{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T16:15:58Z","timestamp":1758125758399,"version":"3.44.0"},"reference-count":21,"publisher":"Emerald","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,19]]},"abstract":"<jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>Over the decades, simultaneous localization and mapping (SLAM) techniques have been extensively researched and applied in robotic mapping. In complex environments, SLAM systems using a single sensor, such as a camera or light detection and ranging (LiDAR), often cannot meet the accuracy and map consistency requirements. This study aims to propose a tightly-coupled LiDAR-inertial SLAM system, which aims to achieve higher accuracy and map consistency for robotic mapping in complex environments.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design\/methodology\/approach<\/jats:title>\n                  <jats:p>This paper presents TC-Mapper, a tightly coupled LiDAR-inertial SLAM system based on LIO-SAM. The authors introduce the normal distribution-based loop closure detection method to the original one (i.e. the radius search-based method), which can enhance the accuracy and map consistency for robotic mapping. To further suppress map drift in complex environments, this paper incorporates a gravity factor into the original factor graph. In addition, TC-Mapper introduces incremental voxels (iVox) as the point cloud spatial data structure.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>Extensive experiments in public and self-collected data sets demonstrate that TC-Mapper has high accuracy and map consistency.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Originality\/value<\/jats:title>\n                  <jats:p>TC-Mapper has two types of loop closure detections: the normal distribution-based method for correcting large drifts and the radius search-based method for fine-stitching, which can achieve higher accuracy and map consistency. The authors introduce iVox as the point cloud spatial data structure, which strives to attain a balance between precision and efficiency to the greatest extent feasible.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1108\/ir-06-2024-0265","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T06:04:48Z","timestamp":1737439488000},"page":"500-508","source":"Crossref","is-referenced-by-count":0,"title":["TC-Mapper: tightly-coupled LiDAR-inertial SLAM for robotic mapping in complex environments"],"prefix":"10.1108","volume":"52","author":[{"given":"Xiangdi","family":"Yue","sequence":"first","affiliation":[{"name":"Hunan Normal University School of Engineering and Design, , Changsha,","place":["China"]}]},{"given":"Jiawei","family":"Chen","sequence":"additional","affiliation":[{"name":"Hunan Normal University School of Engineering and Design, , Changsha,","place":["China"]}]},{"given":"Yihuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua Automotive Research Institute Intelligent Connected Vehicle Center, , SuZhou,","place":["China"]}]},{"given":"Siming","family":"Huang","sequence":"additional","affiliation":[{"name":"CASIC Space Engineering Development Co. Ltd , Beijing,","place":["China"]}]},{"given":"Jiaji","family":"Pan","sequence":"additional","affiliation":[{"name":"Hunan Normal University School of Engineering and Design, , Changsha,","place":["China"]}]},{"given":"Miaolei","family":"He","sequence":"additional","affiliation":[{"name":"Hunan Normal University School of Engineering and Design, , Changsha,","place":["China"]}]}],"member":"140","published-online":{"date-parts":[[2025,1,23]]},"reference":[{"issue":"2","key":"2025091707182334400_ref001","doi-asserted-by":"crossref","first-page":"4861","DOI":"10.1109\/LRA.2022.3152830","article-title":"Faster-LIO: lightweight tightly coupled Lidar-Inertial odometry using parallel sparse incremental voxels","volume":"7","author":"Bai","year":"2022","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"2","key":"2025091707182334400_ref002","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1109\/34.121791","article-title":"A method for registration of 3-D shapes","volume":"14","author":"Besl","year":"1992","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2025091707182334400_ref003","first-page":"2743","article-title":"The normal distributions transform: a new approach to laser scan matching","volume-title":"Proceedings 2003 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. 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