kochlisGit/Shadow-Hand-Controller

Construction of controllers for Shadow-Hand in Mujoco environment, using Deep Learning. 2 Different methods were used to create the controllers: a) Behavioral Cloning b) Deep Reinforcement Learning

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This project helps researchers and roboticists develop controllers for the Shadow-Hand, a 3D robotic hand model. By providing sign-language gesture commands, it outputs the precise motor control signals needed for the hand to perform those gestures in a simulated environment. This tool is designed for those working on robotic manipulation and human-robot interaction.

No commits in the last 6 months.

Use this if you are developing or experimenting with robotic hand control in a simulated environment and need a way to translate high-level gesture commands into low-level motor actions.

Not ideal if you are looking for a physical robot controller ready for immediate deployment without simulation or deep learning model development.

robotics robotic-hand-control human-robot-interaction robotic-simulation gesture-recognition
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

22

Forks

4

Language

Python

License

MIT

Last pushed

Aug 15, 2023

Commits (30d)

0

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