Design of an HF-Band RFID System with Multiple Readers and Passive Tags for Indoor Mobile Robot Self-Localization

Abstract

Radio frequency identification (RFID) technology has already been explored for efficient self-localization of indoor mobile robots. A mobile robot equipped with RFID readers detects passive RFID tags installed on the floor in order to locate itself. The Monte-Carlo localization (MCL) method enables the localization of a mobile robot equipped with an RFID system with reasonable accuracy, sufficient robustness and low computational cost. The arrangements of RFID readers and tags and the size of antennas are important design parameters for realizing accurate and robust self-localization using a low-cost RFID system. The design of a likelihood model of RFID tag detection is also crucial for the accurate self-localization. This paper presents a novel design and arrangement of RFID readers and tags for indoor mobile robot self-localization. First, by considering small-sized and large-sized antennas of an RFID reader, we show how the design of the likelihood model affects the accuracy of self-localization. We also design a novel likelihood model by taking into consideration the characteristics of the communication range of an RFID system with a large antenna. Second, we propose a novel arrangement of RFID tags with eight RFID readers, which results in the RFID system configuration requiring much fewer readers and tags while retaining reasonable accuracy of self-localization. We verify the performances of MCL-based self-localization realized using the high-frequency (HF)-band RFID system with eight RFID readers and a lower density of RFID tags installed on the floor based on MCL in simulated and real environments. The results of simulations and real environment experiments demonstrate that our proposed low-cost HF-band RFID system realizes accurate and robust self-localization of an indoor mobile robot.

Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model

“…An HF-band RFID system is also adopted to our approach. Compared with our research, a precoordinated map of RFID tags is needed for both [28,29]. In particular, both approaches utilized dense tags in the environment which requires a lot of labor costs to build the map of RFID tags manually.…”

“…Yang et al [28] and Mi et al [29] proposed robot selflocalization systems based on the HF-band RFID sensor and significantly improved the precision. An HF-band RFID system is more robust against the influence of environmental changes than the UHF band, which makes it capable of detecting the RFID tags reliably and precisely.…”

An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor

“…Benelli Giuliano et al uses LF RFID to track different typologies of pebbles on beaches [ 27 ]. Mi Jian et al designed an HF-band RFID system with multiple readers and passive tags for indoor mobile robot self-localization [ 28 ]. Own Chung-Ming et al uses UHF RFID technologies for real-time bus recognition in the Taipei bus station [ 29 ], where the active RFID tag on the bus is combined with the infrared receiver.…”

Omni-Directional Scanning Localization Method of a Mobile Robot Based on Ultrasonic Sensors

“…The types of sensors used in the localization of mobile robots include laser sensors [1,2,3], visional sensors [4,5,6], infrared sensors [7], RFID (Radio Frequency Identification Devices) [8] and ultrasonic sensors [9,10], which compared with other sensors is the most robust and low-cost distance detection device [11]. The sound waves emitted by an ultrasonic sensor encompasses a fan-shaped area, the angle of which is defined as the divergence angle, and all objects that fall within this region can be detected.…”