truelabel

DATASET FACET · FORMAT

Point cloud datasets for physical AI

3D scene or object geometry represented as spatial points, often from depth sensors or reconstruction.

DIRECT ANSWER

Point cloud pages collect datasets where this formatis materially relevant, then add truelabel’s commercial use, consent risk, and deployment fit notes so buyers can decide whether public data is enough.

MATCHED DATASETS

10 catalog entries

Commercial use
License
Modality
Task
Robot

10 of 10 datasets

RLBench

Commercial use unclear · Large simulated task suite; source materials define current task count.

A simulated robot learning benchmark with many manipulation tasks in CoppeliaSim.

  • RGB-D
  • Proprioception
  • Robot Grasping

ManiSkill

Source appears permissive; verify data terms · Simulation suite with tasks and environments maintained by the ManiSkill project.

A simulation benchmark and toolkit for manipulation skills and embodied AI policy evaluation.

  • RGB-D
  • Proprioception
  • Robot Grasping

HOI4D

Commercial use unclear · Human-object interaction dataset with 4D annotations; exact release details live on the source site.

A 4D egocentric human-object interaction dataset with RGB-D and pose-oriented annotations.

  • Egocentric video
  • RGB-D
  • Human Object Interaction

DexYCB

Commercial use unclear · Dexterous grasping dataset with YCB objects and pose labels.

A dexterous hand-object interaction dataset centered on grasping YCB objects with 3D annotations.

  • RGB-D
  • Motion capture
  • Human Object Interaction

ScanNet

Commercial use restricted · Large indoor RGB-D scene reconstruction corpus.

An indoor RGB-D reconstruction dataset used for 3D scene understanding.

  • RGB-D
  • Point cloud
  • Navigation

Habitat datasets

Commercial use unclear · Multiple scene and task datasets under the AI Habitat ecosystem.

A family of embodied AI datasets and simulation assets for navigation and rearrangement research.

  • RGB-D
  • Point cloud
  • Navigation

BEHAVIOR

Commercial use unclear · Household activity benchmark and simulation assets.

A benchmark for household activities and embodied AI tasks in simulation.

  • RGB-D
  • Proprioception
  • Household Manipulation

Waymo Open Dataset

Commercial use restricted · Large autonomous driving scenes with cameras and LiDAR.

A large autonomous driving dataset with camera, LiDAR, and labeled traffic scenes.

  • RGB-D
  • Point cloud
  • Navigation

ObjectFolder

Commercial use unclear · Object-centric multimodal assets; source materials define current object count and modalities.

A dataset family for object-centric physical properties, geometry, and multimodal perception research.

  • RGB-D
  • Tactile
  • Robot Grasping

RoboCasa

Commercial use unclear · RoboCasa365 source materials describe 365 everyday tasks, 2,500 kitchen environments, 600+ hours of human demonstration data, and 1,600+ hours of synthetic demonstrations.

A large-scale kitchen simulation framework and dataset family for everyday manipulation tasks in diverse household environments.

  • RGB-D
  • Proprioception
  • Household Manipulation

FACET REVIEW PATHS

Do not treat this tag as the whole sourcing decision

Facet groupings are discovery aids, not final recommendations. A shared modality, task, robot, format, license, or commercial-use label only says that datasets are worth comparing; it does not prove that the source is safe, complete, or useful for a target model.

Use this grouping to shortlist candidates, then open the dataset profiles, run fit and license checks, and compare sources against the buyer's target environment. Thin tag results become useful only when they route the reader into deeper evidence and action surfaces.

The external references below keep the facet grounded in robotics data practice. They help reviewers understand why format, embodiment, trajectory quality, licensing, and real-world coverage matter before a team commits engineering time to ingestion.

When a facet has only a few matching datasets, treat that as a signal rather than a weakness. It may mean the public corpus is thin for that robot, task, or format, and the next move is a custom supplement with the facet written into acceptance criteria.

INTERNAL LINKS

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EXTERNAL REFERENCES

Source context to verify

TRUELABEL ROUTING

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