{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:24:33Z","timestamp":1754155473290,"version":"3.41.2"},"reference-count":33,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:00:00Z","timestamp":1725494400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IR"],"published-print":{"date-parts":[[2024,12,2]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Accurate mapping is crucial for the positioning and navigation of mobile robots. Recent advancements in algorithms and the accuracy of LiDAR sensors have led to a gradual improvement in map quality. However, challenges such as lag in closing loops and vignetting at map boundaries persist due to the discrete and sparse nature of raster map data. The purpose of this study is to reduce the error of map construction and improve the timeliness of closed loop.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>In this letter, the authors introduce a method for dynamically adjusting point cloud distance constraints to optimize data association (ODA-d), effectively addressing these issues. The authors propose a dynamic threshold optimization method for matching point clouds to submaps during scan matching.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Large deviations in LiDAR sensor point cloud data, when incorporated into the submap, can result in irreparable errors in correlation matching and loop closure optimization. By implementing a data association framework with double constraints and dynamically adjusting the matching threshold, the authors significantly enhance submap quality. In addition, the authors introduce a dynamic fusion method that accounts for both submap size and the distance between submaps during the mapping process. ODA-d reduces errors between submaps and facilitates timely loop closure optimization.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The authors validate the localization accuracy of ODA-d by examining translation and rotation errors across three open data sets. Moreover, the authors compare the quality of map construction in a real-world environment, demonstrating the effectiveness of ODA-d.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ir-12-2023-0341","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T07:53:16Z","timestamp":1725349996000},"page":"936-946","source":"Crossref","is-referenced-by-count":0,"title":["Optimize data association of point cloud to improve the quality of mapping and positioning"],"prefix":"10.1108","volume":"51","author":[{"given":"Guangbing","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Letian","family":"Quan","sequence":"additional","affiliation":[]},{"given":"Kaixuan","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Shunqing","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Shugong","family":"Xu","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2024,9,5]]},"reference":[{"key":"key2024112907361823100_ref001","first-page":"34","article-title":"The simultaneous localization and mapping (SLAM)-an overview","volume":"2","year":"2021","journal-title":"Surveying and Geospatial Engineering Journal"},{"issue":"4","key":"key2024112907361823100_ref002","doi-asserted-by":"publisher","first-page":"9107","DOI":"10.1109\/LRA.2022.3189785","article-title":"Situational graphs for robot navigation in structured indoor environments","volume":"7","year":"2022","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"6","key":"key2024112907361823100_ref003","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TRO.2016.2624754","article-title":"Past, present, and future of simultaneous localization and mapping: toward the robust-perception age","volume":"32","year":"2016","journal-title":"IEEE Transactions on Robotics"},{"issue":"4","key":"key2024112907361823100_ref004","doi-asserted-by":"crossref","first-page":"2074","DOI":"10.1109\/TRO.2022.3150683","article-title":"Lcdnet: deep loop closure detection and point cloud registration for lidar slam","volume":"38","year":"2022","journal-title":"IEEE Transactions on Robotics"},{"issue":"2","key":"key2024112907361823100_ref005","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1109\/TASE.2019.2940543","article-title":"Robust visual localization in dynamic environments based on sparse motion removal","volume":"17","year":"2020","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"first-page":"222","article-title":"Large scale 2D laser slam using truncated signed distance functions","year":"2019","key":"key2024112907361823100_ref006"},{"issue":"4","key":"key2024112907361823100_ref007","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1504\/IJMIC.2022.125544","article-title":"Front-end matching optimised algorithm of cartographer with multi-resolution layered search strategy","volume":"40","year":"2022","journal-title":"International Journal of Modelling, Identification and Control"},{"issue":"10","key":"key2024112907361823100_ref008","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3251722","article-title":"SID-SLAM: semi-direct information-driven RGB-D SLAM","volume":"8","year":"2023","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"1","key":"key2024112907361823100_ref009","first-page":"48","article-title":"Range-aided pose-graph-based SLAM: applications of deployable ranging beacons for unknown environment exploration","volume":"6","year":"2020","journal-title":"IEEE Robotics and Automation Letters"},{"key":"key2024112907361823100_ref010","unstructured":"Grupp, M. 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