{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T20:23:33Z","timestamp":1780431813129,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,16]],"date-time":"2020-07-16T00:00:00Z","timestamp":1594857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In an indoor environment, object identification and localization are paramount for human-object interaction. Visual or laser-based sensors can achieve the identification and localization of the object based on its appearance, but these approaches are computationally expensive and not robust against the environment with obstacles. Radio Frequency Identification (RFID) has a unique tag ID to identify the object, but it cannot accurately locate it. Therefore, in this paper, the data of RFID and laser range finder are fused for the better identification and localization of multiple dynamic objects in an indoor environment. The main method is to use the laser range finder to estimate the radial velocities of objects in a certain environment, and match them with the object\u2019s radial velocities estimated by the RFID phase. The method also uses a fixed time series as \u201csliding time window\u201d to find the cluster with the highest similarity of each RFID tag in each window. Moreover, the Pearson correlation coefficient (PCC) is used in the update stage of the particle filter (PF) to estimate the moving path of each cluster in order to improve the accuracy in a complex environment with obstacles. The experiments were verified by a SCITOS G5 robot. The results show that this method can achieve an matching rate of 90.18% and a localization accuracy of 0.33m in an environment with the presence of obstacles. This method effectively improves the matching rate and localization accuracy of multiple objects in indoor scenes when compared to the Bray-Curtis (BC) similarity matching-based approach as well as the particle filter-based approach.<\/jats:p>","DOI":"10.3390\/s20143948","type":"journal-article","created":{"date-parts":[[2020,7,16]],"date-time":"2020-07-16T10:54:46Z","timestamp":1594896886000},"page":"3948","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID"],"prefix":"10.3390","volume":"20","author":[{"given":"Wenpeng","family":"Fu","sequence":"first","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6343-4645","authenticated-orcid":false,"given":"Ran","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"},{"name":"Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0889-8890","authenticated-orcid":false,"given":"Rashid","family":"Ali","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"},{"name":"Department of Computer Science, University of Turbat, Balochistan 92600, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongping","family":"He","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenghong","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2568","DOI":"10.1109\/COMST.2019.2911558","article-title":"A survey of indoor localization systems and technologies","volume":"21","author":"Zafari","year":"2019","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"24846","DOI":"10.1109\/ACCESS.2018.2830762","article-title":"Reliable and cooperative target tracking based on WSN and WiFi in indoor Wireless Networks","volume":"6","author":"Luo","year":"2018","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1109\/TIE.2009.2012457","article-title":"Ceiling-based visual positioning for an indoor mobile robot with monocular vision","volume":"56","author":"Xu","year":"2009","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1109\/TMECH.2018.2820172","article-title":"Accurate and real-time 3-D tracking for the following robots by fusing vision and ultrasonar information","volume":"23","author":"Wang","year":"2018","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"29283","DOI":"10.1109\/ACCESS.2018.2834916","article-title":"Object tracking in vary lighting conditions for fog based intelligent surveillance of public spaces","volume":"6","author":"Liu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xing, B.Y., Zhu, Q.M., Pan, F., and Feng, X.X. (2018). Marker-based multi-sensor fusion indoor localization system for micro air vehicles. J. Sens., 18.","DOI":"10.3390\/s18061706"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"64971","DOI":"10.1109\/ACCESS.2020.2985053","article-title":"Data fusion of UWB and IMU based on unscented Kalman filter for indoor localization of Quadrotor UAV","volume":"8","author":"You","year":"2020","journal-title":"IEEE Access"},{"key":"ref_8","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_9","doi-asserted-by":"crossref","first-page":"34455","DOI":"10.1109\/ACCESS.2020.2974285","article-title":"UAV positioning based on multi-sensor fusion","volume":"8","author":"Peng","year":"2020","journal-title":"IEEE Access"},{"key":"ref_10","first-page":"3570","article-title":"Design of indoor lidar navigation system","volume":"44","author":"Shi","year":"2015","journal-title":"Infrared Laser Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4901","DOI":"10.1109\/JSEN.2020.2966034","article-title":"Fusion of 3D LIDAR and camera data for object detection in autonomous vehicle applications","volume":"20","author":"Zhao","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1109\/TIE.2013.2248333","article-title":"Mobile robot localization using the phase of passive UHF RFID signals","volume":"61","author":"DiGiampaolo","year":"2014","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3733","DOI":"10.1109\/JSEN.2019.2894714","article-title":"A low-cost INS and UWB fusion pedestrian tracking system","volume":"19","author":"Tian","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2417","DOI":"10.3788\/OPE.20162410.2417","article-title":"Indoor positioning by using scanning infrared laser and ultrasonic technology","volume":"24","author":"Wu","year":"2016","journal-title":"Opt. Precis. Eng."},{"key":"ref_15","first-page":"242","article-title":"Laser radar based on scanning image tracking","volume":"5","author":"Qu","year":"2012","journal-title":"Chin. Opt."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11805","DOI":"10.3390\/s140711805","article-title":"An UGV indoor positioning system using laser scan matching for large-area real-time applications","volume":"14","author":"Tang","year":"2014","journal-title":"Sensors"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8","DOI":"10.3788\/OPE.20192701.0008","article-title":"Object geo-location based on laser range finder for airborne electro-optical imaging systems","volume":"27","author":"Zhang","year":"2019","journal-title":"Opt. Precisioneng."},{"key":"ref_18","first-page":"55","article-title":"Dynamic object location with radio frequency identification and laser information","volume":"40","author":"Liu","year":"2018","journal-title":"J. Electron. Inf."},{"key":"ref_19","first-page":"1317","article-title":"Voting for voting in online point cloud object detection","volume":"1","author":"Wang","year":"2015","journal-title":"Robot. Sci. Syst."},{"key":"ref_20","first-page":"437","article-title":"Detection, tracking and identification of dynamic obstacles in driverless vehicles based on laser radar","volume":"38","author":"Huang","year":"2016","journal-title":"Robot"},{"key":"ref_21","first-page":"167","article-title":"Infrared and laser fusion object identification method","volume":"47","author":"Tong","year":"2018","journal-title":"Infrared Laser Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"781380","DOI":"10.1155\/2015\/781380","article-title":"On Tracking dynamic objects with long range passive UHF RFID using a mobile robot","volume":"11","author":"Liu","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Fan, X.Y., Wang, F., Gong, W., Zhang, L., and Liu, J.C. (2018, January 2\u20136). Multiple object activity identification using RFIDs: A multipath-aware deep learning solution. Proceedings of the 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), Vienna, Austria.","DOI":"10.1109\/ICDCS.2018.00060"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1023\/B:WINE.0000044029.06344.dd","article-title":"LANDMARC: Indoor location sensing using active RFID","volume":"10","author":"Ni","year":"2004","journal-title":"Wirel. Netw."},{"key":"ref_25","unstructured":"Hightower, J., Borriello, G., and Wang, R. (2000). SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength, Department of Computer Science and Engineering, University of Washington. Technic Report 2000-02-02."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhao, Y.Y., Liu, Y.H., and Ni, L.M. (2007, January 10\u201314). VIRE: Active RFID-based localization using Virtual Reference Elimination. Proceedings of the 2007 International Conference on Parallel Processing (ICPP 2007), Xi\u2019an, China.","DOI":"10.1109\/ICPP.2007.84"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"78947","DOI":"10.1109\/ACCESS.2018.2885648","article-title":"Sensor fusion for tour-guide robot localization","volume":"6","author":"Gonzalez","year":"2018","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2226","DOI":"10.1109\/TIE.2011.2109330","article-title":"A hierarchical algorithm for indoor mobile robot localization using rfid sensor fusion","volume":"58","author":"Choi","year":"2011","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Suparyanto, A., Fatimah, R.N., Widyotriatmo, A., and Nazaruddin, Y.Y. (2018, January 30\u201331). Port container truck localization using sensor fusion technique. Proceedings of the 2018 5th International Conference on Electric Vehicular Technology (ICEVT), Surakarta, Indonesia.","DOI":"10.1109\/ICEVT.2018.8628318"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wang, C.S., and Chen, C.L. (2014, January 11\u201314). RFID-based and Kinect-based indoor positioning system. Proceedings of the 2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE), Aalborg, Denmark.","DOI":"10.1109\/VITAE.2014.6934458"},{"key":"ref_31","unstructured":"Li, X.Y., Zhang, Y.Z., Marsic, I., and Burd, R.S. (2017). Online people tracking and identification with RFID and Kinect. arXiv."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Parr, A., Miesen, R., Kirsch, F., and Vossiek, M. (2012, January 3\u20135). A novel method for UHF RFID tag tracking based on acceleration data. Proceedings of the 2012 IEEE International Conference on RFID (RFID), Orlando, FL, USA.","DOI":"10.1109\/RFID.2012.6193037"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Faramondi, L., Inderst, F., Pascucci, F., Setola, R., and Delprato, U. (2013, January 28\u201331). An enhanced indoor positioning system for first responders. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, Montbeliard-Belfort, France.","DOI":"10.1109\/IPIN.2013.6817921"},{"key":"ref_34","unstructured":"Vorst, P., and Zell, A. (2010, January 7\u20139). A comparison of similarity measures for localization with passive rfid fingerprints. Proceedings of the ISR 2010 (41st International Symposium on Robotics) and ROBOTIK 2010 (6th German Conference on Robotics), Munich, Germany."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Vorst, P., Koch, A., and Zell, A. (2011, January 15\u201316). Efficient self-adjusting, similarity-based location fingerprinting with passive UHF RFID. Proceedings of the 2011 IEEE International Conference on RFID-Technologies and Applications, Sitges, Spain.","DOI":"10.1109\/RFID-TA.2011.6068632"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Shyam, R., and Singh, Y.N. (2015, January 19\u201320). Face recognition using augmented local binary pattern and Bray Curtis dissimilarity metric. Proceedings of the 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India.","DOI":"10.1109\/SPIN.2015.7095267"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Samantaray, A.K., and Rahulkar, A.D. (2019, January 6\u20138). Comparison of similarity measurement metrics on medical image data. Proceedings of the 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India.","DOI":"10.1109\/ICCCNT45670.2019.8944781"},{"key":"ref_38","unstructured":"Li, X., Zhang, Y., and Amin, M.G. (2009, January 27\u201328). Multifrequency-based range estimation of RFID Tags. Proceedings of the 2009 IEEE International Conference on RFID, Orlando, FL, USA."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"47468","DOI":"10.1109\/ACCESS.2020.2972034","article-title":"An improved DBSCAN algorithm based on the neighbor similarity and fast nearest neighbor query","volume":"8","author":"Li","year":"2020","journal-title":"IEEE Access"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Fu, Y.L., Liu, R., Zhang, H., Liang, G.L., Shafiq, U.R., and Liu, L.X. (2019). Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder. Int. J. Distrib. Sens. Netw., 7.","DOI":"10.1177\/1550147719860990"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"61628","DOI":"10.1109\/ACCESS.2019.2915673","article-title":"Multiple ant colony optimization based on Pearson Correlation Coefficient","volume":"7","author":"Zhu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_42","unstructured":"Chen, G., Liu, Q., Wei, Y.K., and Yu, Q. (2016, January 14\u201317). An efficient indoor location system in WLAN based on database partition and euclidean distance-weighted Pearson Correlation Coefficient. Proceedings of the 2016 2nd IEEE International Conference on Computer and Communications (ICCC), Chengdu, China."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Cardoso, A.D.V., Nedjah, N., and Macedo Mourelle, L.D. (2019, January 24\u201327). Accelerating template matching for efficient object tracking. Proceedings of the 2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS), Armenia, Colombia.","DOI":"10.1109\/LASCAS.2019.8667596"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/14\/3948\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:48:56Z","timestamp":1760176136000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/14\/3948"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,16]]},"references-count":43,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["s20143948"],"URL":"https:\/\/doi.org\/10.3390\/s20143948","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,16]]}}}