There have been some efforts to use general-purpose commercially available UAVs for bridge inspection. The main challenge is that most existing technologies rely on general-purpose UAV platforms and there is no verified methodology for UAV-enabled bridge inspection principles and relevant considerations to reliably obtain inspection data. This project performed preliminary work to support use of Unmanned Aerial Vehicles (UAV)-based for bridge inspections, providing an economical and safer alternative to conventional inspection practices. The effectiveness of the algorithm is illustrated. The experimental results show that the proposed algorithm has a good isolation effect on the high maneuverability of the carrier, which means that the pointing to the communication satellite is more accurate and achieves better communication quality under the high maneuvering state. Finally, the proposed algorithm is verified by experiments. In this paper, we propose a synthetic deviation correction algorithm when the carrier is in the high maneuvering state, the measurement error is converted into the deviation of the azimuth as well as the pitch of the antenna that needs to be corrected to correct the pointing of the SOTM antenna. However, due to the errors of the measurement system, tracking deviation will inevitably occur, especially when the moving carrier is in ahigh maneuvering state, which may cause communication failures. The normal running of the SOTM system requires its antenna beam to track the target communication satellite accurately at all times. Using Satcom-On-The-Move (SOTM) antenna on moving carriers to track communication satellites is a rapidly developing technology. This research would invoke richer dialogue for the researchers and practitioners to select and use suitable drones and develop subsequent policies for different transportation scenarios under uncertainty. The results show that when the physical specification criteria are met, the economic factor is most imperious to the overall performance of the drone, followed by functional performance and technical responsiveness. To evaluate the model further, a number of analyses, such as Bayesian inference algorithm (belief propagation) and sensitivity analyses have been carried out. To that end, we have developed a Bayesian network approach to portray the causal relationships between the various factors that affect drone selection based on their performance, and subsequently, predicted the posterior probability of drone performance conditioned upon the aforementioned salient criteria. In this study, we present a Bayesian Network (BN) approach to predict the overall performance of drone technology through four prime criteria (factors), namely: physical specification, technical responses, functional performance, and economic cost. In this case, we need to scientifically assess and confirm drone performance in logistics and transportation. However, the selection of drones for a particular job is quite sensitive and not all drones are feasible for any job. Remote medical support, commodities transportation within due time, live-action movies, cinematography, distant communication support, and many other provisions are provided by drones right now. The test procedure is validated using two different multicopters.Īpplications of drone technology are gradually becoming widespread all over the world. It experimentally determines nine maneuverability and agility metrics using only on-board flight controller logs. A new test procedure, derived from manned aircraft industry practices and research, based on a simple open-loop step input maneuver, was developed. Nevertheless, some of these are not directly applicable to small-size unmanned aircraft. Numerous maneuverability and agility metrics, together with detailed test procedures and minimum requirements, exist for manned aircraft. However, currently no published research determines objectively, quantitatively, and experimentally, the maneuverability and agility of multicopters. The main advantages of a multicopter are its compactness, robustness, and low cost to build and repair. They are a type of helicopter with three or more, usually fixed-pitch, propellers that lift and control the platform by individually changing their rotational velocities. Multicopters are the most popular rotary type of unmanned aerial vehicles.
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