sdsubhajitdas/Rocket_Lander_Gym
💥💥 This is a easy installable extension for OpenAi Gym Environment. This simulates SpaceX Falcon landing.
This project provides a simulation environment for training an AI to land a SpaceX Falcon rocket. It takes in control inputs like throttle and gimbal commands and outputs the rocket's position, velocity, and angle. Researchers and students in reinforcement learning can use this to develop and test autonomous landing algorithms.
No commits in the last 6 months.
Use this if you are developing or experimenting with AI agents for controlling rocket landings in a simulated environment.
Not ideal if you are looking for a pre-trained rocket landing AI or a non-simulated, real-world control system.
Stars
58
Forks
5
Language
Python
License
MIT
Category
Last pushed
Jul 24, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sdsubhajitdas/Rocket_Lander_Gym"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
vietnh1009/Super-mario-bros-PPO-pytorch
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
taherfattahi/ppo-rocket-landing
Proximal Policy Optimization (PPO) algorithm using PyTorch to train an agent for a rocket...
anh-nn01/Lunar-Lander-Double-Deep-Q-Networks
An AI agent that use Double Deep Q-learning to teach itself to land a Lunar Lander on OpenAI universe
Itomigna2/Muesli-lunarlander
Muesli RL algorithm implementation (PyTorch) (LunarLander-v2)
fvalka/atc-reinforcement-learning
Reinforcement learning for an air traffic control task. OpenAI gym based simulation.