Successive Convexification for Satellite Swarms Trajectory Planning and Collision Avoidance

This study presents a decentralized trajectory planning method for satellite swarms that generates fuel-efficient and collision-free trajectories using successive convexification. Firstly, the satellite swarm trajectory planning problem is transformed into a time-continuous optimal control problem that considers state and control constraints, as well as J
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perturbation. The problem considers collision avoidance not only among satellites, but also between satellites and external obstacles. Secondly, non-convex constraints are transformed into forms that conform to the convex optimization problem through linearization and discretization. A trust region constraint is added to the objective function to establish convex optimal control problems that can be solved numerically. Thirdly, a decentralized successive convexification method is proposed by decoupling the inter-satellite collision constraints. Finally, numerical simulation results demonstrate that the proposed method is nearly an order of magnitude faster than the pseudospectral method, with comparable optimality.