Small unmanned aircraft, such as gliders and fixed-wing drones, are limited by battery capacity and flight time. In nature, birds and glider pilots extend their range by exploiting atmospheric energy sources such as thermal updrafts and wind gradients. For autonomous aircraft, detecting and using these energy sources requires real-time decision-making under uncertainty.<\/p>\n\n\n\n
Led by Aamir Ahmad at the University of Stuttgart\u2019s Institute of Flight Mechanics and Flight Control, the project \u201cDecision Making for Environmental Energy Exploitation with Small Aircraft\u201d<\/strong> (2021\u20132025) investigated how small aircraft can autonomously detect and exploit atmospheric energy to extend endurance. <\/p>\n\n\n\n The project addresses a key limitation of small autonomous aircraft: limited flight time due to battery constraints. By enabling aircraft to harvest energy from the environment, it can significantly extend mission duration for applications such as environmental monitoring, wildlife observation, and surveillance. The methods also contribute to broader questions in decision-making under uncertainty, showing how learning-based approaches can be combined with classical control to produce robust, energy-aware autonomy. <\/p>\n\n\n\nKey results<\/h2>\n\n\n\n
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Why it matters<\/h2>\n\n\n\n
This project produced the following peer-reviewed publications:<\/h2>\n\n\n\n
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