This work introduces TrajDiffuser, a compositional diffusion-based flexible and concurrent trajectory generator for 6 degrees of freedom powered descent guidance. TrajDiffuser is a statistical model that learns the multi-modal distributions of a dataset of simulated optimal trajectories, each subject to only one or few constraints that may vary for different trajectories. During inference, the trajectory is generated simultaneously over time, providing stable long-horizon planning, and constraints can be composed together, increasing the model's generalizability and decreasing the training data required. The generated trajectory is then used to initialize an optimizer, increasing its robustness and speed.

翻译：本文提出TrajDiffuser，一种基于组合扩散的灵活并发轨迹生成器，用于六自由度动力下降制导。TrajDiffuser是一种统计模型，通过学习模拟最优轨迹数据集的多模态分布进行训练，其中每条轨迹仅受单个或少数约束条件限制，且不同轨迹的约束可能各不相同。在推理过程中，轨迹随时间同步生成，实现了稳定的长时程规划，同时支持约束条件的组合应用，从而增强了模型的泛化能力并降低了训练数据需求。生成的轨迹随后用于优化器初始化，有效提升了优化过程的鲁棒性与收敛速度。