2,257 research outputs found
RePos : relative position estimation of UHF-RFID tags for item-level localization
Radio frequency identification (RFID) technology brings tremendous applications in location-based services. Specifically, ultra-high frequency (UHF) RFID tag positioning based on phase (difference) of arrival (PoA/PDoA) has won great attention, due to its better positioning accuracy than signal strength-based methods. In most cases, such as logistics, retailing, and smart inventory management, the relative orders of the objects are much more attractive than absolute positions with centimetre-level accuracy. In this paper, a relative positioning (RePos) approach based on inter-tag distance and direction estimation is proposed. In the RePos positioning system, the measured phases are reconstructed based on unwrapping method. Then the distances from antenna to the tags are calculated using the distance differences of pairs of antenna's positions via a least-squares method. The relative relationships of the tags, including relative distances and angles, are obtained based on the geometry information extracted from PDoA. The experimental results show that the RePos RFID positioning system can realize about 0.28-meter ranging accuracy, and distinguish the levels and columns without ambiguity
RF Localization in Indoor Environment
In this paper indoor localization system based on the RF power measurements of the Received Signal Strength (RSS) in WLAN environment is presented. Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need new infrastructure (it reuses already and widely deployed equipment), and the RSS measurement is part of the normal operating mode of wireless equipment. We derive the Cramer-Rao Lower Bound (CRLB) of localization accuracy for RSS measurements. In analysis of the bound we give insight in localization performance and deployment issues of a localization system, which could help designing an efficient localization system. To compare different machine learning approaches we developed a localization system based on an artificial neural network, k-nearest neighbors, probabilistic method based on the Gaussian kernel and the histogram method. We tested the developed system in real world WLAN indoor environment, where realistic RSS measurements were collected. Experimental comparison of the results has been investigated and average location estimation error of around 2 meters was obtained
A phase-based technique for localization of uhf-rfid tags moving on a conveyor belt: Performance analysis and test-case measurements
A new phase-based technique for localization and
tracking of items moving along a conveyor belt and equipped with
ultrahigh frequency-radio frequency identification (UHF-RFID)
tags is described and validated here. The technique is based on
a synthetic-array approach that takes advantage of the fact that
the tagged items move along a conveyor belt whose speed and
path are known apriori. In this framework, a joint use is done
of synthetic-array radar principles, knowledge-based processing,
and efficient exploitation of the reader-tag communication signal.
The technique can be easily implemented in any conventional
reader based on an in-phase and quadrature receiver and it does
not require any modification of the reader antenna configurations
usually adopted in UHF-RFID portals. Numerical results are used
to investigate the performance analysis of such methods, and
also to furnish system design guidelines. Finally, the localization
capability is also demonstrated through a measurement campaign
in a real conveyor belt scenario, showing that a centimeter-order
accuracy in the tag position estimation can be achieved even in
a rich multipath environment
Indoor localization systems-tracking objects and personnel with sensors, wireless networks and RFID
Advances in ubiquitous mobile computing and rapid spread of information
systems have fostered a growing interest in indoor location-aware or location-based
technologies. In this paper we will introduce the primary technologies used in indoor
localization systems by classifying them in three categories: Non-RF technologies,
Active-RF technologies and Passive-RF technologies. Both commercialized products and
research prototypes in all categories are involved in our discussion. The Passive-RF
technologies are further divided into âMobile tagâ and âMobile readerâ systems. We
expect such classification can cover most of the indoor localization systems. Features of
these systems are briefly compared at the end of this paper
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The Design and Implementation of a Mobile RFID Tag Sorting Robot
Libraries, manufacturing lines, and offices of the future all stand to benefit from knowing the exact spatial order of RFID-tagged books, components, and folders, respectively. To this end, radio- based localization has demonstrated the potential for high accuracy. Key enabling ideas include motion-based synthetic aperture radar, multipath detection, and the use of different frequencies (channels). But indoors in real-world situations, current systems often fall short of the mark, mainly because of the prevalence and strength of "multipath" reflections of the radio signal off nearby objects. In this paper we describe the design and implementation of MobiTagbot, an autonomous wheeled robot reader that conducts a roving survey of the above such areas to achieve an exact spatial order of RFID- tagged objects in very close (1â6 cm) spacings. Our approach leverages a serendipitous correlation between the changes in multipath reflections that occur with motion and the effect of changing the carrier frequency (channel) of the RFID query. By carefully observing the relationship between channel and phase, MobiTagbot detects if multipath is likely prevalent at a given robot reader location. If so, MobiTagbot excludes phase readings from that reader lo- cation, and generates a final location estimate using phase readings from other locations as the robot reader moves in space. Experimentally, we demonstrate that cutting-edge localization algorithms including Tagoram are not accurate enough to exactly order items in very close proximity, but MobiTagbot is, achieving nearly 100% ordering accuracy for items at low (3â6 cm) spacings and 86% accuracy for items at very low (1â3 cm) spacings
Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0
Within the context of Industry 4.0, mobile robot systems such as automated
guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major
areas challenging current communication and localization technologies. Due to
stringent requirements on latency and reliability, several of the existing
solutions are not capable of meeting the performance required by industrial
automation applications. Additionally, the disparity in types and applications
of unmanned vehicle (UV) calls for more flexible communication technologies in
order to address their specific requirements. In this paper, we propose several
use cases for UVs within the context of Industry 4.0 and consider their
respective requirements. We also identify wireless technologies that support
the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl
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