ResearchResearch paperRobotics & Embodied AI1 source · Oct 14, 2026

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

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.

Key points

  • 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.

Sources (1)

  • [1]Coordi-pi: Coordination-Aware Dual-Hand Action Representation for Bimanual Dexterous Manipulation
    arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 14, 08:08 AM
    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.

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 14, 2026Back on Track: Deployment-time Policy Improvement via World Model Planning
  2. Oct 14, 2026MorphAct: Robot Policies Morphing with the Worlds They Act In
  3. Oct 14, 2026G^3VLA: Geometric Inductive Bias for Vision-Language-Action Models
  4. Oct 13, 2026Breaking the Average: Overcoming Convergent Defaults in Robotic Manipulation via Diagnostic Chain-of-Thought and Structured Guidance
  5. Oct 13, 2026WAVE-0: Bridging VLA Policies and WAMs with Lightweight Latent Future Prediction
  6. Oct 13, 2026GreenWAM: A World Foundation Model for Robotics

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