Moving Object Localization Based on UHF RFID Phase and Laser Clustering

• Main Authors: Yulu Fu, Changlong Wang, Ran Liu, Gaoli Liang, Hua Zhang, Shafiq Ur Rehman
• Format: Article
• Language: English
• Published: MDPI AG 2018-03-01
• Series: Sensors
• Subjects: RFID; phase difference; laser clustering; velocity matching; particle filter
• Online Access: http://www.mdpi.com/1424-8220/18/3/825

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.