![]() Comput Electr Eng 74:184–195ĭ’Urso F, Santoro C, Santoro FF (2019) An integrated framework for the realistic simulation of multi-UAV applications. Springer, Cham, pp 155−183ĭ’Souza JM, Guruprasad KR, Padman A (2019) A realistic simulation platform for multi-quadcopter search using downward facing cameras. Ros-based approach for unmanned vehicles in civil applications. The AFC agent detects and identifies all the assigned objects with a recall score of 1.00, a precision score of 0.9563, an accuracy score of 0.9573, an F1 score of 0.9776, an efficiency score of 0.5239, a detection total time score of 225.5 s, and an identification total time of 275 s and outperforms a human operator.Īl-Kaff A, Moreno FM, Hussein A (2019). We conduct tests on the AFC agent, and the results show that the agent successfully controls the UAV in three performed test cases and a total of nine implemented missions. It captures the video images acquired from a solitary onboard, front-facing camera which are handled off-board on a computer. The agent implements several image handling algorithms to detect and identify objects from their colors and shapes. The AFC agent performs search and survey missions that entail commanding the UAV while performing object classifications and recognition tasks. We design the AFC agent architecture to consist of data acquisition, perception, localization, mapping, control, and planning modules. The specific problem of this research is the indoor environment because of the perplexing characteristics of the required flight mechanics. ![]() Consequently, this research addresses the general problem of designing an agent-based autonomous flight control (AFC) architecture of a UAV to facilitate autonomous routing/navigation in uncharted and unascertained environments of organized foyer surroundings. several airframes were tested for optimizing and adapting for different operational scenarios.One of the major challenges in designing an autonomous agent system is to achieve the objective of recreating human-like cognition by exploiting the growing pragmatic architectures that act intelligently and intuitively in vital fields. The flight tests of the entire system are carried out in different flight configurations, i.e. The Futaba SBUS.2 is used for communication between sensors, actuators and autopilot. In order to maximum flexibility in the application all control electronics are designed as expandable systems of hardware modules. For safety reasons each hardware node has its own CPU. The hardware based on the ARM Cortex M4 architecture. ![]() ![]() The most important sensors will be introduced. Therefore, essential part of the project are the necessary hardware design of the control electronics and the connected sensor subsystems. ![]() The mathematical basics were analysed and transfered into a closed software system supported by Matlab/Simulink and by practical flight tests. Based on a theoretical model, a flight control system (autopilot) is designed for an UAV. ![]()
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