Alice Buffi

This article presents the in vivo validation of an inductive wireless power transfer (WPT) system integrated for the first time into a magnetically controlled robotic capsule endoscopy platform. The proposed system enables continuous power delivery to the capsule without the need for onboard batteries, thus extending operational time and reducing size constraints. The WPT system operates through a resonant inductive coupling mechanism, based on a transmitting (Tx) coil mounted on the end-effector of a robotic arm that also houses an external permanent magnet (EPM) and a localization coil for precise capsule manipulation. To ensure robust and stable power transmission in the presence of coil shift, misalignment, or rotation, a 3-D receiving (Rx) coil and a closed-loop adaptive control system are implemented. The system has been extensively characterized in laboratory settings and validated through in vivo experiments using a porcine model, demonstrating reliable power transfer and effective robotic navigation in realistic gastrointestinal conditions: the average received power was 110 mW at a distance of 9 cm between the coils, with variable capsule rotation angles. The results confirm the feasibility of the proposed WPT approach for autonomous, battery-free robotic capsule endoscopy, paving the way for enhanced diagnostic in gastrointestinal medicine.

In this paper we present a method for UHF-RFID tag localization via phase measurements gathered during a circular trajectory of the reader antenna, i.e., ORBITER . The localization is pursued by exploiting both the minimum and the variability of the unwrapped phase curve via appropriate mathematical operators. We investigate the sensitivity of the method, by highlighting the conditions for its applicability and the proper choise of the measurement parameters. For the experimental validation, we use a 3D Cartesian portal for antenna motion along circular trajectories, which allows us to assess performance and reliability of the method in a controlled environment. Results show that the proposed method achieves good accuracy and robustness in localizing UHF-RFID passive tags. The method finds applications in both indoor and outdoor scenarios.

This paper presents the development and testing of a robot designed for automated inventory and 3D localization of items in high-density shelving systems. To enhance accuracy in locating UHF-RFID tagged objects by using synthetic aperture-based methods, rotating antennas are installed on the robot. This allows more degrees of freedom in antenna trajectory, by reaching large synthetic apertures that may deliver high-performance localization. The robot can navigate complex environments by utilizing a depth camera and a visual odometry system, and it can effectively avoid obstacles with the help of a Laser Imaging Detection And Ranging system. Extensive testing is conducted in a realistic shop-like scenario where tagged products are placed on either wooden shelves or hung on metal racks. The robot navigation capabilities are verified together with its inventory and localization performance for different visibility conditions of the tagged items.

The IEEE Journal of Radio Frequency Identification (JRFID) has the pleasure to host a joint Special Issue collecting extended versions of papers coming from two international conferences held in 2022. The first is the IEEE International Conference on RFID-Technology and Applications (RFID-TA) , held in Cagliari, Italy, on September 12-14, 2022. The second is the International Symposium on Advances in RFID Technology and Electromagnetics for IoT organized within the International Conference on Smart and Sustainable Technologies ( SpliTech ), hosted in Split and Bol, Croatia, on July 5-8, 2022. SpliTech was technically co-sponsored by the IEEE Council on RFID (CRFID).

This year, the IEEE Journal of Radio Frequency Identification (JRFID), decided to host a joint Special Issue collecting extended versions of papers coming from two international events. The former is the IEEE International Conference on RFID Technology and Applications (RFID-TA) 2021, virtually held in Delhi, India, on October 6-8, 2021. The latter is the International Symposium on Advances in RFID Technology organized within the International Conference on Smart and Sustainable Technologies (SpliTech), hosted in Split and Bol, Croatia, on September 8-11, 2021. SpliTech was technically co-sponsored by the IEEE and technically media sponsored by the IEEE Council on RFID (CRFID).

This paper describes a UHF-RFID robotic system for tagged-item inventory and localization. A mobile robot is equipped with wheeled rotary encoders and a UHF-RFID reader connected to multiple antennas. At first, the robot reconstructs its trajectory by exploiting a sensor-fusion method combining odometry data with phase data gathered by on-board antennas from an infrastructure of passive reference tags. Then, it leverages its reconstructed trajectory to localize target tags placed at unknown locations through a multi-antenna synthetic-aperture-radar (SAR) approach. A Particle Swarm Optimization is applied to speed up the position estimation. An experimental campaign conducted in an office environment is presented to verify the system features and feasibility. The performance of the proposed method for both tag localization and robot self-localization is compared with respect to the case of trajectories reconstructed only by odometry data or through a commercial Laser Range Finder mounted on the robot. Particularly, the effect of the cumulated drift of the estimated trajectory on the tag localization performance is investigated.

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety.

This article addresses the problem of determining the location of pallets carried by forklifts inside a warehouse, which are recognized thanks to an onboard Radio Frequency IDentification (RFID) system at the ultra-high-frequency (UHF) band. By reconstructing the forklift trajectory and orientation, the location of the pallets can be associated with the forklift position at the time of unloading events. The localization task is accomplished by means of an easy-to-deploy combination of onboard sensors, i.e., an inertial measurement unit (IMU) and an optical flow sensor (OFS), with a commercial ultra-wideband (UWB) system through an Unscented Kalman Filter (UKF) algorithm, which estimates the forklift pose over time. The proposed sensor fusion approach contributes to the localization error mitigation by preventing drifts in the trajectory reconstruction. The designed methos was at first evaluated by means of a simulation framework and then through an experimental analysis conducted in a large warehouse with a size of about 4000 m².

The I-READ 4.0 project is aimed at developing an integrated and autonomous Cyber-Physical System for automatic management of very large warehouses with a high-stock rotation index. Thanks to a network of Radio Frequency Identification (RFID) readers operating in the Ultra-High-Frequency (UHF) band, both fixed and mobile, it is possible to implement an efficient management of assets and forklifts operating in an indoor scenario. A key component to accomplish this goal is the UHF-RFID Smart Gate, which consists of a checkpoint infrastructure based on RFID technology to identify forklifts and their direction of transit. This paper presents the implementation of a UHF-RFID Smart Gate with a single reader antenna with asymmetrical deployment, thus allowing the correct action classification with reduced infrastructure complexity and cost. The action classification method exploits the signal phase backscattered by RFID tags placed on the forklifts. The performance and the method capabilities are demonstrated through an on-site demonstrator in a real warehouse.

The use of radio frequency identification (RFID) technology for the traceability of products throughout the production chain, warehouse management, and the retail network is spreading in the last years, especially in those industries in line with the concept of Industry 4.0. The last decade has seen the development of increasingly precise and high-performance methods for the localization of goods. This work proposes a reliable 2-D localization methodology that is faster and provides a competitive accuracy, concerning the state-of-the-art techniques. The proposed method leverages a phase-distance model and exploits the synthetic aperture approach and unwrapping techniques for facing phase ambiguity and multipath phenomena. Trilateration applied on consecutive phase readings allows finding hyperbolae as the localization solution space. Analytic calculus is used to compute intersections among the conics that estimate the tag position. An algorithm computes intersections quality to select the best estimation. Experimental tests are conducted to assess the quality of the proposed strategy. A mobile robot equipped with a reader antenna localizes in 2-D the tags placed in an indoor scenario and reconstructs the map of the environment through a simultaneous localization and mapping (SLAM) algorithm. Note to Practitioners —A localization technology based on passive ultrahigh-frequency (UHF) radio frequency identification (RFID) is an enabling technology for intelligent warehouses, logistics, and retails. For this reason, this work presents a novel method to estimate the tag location with high accuracy. A reader antenna is mounted on an autonomous mobile robot that can move in an indoor or outdoor environment due to a simultaneous localization and mapping (SLAM) algorithm. The motion of the antenna generates a synthetic aperture. The system receives the phase measurements from the RFID tags and generates a distance model through phase unwrapping. In such a way, the possible locations of the tags in the environment are generated, creating conics. The trilateration step is performed analytically, intersecting the obtained conics. The resulting estimations are very accurate and not computation expensive. Therefore, the proposed approach can be employed in any application where localizing objects is fundamental even when reduced computational power is available, e.g., in warehouses where the products are at known heights, or where the items are placed on a fixed infrastructure, such as high-shelves logistics, to produce the inventory of the tagged objects within each shelf.