Onboard Deep Reinforcement Learning: Deployment and Testing for CubeSat Attitude Control

Recent progress in Reinforcement Learning (RL), especially deep RL, has created new possibilities for autonomous control in complex and uncertain environments. This study explores these possibilities through a practical approach, implementing an RL agent on a custom-built CubeSat. The CubeSat, equip...

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Autors principals:	Sajjad Zahedi, Jafar Roshanian, Mehran Mirshams, Krasin Georgiev
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-01-01
Col·lecció:	Engineering Proceedings
Matèries:	CubeSat reinforcement learning Intelligent Control hardware-in-loop
Accés en línia:	https://www.mdpi.com/2673-4591/121/1/26
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