{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:53:57Z","timestamp":1760241237875,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T00:00:00Z","timestamp":1576540800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2018YFB0505200"],"award-info":[{"award-number":["2018YFB0505200"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Visual inertial odometers (VIOs) have received increasing attention in the area of indoor positioning due to the universality and convenience of the camera. However, the visual observation of VIO is more susceptible to the environment, and the error of observation affects the final positioning accuracy. To address this issue, we analyzed the causes of visual observation error that occur under different scenarios and their impact on positioning accuracy. We propose a new method of using the short-time reliability of pedestrian dead reckoning (PDR) to aid in visual integrity monitoring and to reduce positioning error. The proposed method selects optimized positioning by automatically switching between outputs from VIO and PDR. Experiments were carried out to test and evaluate the proposed PDR-assisted visual integrity monitoring. The sensor suite of experiments consisted of a stereo camera and an inertial measurement unit (IMU). Results were analyzed in detailed and indicated that the proposed system performs better for indoor positioning within an environment that contains low illumination, little background texture information, or few moving objects.<\/jats:p>","DOI":"10.3390\/s19245577","type":"journal-article","created":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T03:19:36Z","timestamp":1576811976000},"page":"5577","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Pedestrian Dead Reckoning-Assisted Visual Inertial Odometry Integrity Monitoring"],"prefix":"10.3390","volume":"19","author":[{"given":"Yuqin","family":"Wang","sequence":"first","affiliation":[{"name":"School of Informatics, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3348-4358","authenticated-orcid":false,"given":"Ao","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Informatics, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhichao","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Informatics, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingxiang","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Informatics, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7648-8709","authenticated-orcid":false,"given":"Huiru","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Newtownabbey BT37 0QB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Causa, F., Vetrella, A.R., Fasano, G., and Accardo, D. (2018, January 23\u201326). Multi-UAV formation geometries for cooperative navigation in GNSS-challenging environments. Proceedings of the IEEE\/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, USA.","DOI":"10.1109\/PLANS.2018.8373453"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Al-Ammar, M.A., Alhadhrami, S., Al-Salman, A., Alarifi, A., Al-Khalifa, H.S., Alnafessah, A., and Alsaleh, M. (2014, January 6\u20138). Comparative Survey of Indoor Positioning Technologies, Techniques, and Algorithms. Proceedings of the International Conference on Cyberworlds, Santander, Spain.","DOI":"10.1109\/CW.2014.41"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hameed, A., and Ahmed, H.A. (2018, January 24\u201325). Survey on indoor positioning applications based on different technologies. Proceedings of the 12th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS), Karachi, Pakistan.","DOI":"10.1109\/MACS.2018.8628462"},{"key":"ref_4","unstructured":"Alkhawaja, F., Jaradat, M., and Romdhane, L. (April, January 26). Techniques of Indoor Positioning Systems (IPS): A Survey. Proceedings of the Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"97466","DOI":"10.1109\/ACCESS.2019.2929133","article-title":"A Survey on Odometry for Autonomous Navigation Systems","volume":"7","author":"Mohamed","year":"2019","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1109\/COMST.2015.2464084","article-title":"Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons","volume":"18","author":"He","year":"2016","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"33440","DOI":"10.1109\/ACCESS.2018.2837497","article-title":"A Protocol-Channel-Based Indoor Positioning Performance Study for Bluetooth Low Energy","volume":"6","year":"2018","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Feng, Z., and Hao, S. (2017, January 9\u201310). Low-Light Image Enhancement by Refining Illumination Map with Self-Guided Filtering. Proceedings of the IEEE International Conference on Big Knowledge (ICBK), Hefei, China.","DOI":"10.1109\/ICBK.2017.37"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5376","DOI":"10.1109\/JSEN.2016.2565899","article-title":"Indoor Pedestrian Localization With a Smartphone: A Comparison of Inertial and Vision-Based Methods","volume":"16","author":"Elloumi","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Filipenko, M., and Afanasyev, I. (2018, January 25\u201327). Comparison of Various SLAM Systems for Mobile Robot in an Indoor Environment. Proceedings of the International Conference on Intelligent Systems (IS), Funchal-Madeira, Portugal.","DOI":"10.1109\/IS.2018.8710464"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Huang, G. (2019). Visual-Inertial Navigation: A Concise Review. arXiv, Available online: https:\/\/arxiv.org\/abs\/1906.02650.","DOI":"10.1109\/ICRA.2019.8793604"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1109\/TMECH.2013.2276404","article-title":"Vision-Aided Inertial Navigation Based on Ground Plane Feature Detection","volume":"19","author":"Panahandeh","year":"2014","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_13","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. Rob."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.robot.2017.03.019","article-title":"S-PTAM: Stereo Parallel Tracking and Mapping","volume":"93","author":"Pire","year":"2017","journal-title":"Rob. Autom. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Mainetti, L., Patrono, L., and Sergi, I. (2014, January 17\u201319). A survey on indoor positioning systems. Proceedings of the 22nd International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia.","DOI":"10.1109\/SOFTCOM.2014.7039067"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Garcia-Villalonga, S., and Perez-Navarro, A. (2015, January 13\u201316). Influence of human absorption of Wi-Fi signal in indoor positioning with Wi-Fi fingerprinting. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Banff, AB, Canada.","DOI":"10.1109\/IPIN.2015.7346778"},{"key":"ref_17","unstructured":"Kourogi, M., and Kurata, T. (2003, January 7\u201310). Personal positioning based on walking locomotion analysis with self-contained sensors and a wearable camera. Proceedings of the 2nd IEEE and ACM International Symposium on Mixed and Augmented Reality, Washington, DC, USA."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6460","DOI":"10.1109\/JSEN.2019.2907716","article-title":"Real-Time 3D Motion Tracking and Reconstruction System Using Camera and IMU Sensors","volume":"19","author":"Li","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Mourikis, A.I., and Roumeliotis, S.I. (2007, January 10\u201314). A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation. Proceedings of the IEEE International Conference on Robotics and Automation, Roma, Italy.","DOI":"10.1109\/ROBOT.2007.364024"},{"key":"ref_20","unstructured":"Bloesch, M., Omari, S., Hutter, M., and Siegwart, R. (Octomber, January 28). Robust visual inertial odometry using a direct EKF-based approach. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany."},{"key":"ref_21","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. Rob."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Albrecht, A., and Heide, N. (2018, January 20\u201323). Improving stereo vision based SLAM by integrating inertial measurements for person indoor navigation. Proceedings of the 4th International Conference on Control, Automation and Robotics (ICCAR), Auckland, New Zealand.","DOI":"10.1109\/ICCAR.2018.8384694"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TIM.2017.2754678","article-title":"Novel EKF-Based Vision\/Inertial System Integration for Improved Navigation","volume":"67","author":"Karamat","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Calhoun, S.M., and Raquet, J. (2016, January 11\u201314). Integrity determination for a vision based precision relative navigation system. Proceedings of the IEEE\/ION Position, Location and Navigation Symposium (PLANS), Savannah, GA, USA.","DOI":"10.1109\/PLANS.2016.7479713"},{"key":"ref_25","unstructured":"Calhoun, S., Raquet, J., and Peterson, G. (2015, January 26\u201328). Vision-aided integrity monitor for precision relative navigation systems. Proceedings of the International Technical Meeting of the Institute of Navigation, Dana Point, CA, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1109\/TIM.2012.2214934","article-title":"Multisensor Contour Following With Vision, Force, and Acceleration Sensors for an Industrial Robot","volume":"62","author":"Koch","year":"2013","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2706","DOI":"10.1109\/TIM.2010.2045258","article-title":"Color-Based Monocular Visuoinertial 3-D Pose Estimation of a Volant Robot","volume":"59","author":"Kyriakoulis","year":"2010","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Altinpinar, O.V., and Yal\u00e7in, M.E. (2018, January 2\u20135). Design of a pedestrian dead-reckoning system and comparison of methods on the system. Proceedings of the 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey.","DOI":"10.1109\/SIU.2018.8404332"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gobana, F.W. (2018, January 17\u201319). Survey of Inertial\/magnetic Sensors Based pedestrian dead reckoning by multi-sensor fusion method. Proceedings of the International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea.","DOI":"10.1109\/ICTC.2018.8539576"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Jimenez, A.R., Seco, F., Prieto, C., and Guevara, J. (2009, January 26\u201328). A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU. Proceedings of the IEEE International Symposium on Intelligent Signal Processing, Budapest, Hungary.","DOI":"10.1109\/WISP.2009.5286542"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9532","DOI":"10.1109\/JSEN.2019.2926124","article-title":"An Experimental Heuristic Approach to Multi-Pose Pedestrian Dead Reckoning Without Using Magnetometers for Indoor Localization","volume":"19","author":"Lee","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yan, J., He, G., Basiri, A., and Hancock, C. (2018, January 14\u201317). Vision-aided indoor pedestrian dead reckoning. Proceedings of the IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Houston, TX, USA.","DOI":"10.1109\/I2MTC.2018.8409599"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2288","DOI":"10.1109\/TIM.2014.2304365","article-title":"Selective Integration of GNSS, Vision Sensor, and INS Using Weighted DOP Under GNSS-Challenged Environments","volume":"63","author":"Won","year":"2014","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1587\/transinf.E94.D.1137","article-title":"Design and Implementation of Pedestrian Dead Reckoning System on a Mobile Phone","volume":"94-D","author":"Kamisaka","year":"2011","journal-title":"IEICE Trans. Inf. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/MAES.2016.150255","article-title":"Stereo-camera visual odometry for outdoor areas and in dark indoor environments","volume":"31","author":"Ruppelt","year":"2016","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/34.601246","article-title":"In defense of the eight-point algorithm","volume":"19","author":"Hartley","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2327","DOI":"10.3390\/s17102327","article-title":"Comparing the Performance of Indoor Localization Systems through the EvAAL Framework","volume":"17","author":"Park","year":"2017","journal-title":"Sensors"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/24\/5577\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:43:03Z","timestamp":1760190183000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/24\/5577"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,17]]},"references-count":37,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19245577"],"URL":"https:\/\/doi.org\/10.3390\/s19245577","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,12,17]]}}}