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.

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