On Development of 100-Gram-Class Spacecraft for Swarm Applications

A novel space system architecture is proposed, which would enable 100-g-class spacecraft to be flown as swarms (100 s-1000 s) in low Earth orbit. Swarms of Silicon Wafer Integrated Femtosatellites (SWIFT) present a paradigm-shifting approach to distributed spacecraft development, missions, and applications. Potential applications of SWIFT swarms include sparse aperture arrays and distributed sensor networks. New swarm array configurations are introduced and shown to achieve the effective sparse aperture driven from optical performance metrics. A system cost analysis based on this comparison justifies deploying a large number of femtosatellites for sparse aperture applications. Moreover, this paper discusses promising guidance, control, and navigation methods for swarms of femtosatellites equipped with modest sensing and control capabilities

On Development of 100-Gram-Class Spacecraft for Swarm Applications

A novel space system architecture is proposed, which would enable 100-g-class spacecraft to be flown as swarms (100 s-1000 s) in low Earth orbit. Swarms of Silicon Wafer Integrated Femtosatellites (SWIFT) present a paradigm-shifting approach to distributed spacecraft development, missions, and applications. Potential applications of SWIFT swarms include sparse aperture arrays and distributed sensor networks. New swarm array configurations are introduced and shown to achieve the effective sparse aperture driven from optical performance metrics. A system cost analysis based on this comparison justifies deploying a large number of femtosatellites for sparse aperture applications. Moreover, this paper discusses promising guidance, control, and navigation methods for swarms of femtosatellites equipped with modest sensing and control capabilities

Swarm keeping strategies for spacecraft under J2 and atmospheric drag perturbations

This thesis presents several new open-loop guidance methods for spacecraft swarms comprised of hundreds to thousands of agents with each spacecraft having modest capabilities. These methods have three main goals: preventing relative drift of the swarm, preventing collisions within the swarm, and minimizing the fuel used throughout the mission. The development of these methods progresses by eliminating drift using the Hill-Clohessy-Wiltshire equations, removing drift due to nonlinearity, and minimizing the $J_2$ drift. In order to verify these guidance methods, a new dynamic model for the relative motion of spacecraft is developed. These dynamics are exact and include the two main disturbances for spacecraft in Low Earth Orbit (LEO), $J_2$ and atmospheric drag. Using this dynamic model, numerical simulations are provided at each step to show the effectiveness of each method and to see where improvements can be made. The main result is a set of initial conditions for each spacecraft in the swarm which provides hundreds of collision-free orbits in the presence of $J_2$. Finally, a multi-burn strategy is developed in order to provide hundreds of collision free orbits under the influence of atmospheric drag. This last method works by enforcing the initial conditions multiple times throughout the mission thereby providing collision free motion for the duration of the mission

Random Finite Set Theory and Optimal Control of Large Collaborative Swarms

Controlling large swarms of robotic agents has many challenges including, but not limited to, computational complexity due to the number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm's configuration. This work generalizes the swarm state using Random Finite Set (RFS) theory and solves the control problem using Model Predictive Control (MPC) to overcome the aforementioned challenges. Computationally efficient solutions are obtained via the Iterative Linear Quadratic Regulator (ILQR). Information divergence is used to define the distance between the swarm RFS and the desired swarm configuration. Then, a stochastic optimal control problem is formulated using a modified L2^2 distance. Simulation results using MPC and ILQR show that swarm intensities converge to a target destination, and the RFS control formulation can vary in the number of target destinations. ILQR also provides a more computationally efficient solution to the RFS swarm problem when compared to the MPC solution. Lastly, the RFS control solution is applied to a spacecraft relative motion problem showing the viability for this real-world scenario.Comment: arXiv admin note: text overlap with arXiv:1801.0731

Probabilistic guidance of distributed systems using sequential convex programming

In this paper, we integrate, implement, and validate formation flying algorithms for a large number of agents using probabilistic guidance of distributed systems with inhomogeneous Markov chains and model predictive control with sequential convex programming. Using an inhomogeneous Markov chain, each agent determines its target position during each iteration in a statistically independent manner while the distributed system converges to the desired formation. Moreover, the distributed system is robust to external disturbances or damages to the formation. Once the target positions are assigned, an optimal control problem is formulated to ensure that the agents reach the target positions while avoiding collisions. This problem is solved using sequential convex programming to determine optimal, collision-free trajectories and model predictive control is implemented to update these trajectories as new state information becomes available. Finally, we validate the probabilistic guidance of distributed systems and model predictive control algorithms using the formation flying testbed

Distributed Control Of An Evolving Satellite Assembly During In-Orbit Construction

This paper presents a method for controlling sets of docked satellites during in-orbit construction of a large-scale satellite assembly from a swarm of heterogeneous satellites. Such a system can be used to enable missions from sparse aperture telescopes to elaborate space stations. Once two or more agents from the swarm are docked, the resulting assembly is an over-actuated system so position and attitude controllers must determine which of the available actuators to use. Typically, control allocation for over-actuated systems is done using a simple linear program, but for this scheme the mass properties and number of control points changes. As a result, the linear program solved changes with each new agent that docks with the assembly so the agents must know how to alter the linear program for additional agents and remove control points whose plumes would interact with those agents. In most systems, this linear program is solved by a central computer, but for this system the actuators belong to distinct agents so to increase reliability, each agent solves the same linear program and executes its portion of the resulting control command. This paper sets up the general linear program that each agent in the assembly must solve and then establishes the rules for altering that program when new agents dock. Initial simulations allow the agents to dock as they come into proximity along their respective trajectories to their target locations. This can lead to instability and uncontrollability if the agents dock in certain configurations, so the control allocation rules are extended to prevent uncontrollable or unstable docking scenarios. The logic used for this is based on the moment of inertia and the available actuation ability. Simulations in 6DOF perturbed satellite dynamics show the efficacy of this approach in preventing uncontrollable assemblies and bringing the assemblies together into the desired final configuration

Swarming Proxima Centauri: Optical Communication Over Interstellar Distances

Interstellar communications are achievable with gram-scale spacecraft using swarm techniques introduced herein if an adequate energy source, clocks and a suitable communications protocol exist. The essence of our approach to the Breakthrough Starshot challenge is to launch a long string of 100s of gram-scale interstellar probes at 0.2c in a firing campaign up to a year long, maintain continuous contact with them (directly amongst each other and via Earth utilizing the launch laser), and gradually, during the 20-year cruise, dynamically coalesce the long string into a lens-shaped mesh network $\sim$100,000 km across centered on the target planet Proxima b at the time of fly-by. In-flight formation would be accomplished using the "time on target" technique of grossly modulating the initial launch velocity between the head and the tail of the string, and combined with continual fine control or "velocity on target" by adjusting the attitude of selected probes, exploiting the drag imparted by the ISM. Such a swarm could tolerate significant attrition, e.g., by collisions enroute with interstellar dust grains, thus mitigating the risk that comes with "putting all your eggs in one basket". It would also enable the observation of Proxima b at close range from a multiplicity of viewpoints. Swarm synchronization with state-of-the-art space-rated clocks would enable operational coherence if not actual phase coherence in the swarm optical communications. Betavoltaic technology, which should be commercialized and space-rated in the next decade, can provide an adequate primary energy storage for these swarms. The combination would thus enable data return rates orders of magnitude greater than possible from a single probe.Comment: Submission to the Breakthrough Starshot Challenge Communications Group Final Repor