We present a new vision for smart objects and the Internet of Things wherein mobile robots interact with wirelessly-powered, long-range, ultra-high frequency radio frequency identification (UHF RFID) tags outfitted with sensing capabilities. We explore the technology innovations driving this vision by examining recently-commercialized sensor tags that could be affixed-to or embedded-in objects or the environment to yield true embodied intelligence. Using a pair of autonomous mobile robots outfitted with UHF RFID readers, we explore several potential applications where mobile robots interact with sensor tags to perform tasks such as: soil moisture sensing, remote crop monitoring, infrastructure monitoring, water quality monitoring, and remote sensor deployment.
Roboticists have employed RFID to great effect. The unique identifier has proved useful for object recognition @cite_11 , as a high-confidence landmark in SLAM implementations @cite_4 , for waypoint navigation @cite_1 , and as a complementary sensing modality for multi-sensor fusion @cite_3 . Many of these systems rely on low-frequency (LF) and high-frequency (HF) RFID tags, which have very short read ranges (5-10 @math cm ). In contrast, ultra-high frequency (UHF) tags can be used for both short-range operation @cite_15 as well as long-range operation out to several meters @cite_18 . In robotics, UHF RFID tags have been used for robot localization @cite_20 , to locate tagged objects @cite_8 , for medication delivery @cite_23 , and for manipulation @cite_2 .
@cite_18 @cite_4 @cite_8 @cite_1 @cite_3 @cite_23 @cite_2 @cite_15 @cite_20 @cite_11
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We address the challenge of finding and navigating to an object with an attached ultra-high frequency radiofrequency identification (UHF RFID) tag. With current off-theshelf technology, one can affix inexpensive self-adhesive UHF RFID tags to hundreds of objects, thereby enabling a robot to sense the RF signal strength it receives from each uniquely identified object. The received signal strength indicator (RSSI) associated with a tagged object varies widely and depends on many factors, including the object’s pose, material properties and surroundings. This complexity creates challenges for methods that attempt to explicitly estimate the object’s pose. We present an alternative approach that formulates finding and navigating to a tagged object as an optimization problem where the robot must find a pose of a directional antenna that maximizes the RSSI associated with the target tag. We then present three autonomous robot behaviors that together perform this optimization by combining global and local search. The first behavior uses sparse sampling of RSSI across the entire environment to move the robot to a location near the tag; the second samples RSSI over orientation to point the robot toward the tag; and the third samples RSSI from two antennas pointing in different directions to enable the robot to approach the tag. We justify our formulation using the radar equation and associated literature. We also demonstrate that it has good performance in practice via tests with a PR2 robot from Willow Garage in a house with a variety of tagged household objects. We present a unique multi-antenna RFID reader (a sensor) embedded in a robot's manipulator that is designed to operate with ordinary UHF RFID tags in a short-range, near-field electromagnetic regime. Using specially designed near-field antennas enables our sensor to obtain spatial information from tags at ranges of less than 1 meter. In this work, we characterize the near-field sensor's ability to detect tagged objects in the robots manipulator, present robot behaviors to determine the identity of a grasped object, and investigate how additional RF signal properties can be used for “pre-touch” capabilities such as servoing to grasp an object. The future combination of long-range (far-field) and short-range (near-field) UHF RFID sensing has the potential to enable roboticists to jump-start applications by obviating or supplementing false-positive-prone visual object recognition. These techniques may be especially useful in the healthcare and service sectors, where mis-identification of an object (for example, a medication bottle) could have catastrophic consequences. In recent years, there has been an increasing interest within the robotics community in investigating whether Radio Frequency Identification (RFID) technology can be utilized to solve localization and mapping problems in the context of mobile robots. We present a novel sensor model which can be utilized for localizing RFID tags and for tracking a mobile agent moving through an RFID-equipped environment. The proposed probabilistic sensor model characterizes the received signal strength indication (RSSI) information as well as the tag detection events to achieve a higher modeling accuracy compared to state-of-the-art models which deal with one of these aspects only. We furthermore propose a method that is able to bootstrap such a sensor model in a fully unsupervised fashion. Real-world experiments demonstrate the effectiveness of our approach also in comparison to existing techniques. Radio Frequency Identification (RFID) technology has been widely used in inventory management in many scenarios, e.g., warehouses, retail stores, hospitals, etc. This paper investigates a challenging problem of complete identification of missing tags in large-scale RFID systems. Although this problem has attracted extensive attention from academy and industry, the existing work can hardly satisfy the stringent real-time requirements. In this paper, a Slot Filter-based Missing Tag Identification (SFMTI) protocol is proposed to reconcile some expected collision slots into singleton slots and filter out the expected empty slots as well as the unreconcilable collision slots, thereby achieving the improved time-efficiency. The theoretical analysis is conducted to minimize the execution time of the proposed SFMTI. We then propose a cost-effective method to extend SFMTI to the multi-reader scenarios. The extensive simulation experiments and performance results demonstrate that the proposed SFMTI protocol outperforms the most promising Iterative ID-free Protocol (IIP) by reducing nearly 45 of the required execution time, and is just within a factor of 1.18 from the lower bound of the minimum execution time. Radio frequency identification (RFID) technologies are poised to revolutionize retail, warehouse, and supply chain management. One of their interesting applications is to automatically detect missing tags in a large storage space, which may have to be performed frequently to catch any missing event such as theft in time. Because RFID systems typically work under low-rate channels, past research has focused on reducing execution time of a detection protocol to prevent excessively long protocol execution from interfering normal inventory operations. However, when active tags are used for a large spatial coverage, energy efficiency becomes critical in prolonging the lifetime of these battery-powered tags. Furthermore, much of the existing literature assumes that the channel between a reader and tags is reliable, which is not always true in reality because of noise interference in the environment. Given these concerns, this paper makes three contributions. First, we propose a novel protocol design that considers both energy efficiency and time efficiency. It achieves multifold reduction in both energy cost and execution time when compared to the best existing work. Second, we reveal a fundamental energy-time tradeoff in missing-tag detection, which can be flexibly controlled through a couple of system parameters in order to achieve desirable performance. Third, we extend our protocol design to consider channel error under two different models. We find that energy time cost will be higher in unreliable channel conditions, but the energy-time tradeoff relation persists. RFID (radio frequency identification) technologies are poised to revolutionize retail, warehouse and supply chain management. One of their interesting applications is to automatically detect missing tags (and the associated objects) in a large storage space. In order to timely catch any missing event such as theft, the detection operation may have to be performed frequently. Because RFID systems typically work under low-rate channels, past research has focused on reducing execution time of a detection protocol, in order to prevent excessively-long protocol execution from interfering normal inventory operations. However, when active tags are used to provide a large spatial coverage, energy efficiency becomes critical in prolonging the lifetime of these battery-powered tags. Existing literature lacks thorough study on how to conserve energy in the process of missing-tag detection and how to jointly optimize energy efficiency and time efficiency. This paper makes two important contributions: First, we propose a novel protocol design that takes both energy efficiency and time efficiency into consideration. It achieves multi-fold reduction in both energy cost and execution time when comparing with the best existing work. In some cases, the reduction is more than an order of magnitude. Second, we reveal a fundamental energy-time tradeoff in missing-tag detection. Through our analytical framework, we are able to flexibly control the tradeoff through a couple of system parameters in order to achieve desirable performance. Reliable and energy-efficient reading of Radio Frequency IDentification (RFID) tags is of utmost importance, especially in mobile and dense tag settings. We identify tag collisions as a main source of inefficiency in terms of wasting both medium access control (MAC) frame slots and reader’s energy. We propose modulation silencing (MS), a reader-tag interaction framework to limit the effect of tag collisions. Utilizing relatively simple circuitry at the tag, MS enhances the performance of existing anti-collision protocols by allowing readers to terminate collision slots once a decoding violation is detected. With shorter collision slots, we revisit the performance metrics and introduce a new generalized time efficiency metric and an optimal frame selection formula that takes into consideration the MS effects. Through analytical solutions and extensive simulations, we show that the use of MS results in significant performance gains under various scenarios. In order to protect privacy, Radio Frequency Identification (RFID) systems employ Privacy-Preserving Authentication (PPA) to allow valid readers to explicitly authenticate their dominated tags without leaking private information. Typically, an RF tag sends an encrypted message to the reader, then the reader searches for the key that can decrypt the cipher to identify the tag. Due to the large-scale deployment of today's RFID systems, the key search scheme for any PPA requires a short response time. Previous designs construct balance-tree based key management structures to accelerate the search speed to O(logN), where N is the number of tags. Being efficient, such approaches are vulnerable to compromising attacks. By capturing a small number of tags, compromising attackers are able to identify other tags that have not been corrupted. To address this issue, we propose an Anti- Compromising authenticaTION protocol, ACTION, which employs a novel sparse tree architecture, such that the key of every tag is independent from one another. The advantages of this design include: 1) resilience to the compromising attack, 2) reduction of key storage for tags from O(logN) to O(1), which is significant for resource critical tag devices, and 3) high search efficiency, which is O(logN), as good as the best in the previous designs. Purpose – Radio frequency identification (RFID) is a technology for tracking objects that is expected to be widely adopted in very near future. A reader device sends probes to a set of RFID tags, which then respond to the request. A tag is recognized only when it is the only one to respond to the probe. Only reader has collision detection capability. The problem considered here is to minimize the number of probes necessary for reading all the tags, assuming that the number of tags is known in advance.Design methodology approach – Well known binary and n‐ary partitioning algorithms can be applied to solve the problem for the case of known number of tags. A new randomized hybrid tag identification protocol has been proposed, which combines the two partitioning algorithms into a more efficient one. The new scheme optimizes the binary partition protocol for small values of n (e.g. n=2, 3, 4). The hybrid scheme then applies n‐ary partition protocol on the whole set, followed by binary partition on the tags tha... A radio frequency identification (RFID) reader recognizes objects through wireless communications with RFID tags. Tag collision arbitration for passive tags is a significant issue for fast tag identification due to communication over a shared wireless channel. This paper presents an adaptive memoryless protocol, which is an improvement on the query tree protocol. Memoryless means that tags need not have additional memory except ID for identification. To reduce collisions and identify tags promptly, we use information obtained from the last process of tag identification at a reader. Our performance evaluation shows that the adaptive memoryless protocol causes fewer collisions and takes shorter delay for recognizing all tags while preserving lower communication overhead than other tree based tag anticollision protocols