Constellation autonomous mission planning algorithm based on distributed co-evolution.

Constellation collaborative autonomous mission planning is an important part of satellite autonomous management and control technology. Firstly, this paper proposes a distributed constellation collaborative iterative optimization strategy, in which each satellite in the constellation participates in the coordinated optimization of the system mission plan as an independent agent through the three-phase cooperative behavior of "receive", "update", and "release". Secondly, a distributed co-evolution algorithm is designed on the basis of this strategy, which allows multiple sub-populations distributed on different satellites to parallelly evolve with information interactions and continuously optimize the combination of plans for each satellite. Finally, this paper conducts simulation experiments m the S698PM embedded development environment. Through comparative tests with the greedy algorithm, the centralized genetic algorithm and CPLEX, the applicability and effectiveness of the proposed method in harsh communication environments and large-scale problems are verified. [ABSTRACT FROM AUTHOR]