Convex optimization for proximity maneuvering of a spacecraft with a robotic manipulator

Abstract

This paper presents a convex optimization-based guidance algorithm for maneuvering a spacecraft equipped with a robotic manipulator. A local solution to the original optimization problem is found by solving a collection of simpler convex programming problems. Given the deterministic convergence properties of convex programming, the proposed algorithm can be implemented onboard a spacecraft and used for real-time applications. To reduce the complexity of the original optimization problem, we first divide the maneuver into two simultaneously occurring sub-maneuvers: a system-wide translation and an internal re-configuration. These two sub-maneuvers are individually optimized using a sequential convex optimization approach to overcome the presence of non-convex inequality and nonlinear equality constraints. The paradigmatic example of capturing a tumbling object is used throughout the paper to illustrate the use of the proposed optimization approach. Additionally, a new explicitly convex formulation of a line-of-sight constraint is introduced.