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 J2 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.