Machine learning techniques can be effectively leveraged to improve the accuracy of orbit estimation and atmospheric density modeling, which are critical for enhancing space safety and mitigating the risks of collisions between space objects.
Automated localization of astronaut photography using image retrieval is efficient and accurate.
Proposing an extensible hook system for cubesat swarms to enhance cooperation and save fuel.
提案された非特異高速端面滑りモードに基づく適応スムーズ制御法は、分散型宇宙望遠鏡デモンストレーションミッションの効率を向上させる。
Developing a novel MSS-OTALG guidance law for precision soft landing in hazardous terrain with low fuel consumption and robustness.
提案された画像検索を活用した新しいアプローチ、EarthLocは、宇宙からの写真の地理的位置を効率的に特定します。
MPC is effective for safe rendezvous with non-cooperative tumbling targets in space missions.
The author presents an Online Supervised Training method to bridge the domain gap in spaceborne neural networks for spacecraft navigation during Rendezvous and Proximity Operations.
The author presents a hybrid dynamical system approach for impulsive control in spacecraft rendezvous, focusing on separating out-of-plane and in-plane dynamics with tailored feedback control laws.
The authors introduce dSGP4, a differentiable version of the SGP4 model, enabling precise computations and integration with machine learning algorithms to enhance orbital predictions.