Release Notes#
v0.1.1#
This release includes bug fixes, documentation improvements, CI and infrastructure updates, and several API and workflow enhancements over v0.1.0.
Features and improvements
Object configuration: Object configuration is now created as soon as an asset is called, so users can edit object properties before a scene is created (#239).
Scene export: Added support for saving a scene to a flattened USD file (#237). Scene export now correctly handles double-precision poses and adds contact reporters when exporting rigid objects (#242).
Parallel environment evaluation: Enabled parallel environment evaluation for GR00T policy runner, with documentation for closed-loop GR00T workflows (#231, #236).
Episode length: Increased episode length for loco-manipulation to support rollout through box drop (#235).
Microwave example: Increased reset openness for the microwave example (#311).
Bug fixes
Reference object poses: Fixed reference object poses so they correctly account for the parent object’s initial pose; poses are now relative and composed at compile time (#232).
IsaacLab-to-stage path conversion: Fixed a bug when the asset name appeared twice in the prim path (replaced both instances instead of one) (#241).
qpsolvers: Patched breakage with Isaac Lab 2.3 due to
qpsolversupgrade by pinning to 4.8.1 (#252).Parallel eval: Removed comments that were breaking the parallel eval run commands (#262).
Documentation
Multi-versioned docs: Documentation is now versioned so users can read docs that match their release (#272, #300).
Links and structure: Updated README docs link to the public location (#270), corrected doc pointers (#301), and added release warnings (#303).
Installation: Private Omniverse/Nucleus access is described on a separate page to clarify it is not required for normal installation (#261).
Infrastructure and CI
Runners: Release 0.1.1 CI runners moved from local (Zurich) to AWS (#433).
CI workflow: Added YAML anchors to reduce repetition in the CI workflow (#245).
Contribution guide: Added signoff requirements for external contributions (#238).
Docker: Fixed Dockerfile pip usage and added SSL certificate support for Lightwheel SDK (#449).
Tests: Finetuned GR00T locomanip model is now generated on the fly in tests instead of mounting a pre-finetuned models directory, improving public CI compatibility and testing the fine-tuning pipeline (#247).
Assets and tests
G1 WBC: Updated G1 WBC embodiment file paths to use S3 (#251).
Test assets: Removed internal or custom-only assets from tests: custom cracker box (#234), custom USD in ObjectReference test (#240), internal asset from USD utils test (#244). ObjectReference test now composes USD on the fly via scene export (#240).
v0.1.0#
This initial release of Isaac Lab Arena delivers the first version of the composable task definition API. Also included are example workflows for static manipulation tasks and loco-manipulation tasks including GR00T GN1.5 finetuning and evaluation.
Key features of this release include:
Composable Task Definition: Base-class definition for
Task,Embodiment, andScenethat can be subclassed to create new tasks, embodiments, and scenes.ArenaEnvBuilderfor convertingScene,Embodiment, andTaskinto an Isaac Lab runnable environment.Metrics: Mechanism for adding task-specific metrics which are reported during evaluation.
Isaac Lab Mimic Integration: Integration with Isaac Lab Mimic to automatically generate Mimic definitions for available tasks.
Example Workflows: Two example workflows for static manipulation tasks and loco-manipulation tasks.
GR00T GN1.5 Integration: Integration with GR00T GN1.5 including a example workflows for finetuning and evaluating the model on the static and loco-manipulation workflows.
Known limitations:
Number of Environments/Tasks: This initial is intended to validation the composable task definition API, and comes with a limited set of tasks and workflows.
Loco-manipulation GR00T GN1.5 finetuning: GR00T GN1.5 finetuning for loco-manipulation requires a large amount of GPU resources. (Note that static manipulation finetuning can be performed on a single GPU.)