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However, existing open-source datasets lack representation of geometrically degenerate environments, limiting the development and benchmarking of robust LiDAR SLAM algorithms. To address this gap, we introduce GEODE, a comprehensive multi-LiDAR, multi-scenario dataset specifically designed to include real-world geometrically degenerate environments. GEODE comprises 64 trajectories spanning over 64\u00a0km across seven diverse settings with varying degrees of degeneracy. The data was meticulously collected to promote the development of versatile algorithms by incorporating various LiDAR sensors, stereo cameras, IMUs, and diverse motion conditions. We evaluate state-of-the-art SLAM approaches using the GEODE dataset to highlight current limitations in LiDAR SLAM techniques. This extensive dataset will be publicly available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/thisparticle.github.io\/geode\">https:\/\/thisparticle.github.io\/geode<\/jats:ext-link>\n                    , supporting further advancements in LiDAR-based SLAM.\n                  <\/jats:p>","DOI":"10.1177\/02783649251344967","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T13:05:43Z","timestamp":1749474343000},"page":"6-22","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Heterogeneous LiDAR dataset for benchmarking robust localization in diverse degenerate scenarios"],"prefix":"10.1177","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9011-4981","authenticated-orcid":false,"given":"Zhiqiang","family":"Chen","sequence":"first","affiliation":[{"name":"Sun Yat-sen University"},{"name":"The University of Hong Kong"}]},{"given":"Yuhua","family":"Qi","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Dapeng","family":"Feng","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Xuebin","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Hongbo","family":"Chen","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3535-6886","authenticated-orcid":false,"given":"Xiangcheng","family":"Hu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}]},{"given":"Jin","family":"Wu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"},{"name":"University of Science and Technology Beijing"}]},{"given":"Kelin","family":"Peng","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Peng","family":"Lu","sequence":"additional","affiliation":[{"name":"The University of Hong Kong"}]}],"member":"179","published-online":{"date-parts":[[2025,6,9]]},"reference":[{"key":"e_1_3_5_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3126010"},{"key":"e_1_3_5_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364915614638"},{"key":"e_1_3_5_4_1","doi-asserted-by":"crossref","unstructured":"Catalano I Yu X Queralta JP (2023) Towards robust UAV tracking in GNSS-denied environments: a multi-lidar multi-UAV dataset. 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