Akademik Veri Yönetim Sistemi
12th International Conference on Mechanical and Aerospace Engineering (ICMAE), ELECTR NETWORK, 16 - 19 Temmuz 2021, ss.365-372
In this work we present the design and development process of an avionics architecture for missions that require highly coordinated flight of a fleet of autonomous fixed-wing micro UAVs. Applications such as signal tracking or dynamic object tracking with multiple UAVs allow a cost-effective and minimum-risk alternative to missions which have been historically handled with manned aircraft. As such, for these specific applications, we have developed a micro-avionics architecture structured around an in-house customized open-source autopilot and an indigenous Linux based single board payload/flight management computer. The essential 5-km range telemetry and control link radio is backed up by high-power long-range IEEE 802.11n (WiFi) radio device. The redundancy of communication not only improves the reliability of the avionics architecture, but also enables the trade-off between bandwidth and power efficiency. The architecture is capable of transmitting data at rates above 200 kbps up to 4 km away from its ground station equipped with the developed miniature patch antenna tracker. The payload/flight management computer is ready to run a CSI/USB connected daylight or low-illumination infra-red camera, a USB connected software defined radio and different types of sensor payloads such as radar/lidar range sensors and RGBD cameras. Tied to this architecture, we have designed a Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) testing system with MAVlink communication protocol interlinking hardware to Matlab based UAV dynamic models and tracking algorithms. This system allows comprehensive simulation and testing of designed control and guidance algorithms before flight tests while minimizing cost and crash risk. We have successfully used the avionics architecture in flight tests that involve (a) system identification of flight vehicles and (b) tracking and identification of signal sources using multiple UAVs.