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Mars Landing Control via Reinforcement Learning by Vahid Ataei is a document available to read on EtoBox.

The document presents a novel integrated guidance and control algorithm for pinpoint Mars landing using reinforcement learning. The algorithm directly maps the estimated lander state to actuator commands using a policy trained with reinforcement learning. Specifically, proximal policy optimization is used to learn a policy that results in accurate and fuel efficient trajectories. Simulation results demonstrate the algorithm

Author
Vahid Ataei
Language
EN