A new stochastic differential dynamic programming method optimizes coupled trajectory design and orbit determination under partial observability, producing navigation-aware solutions with lower fuel consumption than deterministic local optimization in examples like the circular restricted three-body
Interior Point Differential Dynamic Programming
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DADDy combines differential dynamic programming with differential algebra to accelerate constrained fuel-optimal low-thrust trajectory optimization, reporting 41-88% runtime reductions on Sun-centred, Earth-Moon and Earth-centred benchmarks while retaining convergence.
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Stochastic Differential Dynamic Programming for Trajectory Optimization under Partial Observability
A new stochastic differential dynamic programming method optimizes coupled trajectory design and orbit determination under partial observability, producing navigation-aware solutions with lower fuel consumption than deterministic local optimization in examples like the circular restricted three-body
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Taylor polynomial-based constrained solver for fuel-optimal low-thrust trajectory optimisation
DADDy combines differential dynamic programming with differential algebra to accelerate constrained fuel-optimal low-thrust trajectory optimization, reporting 41-88% runtime reductions on Sun-centred, Earth-Moon and Earth-centred benchmarks while retaining convergence.