The primary objective of this project is to study navigation and coordinated control techniques for autonomous unmanned vehicles that may exhibit different characteristics (heterogeneous formations). This can be due to operating in various domains (e.g., aerial or aquatic vehicles) or varying characteristics and/or capabilities such as vehicle size, energy autonomy, instrumentation, and equipped sensors.
The use of robot formations, particularly Surface Autonomous Surface Vehicles (ASVs) and Unmanned Aerial Vehicles (UAVs), has proven to be beneficial for various tasks. For instance, they are useful for environmental monitoring or simultaneous image acquisition from different perspectives.
Our objective is to design a fully autonomous small-scale drone capable of vertical takeoff and following predefined missions. These missions include navigation based on waypoints or loitering. Autonomous landing is a critical component of the mission.
We are addressing this significant challenge through the automatic visual detection of a landing pad using machine learning and computer vision techniques.
Among our areas of interest are applications such as public area monitoring and humanitarian cargo delivery in restricted access zones.
One of the valuable platforms to address these issues is a "Transition eVTOL" vehicle configuration, which we are designing within our research group.
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