AI Applications in Diverse Fields for Aerospace Development

Résumé : The challenges of aerospace development are driving innovation in AI across diverse fields. Automatic decision-making is crucial not just for aerospace systems themselves, but also for their seamless interaction with human operators. AI should even anticipate and directly provide the resources they’ll need, like plant growth systems for long-duration space missions. This presentation explores the use of various AI techniques, including supervised and unsupervised learning, as well as reinforcement learning and planning. We’ll see how these tools can be applied in pure aerospace tasks (like vision-based runway detection), human-computer interaction (e.g. brain-computer interfaces), and even precision agriculture (e.g. plant growth monitoring). By examining such diverse applications through the lens of different AI tools, we can identify promising new avenues for future research.