Lander.AIは風の影響を受ける状況で高精度な着陸を実現し、ドローンの自律性と安全性を向上させる。
Autonomous drone system using visual-inertial sensors for under-canopy navigation in forests.
The author introduces Lander.AI, an advanced Deep Reinforcement Learning agent designed to enhance drone autonomy and safety during dynamic platform landings. The approach leverages bio-inspired learning to adapt to external forces like wind, showcasing significant improvements in landing precision and error recovery.
The author presents a fully autonomous drone system capable of recharging near powerlines, enabling extended operational endurance through continuous flight cycles.
The author proposes a method for autonomous precision drone landing using fiducial markers and a multi-payload camera, minimizing data requirements and achieving successful landings from longer distances.