Optimization and decision-making framework for multi-staged asteroid deflection campaigns under epistemic uncertainties

In this study, we introduce a framework for planning and assessing multi-spacecraft asteroid deflection campaigns. In the scenario considered, a near-Earth asteroid (NEA) is nudged away from gravitational keyholes via a kinetic impactor (KI) technique, lest its passage should incur an Earth collision in the future. An asteroid orbiter or/and an impactor is/are used in the precursor stage to obtain uncertain information about the target asteroid, whose launch date and trajectory are optimized using Chebyshev's method and a genetic algorithm. The KI mass is optimized through Monte Carlo simulations to improve the robustness of the method and achieve the minimum required probability of success (PoS). Case scenarios targeting Apophis and Bennu substantiate the utility of the framework in optimizing different deflection campaign architectures and making decisions amongst them via newly proposed visualization methods. •We model near-Earth asteroid (NEAs) mitigation campaigns under uncertainties.•Precursors reduce the kinetic impact uncertainties at the cost of time and mass.•Different types of precursors, including a non-precursor option, are considered.•Stochastic optimization and robustness quantifications are performed concurrently.