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arXiv AI By Atin Chowdhury, Piyush Joshi

Curriculum-Driven Deep Reinforcement Learning for Autonomous Far-Range Rocket Landing

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The paper introduces a curriculum-driven deep reinforcement learning framework for autonomous far-range rocket landing. It uses a three-stage curriculum, critic warm‑up, rehearsal to avoid catastrophic forgetting, and a high‑dimensional observation vector with a full 3×3 rotation matrix. The redesigned reward function bounds per‑step rewards and accumulates progress, yielding a 99.98% success rate over 100,000 episodes, far surpassing the baseline.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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