The RFID (Radio Frequency IDentification) tag technology is expected as a tool of localization. By the localization of RFID tags, a mobile robot which installs in RFID readers can recognize surrounding environments. In addition, RFID tags can be applied to a navigation system for walkers. In this paper, we propose an adaptive likelihood distribution scheme for the localization of RFID tags. This method adjusts the likelihood distribution depending on the signal intensity from RFID tags. We carry out the performance evaluation of estimated position error by both computer simulations and implemental experiments. We show that the proposed system is more effective than the conventional system.

RFID (Radio Frequency Identification) technology is expected to be used as a localization tool. By the localization of RFID tags, a mobile robot equipped with an RFID reader can recognize the surrounding environment. In this paper, we propose a novel effective scheme called the communication range recognition (CRR) scheme for localizing RFID tags. In this scheme, an RFID reader determines the boundaries of the communication range when it is appropriately positioned by the robot. We evaluate the estimated position accuracy through numerous experiments. We show that the moving distance of the RFID reader in the proposed scheme is lower than that in conventional schemes.

Second-order sampling of 2-D frequency distributions is examined in this paper. When a figure in the frequency space can fill up the entire frequency space by tiling, we call this figure a tiling cluster. We also introduce the concept of pair regions. The results obtained for the second-order sampling of 1-D and 2-D frequency distributions are arranged using these two concepts. The sampling functions and sampling positions of second-order sampling of a 2-D rectangular-complement highpass frequency distribution, which have not been solved until now, are explicitly presented by using these two concepts.

The RFID tag system has received a lot of attention for ubiquitous computing. An RFID tag is attached to an object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag and derives appropriate information about the object. One important application in the RFID technology is localizing RFID tags, which can be very useful in acquiring the position information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for mobile robots. This paper proposes a new adaptive multi-range-sensing method for 3D localization of passive RFID tags by using a probabilistic approach. In this method, a mobile object (human, robot, etc.) with an RFID reader estimates the positions of RFID tags with multiple communication ranges dynamically. The effectiveness of the proposed method was demonstrated in experiments.

The RFID tag system has received attention as an identification source. Each RFID tag is attached to some object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag, and derives appropriate information about the object. One of important applications of the RFID technology is the position estimation of RFID tags. It can be very useful to acquire the location information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for robots etc. In this paper, we propose a new position estimation method of RFID tags by using a probabilistic approach. In this method, mobile objects (person and robot, etc.) with RFID readers estimate the positions of RFID tags with multiple communication ranges. We show the effectiveness of the proposed method by computer simulations.