drl_grasping
robo-gym
| drl_grasping | robo-gym | |
|---|---|---|
| 4 | 4 | |
| 326 | 371 | |
| - | 4.0% | |
| 0.0 | 0.0 | |
| over 1 year ago | about 2 years ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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drl_grasping
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Researchers at The University of Luxembourg Develop a Method to Learn Grasping Objects on the Moon from 3D Octree Observations with Deep Reinforcement Learning
Continue reading| Check out the paper,and github link
- ROS 2 + Ignition + OpenAI Gym Deep RL Example
- ROS 2 + Ignition + OpenAI Gym Tutorial
- Deep Reinforcement Learning for Robotic Grasping from Octrees
robo-gym
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Simulating robotic arm for object manipulation
what about robo-gym https://github.com/jr-robotics/robo-gym?
- Joanneum Research Institute Release Version 1.0.0 Of Robo-Gym, An Open Source Toolkit For Distributed Deep Reinforcement Learning On Real And Simulated Robots
What are some alternatives?
pytorch-blender - :sweat_drops: Seamless, distributed, real-time integration of Blender into PyTorch data pipelines
IsaacGymEnvs - Isaac Gym Reinforcement Learning Environments
rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.
modelicagym - Modelica models integration with Open AI Gym
gym-pybullet-drones - PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
football - Check out the new game server:
lodtree - A simple rust library to help create octrees and quadtrees for chunked level of detail
MuJoCo_RL_UR5 - A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.