MuJoCo_RL_UR5 VS robo-gym

Compare MuJoCo_RL_UR5 vs robo-gym and see what are their differences.

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. (by PaulDanielML)

robo-gym

An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots. (by jr-robotics)
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MuJoCo_RL_UR5 robo-gym
1 4
303 371
- 0.0%
0.0 0.0
over 1 year ago about 2 years ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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MuJoCo_RL_UR5

Posts with mentions or reviews of MuJoCo_RL_UR5. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-22.

robo-gym

Posts with mentions or reviews of robo-gym. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-22.

What are some alternatives?

When comparing MuJoCo_RL_UR5 and robo-gym you can also consider the following projects:

IsaacGymEnvs - Isaac Gym Reinforcement Learning Environments

Unity-Robotics-Hub - Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.

drl_grasping - Deep Reinforcement Learning for Robotic Grasping from Octrees

myosuite - MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.

rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

Wave-Defense-Learning-Environment - A videogame made with PyGame turned into an Open AI Gym Learning Environment for Reinforcement Learning agents.

modelicagym - Modelica models integration with Open AI Gym

HighwayEnv - A minimalist environment for decision-making in autonomous driving

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).