Research/ SPACE AI & AUTONOMY
Atmospheric Entry
Dillon Martin
Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics · Guidance, Dynamics & ControlOpenAlex topic: Guidance and Control Systems
OpenAlexSpacecraft Dynamics and Control · Guidance and Control Systems · Reinforcement Learning in Robotics
The development of atmospheric entry guidance methods is crucial to achieving the requirements for future missions to Mars; however, many missions implement a unique controller which are spacecraft specific. Here we look at the implementation of neural networks as a baseline controller that will work for a variety of different spacecraft. To accomplish this, a simulation is developed and validated with the Apollo controller. A feedforward neural network controller is then analyzed and compared to the Apollo case.