Autonomous Vision-Based Control for Spacecraft Navigation Around an Asteroid

Deep space exploration missions face significant environmental uncertainties, while navigation and guidance systems suffer from high latency due to their dependence on ground-based infrastructure. Therefore, the development of autonomous deep space exploration technologies is crucial for advancing future missions. Building on this foundation, this paper focuses on vision-based hovering control in close proximity to an asteroid within deep space environments. We begin by constructing an image dynamics model based on the image Jacobian matrix of feature points, followed by a controllability analysis using the controllability matrix. Subsequently, an image-based extended Kalman filter is developed to estimate the lander's current velocity state. Leveraging this foundation, a 6-DOF controller is designed using the backstepping method, enabling autonomous, fixed-point hovering in close proximity to an asteroid. Finally, the effectiveness and superiority of the proposed method are validated through simulations and comparative analysis.