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An algorithm to guide the capture of a tumbling resident space object by a spacecraft equipped with a robotic manipulator is presented. A solution to the guidance problem is found by solving a collection of convex programming problems. As convex programming offers deterministic convergence properties, this algorithm is suitable for onboard implementation and real-time use. A set of hardware-in-the-loop experiments substantiates this claim. To cast the guidance problem as a collection of convex programming problems, the capture maneuver is divided into two simultaneously occurring sub-maneuvers: a system-wide translation and an internal re-configuration. These two sub-maneuvers are optimized in two consecutive steps. A sequential convex programming procedure, overcoming the presence of non-convex constraints and nonlinear dynamics, is used on both optimization steps. A proof of convergence is offered for the system-wide translation, while a set of structured heuristics—trust regions—is used for the optimization of the internal re-configuration sub-maneuver. Videos of the numerically simulated and experimentally demonstrated maneuvers are included as supplementary material.

The article of record as published may be found at http://dx.doi.org/10.2514/6.2018-2220 The objective of this research is to investigate the dynamics, and reachability characteristics of a spacecraft (commonly referred to as the deputy) conducting proximity maneuvers about a resident space object (commonly referred to as the chief) in a tumbling state of motion. Specifically, the goal is to identify initial conditions from which a specified maneuver is feasible, within a specified amount of time. This research question can be answered by solving a reachability problem, and computing a backwards reachable set. However, the complexity of the relative roto-translational dynamics of this scenario poses challenges for existing reachability tools. This paper presents the 6-DOF roto-translational relative spacecraft dynamics, from the perspective of the tumbling chief. A method based on minimum time optimal control is proposed for computation and visualization of backwards reachable sets for both relative translation and rotation, in the particular case of a chief in circular orbit spinning about a principal axis coinciding with the orbit normal. The proposed method makes the problem more tractable and provides insight into the reachability characteristics of this scenario.

The article of record as published may be found at http://dx.doi.org/10.2514/1.A33769 Ground-based testbeds are critical to develop and test different elements of spacecraft guidance, navigation, and control subsystems. This paper provides an in-detail description of a state-of-the-art air-bearing testbed used to develop guidance, navigation, and control methods for close-proximity operations. Test vehicles, representing spacecraft, float via air bearings over a horizontally leveled granite monolith and move with two translational degrees of freedom and one rotational degree of freedom under the effect of thrusters and reaction wheel actuators. This setup achieves a quasi-frictionless and low residual acceleration dynamic environment. The testbed experimental setup as well as the vehicle hardware and software architectures are discussed in detail. Characterization of different testbed elements is provided. Finally, a test campaign is used to showcase its capabilities and to illustrate the testbed operations.

The article of record as published may be found at http://dx.doi.org/10.1007/s12567-017-0155-7 An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear–quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser’s maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a groundbased air-bearing test bed, using spacecraft simulators that float over a granite table.

Presented at AIAA/AAS Astrodynamics Specialist Conference, Long Beach, CA. The article of record as published may be found at https://doi.org/10.2514/6.2016-5269 In this paper, Model Predictive Control (MPC) approaches are applied to multiple obstacle avoidance maneuvers for spacecraft rendezvous and docking. For safe obstacle avoidance, keep-out constraints are introduced by bounding ellipsoids around obstacles. In a linear quadratic MPC (LQ-MPC) framework, the rotating hyperplane method is used to convexify the obstacle avoidance constraints. A new method using two hyperplanes for convexification of the constraints is also proposed to improve performance of the LQ-MPC approach. A nonlinear MPC (NMPC) approach that deals with the nonlinear obstacle constraints directly is also applied to solve the spacecraft proximity maneuvering problems by using the nonlinear programming solver IPOPT (Interior Point OPTimizer). Real-time implementation of the MPC solutions is analyzed and compared on a physical test bed using several test cases. Numerical simulations and experiments demonstrate the obstacle avoidance as well as real-time operation capabilities of the considered control approaches.