Abstract
The purpose of this study is to propose a novel mobile robot localization method applicable to outdoor environments, such as an uneven terrain. In order to solve the robot localization problem, we exploit state of the art graph-based SLAM (Simultaneous Localization and Mapping) algorithm and ICP (Iterative Closest Point) algorithm considering the gyroscopic data as a constraint for a graph structure. We confirm our method by testing actual sensor data acquired from a vehicle in outdoor environments and show that our proposed method is improved and suitable for uneven terrain.
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Oh, T., Kim, H., Lee, D., Roh, H.C., Myung, H. (2015). Graph Structure-Based Simultaneous Localization and Mapping with Iterative Closest Point Constraints in Uneven Outdoor Terrain. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_3
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DOI: https://doi.org/10.1007/978-3-319-16841-8_3
Publisher Name: Springer, Cham
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