Custom vs Off-the-Shelf Robotics Datasets

Does a public dataset already cover your skill and environment?

Ego4D and EgoScale offer broad scale for pretraining; EgoDex offers strong hand pose. None is built to a specific manipulation skill in a specific environment — check /compare/best-egocentric-video-datasets-for-robotics before assuming a gap needs custom capture.

Does the license allow what you need?

CC BY-NC and CC BY-NC-ND datasets prohibit commercial training. Confirm current license text before building a roadmap around any public corpus — see /compare/public-dataset-licenses and /guides/research-only-vs-commercial-dataset-licenses.

Do you need synchronized depth, IMU or 3D hand pose?

Manipulation and whole-body policies often need metric depth and hand pose the public corpora do not carry throughout. Custom collection ships these as standard streams.

Do you need buyer-owned rights to the data and derived models?

A public dataset's terms apply to everyone who uses it. Custom collection is delivered on a license written for your engagement — see /guides/buyer-owned-training-data.

Can you combine both?

A common pattern is broad pretraining on a public corpus, then fine-tuning on a smaller custom batch collected to the target skill and environment.

• Assuming "public" means "commercially licensed" — several of the largest egocentric datasets are non-commercial.
• Committing to custom collection before checking whether an existing public dataset already covers the skill and environment.
• Mixing data with different sync guarantees into one training run without checking each source's method.
• Building a product roadmap around a dataset before confirming its current license terms, which can change between releases.

• On-demand data collection vs dataset marketplacesCommissioning capture to your spec versus buying footage a marketplace already lists.

Need footage captured to your own spec? Request a custom dataset.

• Stereo Cameras vs RGB-D Sensors for Robotics DataStereo cameras vs RGB-D sensors for robotics data collection: how each produces depth, egocentric fit, calibration and sync, and when to choose each.
• Egocentric Pretraining Datasets ComparedEgoScale, EgoVerse and Egocentric-10K compared for robot pretraining: scale, labels and license, and what a custom collection adds.
• Human Demonstration Data vs Teleoperation DataHuman egocentric demonstration versus robot teleoperation for training data: embodiment fit, scale, cost, and when each — or a blend — is the right call.
• Head Cameras vs Wrist Cameras for Robot LearningWhat a head-mounted camera sees versus a wrist camera, why manipulation policies need both, and how Firsthand hardware-syncs them onto one clock.
• Global Shutter vs Rolling Shutter for Robotics DataWhy rolling-shutter skew corrupts fast-motion frames in egocentric capture, and why global-shutter cameras keep geometry consistent with depth and pose.