approach and a heterogeneous mapping of the environment. This article shows how a priori knowledge available in the form of a map can be fused within an EKF-SLAM framework to obtain more accuracy on the vehicle poses and map estimates. Simulation and experimental results are given to show these improvements.
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Chanier, F., Checchin, P., Blanc, C., Trassoudaine, L. (2009). Map Fusion Based on a Multi-Map SLAM Framework. In: Hahn, H., Ko, H., Lee, S. (eds) Multisensor Fusion and Integration for Intelligent Systems. Lecture Notes in Electrical Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89859-7_30
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DOI: https://doi.org/10.1007/978-3-540-89859-7_30
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