truelabel

DATASET FACET · MODALITY

Proprioception datasets for physical AI

Robot state streams such as joint positions, velocities, gripper state, and end-effector poses.

DIRECT ANSWER

Proprioception pages collect datasets where this modalityis 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

24 catalog entries

Commercial use
License
Task
Robot
Format

24 of 24 datasets

Open X-Embodiment

Published May 2026 · custom

A large cross-institution collection of robot demonstrations spanning many embodiments and manipulation tasks.

  • Multi-institution robot demonstration corpus; exact per-task scale varies by contributing dataset.
  • Commercial use unclear
  • Best for: robot foundation model pretraining
  • RGB-D
  • Proprioception
  • Robot Grasping

DROID

Published May 2026 · custom

A real-world robot manipulation dataset focused on diverse teleoperated demonstrations outside narrow lab-only settings.

  • Large real-world manipulation corpus; check source for current release counts.
  • Commercial use unclear
  • Best for: real-world manipulation pretraining
  • Teleoperation
  • RGB-D
  • Robot Grasping

BridgeData V2

Published May 2026 · custom

A robot manipulation dataset from Berkeley focused on real-world behavior cloning and task generalization.

  • Robot manipulation demonstrations across multiple tasks; source release describes exact split.
  • Commercial use unclear
  • Best for: behavior cloning
  • RGB-D
  • Proprioception
  • Robot Grasping

RT-1

Published May 2026 · custom

A robotics transformer data release associated with language-conditioned robot manipulation research.

  • Large language-conditioned robot demonstrations described in the source paper and project materials.
  • Commercial use unclear
  • Best for: language-conditioned robotics
  • RGB-D
  • Proprioception
  • Household Manipulation

ALOHA

Published May 2026 · custom

A low-cost bimanual teleoperation platform and dataset family used for imitation learning in dexterous manipulation.

  • Task-specific demonstrations released around the ALOHA platform and follow-on projects.
  • Commercial use unclear
  • Best for: bimanual imitation learning
  • Teleoperation
  • RGB-D
  • Bimanual Manipulation

RoboMimic

Published May 2026 · mit

A benchmark and dataset framework for robot imitation learning with standardized tasks and evaluation utilities.

  • Benchmark datasets and demonstration formats vary by task suite.
  • Source appears permissive; verify data terms
  • Best for: imitation-learning baselines
  • Proprioception
  • RGB-D
  • Robot Grasping

RoboNet

Published May 2026 · custom

A multi-robot dataset for visual foresight and manipulation policy research.

  • Multi-robot manipulation dataset; source materials specify exact robot/task counts.
  • Commercial use unclear
  • Best for: visual dynamics
  • RGB-D
  • Proprioception
  • Robot Grasping

Meta-World

Published May 2026 · mit

A simulated manipulation benchmark for multi-task and meta-reinforcement learning.

  • Benchmark suite of simulated manipulation tasks.
  • Source appears permissive; verify data terms
  • Best for: multi-task RL
  • Proprioception
  • Robot Grasping

RLBench

Published May 2026 · custom

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

  • Large simulated task suite; source materials define current task count.
  • Commercial use unclear
  • Best for: simulated manipulation
  • RGB-D
  • Proprioception
  • Robot Grasping

CALVIN

Published May 2026 · custom

A benchmark for language-conditioned long-horizon robot manipulation in simulated environments.

  • Long-horizon simulated benchmark and demonstrations.
  • Commercial use unclear
  • Best for: language-conditioned policy evaluation
  • RGB-D
  • Proprioception
  • Household Manipulation

ManiSkill

Published May 2026 · apache-2

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

  • Simulation suite with tasks and environments maintained by the ManiSkill project.
  • Source appears permissive; verify data terms
  • Best for: simulated manipulation
  • RGB-D
  • Proprioception
  • Robot Grasping

BEHAVIOR

Published May 2026 · custom

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

  • Household activity benchmark and simulation assets.
  • Commercial use unclear
  • Best for: household task taxonomies
  • RGB-D
  • Proprioception
  • Household Manipulation

BC-Z

Published May 2026 · custom

A behavior cloning project focused on zero-shot task generalization for robots.

  • Task demonstrations and model references associated with the BC-Z project.
  • Commercial use unclear
  • Best for: behavior cloning
  • RGB-D
  • Proprioception
  • Robot Grasping

RoboSuite

Published May 2026 · mit

A simulation framework and benchmark suite for robot manipulation tasks.

  • Simulation tasks and assets for manipulation research.
  • Source appears permissive; verify data terms
  • Best for: robot manipulation simulation
  • RGB-D
  • Proprioception
  • Robot Grasping

RH20T

Published May 2026 · custom

A real-world contact-rich robot manipulation dataset with multimodal sensing, force, audio, and human demonstration video.

  • Source describes more than 110,000 contact-rich manipulation sequences with visual, force, audio, action, and human demonstration signals.
  • Commercial use unclear
  • Best for: contact-rich manipulation
  • Teleoperation
  • RGB-D
  • Robot Grasping

AgiBot World

Published May 2026 · custom

A large-scale real-world robot manipulation dataset family for fine-grained manipulation, tool use, and multi-robot collaboration.

  • Hugging Face organization page describes the Beta release as 1M+ trajectories and 2,976.4 hours across 217 tasks, 87 skills, 3,000+ objects, and 100+ real-world scenarios.
  • Commercial use unclear
  • Best for: large-scale manipulation pretraining
  • Teleoperation
  • RGB-D
  • Household Manipulation

RoboCasa

Published May 2026 · custom

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

  • RoboCasa365 source materials describe 365 everyday tasks, 2,500 kitchen environments, 600+ hours of human demonstration data, and 1,600+ hours of synthetic demonstrations.
  • Commercial use unclear
  • Best for: large-scale kitchen simulation
  • RGB-D
  • Proprioception
  • Household Manipulation

LIBERO

Published May 2026 · custom

A benchmark suite for lifelong robot learning and language-conditioned manipulation tasks.

  • Benchmark datasets are organized around multiple LIBERO task suites, including spatial, object, goal, and long-horizon manipulation variants.
  • Commercial use unclear
  • Best for: VLA benchmark evaluation
  • RGB-D
  • Proprioception
  • Robot Grasping

RoboSet

Published May 2026 · custom

A real-world multi-task kitchen manipulation dataset with teleoperated and kinesthetic demonstrations.

  • Source describes 30,050 trajectories, including 9,500 collected through teleoperation, across 12 skills and 38 tasks with four camera views.
  • Commercial use unclear
  • Best for: real-world kitchen manipulation
  • Teleoperation
  • RGB-D
  • Household Manipulation

RoboTurk

Published May 2026 · custom

A large-scale teleoperation data collection platform and dataset family for robot manipulation tasks.

  • Project materials describe over 100 hours of real robot data and thousands of successful manipulation demonstrations collected through remote users.
  • Commercial use unclear
  • Best for: teleoperation collection design
  • Teleoperation
  • RGB-D
  • Robot Grasping

UMI

Published May 2026 · custom

Universal Manipulation Interface is an in-the-wild human demonstration framework for transferring portable gripper data to robot policies.

  • Project materials emphasize portable in-the-wild data collection and fast demonstrations for tasks such as cup manipulation, dish washing, cloth folding, and dynamic tossing.
  • Commercial use unclear
  • Best for: portable in-the-wild demonstrations
  • Egocentric video
  • Teleoperation
  • Bimanual Manipulation

FurnitureBench

Published May 2026 · custom

A real-world long-horizon furniture assembly benchmark with successful demonstration data.

  • Documentation describes 219.6 hours and 5,100 successful furniture assembly demonstrations collected with controller and keyboard inputs.
  • Commercial use unclear
  • Best for: long-horizon assembly
  • Teleoperation
  • RGB-D
  • Furniture Assembly

TACO Play

Published May 2026 · custom

A kitchen robot manipulation dataset with Franka arm interaction data available through TensorFlow Datasets.

  • TensorFlow Datasets documentation lists TACO Play as Franka kitchen interaction data with train and test splits and a 47.77 GiB dataset size.
  • Commercial use unclear
  • Best for: TFDS robotics ingestion
  • RGB-D
  • Proprioception
  • Household Manipulation

LeRobot datasets

Published May 2026 · custom

A Hugging Face robotics dataset ecosystem and standardized dataset format for multimodal robot learning data.

  • LeRobot documentation describes a standardized dataset ecosystem on Hugging Face Hub using Parquet for tabular data and MP4 for video observations.
  • Commercial use unclear
  • Best for: robotics dataset distribution
  • Teleoperation
  • RGB-D
  • Robot Grasping

READ THE TAG WITH CARE

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.

Where to go next

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