{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:02:37Z","timestamp":1760241757999,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,12]],"date-time":"2018-08-12T00:00:00Z","timestamp":1534032000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["2042017KF0235"],"award-info":[{"award-number":["2042017KF0235"]}]},{"name":"the National Key Research Program","award":["2016YFF0103502"],"award-info":[{"award-number":["2016YFF0103502"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-precision indoor three-dimensional maps are a prerequisite for building information models, indoor location-based services, etc., but the indoor mapping solution is still in the stage of technological experiment and application scenario development. In this paper, indoor mapping equipment integrating a three-axis laser scanner and panoramic camera is designed, and the corresponding workflow and critical technologies are described. First, hardware design and software for controlling the operations and calibration of the spatial relationship between sensors are completed. Then, the trajectory of the carrier is evaluated by a simultaneous location and mapping framework, which includes reckoning of the real-time position and attitude of the carrier by a filter fusing the horizontally placed laser scanner data and inertial measurement data, as well as the global optimization by a closed-loop adjustment using a graph optimization algorithm. Finally, the 3D point clouds and panoramic images of the scene are reconstructed from two tilt-mounted laser scanners and the panoramic camera by synchronization of the position and attitude of the carrier. The experiment was carried out in a five-story library using the proposed prototype system; the results demonstrate accuracies of up to 3 cm for 2D maps, and up to 5 cm for 3D maps, and the produced point clouds and panoramic images can be utilized for modeling and further works related to large-scale indoor scenes. Therefore, the proposed system is an efficient and accurate solution for indoor 3D mapping.<\/jats:p>","DOI":"10.3390\/rs10081269","type":"journal-article","created":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T11:27:13Z","timestamp":1534159633000},"page":"1269","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1581-634X","authenticated-orcid":false,"given":"Pengcheng","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0866-6678","authenticated-orcid":false,"given":"Qingwu","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"}]},{"given":"Shaohua","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"}]},{"given":"Mingyao","family":"Ai","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"},{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7948-2828","authenticated-orcid":false,"given":"Qingzhou","family":"Mao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"(2016). 1. Gunduz; M; Isikdag; U; Basaraner; M. A review of recent research in indoor modelling & mapping. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 289\u2013294.","DOI":"10.5194\/isprs-archives-XLI-B4-289-2016"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1016\/j.autcon.2010.06.007","article-title":"Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques","volume":"19","author":"Tang","year":"2010","journal-title":"Autom. Constr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1109\/JSTSP.2014.2381153","article-title":"Fast, automated, scalable generation of textured 3D models of indoor environments","volume":"9","author":"Turner","year":"2015","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1007\/s11263-014-0711-y","article-title":"Reconstructing the world's museums","volume":"110","author":"Xiao","year":"2014","journal-title":"Int. J. Comp. Vis."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kim, M.K., Li, B., Park, J.S., Lee, S.J., and Sohn, H.G. (2014, January 2\u20135). Optimal locations of terrestrial laser scanner for indoor mapping using genetic algorithm. Proceedings of the 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014), Gwangju, South Korea.","DOI":"10.1109\/ICCAIS.2014.7020546"},{"key":"ref_6","first-page":"155","article-title":"Studies on the use of terrestrial laser scanning in the maintenance of buildings belonging to the cultural heritage","volume":"1","author":"Bernat","year":"2014","journal-title":"Int. J. Child. Rights"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Jamali, A., Anton, F., and Mioc, D. (2018). A novel method of combined interval analysis and homotopy continuation in indoor building reconstruction. Eng. Optim., 1\u20137.","DOI":"10.1080\/0305215X.2018.1472253"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"103","DOI":"10.5194\/isprs-archives-XLII-2-W1-103-2016","article-title":"3D indoor building environment reconstruction using least square adjustment, polynomial kernel, interval analysis and homotopy continuation","volume":"XLII-2\/W1","author":"Jamali","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1016\/j.measurement.2013.03.006","article-title":"Review of mobile mapping and surveying technologies","volume":"46","author":"Puente","year":"2013","journal-title":"Meas. J. Int. Meas. Confed."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"347","DOI":"10.14358\/PERS.84.6.347","article-title":"On a novel 360\u00b0 panoramic stereo mobile mapping system","volume":"84","author":"Blaser","year":"2018","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_11","unstructured":"Hu, Q., Mao, Q., Chen, X., and Wen, G. (2013). An Integrated Mobile 3D Measuring Device. (No. CN203148438U), China Patent."},{"key":"ref_12","first-page":"1","article-title":"Mobile mapping technology and its applications","volume":"4","author":"Li","year":"2006","journal-title":"Geospat. Inf."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Engel, J., Schops, T., and Cremers, D. (2014, January 6\u201312). LSD-SLAM: Large-Scale Direct Monocular SLAM. Proceedings of the European Conference on Computer Vision (ECCV), Zurich, Switzerland. Part II.","DOI":"10.1007\/978-3-319-10605-2_54"},{"key":"ref_14","unstructured":"Forster, C., Pizzoli, M., and Scaramuzza, D. (June, January 31). SVO: Fast semi-direct monocular visual odometry. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1109\/TRO.2017.2705103","article-title":"ORB-SLAM2: An open-source SLAM system for monocular, stereo, and RGB-D cameras","volume":"33","author":"Tardos","year":"2017","journal-title":"IEEE Trans. Robot."},{"key":"ref_16","unstructured":"Choi, S., Zhou, Q.Y., and Koltun, V. (2015, January 7\u201312). Robust reconstruction of indoor scenes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Endres, F., Hess, J., Engelhard, N., Sturm, J., Cremers, D., and Burgard, W. (2012, January 14\u201318). An evaluation of the RGB-D SLAM system. Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6225199"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/TRO.2006.889486","article-title":"Improved techniques for grid mapping with Rao-Blackwellized particle filters","volume":"23","author":"Grisetti","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Konolige, K., Grisetti, G., Kummerle, R., Limketkai, B., and Vincent, R. (2010, January 18\u201322). Efficient sparse pose adjustment for 2D mapping. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan.","DOI":"10.1109\/IROS.2010.5649043"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kohlbrecher, S., Stryk, O.V., Meyer, J., and Klingauf, U. (2011, January 1\u20135). A flexible and scalable SLAM system with full 3D motion estimation. Proceedings of the 2011 IEEE International Symposium on the Safety, Security, and Rescue Robotics (SSRR), Kyoto, Japan.","DOI":"10.1109\/SSRR.2011.6106777"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Hess, W., Kohler, D., Rapp, H., and Andor, D. (2016, January 16\u201321). Real-time loop closure in 2D LIDAR SLAM. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487258"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ikehata, S., Yang, H., and Furukawa, Y. (2015, January 7\u201313). Structured indoor modeling. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile.","DOI":"10.1109\/ICCV.2015.156"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Sanchez, V., and Zakhor, A. (October, January 30). Planar 3D modeling of building interiors from point cloud data. Proceedings of the 2012 19th IEEE International Conference on the Image Processing (ICIP), Orlando, FL, USA.","DOI":"10.1109\/ICIP.2012.6467225"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1109\/TVCG.2015.2505296","article-title":"Layer-wise floorplan extraction for automatic urban building reconstruction","volume":"22","author":"Sui","year":"2016","journal-title":"IEEE Trans. Vis. Comp. Gr."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhou, Q.Y., and Koltun, V. (2014). Color map optimization for 3D reconstruction with consumer depth cameras. ACM Trans. Gr., 33.","DOI":"10.1145\/2601097.2601134"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hedau, V., Hoiem, D., and Forsyth, D. (October, January 29). Recovering the spatial layout of cluttered rooms. Proceedings of the 2009 IEEE 12th International Conference on the Computer Vision, Kyoto, Japan.","DOI":"10.1109\/ICCV.2009.5459411"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Pintore, G., Ganovelli, F., Gobbetti, E., and Scopigno, R. (2016, January 8\u201316). Mobile mapping and visualization of indoor structures to simplify scene understanding and location awareness. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-48881-3_10"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"52","DOI":"10.18005\/JRST0103001","article-title":"Point cloud clustering for 3D modeling assistance using a panoramic layered range image","volume":"1","author":"Nakagawa","year":"2013","journal-title":"J. Remote Sens. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"173","DOI":"10.5194\/isprsannals-II-3-173-2014","article-title":"Design of an indoor mapping system using three 2D laser scanners and 6 DOF SLAM","volume":"II-3","author":"Vosselman","year":"2014","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"289","DOI":"10.5194\/isprsannals-II-5-W2-289-2013","article-title":"Mobile laser scanning for indoor modelling","volume":"II-5\/W2","author":"Thomson","year":"2013","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_31","unstructured":"Zhang, Q., and Pless, R. (October, January 28). Extrinsic calibration of a camera and laser range finder (improves camera calibration). Proceedings of the 2004 IEEE\/RSJ International Conference on the Intelligent Robots and Systems (IROS), Sendai, Japan."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1002\/rob.20315","article-title":"Error modeling and calibration of exteroceptive sensors for accurate mapping applications","volume":"27","author":"Underwood","year":"2010","journal-title":"J. Field Robot."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Li, Q.C., Muller, F., and Rauschenbach, T. (September, January 29). Simulation-based comparison of 2D scan matching algorithms for different rangefinders. Proceedings of the 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland.","DOI":"10.1109\/MMAR.2016.7575261"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Li, J., Zhong, R., Hu, Q., and Ai, M. (2016). Feature-based laser scan matching and its application for indoor mapping. Sensors, 16.","DOI":"10.3390\/s16081265"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"533","DOI":"10.5194\/isprs-archives-XLI-B5-533-2016","article-title":"Improved real-time scan matching using corner features","volume":"XLI-B5","author":"Mohamed","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_36","unstructured":"Mallick, M., Morelande, M., and Mihaylova, L. (2012, January 9\u201312). Continuous-discrete filtering using EKF, UKF, and PF. Proceedings of the 15th International Conference on Information Fusion, Singapore."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Barfoot, T.D. (2017). State Estimation for Robotics, Cambridge University Press.","DOI":"10.1017\/9781316671528"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/TRO.2012.2197158","article-title":"Bags of binary words for fast place recognition in image sequences","volume":"28","author":"Tardos","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Dub\u00e9, R., Dugas, D., Stumm, E., Nieto, J., Siegwart, R., and Cadena, C. (arXiv, 2016). SegMatch: Segment based loop-closure for 3D point clouds, arXiv.","DOI":"10.1109\/ICRA.2017.7989618"},{"key":"ref_40","unstructured":"Sameer, A., and Keir, M. (2017, October 23). Ceres Solver. Available online: http:\/\/ceres-solver.org."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/0024-3795(95)00543-9","article-title":"Quaternions and matrices of quaternions","volume":"251","author":"Zhang","year":"1997","journal-title":"Linear Algebra Its Appl."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"506","DOI":"10.3389\/fpsyg.2013.00506","article-title":"Basic level scene understanding: Categories, attributes and structures","volume":"4","author":"Xiao","year":"2013","journal-title":"Front. Psychol."},{"key":"ref_43","unstructured":"Qi, C.R., Su, H., Mo, K., and Guibas, L.J. (arXiv, 2016). PointNet: Deep learning on point sets for 3D classification and segmentation, arXiv."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1269\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:18:17Z","timestamp":1760195897000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1269"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,12]]},"references-count":43,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["rs10081269"],"URL":"https:\/\/doi.org\/10.3390\/rs10081269","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,8,12]]}}}