prototwin/RLExamples

PotoTwin Reinforcement Learning Examples

25
/ 100
Experimental

This provides ready-to-use examples for training intelligent agents within robotics and industrial automation simulations. It takes your ProtoTwin simulation models as input and produces trained reinforcement learning agents capable of performing complex tasks like balancing a pole, walking, or robotic manipulation. This is for robotics engineers, automation specialists, and researchers developing autonomous systems.

No commits in the last 6 months.

Use this if you are a robotics engineer or researcher looking to apply reinforcement learning to simulated robotic systems for tasks like control, navigation, or complex manipulation.

Not ideal if you are looking for a general-purpose reinforcement learning framework that doesn't require the ProtoTwin simulation platform.

robotics industrial automation simulation training autonomous systems robot control
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 0 / 25

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Language

Python

License

MIT

Last pushed

Sep 08, 2025

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