mahyaret/kuka_rl
Reinforcement Learning Experiments using PyBullet
This project helps robotics engineers and researchers train virtual Kuka robotic arms to grasp objects using machine learning techniques. It takes simulated robot movement and environmental feedback as input to teach the robot how to perform grasping tasks more effectively, outputting a trained model that can control the robot's actions. It's designed for those developing or studying robotic manipulation in simulated environments.
136 stars. No commits in the last 6 months.
Use this if you are a robotics researcher or engineer looking for a way to experiment with and implement reinforcement learning algorithms for robotic grasping in a simulated environment.
Not ideal if you are looking for a solution to control a physical robotic arm directly or if you need to perform tasks other than grasping.
Stars
136
Forks
23
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jul 10, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mahyaret/kuka_rl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning...
Denys88/rl_games
RL implementations
pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild