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With a 6 m/s increase in the Delta-V budget, the deep reinforcement learning approach shortened the #aerobraking time by 68.3% 📉. The DRL algorithm does not encounter any thermal violations over 40 episodes compared to the 2.8 average thermal violations experienced by the state-of-the-art heuristic https://arc.aiaa.org/doi/10.2514/6.2022-2497
Content Warning
With a 6 m/s increase in the Delta-V budget, the deep reinforcement learning approach shortened the #aerobraking time by 68.3% 📉. The DRL algorithm does not encounter any thermal violations over 40 episodes compared to the 2.8 average thermal violations experienced by the state-of-the-art heuristic https://arc.aiaa.org/doi/10.2514/6.2022-2497
Content Warning
Content Warning
Content Warning
With a 6 m/s increase in the Delta-V budget, the deep reinforcement learning approach shortened the #aerobraking time by 68.3% 📉. The DRL algorithm does not encounter any thermal violations over 40 episodes compared to the 2.8 average thermal violations experienced by the state-of-the-art heuristic https://arc.aiaa.org/doi/10.2514/6.2022-2497