Abstract— Passive Radio Frequency Identification (RFID) is being increasingly used in mobile robotics applications, as it provides inexpensive and effective solutions to data association issues in basic navigation tasks. Nonetheless, problems related to sensitivity of the signal to interference and reflections, and missing tag range and bearing information are open. In this paper, we propose a novel approach to passive RFID, which tackles those issues using fuzzy reasoning. Specifically, first, we present a fuzzy antenna model. Then, based on this model, we describe two fuzzy logic methods for tag localization. One allows us to accurately localize passive tags in the environment and to generate what we call an RFID-augmented map; the other is suited for estimating the bearing of a tag relative to the robot. The general use of both methods is in object localization, map building, environment monitoring, and robot pose estimation. Results of experimental tests demonstrate that fuzzy logic is appropriate to operate under uncertainty in RFID systems, and allows for accurate tag localization. I. INTRODUCTION N the last years, Radio Frequency Identification (RFID) has received great attention, since it supplies an inexpensive and effective technology for object identification and tracking with a wide range of applications. Examples include inventory management, industry automation, ID badges and access control, equipment and personnel tracking. RFID systems typically consist of radio frequency (RF) tags, a reader with one or more antennas, and a software to process the tag readings. The reader interrogates the tags, receiving their ID code and other information stored in their memory. Compared to conventional identification systems, such as barcodes, RFID tags offer several advantages, since they do not require direct line-of-sight; moreover, multiple tags can be detected simultaneously [1]. Recently, RFID has appeared on the scene of mobile robotics, promising to contribute solutions to data association problems in navigation tasks, such as localization and mapping [2], [3]. Nevertheless, in order for RFID sensors to be effectively used in mobile robotics applications, some issues have to be tackled. First, due to low cost and low power constraints, RFID devices are sensitive to interference and reflections from other objects. Therefore, RFID readings are generally affected by high Manuscript received March 1, 2009. A. Milella, D. Di Paola, G. Cicirelli, and A. Distante are with the Institute of Intelligent Systems for Automation, Italian National Research Council, via G. Amendola 122/D, 70126, Bari, Italy. Corresponding author: Annalisa Milella; e-mail: milella@ba.issia.cnr.it; tel.: +39 080 5929447. uncertainty. Moreover, at least in the case of passive tags, an RFID reader can only determine whether a tag is present or not in its reading range, while it is not able to provide information about the position of the tag [4], [5]. These issues may be partially solved using active RFID [6]-[8]; however, active transponders are more costly than passive ones, and have a limited lifetime. Methods to localize passive RFID tags and integrate them in mobile robotics systems have been developed by a few authors. For instance, in [9] Hähnel et al. suggest a particle filtering method for localizing passive tags in a previously built map of the environment, using a mobile robot equipped with an RFID device and a laser rangefinder. Specifically, while the robot moves in the environment, the location of a tag is estimated starting from a set of particles, whose weights are updated at each successful detection of the tag, using the Bayes rule and a probabilistic model of the antenna. Bayesian solutions for tag localization are also adopted in [4], [10], [11]. In [4], two RFID tag-positioning algorithms are developed, namely an online approach and an offline approach. The offline method is equivalent to the one proposed in [9]. The online algorithm is based on a simplified antenna model that defines a high probability region, instead of describing the probability at each location, in order to achieve computational efficiency. In [10], RFID tags are used for obstacle detection and avoidance. The Bayes rule is applied to estimate tag positions. Tags are also used as landmarks for robot localization based on visual input from a stereovision device. In [11], the tag localization algorithm is formalized as a non-linear stochastic inversion problem. Several readers, equipped with rotating antennas, take observations. The reading units are connected in a local network with a server, which gathers the data and executes the localization task. In this paper, we propose an alternative approach to passive RFID. As in [9], we use a mobile robot equipped with an RFID device, and refer to a model of the antenna reading range for tag localization. However, our approach is unique in that it uses fuzzy reasoning to both learn a model of the RFID system and localize the tags. Specifically we present two fuzzy logic-based tag localization approaches. The general use of both methods is in object identification and localization, map building, environment monitoring, and robot pose estimation. The first one, named Fuzzy Tag Localization (FTL), aims at localizing accurately passive tags in the environment, in order to generate what we refer to as an RFID-augmented A Fuzzy Logic Approach to Passive RFID for Mobile Robot Applications Annalisa Milella, Donato Di Paola, Grazia Cicirelli, and Arcangelo Distante I The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems October 11-15, 2009 St. Louis, USA 978-1-4244-3804-4/09/$25.00 ©2009 IEEE 5561