A Framework for Analyzing Fog-Cloud Computing Cooperation Applied to Information Processing of UAVs

Unmanned aerial vehicles (UAVs) are a relatively new technology. Their application can often involve complex and unseen problems. For instance, they can work in a cooperative-based environment under the supervision of a ground station to speed up critical decision-making processes. However, the amount of information exchanged among the aircraft and ground station is limited by high distances, low bandwidth size, restricted processing capability, and energy constraints. These drawbacks restrain large-scale operations such as large area inspections. New distributed state-of-the-art processing architectures, such as fog computing, can improve latency, scalability, and efficiency to meet time constraints via data acquisition, processing, and storage at different levels. Under these amendments, this research work proposes a mathematical model to analyze distribution-based UAVs topologies and a fog-cloud computing framework for large-scale mission and search operations. The tests have successfully predicted latency and other operational constraints, allowing the analysis of fog-computing advantages over traditional cloud-computing architectures.Comment: Volume 2019, Article ID 7497924, 14 page

Heterogeneous Multi-Robot Collaboration for Coverage Path Planning in Partially Known Dynamic Environments

This research presents a cooperation strategy for a heterogeneous group of robots that comprises two Unmanned Aerial Vehicles (UAVs) and one Unmanned Ground Vehicles (UGVs) to perform tasks in dynamic scenarios. This paper defines specific roles for the UAVs and UGV within the framework to address challenges like partially known terrains and dynamic obstacles. The UAVs are focused on aerial inspections and mapping, while UGV conducts ground-level inspections. In addition, the UAVs can return and land at the UGV base, in case of a low battery level, to perform hot swapping so as not to interrupt the inspection process. This research mainly emphasizes developing a robust Coverage Path Planning (CPP) algorithm that dynamically adapts paths to avoid collisions and ensure efficient coverage. The Wavefront algorithm was selected for the two-dimensional offline CPP. All robots must follow a predefined path generated by the offline CPP. The study also integrates advanced technologies like Neural Networks (NN) and Deep Reinforcement Learning (DRL) for adaptive path planning for both robots to enable real-time responses to dynamic obstacles. Extensive simulations using a Robot Operating System (ROS) and Gazebo platforms were conducted to validate the approach considering specific real-world situations, that is, an electrical substation, in order to demonstrate its functionality in addressing challenges in dynamic environments and advancing the field of autonomous robots.The authors also would like to thank their home Institute, CEFET/RJ, the federal Brazilian research agencies CAPES (code 001) and CNPq, and the Rio de Janeiro research agency, FAPERJ, for supporting this work.info:eu-repo/semantics/publishedVersio

Sensors Fusion and Multidimensional Point Cloud Analysis for Electrical Power System Inspection

Thermal inspection is a powerful tool that enables the diagnosis of several components at its early stages. One critical aspect that influences thermal inspection outputs is the infrared reflection from external sources. This situation may change the readings, demanding that an expert correctly define the camera position, which is a time consuming and expensive operation. To mitigate this problem, this work proposes an autonomous system capable of identifying infrared reflections by filtering and fusing data obtained from both stereo and thermal cameras. The process starts by acquiring readings from multiples Observation Points (OPs) where, at each OP, the system processes the 3D point cloud and thermal image by fusing them together. The result is a dense point cloud where each point has its spatial position and temperature. Considering that each point’s information is acquired from multiple poses, it is possible to generate a temperature profile of each spatial point and filter undesirable readings caused by interference and other phenomena. To deploy and test this approach, a Directional Robotic System (DRS) is mounted over a traditional human-operated service vehicle. In that way, the DRS autonomously tracks and inspects any desirable equipment as the service vehicle passes them by. To demonstrate the results, this work presents the algorithm workflow, a proof of concept, and a real application result, showing improved performance in real-life conditions

An edge–fog architecture for distributed 3D reconstruction

Nowadays, numerous facilities that provide essential services operate with little or even no human supervision. In this context, electrical power substations can be entirely autonomous or remotely operated, and may be difficult to access. This scenario increases the need of remote monitoring for predictive maintenance and problem analysis by using imaging and 3D reconstruction of the environment. 3D reconstruction processes are concentrated in academic and commercial applications, but they are non scalable and fail to provide remote real time data analysis. This research proposes a novel color 3D scanner architecture environment for remote real time multiple sensor processing and reconstruction. The goal is to present a more efficient system based upon scalability and low latency applications, where multiple sensors can be added without losing the overall processing capability. For this purpose, this study approaches this problem in two ways. First, it improves 3D reconstruction algorithms by enhancing individual performance. Second, to optimize the entire system, it distributes the running processes in individual layers, interconnected by an edge–fog architecture. This architecture enables the use of multiple devices by optimizing payload distribution, latency, and throughput in the network. Unlike previous studies, the results present a thorough analysis of architecture efficiency when multiple sensors are operating in parallel instead of the traditional centralized architecture. Finally, this work provides the basis for real-time remote presence applications. •A new approach of distributed sensor fusion.•An Edge–Fog Architecture for 3D reconstruction.•Very Fast and Reliable.•Tested in real cases.•Applied in electrical power stations remote supervision

Photogrammetric Process to Monitor Stress Fields Inside Structural Systems

This research employs displacement fields photogrammetrically captured on the surface of a solid or structure to estimate real-time stress distributions it undergoes during a given loading period. The displacement fields are determined based on a series of images taken from the solid surface while it experiences deformation. Image displacements are used to estimate the deformations in the plane of the beam surface, and Poisson’s Method is subsequently applied to reconstruct these surfaces, at a given time, by extracting triangular meshes from the corresponding points clouds. With the aid of the measured displacement fields, the Boundary Element Method (BEM) is considered to evaluate stress values throughout the solid. Herein, the unknown boundary forces must be additionally calculated. As the photogrammetrically reconstructed deformed surfaces may be defined by several million points, the boundary displacement values of boundary-element models having a convenient number of nodes are determined based on an optimized displacement surface that best fits the real measured data. The results showed the effectiveness and potential application of the proposed methodology in several tasks to determine real-time stress distributions in structures

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

Different practical applications have emerged in the last few years, requiring periodic and detailed inspections to verify possible structural changes. Inspections using Unmanned Aerial Vehicles (UAVs) should minimize flight time due to battery time restrictions and identify the terrain’s topographic features. In this sense, Coverage Path Planning (CPP) aims at finding the best path to coverage of a determined area respecting the operation’s restrictions. Photometric information from the terrain is used to create routes or even refine paths already created. Therefore, this research’s main contribution is developing a methodology that uses a metaheuristic algorithm based on point cloud data to inspect slope and dams structures. The technique was applied in a simulated and real scenario to verify its effectiveness. The results showed an increasing 3D reconstructions’ quality observing optimizing photometric and mission time criteria

Design of an Over-Actuated Hexacopter Tilt-Rotor for Landing and Coupling in Power Transmission Lines

It is known that new power transmission line inspection techniques have been developed over the last few years with great potential to improve and, in some cases, even replace traditional inspection procedures such as using helicopters and cars. A series of Unmanned Aerial Vehicles (UAVs) such as fixed-wing or rotary-wing UAVs, and vehicles that climb on the power transmission line, promise to revolutionize the inspection market. In this light, at least 39 new research studies and/or products have been conducted and/or introduced to the market, respectively. However, in an incipient way, some works point to the fusion of some technologies: the development of multi-rotor UAVs and the ability to connect and move over the power transmission line. In line with this, the current work was proposed, with significant unprecedented advances (such as an over-actuated control capacity with tilt rotors, the capability of a displacement in the angle, and the maintenance of active motors on the power transmission line), and the design, modeling, and control of an over-actuated UAV able to move over the conductor cable without the need for a new locomotion system is presented. The aircraft allows for a greater response and the indispensable ability to approximate landing in a power transmission line arbitrary position rather than the catenary lowest point (due to its ability to forward/backward move using the tilting rotors). Its design is detailed, its subsystems are described, and its normal and coupled flight mode dynamics are modeled. The results show good stability and reliable maneuvers for the coupling-to-power-transmission-line flight mode, without any overshoots, and the ability to follow the entire catenary through different Real Control Action (RCA) sets

Thrombocytopenia After Transcatheter Valve-in-Valve Implantation: Prognostic Marker or Mere Finding?

Abstract Objective: To analyze the behavior of platelets after transcatheter valve-in-valve implantation for the treatment of degenerated bioprosthesis and how they correlate with adverse events upon follow-up. Methods: Retrospective analysis of 28 patients who received a valve-in-valve implant, 5 in aortic, 18 in mitral and 5 in tricuspid positions. Data were compared with 74 patients submitted to conventional redo valvular replacements during the same period, and both groups' platelet curves were analyzed. Statistical analysis was conducted using the IBM SPSS Statistics(r) 20 for Windows. Results: All patients in the valve-in-valve group developed thrombocytopenia, 25% presenting mild (50%. Conclusion: Although thrombocytopenia is an extremely common finding after valve-in-valve procedures, the degree of platelet count drop did not correlate with greater incidence of postoperative adverse outcomes in our study population