attitude-control

This paper explores deep reinforcement learning for attitude control of spacecraft during hypersonic re-entry. It demonstrates that state-of-the-art RL and hybrid controllers can outperform traditional PID controllers with gain scheduling, especially when dynamics randomization is used to improve robustness and generalization.