Abstract
With the development of intelligent technology, the problem of LiDAR-based localization has played an increasingly important role in the localization of robots in unmanned systems. Since the dense point clouds from the environment requires a large amount of memory, specific and stable structural features, such as pole-like objects in the environment, can serve as the ideal landmarks for localization in unmanned systems, which can effectively reduce the memory usage and mitigate the effects of dynamic environment changes. In this paper, the authors propose a pole-like objects extraction approach and then, it is applied into the localization system of mobile robots. Under the same experimental conditions, the proposed method can extract more pole-like objects and achieve better long-term localization accuracy than some existing methods in different urban environmental datasets.
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DONG Yi is a youth editorial board member for Journal of Systems Science & Complexity and was not involved in the editorial review or the decision to publish this article. The authors declare that there are no competing interests.
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This work was supported by Shanghai Rising-Star Program under Grant No. 22QA1409400, the National Natural Science Foundation of China under Grant Nos. 62073241 and 62173250, and Shanghai Municipal Science and Technology Major Project under Grant No. 2021SHZDZX0100.
This paper was recommended for publication by Editor ZHAO Yanlong.
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Hong, X., Dong, Y. Poles Extraction Based LiDAR Localization for Autonomous Robot Systems. J Syst Sci Complex 37, 1413–1424 (2024). https://doi.org/10.1007/s11424-024-3173-5
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DOI: https://doi.org/10.1007/s11424-024-3173-5