Goal-Oriented Trajectories About Minor Bodies Using Sequential Convex Programming: a Stochastic Approach

The exploration of minor bodies is crucial for understanding the solar system’s origins and resource potential. Small satellites, appealing in this context, face challenges such as limited control, state uncertainties, and command errors. Traditional trajectory design methods, which focus on nominal paths, are labor-intensive and lack robustness. This work introduces a novel methodology combining polynomial chaos expansion and sequential convex programming to compute goal-oriented robust trajectories that account for uncertainties in dynamics, navigation, and control. Numerical simulations demonstrate the method effectiveness in providing robust, feasible solutions, emphasizing the need for a stochastic approach in uncertain environments.