{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T21:23:27Z","timestamp":1776374607972,"version":"3.51.2"},"reference-count":42,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,4,29]],"date-time":"2019-04-29T00:00:00Z","timestamp":1556496000000},"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":["61503073"],"award-info":[{"award-number":["61503073"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61703090"],"award-info":[{"award-number":["61703090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fund of Science and Technology Department, Jilin Province","award":["20170101125JC"],"award-info":[{"award-number":["20170101125JC"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The development and maturation of simultaneous localization and mapping (SLAM) in robotics opens the door to the application of a visual inertial odometry (VIO) to the robot navigation system. For a patrol robot with no available Global Positioning System (GPS) support, the embedded VIO components, which are generally composed of an Inertial Measurement Unit (IMU) and a camera, fuse the inertial recursion with SLAM calculation tasks, and enable the robot to estimate its location within a map. The highlights of the optimized VIO design lie in the simplified VIO initialization strategy as well as the fused point and line feature-matching based method for efficient pose estimates in the front-end. With a tightly-coupled VIO anatomy, the system state is explicitly expressed in a vector and further estimated by the state estimator. The consequent problems associated with the data association, state optimization, sliding window and timestamp alignment in the back-end are discussed in detail. The dataset tests and real substation scene tests are conducted, and the experimental results indicate that the proposed VIO can realize the accurate pose estimation with a favorable initializing efficiency and eminent map representations as expected in concerned environments. The proposed VIO design can therefore be recognized as a preferred tool reference for a class of visual and inertial SLAM application domains preceded by no external location reference support hypothesis.<\/jats:p>","DOI":"10.3390\/s19092004","type":"journal-article","created":{"date-parts":[[2019,4,29]],"date-time":"2019-04-29T07:01:22Z","timestamp":1556521282000},"page":"2004","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation"],"prefix":"10.3390","volume":"19","author":[{"given":"Linlin","family":"Xia","sequence":"first","affiliation":[{"name":"School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyu","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deru","family":"Chi","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northeast Electric Power University, Jilin 132012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanrui","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Liang, X., Chen, H., and Li, Y. (2016, January 3\u20136). Visual Laser-SLAM in Large-Scale Indoor Environments. Proceedings of the IEEE International Conference on Robotics & Biomimetics, Qingdao, China.","DOI":"10.1109\/ROBIO.2016.7866271"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Liu, S., and Tsai, G. (2018, January 21\u201325). PIRVS: An Advanced Visual-Inertial SLAM System with Flexible Sensor Fusion and Hardware Co-Design. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8460672"},{"key":"ref_3","first-page":"98","article-title":"Research on Vehicle Navigation BD\/DR\/MM Integrated Navigation Positioning","volume":"37","author":"Teng","year":"2017","journal-title":"J. Northeast Electr. Power Univ."},{"key":"ref_4","first-page":"90","article-title":"Gesture Recognition Based on Kinect Depth Information","volume":"36","author":"Guo","year":"2016","journal-title":"J. Northeast Dianli Univ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1109\/TPAMI.2007.1049","article-title":"MonoSLAM: Real-Time Single Camera SLAM","volume":"6","author":"Davison","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Klein, G., and Murray, D. (2007, January 13\u201316). Parallel Tracking and Mapping for Small AR Workspaces. Proceedings of the IEEE and ACM International Symposium on Mixed and Augmented Reality, Nara, Japan.","DOI":"10.1109\/ISMAR.2007.4538852"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1109\/TRO.2015.2463671","article-title":"ORB-SLAM: A Versatile and Accurate Monocular SLAM System","volume":"31","author":"Montiel","year":"2015","journal-title":"IEEE Trans. Robot."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1109\/TVT.2015.2388780","article-title":"StructSLAM: Visual SLAM with Building Structure Lines","volume":"64","author":"Zhou","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1016\/j.robot.2012.07.001","article-title":"Cooperative SLAM Using M-Space Representation of Linear Features","volume":"60","author":"Benedettelli","year":"2012","journal-title":"Robot. Auton. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Engel, J., Sch\u00f6ps, T., and Cremers, D. (2014, January 6\u201312). LSD-SLAM: Large-Scale Direct Monocular SLAM. Proceedings of the European Conference on Computer Vision (Computer Vision\u2014ECCV 2014), Zurich, Switzerland.","DOI":"10.1007\/978-3-319-10605-2_54"},{"key":"ref_11","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_12","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/TPAMI.2017.2658577","article-title":"Direct Sparse Odometry","volume":"40","author":"Engel","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_13","first-page":"43","article-title":"Filter Noise Analysis Based on Sub-Pixel Edge Orientation Algorithm","volume":"36","author":"Tian","year":"2016","journal-title":"J. Northeast Dianli Univ."},{"key":"ref_14","first-page":"87","article-title":"A Novel Segmentation Approach for Glass Insulators in Aerial Images","volume":"38","author":"Hu","year":"2018","journal-title":"J. Northeast Electr. Power Univ."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Weiss, S., and Siegwart, R. (2011, January 9\u201313). Real-Time Metric State Estimation for Modular Vision-Inertial Systems. Proceedings of the 2011 IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5979982"},{"key":"ref_16","unstructured":"(2018, October 03). Ethzasl_sensor_fusion. Available online: https:\/\/github.com\/ethz-asl\/ethzasl_sensor_fusion."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Falquez, J.M., Kasper, M., and Sibley, G. (2016, January 9\u201314). Inertial Aided Dense & Semi-Dense Methods for Robust Direct Visual Odometry. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots & Systems, Daejeon, Korea.","DOI":"10.1109\/IROS.2016.7759530"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1177\/0278364914554813","article-title":"Keyframe-Based Visual-Inertial Odometry Using Nonlinear Optimization","volume":"34","author":"Leutenegger","year":"2014","journal-title":"Int. J. Robot. Res."},{"key":"ref_19","unstructured":"Gomez-Ojeda, R., Zu\u00f1iga-No\u00ebl, D., and Moreno, F.A. (2017). PL-SLAM: A Stereo SLAM System through the Combination of Points and Line Segments. arXiv, 1\u201312."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hsiao, M., Westman, E., and Kaess, M. (2018, January 21\u201325). Dense planar-inertial slam with structural constraints. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8461094"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Huang, W., and Liu, H. (2018, January 21\u201325). Online Initialization and Automatic Camera-IMU Extrinsic Calibration for Monocular Visual-Inertial SLAM. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8460206"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Qin, T., and Shen, S. (2017, January 24\u201328). Robust Initialization of Monocular Visual-Inertial Estimation on Aerial Robots. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206284"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Locher, A., Havlena, M., and Van Gool, L. (2018, January 8\u201314). Progressive Structure from Motion. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01225-0_2"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3177853","article-title":"Visual SLAM and structure from motion in dynamic environments: A survey","volume":"51","author":"Saputra","year":"2018","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1109\/LRA.2017.2653359","article-title":"Visual-Inertial Monocular SLAM with Map Reuse","volume":"2","author":"Tardos","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/JAS.2017.7510556","article-title":"Effective Self-Calibration for Camera Parameters and Hand-Eye Geometry Based on Two Feature Points Motions","volume":"4","author":"Sun","year":"2017","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Liu, Y., Chen, Z., and Zheng, W. (2017). Monocular Visual-Inertial SLAM: Continuous Preintegration and Reliable Initialization. Sensors, 17.","DOI":"10.3390\/s17112613"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zuo, X., Xie, X., and Liu, Y. (2017, January 24\u201328). Robust Visual SLAM with Point and Line Features. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8205991"},{"key":"ref_29","first-page":"99","article-title":"On-Manifold Preintegration for Real-Time Visual-Inertial Odometry","volume":"33","author":"Forster","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_30","unstructured":"(2018, June 11). RGB-D SLAM Dataset and Benchmark. Available online: https:\/\/vision.in.tum.de\/data\/datasets\/rgbd-dataset."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"506","DOI":"10.3390\/s18020506","article-title":"Accurate Initial State Estimation in a Monocular Visual-Inertial SLAM System","volume":"18","author":"Mu","year":"2018","journal-title":"Sensors"},{"key":"ref_32","first-page":"85","article-title":"Inverse Quadratic Eigenvalues Problem for Mixed Matrix and Its Optimal Approximation","volume":"38","author":"Zhou","year":"2018","journal-title":"J. Northeast Electr. Power Univ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ruotsalainen, L., Kirkko-Jaakkola, M., Rantanen, J., and M\u00e4kel\u00e4, M. (2018). Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation. Sensors, 18.","DOI":"10.3390\/s18020590"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"69381","DOI":"10.1109\/ACCESS.2018.2880689","article-title":"Stereo Visual-Inertial SLAM with Points and Lines","volume":"6","author":"Liu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1109\/TRO.2018.2853729","article-title":"VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator","volume":"34","author":"Qin","year":"2018","journal-title":"IEEE Trans. Robot."},{"key":"ref_36","unstructured":"K\u00fcmmerle, R., Grisetti, G., and Strasdat, H. (2011, January 9\u201313). G2o: A General Framework for Graph Optimization. Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Qin, T., Li, P., and Shen, S. (2018, January 21\u201325). Relocalization, Global Optimization and Map Merging for Monocular Visual-Inertial SLAM. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8460780"},{"key":"ref_38","unstructured":"Pumarola, A., Vakhitov, A., and Agudo, A. (June, January 29). PL-SLAM: Real-time Monocular Visual SLAM with Points and Lines. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"He, Y., Zhao, J., and Guo, Y. (2018). PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features. Sensors, 18.","DOI":"10.3390\/s18041159"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1177\/0278364915620033","article-title":"The EuRoC Micro Aerial Vehicle Datasets","volume":"35","author":"Burri","year":"2016","journal-title":"Int. J. Robot. Res."},{"key":"ref_41","unstructured":"(2018, December 06). Available online: https:\/\/github.com\/MichaelGrupp\/evo."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Kasyanov, A., Engelmann, F., and St\u00fcckler, J. (2017). Keyframe-Based Visual-Inertial Online SLAM with Relocalization. arXiv, 1\u20138.","DOI":"10.1109\/IROS.2017.8206581"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/9\/2004\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:47:55Z","timestamp":1760186875000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/9\/2004"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,29]]},"references-count":42,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2019,5]]}},"alternative-id":["s19092004"],"URL":"https:\/\/doi.org\/10.3390\/s19092004","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,29]]}}}