This repository contains the implementation and resources used in the doctoral thesis titled "Spatio-Temporal Formation of Unmanned Aerial Vehicles", authored by Davi Juvêncio Gomes de Sousa. The thesis proposes the Hierarchical Vision-Based Formation Control (HVFC) method, which uses a monocular camera as the sole sensor for controlling UAV formations. The method is scalable, eliminates the need for direct communication between drones, and enables the formation of predefined geometric patterns.
The HVFC method extracts relative information from monocular vision to dynamically adjust the position and orientation of UAVs. This approach eliminates the need for global data or external communication while ensuring scalability for formations with multiple drones. The repository includes the tools and files used for both simulation and real-world experiments validating the HVFC.
Stay tuned for more updates as the repository is populated with all necessary data and documentation.
Repository Link: DaviJuvencio-VisionFormation-Thesis