{"ID":2887139,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.02904","arxiv_id":"2508.02904","title":"Global Optimality in Multi-Flyby Asteroid Trajectory Optimization: Theory and Application Techniques","abstract":"Designing optimal trajectories for multi-flyby asteroid missions is scientifically critical but technically challenging due to nonlinear dynamics, intermediate constraints, and numerous local optima. This paper establishes a method that approaches global optimality for multi-flyby trajectory optimization under a given sequence. The original optimal control problem with interior-point equality constraints is transformed into a multi-stage decision formulation. This reformulation enables direct application of dynamic programming in lower dimensions, and follows Bellman's principle of optimality. Moreover, the method provides a quantifiable bound on global optima errors introduced by discretization and approximation assumptions, thus ensuring a measure of confidence in the obtained solution. The method accommodates both impulsive and low-thrust maneuver schemes in rendezvous and flyby scenarios. Several computational techniques are introduced to enhance efficiency, including a specialized solution for bi-impulse cases and an adaptive step refinement strategy. The proposed method is validated through three problems: 1) an impulsive variant of the fourth Global Trajectory Optimization competition problem (GTOC4), 2) the GTOC11 problem, and 3) the original low-thrust GTOC4 problem. Each case demonstrates improvements in fuel consumption over the best-known trajectories. These results give evidence of the generality and effectiveness of the proposed method in global trajectory optimization.","short_abstract":"Designing optimal trajectories for multi-flyby asteroid missions is scientifically critical but technically challenging due to nonlinear dynamics, intermediate constraints, and numerous local optima. This paper establishes a method that approaches global optimality for multi-flyby trajectory optimization under a given...","url_abs":"https://arxiv.org/abs/2508.02904","url_pdf":"https://arxiv.org/pdf/2508.02904v1","authors":"[\"Zhong Zhang\",\"Xiang Guo\",\"Di Wu\",\"Hexi Baoyin\",\"Junfeng Li\",\"Francesco Topputo\"]","published":"2025-08-04T21:10:40Z","proceeding":"math.OC","tasks":"[\"math.OC\",\"eess.SY\"]","methods":"[\"Large Language Model\"]","has_code":false}