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Description
ZIMBOT's demonstration data for a cup manipulation task, last updated April 16, 2026. The dataset likely contains RGB camera observations, end-effector trajectories, gripper states, and action sequences. It is stored in a Zarr archive format for direct programmatic access.
Use Cases
Train imitation learning models based on the recorded action sequences and trajectories.
Benchmark robotic control policies using the provided end-effector position and rotation data.
Develop computer vision models for robotic tasks using the RGB observations.
Analyze gripper state dynamics for manipulation tasks based on the gripper width data.
Strengths
Contains multiple synchronized data modalities: RGB video, robot poses, and gripper states.
Data is stored in Zarr format, which is suitable for efficient, chunked access common in machine learning workflows.
Last update timestamp of 2026-04-16 suggests recent maintenance.
Limitations
Row count and dataset scale are unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
ZIMBOT
Collection Method
Demonstration data for a specific robotic manipulation task.
Time Range
null
Freshness
Last updated 2026-04-16 08:03:18; freshness should be verified.
Geography
null
License is unknown; terms of use must be verified before application.