ProtoMotions Changelog#

Unreleased#

Record changes for the next release in this section. Move completed entries into a dated release section when the release is published.

The following changes are included in this release:

Add configurable target commands, semantic heading axes, recovery-pose resets, and a minimum motion-weight floor for reliable task sampling.
Add soft joint-limit and end-effector position rewards, with safe termination when joint state diverges.
Add baked-FK target observations, odometry corruption/ablation paths, and optional reference-travel feedforward for deployment-oriented tracking.

Switch to Newton 1.0.0 at public commit e7a737c and IsaacLab 3.0 / Isaac Sim 6.0 at IsaacLab commit 4ecd0b036da19ff6ad2bb4d621f886b63e9f6db8 (v3.0.0-beta-712-g4ecd0b).
Make MJCF the single source of truth for robot assets. IsaacLab converts packaged MJCF at load time and preserves multi-axis joint structure and metadata.
Fix friction randomization and combine-mode conversion across Newton, IsaacGym, and IsaacLab, including partial ranges and shared bucketing.
Improve Newton distributed-device selection, joint-name diagnostics, and evaluation handling; align character friction defaults across backends.
Improve scene-object state handling and quaternion, reset, and single-env simulator state behavior.

Add configurable Weights & Biases project names, training iteration limits, and sharded MotionLib loading with runtime shard switching for multi-GPU datasets.
Add PyPI and UV installation support while preserving preconfigured Torch builds.
Improve IsaacLab throughput by collapsing actuator configuration and reducing terrain, motion-reference, and subset-reset hot-path overhead.
Improve quickstart and workflow documentation for pretrained models, G1 deployment, and SLURM training.

Refresh G1 BONES-SEED, SMPL, SOMA, and MaskedMimic pretrained artifacts with authoritative resolved_configs.pt sidecars.
Improve ONNX deployment metadata and the MuJoCo tracker harness, including motion-index selection and exported effort limits.
Improve pretrained-policy inference compatibility between MuJoCo and Newton.