{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T07:10:34Z","timestamp":1765609834226,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,9]],"date-time":"2018-03-09T00:00:00Z","timestamp":1520553600000},"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>RFID (Radio Frequency Identification) offers a way to identify objects without any contact. However, positioning accuracy is limited since RFID neither provides distance nor bearing information about the tag. This paper proposes a new and innovative approach for the localization of moving object using a particle filter by incorporating RFID phase and laser-based clustering from 2d laser range data. First of all, we calculate phase-based velocity of the moving object based on RFID phase difference. Meanwhile, we separate laser range data into different clusters, and compute the distance-based velocity and moving direction of these clusters. We then compute and analyze the similarity between two velocities, and select K clusters having the best similarity score. We predict the particles according to the velocity and moving direction of laser clusters. Finally, we update the weights of the particles based on K clusters and achieve the localization of moving objects. The feasibility of this approach is validated on a Scitos G5 service robot and the results prove that we have successfully achieved a localization accuracy up to 0.25 m.<\/jats:p>","DOI":"10.3390\/s18030825","type":"journal-article","created":{"date-parts":[[2018,3,9]],"date-time":"2018-03-09T12:17:41Z","timestamp":1520597861000},"page":"825","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Moving Object Localization Based on UHF RFID Phase and Laser Clustering"],"prefix":"10.3390","volume":"18","author":[{"given":"Yulu","family":"Fu","sequence":"first","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}]},{"given":"Changlong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}]},{"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"}]},{"given":"Gaoli","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}]},{"given":"Hua","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"}]},{"given":"Shafiq","family":"Ur Rehman","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"},{"name":"Department of Computer Science, Lasbela University of Agriculture, Water and Marine Sciences, Balochistan 90150, Pakistan"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,9]]},"reference":[{"key":"ref_1","unstructured":"Zhao, Y. 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