Temporal Mission Planning of Autonomous Avoidance for Spacecraft Confronting Orbital Threats: An Interval-Based Heuristic Approach

This article studies the mission planning problem of autonomous avoidance for spacecraft subject to orbital threats using the interval-based heuristic search. First, the temporal mission planning model with flexible parameters (FPs) is established, where FPs represent the physical quantities of the durative action assigned at the later stage of the planning. The ordering constraints among the actions are handled by the transition links, whose planning flaws are resolved by upgrading or downgrading the time instants of conflicts. The border states are calculated for selecting the search node by sequentially adding the effects of actions in the partial plan. Meanwhile, the changes of resources along with the state trajectory are updated through the interval-based relaxation. Then, the relaxed planning graph heuristics is adopted to evaluate the cost of the extended node in the search space and recursively extract the planning solution. The satisfactions of constraints are validated by the planning consistency, and the optimal values of all variables are assigned in the feasible interval. Finally, the simulation results demonstrate the effectiveness and advantages of the proposed autonomous avoidance strategy on spacecraft to avoid orbital threats.