An OpenAI gym environment for simulating Goddard's Rocket Problem.
First formulated by R. H. Goddard around 1910, this is a classical problem within dynamic optimization and optimal control. The task is simply to find the optimal thrust profile for a vertically ascending rocket in order for it to reach the maximum possible altitude, given that its mass decreas as the fuel is spent and that it is subject to varying drag and gravity.
The state, and the gym's observation space, of the rocket is its vertical position, velocity and mass.
The rocket engine is assumed to be throttled such that the thrust can be continuously controlled between 0 to some maximum limit.
cd gym-goddard
pip install -e .import gym
env = gym.make('gym_goddard:Goddard-v0')
obs = env.reset()
while True:
obs, reward, done, info = env.step(action=env.action_space.high)
env.render('human')It is, under certain conditions, possible to solve the problem analytically. Please see this notebook for details.