YuhongZhang/HORA-1

HORA: Hand–Object to Robot Action Dataset

Dataset Summary

HORA (Hand–Object to Robot Action) is a large-scale multimodal dataset that converts human hand–object interaction (HOI) demonstrations into robot-usable supervision for cross-embodiment learning. It combines HOI-style annotations (e.g., MANO hand parameters, object pose, contact) with embodied-robot learning signals (e.g., robot observations, end-effector trajectories) under a unified canonical action space. :contentReference[oaicite:5]{index=5} :contentReference[oaicite:6]{index=6}

HORA is constructed from three sources/subsets:

1. HORA(Mocap): custom multi-view motion capture system with tactile-sensor gloves (includes tactile maps).
2. HORA(Recordings): custom RGB(D) HOI recording setup (no tactile).
3. HORA(Public Dataset): derived from multiple public HOI datasets and retargeted to robot embodiments (6/7-DoF arms).

Overall scale: ~150k trajectories across all subsets.

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Key Features

• Unified multimodal representation across subsets, covering both HOI analysis and downstream robotic learning.
• HOI modalities: MANO hand parameters (pose/shape + global transform), object 6DoF pose, object assets, hand–object contact annotations.
• Robot modalities: wrist-view & third-person observations, and end-effector pose trajectories for robotic arms, all mapped to a canonical action space.
• Tactile (mocap subset): dense tactile map for both hand and object (plus object pose & assets).

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Dataset Statistics

Subset	Tactile	#Trajectories	Notes
HORA(Mocap)	✅	63,141	6-DoF object pose + assets + tactile map
HORA(Recordings)	❌	23,560	6-DoF object pose + assets
HORA(Public Dataset)	❌	66,924	retargeted cross-embodiment robot modalities
Total		~150k

Supported Tasks and Use Cases

HORA is suitable for:

• Imitation Learning (IL) / Visuomotor policy learning
• Vision–Language–Action (VLA) model training and evaluation
• HOI-centric research: contact analysis, pose/trajectory learning, hand/object dynamics

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Data Format

Example Episode Structure

Each episode/trajectory may include:

HOI fields

• hand_mano: MANO parameters (pose/shape, global rotation/translation)
• object_pose_6d: 6DoF object pose sequence
• contact: hand–object contact annotations
• object_asset: mesh/texture id or path

Robot fields

• obs_wrist_rgb
• obs_third_rgb
• ee_pose: end-effector pose trajectory (SE(3))
• gripper: gripper open/close command (optional)
• action_space: canonical action space metadata

Tactile fields (mocap only)

• tactile_hand: dense tactile map (time × sensors/vertices)
• tactile_object: dense tactile map

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