Swarms of modular satellites decentralized guidance and target assignment strategy

This paper presents a decentralized guidance and target assignment (DGTA) strategy for reconfiguring swarms made up of hundreds of modules that have limited communication capabilities. This strategy provides a decentralized onboard computation method to address both near-optimal target assignment and collision-free trajectory planning for swarms of modules. To effectively estimate the transfer cost between modules and targets for target assignment, a multilayer perceptron (MLP) is developed via the backward generation method. The decentralized target assignment problem is solved by greedy algorithm according to the result of the efficient estimating solver. A decentralized model predictive control approach is proposed to guide swarm modules towards their assigned targets, while avoiding collisions with other modules. The feasibility of this guidance framework has been demonstrated through rigorous theoretical analysis. Numerical experiment confirms that the MLP-based method shows an accurate and real-time advantage for estimating transfer cost. Furthermore, the DGTA strategy has been shown to possess robustness and generalization ability, as evidenced by its successful application in a pinpoint assembly task involving 125 and 182 modules. The simulation results confirm the feasibility of this approach for in-orbit assembly application.