Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder
Due to the unique and contactless way of identification, radio-frequency identification is becoming an emerging technology for objects tracking. As radio-frequency identification does not provide any distance or bearing information, positioning using radio-frequency identification sensor itself is c...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719860990 |
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| _version_ | 1832547288281513984 |
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| author | Yulu Fu Ran Liu Hua Zhang Gaoli Liang Shafiq ur Rehman Lixiang Liu |
| author_facet | Yulu Fu Ran Liu Hua Zhang Gaoli Liang Shafiq ur Rehman Lixiang Liu |
| author_sort | Yulu Fu |
| collection | DOAJ |
| description | Due to the unique and contactless way of identification, radio-frequency identification is becoming an emerging technology for objects tracking. As radio-frequency identification does not provide any distance or bearing information, positioning using radio-frequency identification sensor itself is challenging. Two-dimensional laser range finders can provide the distance to the objects but require complicated recognition algorithms to acquire the identity of object. This article proposes an innovative method to track the locations of dynamic objects by combining radio-frequency identification and laser ranging information. We first segment the laser ranging data into clusters using density-based spatial clustering of applications with noise (DBSCAN). Velocity matching–based approach is used to track the location of object when the object is in the radio-frequency identification reading range. Since the radio-frequency identification reading range is smaller than a two-dimensional laser range finder, velocity matching–based approach fails to track location of the object when the radio-frequency identification reading is not available. In this case, our approach uses the clustering results from density-based spatial clustering of applications with noise to continuously track the moving object. Finally, we verified our approach on a Scitos robot in an indoor environment, and our results show that the proposed approach reaches a positioning accuracy of 0.43 m, which is an improvement of 67.6% and 84.1% as compared to laser-based and velocity matching–based approaches, respectively. |
| format | Article |
| id | doaj-art-6375a6a5a2d9498bb3ca50709e27e4af |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2019-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-6375a6a5a2d9498bb3ca50709e27e4af2025-02-03T06:45:22ZengWileyInternational Journal of Distributed Sensor Networks1550-14772019-07-011510.1177/1550147719860990Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finderYulu Fu0Ran Liu1Hua Zhang2Gaoli Liang3Shafiq ur Rehman4Lixiang Liu5School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaEngineering Product Development, Singapore University of Technology and Design, SingaporeSchool of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSchool of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaDepartment of Computer Science, Lasbela University of Agriculture, Water and Marine Sciences, Balochistan, PakistanSchool of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaDue to the unique and contactless way of identification, radio-frequency identification is becoming an emerging technology for objects tracking. As radio-frequency identification does not provide any distance or bearing information, positioning using radio-frequency identification sensor itself is challenging. Two-dimensional laser range finders can provide the distance to the objects but require complicated recognition algorithms to acquire the identity of object. This article proposes an innovative method to track the locations of dynamic objects by combining radio-frequency identification and laser ranging information. We first segment the laser ranging data into clusters using density-based spatial clustering of applications with noise (DBSCAN). Velocity matching–based approach is used to track the location of object when the object is in the radio-frequency identification reading range. Since the radio-frequency identification reading range is smaller than a two-dimensional laser range finder, velocity matching–based approach fails to track location of the object when the radio-frequency identification reading is not available. In this case, our approach uses the clustering results from density-based spatial clustering of applications with noise to continuously track the moving object. Finally, we verified our approach on a Scitos robot in an indoor environment, and our results show that the proposed approach reaches a positioning accuracy of 0.43 m, which is an improvement of 67.6% and 84.1% as compared to laser-based and velocity matching–based approaches, respectively.https://doi.org/10.1177/1550147719860990 |
| spellingShingle | Yulu Fu Ran Liu Hua Zhang Gaoli Liang Shafiq ur Rehman Lixiang Liu Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder International Journal of Distributed Sensor Networks |
| title | Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder |
| title_full | Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder |
| title_fullStr | Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder |
| title_full_unstemmed | Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder |
| title_short | Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder |
| title_sort | continuously tracking of moving object by a combination of ultra high frequency radio frequency identification and laser range finder |
| url | https://doi.org/10.1177/1550147719860990 |
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