Moving Object Localization Based on UHF RFID Phase and Laser Clustering

Fu, Yulu; Wang, Changlong; Liu, Ran; Liang, Gaoli; Zhang, Hua; Réhman, Shafiq Ur

doi:10.3390/s18030825

Cited by 29 publications

(28 citation statements)

References 35 publications

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“…Approach Accuracy (m) Remarks Continuous tracking Zhao et al 28 RSS of the virtual reference tags 0.14-0.47 m Need reference tag array No Zhou et al 30 AOA by phase difference 1.7 m Vulnerable to the environment No Kim et al 32 Fusing 40 RFID phase and laser 0.3 m Positioning range is small No Previous approach 41 Fusing RFID and laser based on PF 0.25 m Positioning range is small No Zampella et al 42 RFID and UWB ł 2 m High hardware requirements Yes Retscher and Fu 44 Combined RFID with INS through KF 1-2 m Need to build a model Yes Xie et al 46 Object matching based on RFID and depth camera laser range finder. The third part uses a particle filter to achieve tracking and localization of a dynamic object.…”

Section: Researchersmentioning

confidence: 99%

“…The matching results are used to update the weights of the particle filter. The same implementation is also used by Fu et al 41 For the second approach (laser-based tracking), we ignored the RFID information and only used laser clustering results for tracking by assuming that the initial location of the object is known. The third approach (i.e.…”

Section: Evaluation Of the Positioning Accuracy Under Different Appromentioning

confidence: 99%

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Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder

Liu

Zhang

et al. 2019

International Journal of Distributed Sensor Networks

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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.

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Section: Researchersmentioning

confidence: 99%

Section: Evaluation Of the Positioning Accuracy Under Different Appromentioning

confidence: 99%

Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder

Liu

Zhang

et al. 2019

International Journal of Distributed Sensor Networks

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“…Their algorithm combines two kinematics models and a dual particle filter to achieve fast tracking of dynamic RFID tags. Fu et al [20] studied a new algorithm that uses particle filters to fuse RFID phase and laser clustering from laser sensor to locate moving objects. Scherhaufl et al [21] localized UHF RFID tags by evaluating the phase-of-arrival signal of a tag that is backscattered from several antennas.…”

Section: Introductionmentioning

confidence: 99%

“…We incorporate RFID signal strength information into the particle filter using a pre-trained sensor model to overcome this shortcoming and improve its positioning accuracy. Similar to [20], we use radial velocity matching-based approach to fuse the phase and laser sensor information. Extensive experiments (i.e., different walking velocities and multiple tag scenarios) are conducted to show the effective of our approach.…”

Section: Introductionmentioning

confidence: 99%

An Innovative Approach to Track Moving Object based on RFID and Laser Ranging Information

2020

KSII TIIS

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RFID (Radio Frequency Identification) identifies a specific object by radio signals. As the tag provides a unique ID for the purpose of identification, RFID technology effectively solves the ambiguity and occlusion problem that challenges the laser or camera-based approach. This paper proposes an approach to track a moving object based on the integration of RFID and laser ranging information using a particle filter. To be precise, we split laser scan points into different clusters which contain the potential moving objects and calculate the radial velocity of each cluster. The velocity information is compared with the radial velocity estimated from RFID phase difference. In order to achieve the positioning of the moving object, we select a number of K best matching clusters to update the weights of the particle filter. To further improve the positioning accuracy, we incorporate RFID signal strength information into the particle filter using a pre-trained sensor model. The proposed approach is tested on a SCITOS service robot under different types of tags and various human velocities. The results show that fusion of signal strength and laser ranging information has significantly increased the positioning accuracy when compared to radial velocity matching-based or signal strength-based approaches. The proposed approach provides a solution for human machine interaction and object tracking, which has potential applications in many fields for example supermarkets, libraries, shopping malls, and exhibitions.

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“…In [36], 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.…”

Section: Localizationmentioning

confidence: 99%

Control architecture of a social robot for the navigation and interaction with the environment

Alvarado¹,

Piero²

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Moving Object Localization Based on UHF RFID Phase and Laser Clustering

Cited by 29 publications

References 35 publications

Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder

Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder

An Innovative Approach to Track Moving Object based on RFID and Laser Ranging Information

Control architecture of a social robot for the navigation and interaction with the environment

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