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Juana authored
# Description <!-- Thank you for your interest in sending a pull request. Please make sure to check the contribution guidelines. Link: https://isaac-sim.github.io/IsaacLab/main/source/refs/contributing.html
💡 Please try to keep PRs small and focused. Large PRs are harder to review and merge. --> This PR fixes a bug in actuator initialization where effort limits specified in USD assets were being incorrectly overridden with a very large default value (1.0e9) for explicit actuator models. Fixes # (issue) Previously, the ActuatorBase initialization logic would unconditionally fall back to _DEFAULT_MAX_EFFORT_SIM (1.0e9) for explicit actuator models when effort_limit_sim was not explicitly set in the configuration, even when the USD asset contained finite, meaningful effort limit values. ## Type of change <!-- As you go through the list, delete the ones that are not applicable. --> - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have read and understood the [contribution guidelines](https://isaac-sim.github.io/IsaacLab/main/source/refs/contributing.html) - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [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 <!-- As you go through the checklist above, you can mark something as done by putting an x character in it For example, - [x] I have done this task - [ ] I have not done this task --> --------- Signed-off-by:
Juana <yvetted@nvidia.com>
Signed-off-by:
Kelly Guo <kellyg@nvidia.com>
Co-authored-by:
James Tigue <166445701+jtigue-bdai@users.noreply.github.com>
Co-authored-by:
greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by:
Kelly Guo <kellyg@nvidia.com>