RGB-D Manipulation Dataset

Paired RGB-D recordings of robot manipulation with 3D grasp annotations and force measurements for training depth-aware grasping policies.

Dataset at a Glance

65K+
Video clips
400+
Hours recorded
30+ setups
Environments
6+
Annotation layers

Comparison with Public Datasets

How Claru's dataset compares to publicly available alternatives.

DatasetClipsHoursModalitiesEnvironmentsAnnotations
GraspNet-1Billion97K grasps~10RGB-D190 scenes (lab)6-DoF grasps
ACRONYM8.8M graspsN/A (sim)Synthetic depthSimulatedGrasp labels
Claru RGB-D Manipulation65K+400+RGB-D, F/T30+ real setups3D grasps, poses, forces, trajectories

Use Cases

6-DoF Grasp Planning

Predicting stable grasps using depth for geometry estimation. Example models: GraspNet, Contact-GraspNet, AnyGrasp.

Depth-Conditioned Policies

Policies using depth for spatial reasoning and collision avoidance. Example models: PerAct, 3D Diffusion Policy, RVT.

Object Pose Estimation

Estimating 6-DoF poses from RGB-D for manipulation planning. Example models: FoundationPose, MegaPose, BundleSDF.

Key References

  1. [1]Fang et al.. GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping.” CVPR 2020, 2020. Link
  2. [2]Sundermeyer et al.. Contact-GraspNet: Efficient 6-DoF Grasp Generation.” ICRA 2021, 2021. Link
  3. [3]Wen et al.. FoundationPose: Unified 6D Pose Estimation and Tracking.” CVPR 2024, 2024. Link

How Claru Delivers This Data

Claru captures RGB-D manipulation data with diverse real objects — not just YCB benchmarks. Force/torque sensing adds the contact dynamics dimension pure depth datasets lack.

Frequently Asked Questions

Factory-calibrated RealSense cameras with sub-pixel alignment, validated per-session with checkerboard targets.

500+ unique objects spanning household items, tools, food, and industrial components in varying materials and sizes.

Force/torque contact detection combined with depth-based 3D localization, recording 6-DoF approach poses and grasp types.

Request a Sample Pack

Get a curated sample of rgb-d manipulation data with full annotations to evaluate for your project.