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LeRobot datasets

A growing collection and tooling ecosystem for sharing real and simulated robot learning data.

About

LeRobot provides common tooling around robot datasets, policies, and evaluation workflows. Individual datasets have their own hardware, task, and licensing context, so the catalog is best treated as a family rather than one homogeneous corpus.

Use this entry as a launch point for selecting a concrete dataset, validating its schema, and turning a few episodes into an inspectable baseline before scaling out.

Suggested agent workflows

Copy a prompt into your agent of choice. Each workflow starts small, respects the source terms, and makes the result inspectable in Rerun.

Audit a training slice

Fetch LeRobot datasets from its official source at https://huggingface.co/lerobot. Read and preserve its source terms and citation requirements. Build a reproducible manifest for a representative slice, then load it into Rerun. Inspect the RGB video, Robot state, Actions streams for timestamp gaps, missing samples, calibration problems, and annotation inconsistencies. Summarize the findings and save both the validation script and a Rerun recording that makes every issue easy to review.

Build a baseline pipeline

Use LeRobot datasets to scaffold a baseline pipeline for Imitation learning, Manipulation. Start with a small deterministic cohort and document the selection criteria. Create the dataset adapter, preprocessing steps, train and validation splits, and one lightweight baseline. Log inputs, labels, predictions, losses, and representative failures to Rerun so I can inspect the full experiment timeline. Include exact setup and reproduction commands.

Find useful failure cohorts

Analyze LeRobot datasets and propose a practical cohort taxonomy for Imitation learning, Manipulation. Use available metadata and the RGB video, Robot state, Actions signals to identify hard cases, rare conditions, coverage gaps, and possible leakage between splits. Materialize the cohorts as queryable metadata, log examples from each cohort to Rerun, and produce a short report explaining which cohorts should become regression tests. Do not infer labels that are not present in the source data.