Distribution-Agnostic Robust Trajectory Optimization via Chance-Constrained Reinforcement Learning

arXiv:2606.13605 · math.OC, cs.LG, cs.SY, eess.SY · Submitted 2026-06-11 · Read on arXiv

math.OC, cs.LG, cs.SY, eess.SY

Submitted: 2026-06-11

Updated: 2026-06-11

Comments: Preprint. 39 pages, 16 figures

Journal ref: Aerospace Science and Technology 179 (2026) 113521

DOI: 10.1016/j.ast.2026.113521

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 24× in this paper · explained in 4 episodes
• Robustness — 19× in this paper · explained in 5 episodes
• Benchmark — 18× in this paper · explained in 2 episodes
• Actor — 9× in this paper · explained in 3 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Sequential Convex Programming — 3× in this paper
• American Institute of Aeronautics and Astronautics — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Monte Carlo — 2× in this paper
• Adaptation — 1× in this paper · explained in 1 episode
• Additive Decomposition — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Closed-Loop Control — 1× in this paper · explained in 2 episodes
• Covariance Propagation — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Higher-order statistics — 1× in this paper · explained in 2 episodes
• Lyapunov function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Velocity Dispersion — 1× in this paper · explained in 2 episodes

Sources

• Adaptive Generalized ZEM-ZEV Feedback Guidance for Planetary Landing via a Deep Reinforcement Learning Approach
• Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• Gymnasium: A Standard Interface for Reinforcement Learning Environments

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