RFID Gazebo-Based Simulator With RSSI and Phase Signals for UHF Tags Localization and Tracking

Radio Frequency Identification (RFID) technology is becoming very popular in the new era of Industry 4.0, especially for warehouse management, retails, and logistics. RFID systems can be used for objects identification, localization, and tracking, facilitating everyday operators' efforts. However, the deployment of RFID tags and reader antennas in real-world application scenarios is crucial and takes time. Indeed, deciding where to place tags and/or readers' requires examining many conditions. If some weaknesses appear in the design, the arrangement must be reconsidered. The proposed work presents a novel open-source RFID simulator that allows modeling environments and testing the deployment of RFID tags and antennas apriori. In such a way, validating the performance of the localization or tracking algorithms in simulation, possible weaknesses that could arise may be fixed before facilities are applied on the field. Any number of tags and antennas can be placed in any position in the created scenario, and the simulator provides the phase and the RSSI signals for each tag. Every reader antenna is parametrized so that different antennas of different vendors can be reproduced. The simulator is implemented as a plugin of Gazebo, a widely used robotic framework integrated with the Robot Operating System (ROS), to reach a broad audience. In order to validate the simulator, a warehouse scenario is modeled, and a tag localization algorithm that uses the phase unwrapping technique and hyperbolae intersection method employing a reader antenna mounted on a mobile robot is used to estimate the position of the tags deployed in the scenario. The outcomes of the experiments showed realistic results

Smooth Coverage Path Planning for UAVs with Model Predictive Control Trajectory Tracking

Within the Industry 4.0 ecosystem, Inspection Robotics is one fundamental technology to speed up monitoring processes and obtain good accuracy and performance of the inspections while avoiding possible safety issues for human personnel. This manuscript investigates the robotics inspection of areas and surfaces employing Unmanned Aerial Vehicles (UAVs). The contribution starts by addressing the problem of coverage path planning and proposes a smoothing approach intended to reduce both flight time and memory consumption to store the target navigation path. Evaluation tests are conducted on a quadrotor equipped with a Model Predictive Control (MPC) policy and a Simultaneous Localization and Mapping (SLAM) algorithm to localize the UAV in the environment

Efficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags

The Fourth Industrial Revolution, or Industry 4.0, aims at automating traditional manufacturing and industrial practices using modern smart technology. Autonomous mobile robots equipped with different sensors and employing different techniques have been proposed in the literature in the logistics and inventory warehouse management contexts. Efficient robot motion and planning depend on precise localization, mapping, and awareness of the environment. To properly localize items, recent attempts have been made employing radio frequency identification (RFID) in a 3D environment. This manuscript introduces four least mean squares methods to estimate the 3D positions of tags employing synthetic apertures and phase unwrapping. The proposed methods approach the localization problem solving a system of equations typical of multilateration methods to find the intersections of multiple hyperboloids. The novelty introduced here is the use of unwrapped phase distances to compute pseudo ranges for the multilateration problem. The use of such a technique is feasible thanks to precise mobile robot localization and custom navigation policies. All the analyzed methods are suitable for online localization due to reduced computation timings and have been tested on three different datasets. Two of them contain virtual data that has been generated by simulation, while the other one comes from an indoor experimental setup. Simulated tests show that combined antenna motions in 3D space (including Z-axis) improve the localization obtaining errors under the centimeter for 3D localization. Experimental tests obtained results as low as 13 cm of mean accuracy for 3D localization and 0.21 cm for 2D localization

A multi-antenna sar-based method for UHF RFID tag localization via UGV

This paper presents a multi-antenna approach of the phase-based SARFID method to locate static tags by employing two UHF-RFID reader antennas installed on an Unmanned Grounded Vehicle (UGV). The UGV is remotecontrolled and equipped with Laser Range Finder sensors to move inside an indoor environment, and the knowledge of its trajectory is achieved through a Simultaneous Localization And Mapping procedure. By processing the phase data collected from each reader antenna, different matching functions can be obtained and combined to improve the estimation of the bidimensional tag position. Differently from other localization techniques, neither reference tags (anchor tags), nor large phased array antennas are required

RFID Tag Localization with UGV in Retail Applications

This paper presents the application of the phase-based SARFID technique to locate static tags through an Unmanned Grounded Vehicle (UGV) equipped with a UHF-RFID reader. The UGV is remote-controlled to move inside an indoor environment and the knowledge of its trajectory is achieved through a Simultaneous Localization And Mapping (SLAM) procedure. The bi-dimensional tag position can be estimated with a location error in the order of few centimetres if the phase samples are collected in a proper spatial interval. Differently from other localization techniques, neither reference tags (anchor tags), nor large phased array antennas are required

A Lightweight SLAM algorithm for indoor autonomous navigation

Simultaneous Localization and Mapping (SLAM) algorithms require huge computational power. Most of the state-of-the-art implementations employ dedicated computational machines which in most cases are off-board the robotic platform. In addition, as soon as the environment become large, the update rate of such algorithms is no more suitable for real-time control. The latest implementations rely on visual SLAM, adopting a reduced number of features. However, these methods are not employable in environments with low visibility or that are completely dark. We present here a SLAM algorithm designed for mobile robots requiring reliable solutions even in harsh working conditions where the presence of dust and darkness could compromise the visibility conditions. The algorithm has been optimized for embedded CPUs commonly employed in light-weight robotic platforms. In this paper the proposed algorithm is introduced and its feasibility as SLAM solution for embedded systems is proved both by a simulated and a real testing scenario

RFID Tag Localization with UGV in Retail Applications

This paper presents the application of the phase-based SARFID technique to locate static tags through an Unmanned Grounded Vehicle (UGV) equipped with a UHF-RFID reader. The UGV is remote-controlled to move inside an indoor environment and the knowledge of its trajectory is achieved through a Simultaneous Localization And Mapping (SLAM) procedure. The bi-dimensional tag position can be estimated with a location error in the order of few centimetres if the phase samples are collected in a proper spatial interval. Differently from other localization techniques, neither reference tags (anchor tags), nor large phased array antennas are required

Particle swarm optimization in multi-antenna SAR-based localization for UHF-RFID tags

This paper presents the application of the Particle Swarm Optimization (PSO) in synthetic aperture radar (SAR) methods exploiting multiple antennas for UHF-RFID tag localization. To perform 3D tag positioning, a robot equipped with two reader antennas is moving in the indoor scenario. The applicability of the PSO approach in SAR-based localization is discussed through a numerical analysis and an experimental campaign. A centimeter order localization error is achieved for 3D tag localization with a reduced computational cost with respect to classical SAR-based methods

Towards a Multi-Antenna approach for UHF-RFID tag 3D localization with a Synthetic Aperture Radar Method

This paper proposes a multi-Antenna approach of a synthetic aperture radar method for 3D UHF-RFID tag localization by exploiting an Unmanned Grounded Vehicle (UGV). The UGV is remote-controlled to move inside a complex indoor environment, and the knowledge of the reader antenna trajectories is achieved with millimeter accuracy through a commercial motion tracking system. By processing the tag backscattered signal phase data collected from two RFID reader antennas, coherent and non-coherent combining processing are performed to improve the estimation of the 3D tag position with respect to the case of a single antenna. Differently from other localization techniques, neither reference tags (anchor tags), nor large phased array antennas are required

A Synthetic Aperture UHF RFID Localization Method by Phase Unwrapping and Hyperbolic Intersection

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