Kinematic Alignment
Aligns observation layout, joint semantics, hip-axis geometry, and closed-chain coupling before policy reuse.
Abstract
Whole-body tracking models are becoming reusable motor priors for humanoid robots, but training a high-quality tracker from scratch is expensive and embodiment-specific. Any2Any studies whether pretrained WBT specialists can transfer to new humanoids with minimal adaptation. The framework first performs kinematic alignment to reconcile observation, reference, and action spaces across embodiments, then applies lightweight dynamics adaptation through LoRA modules inserted into dynamics-sensitive parts of the frozen policy.
Across Sonic and Oli-WBT source backbones, Any2Any evaluates six cross-embodiment transfer instances over LimX Oli, LimX Luna, Unitree G1, and Unitree H1, achieving strong tracking performance with a small fraction of the original data and compute.
~1%Pretraining data and compute achieving cross-embodiment transfer
5.26%Trainable parameters with LoRA
4Humanoid platforms
6Cross-embodiment transfer instances
Overview
A pretrained whole-body tracker can be reused on a new humanoid through embodiment adaptation, reducing the target-side training cost from large-scale pretraining to compact post-training.
Method
Any2Any decomposes cross-embodiment transfer into kinematic alignment, which maps observation and action semantics across robot morphologies, and dynamics adaptation, which fine-tunes lightweight LoRA modules for target-specific dynamics.
Dynamics Adaptation
Freezes the pretrained WBT backbone and trains low-rank LoRA factors on target-specific dynamics pathways.
Sonic Transfer Sim2Sim Rollouts
Sonic transfer motions on LimX Oli, LimX Luna, and Unitree H1 in simulation, including Oli dance clips.
Oli-WBT Transfer Sim2Sim Rollouts
Oli-WBT2 transfer motions on Unitree G1, Unitree H1, and LimX Luna in simulation.
Sonic2 Sim2Real Rollouts
Sonic transfer motions on LimX Oli in real-world deployment.
Data and Compute Efficiency
Any2Any maintains higher success rates than training from scratch under reduced data and GPU-hour budgets.
Sonic-based Multi-Robot WBT Experiment
A single Sonic-based whole-body tracker transferred across multiple humanoid embodiments, rolled out simultaneously in simulation at normal speed.
Citation
@article{anonymous2026any2any,
title = {Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking},
author = {Anonymous},
journal = {arXiv preprint arXiv:2605.23733},
year = {2026},
url = {https://arxiv.org/abs/2605.23733}
}