Pick, place & grasping
7Grasping, pick-and-place, and object transfer with robot arms or hands.
Research topic · Robot manipulation
Every record here is a published, source-linked manipulation corpus. Compare what actually decides transfer: episodes, embodiment, camera views, action signals, and usage terms.
A manipulation dataset is only comparable on the fields the source actually reports. These are the axes this topic keeps visible on every record; anything the source does not report stays unreported instead of being estimated.
01
The record's own headline stat (episodes, trajectories, hours). Scale claims stay source-linked; missing scale stays missing.
02
Which arm, hand, or humanoid the trajectories were recorded on — the field a cross-embodiment transfer depends on most.
03
Wrist, external, and depth views reported by the source. View placement drives policy observability.
04
Joint states, end-effector poses, proprioception, or teleoperation traces — what a policy can actually learn to output.
05
Open access is not a usage license. Each record links the official source for current terms.
Grouped by task
Records enter this topic through the published Catalog's manipulation classification; every card links the official source for access and terms. Groups are navigation aids derived from each record's own task labels and description — the record remains authoritative, and unmatched records stay under “General manipulation”.
Records can also appear in the VLA training data topic, which groups the same corpora by training stage instead of task.
Grasping, pick-and-place, and object transfer with robot arms or hands.
Dexterous hands, in-hand reorientation, and fine fingertip control.
Two-arm coordination and bimanual platforms such as ALOHA-class rigs.
Folding, wiping, cleaning, and other deformable-object or contact-rich work.
Multi-robot corpora used to pretrain or transfer manipulation policies.
Failures, interventions, corrections, and recovery during manipulation.
Manipulation records whose own labels do not match a task group yet.
Task groups are derived from each record's own labels and description; they do not replace the record. Use All tasks to see every record.
8 shown · 166 total
lerobot · 2026
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebaseversion": "v3.0", "fps": 30, "features": { "observation.state": { "dtype": "float32", "shape": [ 14 ], "names": [ "leftarmjoint1", "leftarmjoint2", "leftarmjoint3", "leftarmjoint4", "leftarmjoint5"… See the full description on the dataset page:…
lerobot · 2026
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebaseversion": "v3.0", "fps": 30, "features": { "observation.state": { "dtype": "float32", "shape": [ 14 ], "names": [ "leftarmjoint1", "leftarmjoint2", "leftarmjoint3", "leftarmjoint4", "leftarmjoint5"… See the full description on the dataset page:…
lerobot · 2026
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebaseversion": "v3.0", "fps": 30, "features": { "observation.state": { "dtype": "float32", "shape": [ 14 ], "names": [ "leftarmjoint1", "leftarmjoint2", "leftarmjoint3", "leftarmjoint4", "leftarmjoint5"… See the full description on the dataset page:…
UC Berkeley / MIT / Amazon FAR / CMU / XDOF · 2026
ABC-130k is an open bimanual robot manipulation dataset released with the paper 'Scalable Behavior Cloning with Open Data, Training, and Evaluation'. It contains roughly 130,919 episodes (43,090 annotated) totaling about 3,598 hours collected on bimanual YAM stations with two 6-DoF arms and parallel-jaw grippers, spanning ~195 tasks such as pick-and-place,…
130.9K episodes · parallel_jaw · aloha
FFTAI · 2025
ActionNet: A Dataset for Dexterous Bimanual Manipulation
30K trajectories Source-reported scale
Publisher not recorded · 2025
AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
1M trajectories Source-reported scale
agibot-world · 2026
AgiBot World 2026 Real-World Embodied Intelligence Dataset Overview As robotics research advances into real-world scenarios, the demand for authentic, high-quality data has become increasingly urgent. Following AGIBOT WORLD's "ImageNet moment," we now release the AGIBOT WORLD 2026 dataset. Built upon massive real-world scenes, it systematically spans…
13.56TB repository size
AIRoA (AI Robot Association) · 2025
The AIRoA MoMa Dataset is a large-scale, real-world dataset for mobile manipulation collected with the Toyota Human Support Robot (HSR) via leader-follower teleoperation in household environments. It contains 25,469 episodes (~94 hours) sampled at 30 Hz, with synchronized RGB images from head and wrist cameras, joint states, six-axis wrist force-torque…
25.5K episodes
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