Monocular inspection of spacecraft under illumination constraints and avoidance regions

This paper presents an adaptive control approach to information-based guidance and control of a spacecraft carrying out on-orbit inspection by actively computing optimal policies for the spacecraft to achieve the best possible representation of objects within its orbital environment. Due to the complexity of navigating the space environment, it may be impossible to carry out on-orbit servicing to maintain space systems like satellites using a spacecraft equipped with controllers that cannot adapt to changing conditions. In particular, the presence of constraints such as illumination, field-of-view (FOV), minimal fuel, the use of visual-inertial navigation for improved localization, and the need for real-time computation of control policies render the spacecraft motion planning problem challenging. The control framework developed in this paper addresses these challenges by formulating the inspection task as a constrained optimization problem where the goal is to maximize information gained from the cameras, while navigating to the next best view, subject to illumination and FOV constraints. The developed architecture is analyzed using a Lyapunov-based stability analysis and the effectiveness of the planning algorithm is verified in simulation.