Abstract
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.
Highlights
Recent documents show a growing interest in indoor localization due to the high demand of location-based services (LBS) [1,2], for example asset tracking and indoor guidance
The computation of RFID phase velocity is described in Section 3.1, the clustering of laser ranging data is presented in Section 3.2, the estimation of the velocity and moving direction of a cluster is detailed in Section 3.3, and velocity matching and the implementation using a particle filter are detailed in Sections 3.4 and 3.5, respectively
The robot is equipped with a 2D laser range finder (SICK S300), a UHF RFID reader (Speedway Revolution R420 from Impinj, Inc., Seattle, WA, USA) with a sampling frequency of 2 Hz, and two circularly polarized antennas (RFMAX SS8688P from Laird Technologies, London, UK) at two sides of the robot with angles of 45◦
Summary
Recent documents show a growing interest in indoor localization due to the high demand of location-based services (LBS) [1,2], for example asset tracking and indoor guidance. RFID is used to combine with other sensors (for example, laser range finders and visual cameras) to improve the positioning accuracy [23,24,25]. Shirehjini et al used RFID carpets and several peripherals of sensor to build a positioning system based on low-range passive RFID technology [32] Laser-based sensors need to establish a model and complex recognition algorithms to identify the object, which usually requires a pre-training stage and expensive computational time [44,45]. We propose an approach to combine UHF RFID technology and laser ranging information to localize a moving object.
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