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Abstract This paper presents a receding horizon implementation of sequential convex programming for the spacecraft six-degree-of-freedom close proximity to a non-cooperative target satellite. With linearized relative translational dynamics and newly derived discrete rotational equations in terms of modified Rodrigues parameters, nonlinear system dynamics of the original optimal guidance and control problem for proximity are converted into convex ones for sequentially planning. The nonconvex constraint on field-of-view of the visual sensor pointing with coupled attitude and relative position is then approximately relaxed as a convex standard second-order cone, and concave spherical and ellipsoidal obstacle regions respectively around the target's body and solar arrays are convexified by affine constraints in terms of tangent planes. The original nonlinear optimal guidance and control problem is accordingly transformed into a series of second-order cone programming sub-problems via iteratively successive convexification with the trust region constraints, and sequentially solved using disciplined convex programming method. A close-loop guidance and control using the proposed sequential convex programming scheme is then demonstrated by means of receding horizon to robustly drive the spacecraft maneuvering close to the target. Numerical simulations and results reveal that the proposed method provides rapid and reliable guidance and control performance for six-degree-of-freedom close proximity and shows the potential for on-board implementations in real-time applications. [ABSTRACT FROM AUTHOR]

In this paper, a guidance algorithm is presented based on successive convexification for the generation of fuel-optimal 6-DOF spacecraft close proximity trajectory subject to multiple path constraints on sensor field-of-view, collision avoidance, and plume impingement. The whole maneuver process is divided into fly-around and docking phases, where the collision avoidance constraints are only considered in the first stage, while the plume impingement restrictions are implemented when the chaser spacecraft lies within the docking corridor. These discrete decisions are embedded into continuous optimization framework by using the scheme of compound state-triggered constraints. Besides, in order to make full use of the control ability of actuator, the translational and rotational dynamics are reformulated with the thruster configuration. The original optimal guidance problem is converted into a series of convex subproblems by the linearization and discretization of nonlinear system dynamics and constraint functions around the reference trajectory, and iteratively solved by convex programming. Particularly, the algorithm is initialized with an imprecise trajectory obtained from pseudospectral method, and the reference states in the subsequent iterations are obtained by the propagation of the system dynamics in each discrete time interval rather than directly inheriting the latest solution. The convergence analysis is presented to prove that the proposed guidance algorithm converges to the stationary point of original problem under mild conditions. Finally, the effectiveness of the algorithm is demonstrated by numerical simulations. [ABSTRACT FROM AUTHOR]