# Coordi-pi: Coordination-Aware Dual-Hand Action Representation for Bimanual Dexterous Manipulation

arXiv: https://arxiv.org/abs/2610.19753 · HTML: https://mlsanity.com/paper/2610.19753/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Human-video and latent-action pretraining, one of 13 directions in Vision-language-action models.
- First posted on arXiv 14 Oct 2026.

## Placed in

- Vision-language-action models / [Human-video and latent-action pretraining](https://mlsanity.com/vla/human-video-and-latent-action-pretraining/)

## Abstract (arXiv)

Vision-language-action (VLA) models have shown strong potential for general-purpose robotic manipulation, but extending them to bimanual dexterous manipulation introduces a high-dimensional and structured action space. Existing bimanual VLA policies commonly concatenate right- and left-side arm--hand actions at each control timestep, leaving cross-hand interactions implicit within a single action vector. We introduce Coordi-π, a structured action representation for bimanual dexterous manipulation. Coordi-π represents the right- and left-side arm--hand actions as individual action tokens and organizes them into an interleaved sequence, explicitly exposing the two sides within the action sequence. To explicitly encode hand identity and temporal synchronization in this interleaved representation, a learnable hand-identity embedding distinguishes the two sides, while sequence--control-timestep factorized rotary positional encoding (RoPE) separates sequence position from control timestep, allowing actions at the same control timestep to share a temporal coordinate while retaining distinct sequence positions. Across all five bimanual dexterous manipulation tasks in DexJoCo, Coordi-π achieves state-of-the-art performance under both textitrand-obj and textitrand-full, improving the average success rate over π0.5 from 31.9% to 51.3% and from 18.3% to 32.3%, respectively. Coordi-π also consistently outperforms π0.5 across four real-world bimanual dexterous manipulation tasks.