MCAP Robot Logs to Training Set: How to Audit with FiftyOne

FiftyOne 1.19+ provides a workflow for converting accumulated MCAP robot logs into auditable, reproducible training datasets by directly ingesting each recording as a multimodal sample without conversion or custom parsing. Demonstrated using an ungated subset of ABC-130k, a large open bimanual teleoperation dataset, the process enables synchronized playback of camera feeds and robot telemetry while preserving metadata such as task, station, duration, and sensor configuration. To audit a corpus at scale, one representative frame per episode is embedded with CLIP and projected with UMAP, producing an interactive visual map that can reveal task coverage, camera or station differences, outliers, and possible failure patterns. Users can lasso regions of this embedding map to select candidate training data, supplementing visual inspection with reports on task counts, station mix, durations, and cameras. Curation is expressed as a documented dataset filter and exported as a lossless FiftyOne dataset, a manifest for training pipelines, and a recipe file recording the selection criteria, allowing teams to inspect, defend, and reproduce the path from recorded sessions to training-ready data.

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