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Mayank Mittal authored
# Description This MR adds the dexterous cube manipulation environment from IsaacGymEnvs. The implementation is mostly based on the standard AllegroHand environment. However, it includes the following components from the Dextreme work: * Randomization of mass, joint PD gains, friction, and initial state distribution * Tuning of RL-Games from Dextreme work * Exponential moving average (bounded joint position) action term However, it does the following differently since it led to better convergence: * Changes the way out-of-reach termination is computed. Original work seems to do it w.r.t. the goal position, but that seems unnecessary * Removed goal position racking reward. It was tuned too high, which made learning difficult and is not needed ## Type of change - New feature (non-breaking change which adds functionality) ## Screenshots Trained with RSL-RL https://github.com/isaac-orbit/orbit/assets/12863862/8f51e468-2d93-4520-9689-f1e8f1a898e6 ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./orbit.sh --format` - [x] I have made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have run all the tests with `./orbit.sh --test` and they pass - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there