{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T20:39:32Z","timestamp":1769632772285,"version":"3.49.0"},"reference-count":35,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,16]],"date-time":"2021-09-16T00:00:00Z","timestamp":1631750400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61501429"],"award-info":[{"award-number":["61501429"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monocular vision is one of the most commonly used noncontact six-degrees-of-freedom (6-DOF) pose estimation methods. However, the large translational DOF measurement error along the optical axis of the camera is one of its main weaknesses, which greatly limits the measurement accuracy of monocular vision measurement. In this paper, we propose a novel monocular camera and 1D laser rangefinder (LRF) fusion strategy to overcome this weakness and design a remote and ultra-high precision cooperative targets 6-DOF pose estimation sensor. Our approach consists of two modules: (1) a feature fusion module that precisely fuses the initial pose estimated from the camera and the depth information obtained by the LRF. (2) An optimization module that optimizes pose and system parameters. The performance of our proposed 6-DOF pose estimation method is validated using simulations and real-world experiments. The experimental results show that our fusion strategy can accurately integrate the information of the camera and the LRF. Further optimization carried out on this basis effectively reduces the measurement error of monocular vision 6-DOF pose measurement. The experimental results obtained from a prototype show that its translational and rotational DOF measurement accuracy can reach up to 0.02 mm and 15\u2033, respectively, at a distance of 10 m.<\/jats:p>","DOI":"10.3390\/rs13183709","type":"journal-article","created":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T03:47:35Z","timestamp":1632282455000},"page":"3709","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Improve the Estimation of Monocular Vision 6-DOF Pose Based on the Fusion of Camera and Laser Rangefinder"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0493-1887","authenticated-orcid":false,"given":"Zifa","family":"Zhu","sequence":"first","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100149, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Yuebo","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Rujin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Enhai","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Sikang","family":"Zeng","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100149, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Jinhui","family":"Yi","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100149, China"},{"name":"Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chengdu 610209, China"}]},{"given":"Jian","family":"Ding","sequence":"additional","affiliation":[{"name":"Beijing Institute of Spacecraft System Engineering, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wang, F., Dong, H., Chen, Y., and Zheng, N. (2016). An Accurate Non-Cooperative Method for Measuring Textureless Spherical Target Based on Calibrated Lasers. Sensors, 16.","DOI":"10.3390\/s16122097"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1080\/01490419.2010.487800","article-title":"Sub-Centimeter Precision Orbit Determination with GPS for Ocean Altimetry","volume":"33","author":"Bertiger","year":"2010","journal-title":"Mar. Geodesy"},{"key":"ref_3","unstructured":"FARO (2021, July 01). User Manual for the Vantage Laser Tracker. Available online: https:\/\/knowledge.faro.com\/."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1109\/JSEN.2012.2228638","article-title":"An automatic evaluation procedure for 3-D scanners in robotics applications","volume":"13","author":"Moller","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_5","unstructured":"Kien, D.T. (2005). A Review of 3D Reconstruction from Video Sequences. ISIS Technical Report Series, University of Amsterdam."},{"key":"ref_6","first-page":"93","article-title":"Mono Camera and Laser Rangefinding Sensor Position-Pose Measurement System","volume":"31","author":"Chao","year":"2011","journal-title":"Acta Opt. Sin."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.patrec.2018.02.028","article-title":"A simple, robust and fast method for the perspective-n-point problem","volume":"108","author":"Wang","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1109\/TPAMI.2012.41","article-title":"A robust O (n) solution to the perspective-n-point problem","volume":"34","author":"Li","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"103","DOI":"10.14358\/PERS.81.2.103","article-title":"Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry","volume":"81","author":"Karara","year":"2015","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_10","unstructured":"Shahzad, M.G., Roth, G., and Mcdonald, C. (2002, January 27\u201329). Robust 2D Tracking for Real-Time Augmented Reality. Proceedings of the Conference on Vision Interface, Calgary, Canada."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","article-title":"Epnp: An accurate o (n) solution to the pnp problem","volume":"81","author":"Lepetit","year":"2009","journal-title":"Int. J. Comput. Vis."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1142\/S0218001411008774","article-title":"A stable direct solution of perspective-three-point problem","volume":"25","author":"Li","year":"2011","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kneip, L., Scaramuzza, D., and Siegwart, R. (2011, January 20\u201325). A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation. Proceedings of the CVPR 2011, Colorado Springs, CO, USA.","DOI":"10.1109\/CVPR.2011.5995464"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_15","first-page":"239","article-title":"A complete linear 4-point algorithm for camera pose determination","volume":"21","author":"Zhi","year":"2002","journal-title":"AMSS Acad. Sin."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/34.862199","article-title":"Fast and globally convergent pose estimation from video images","volume":"22","author":"Lu","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Meng, X., Cai, J., Wu, Y., Liang, S., and Wang, S. (2018, January 21\u201323). A Navigation Framework for Mobile Robots with 3D LiDAR and Monocular Camera. Proceedings of the IECON 2018 44th Annual Conference of the IEEE Industrial Electronics Society, Washington, DC, USA.","DOI":"10.1109\/IECON.2018.8591329"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Singh, S. (2015, January 26\u201330). Visual-lidar odometry and mapping: Low-drift, robust, and fast. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139486"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Graeter, J., Wilczynski, A., and Lauer, M. (2018, January 1\u20135). LIMO: Lidar-Monocular Visual Odometry. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594394"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1023\/B:VISI.0000043756.03810.dd","article-title":"Data processing algorithms for generating textured 3D building facade meshes from laser scans and camera images","volume":"61","author":"Frueh","year":"2005","journal-title":"Int. J. Comput. Vis."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1007\/s11263-010-0397-8","article-title":"Capturing village-level heritages with a hand-held camera-laser fusion sensor","volume":"94","author":"Bok","year":"2011","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1007\/s00138-003-0133-2","article-title":"Fusion of laser and visual data for robot motion planning and collision avoidance","volume":"15","author":"Baltzakis","year":"2003","journal-title":"Mach. Vis. Appl."},{"key":"ref_23","first-page":"64312626","article-title":"Robust method of vision-based relative pose parameters for non-cooperative spacecrafts","volume":"7","author":"Zhang","year":"2009","journal-title":"J. Harbin Inst. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/0031-3203(89)90071-X","article-title":"Determining camera parameters from the perspective projection of a rectangle","volume":"22","author":"Haralick","year":"1989","journal-title":"Pattern Recognit."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.robot.2019.03.010","article-title":"A fusion method of 1D laser and vision based on depth estimation for pose estimation and reconstruction","volume":"116","author":"Zhang","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1111\/j.1477-9730.2008.00478.x","article-title":"A combined single range and single image device for low-cost measurement of building fa\u00e7ade features","volume":"23","author":"Ordonez","year":"2008","journal-title":"Photogramm. Rec."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kukelova, Z., Bujnak, M., and Pajdla, T. (2008, January 12\u201318). Automatic generator of minimal problem solvers. Proceedings of the European Conference on Computer Vision, Marseille, France.","DOI":"10.1007\/978-3-540-88690-7_23"},{"key":"ref_28","first-page":"1190","article-title":"Analysis of position estimation precision by cooperative target with three feature points","volume":"22","author":"Zhao","year":"2014","journal-title":"Acta Opt. Sin."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"11874","DOI":"10.1109\/JSEN.2020.2978334","article-title":"MiniVO: Minimalistic Range Enhanced Monocular System for Scale Correct Pose Estimation","volume":"20","author":"Giubilato","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Zhao, R., Liu, E., Yan, K., and Ma, Y. (2019). A Convenient Calibration Method for LRF-Camera Combination Systems Based on a Checkerboard. Sensors, 19.","DOI":"10.3390\/s19061315"},{"key":"ref_31","unstructured":"Zhang, Z. (1999, January 20\u201327). Flexible Camera Calibration by Viewing a Plane from Unknown Orientations. Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece."},{"key":"ref_32","first-page":"439","article-title":"A survey of attitude representations","volume":"41","author":"Shuster","year":"1993","journal-title":"Navigation"},{"key":"ref_33","unstructured":"Roweis, S. (2021, July 01). Levenberg-Marquardt Optimization. Available online: https:\/\/cs.nyu.edu\/~roweis\/notes\/lm.pdf."},{"key":"ref_34","first-page":"101","article-title":"The levenberg-marquardt algorithm","volume":"11","author":"Ranganathan","year":"2004","journal-title":"Tutoral LM Algorithm"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"162932","DOI":"10.1016\/j.ijleo.2019.162932","article-title":"Centroid extraction algorithm based on grey-gradient for autonomous star sensor","volume":"194","author":"He","year":"2019","journal-title":"Optik"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/18\/3709\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:00:50Z","timestamp":1760166050000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/18\/3709"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,16]]},"references-count":35,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["rs13183709"],"URL":"https:\/\/doi.org\/10.3390\/rs13183709","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,16]]}}}