Egocentric Hotel Lobby and Common Area Cleaning Data

Egocentric hotel lobby and common area cleaning data is first-person video of one hospitality task: vacuuming and mopping lobby floors, dusting furniture, polishing glass and emptying bins. It is recorded from the cleaner viewpoint, close to what a robot onboard camera would see while working a public area, with depth, 3D hand pose, contact events and frame-accurate action segments aligned on one hardware clock. Teams searching for lobby cleaning robot training data, egocentric hotel common area cleaning video or a hospitality public area cleaning dataset are usually looking for this.

On this site the data is human capture: a paid, consented contributor wears the rig and performs the task from a written skill spec. It is not robot or teleoperation data. It is custom hotel data collection rather than a ready-made library, with the task written down, collected on demand and delivered as validated episodes.

The task catalog states one row for this task: Lobby & Common-Area Cleaning, in the Hotel & Lodging environment. It is rated Easy, its capture mode is Phone (head-mounted) / multiview rig, and it is listed as Ready to deploy.

This page claims no delivered hours, and no hotel lobby footage is published on the site. The first table below gives the row exactly as the catalog words it.

The row reads "Vacuum and mop lobby floors, dust furniture, polish glass and empty bins." The site states the physical chores only: vacuuming and mopping floors, dusting furniture, polishing glass and emptying bins. It names no cleaning product, no chemical, no brand of equipment, no hotel and no cleaning time, and it does not say what a finished lobby looks like.

Because the site states none of those details, this page does not either. Which chores are in scope, where an episode starts and ends, and what counts as finished are agreed in the written spec. The second table below sets each item against what the site does and does not state.

Several of the chores also appear as separate rows elsewhere in the catalog. Vacuuming and Mopping are rows in the Commercial Cleaning & Janitorial environment, both Easy and Active collection. A guest-room row, "Vacuum and dust guest rooms using a vacuum cleaner and microfiber cloths", sits in Hotel & Lodging and is Easy and Ready to deploy. The trash and recycling page lists the lobby row under bin emptying.

The catalog has no separate glass-polishing row, so the glass chore here comes only from the lobby row. The third table below sets the overlap out with each status as the catalog lists it.

A head-mounted phone records the first-person view, and a multiview rig adds synchronized third-person angles when the spec asks for them. A wrist-mounted camera is available alongside the head camera for close-range detail. Each episode follows the episode schema used across Firsthand custom collections: ten streams synced under 2 ms, with head and wrist RGB, depth, 3D hand pose with per-joint visibility, contact and grasp events, and frame-accurate action segments.

For lobby work, contact events mark when the fingers make and break contact with a vacuum, a mop, a cloth or a bin, and action segments mark where one chore ends and the next begins. Depth is delivered with distance-invalid pixels flagged rather than interpolated; the site does not say how that applies to lobby glass, so this page makes no precision claim. The site states no camera count, resolution, frame rate or pace measurement. The fourth table below lists each stream and label.

The hotel room turnover pages cover resetting a guest room after checkout, which the site treats as back-of-house work. This page covers a shared area of the same environment, so the chores and the bystander picture differ.

The commercial janitorial page covers the wider office and building cleaning environment, the floor cleaning page covers mopping, sweeping and vacuuming across settings, and the trash and recycling page covers waste rows. The fifth table below sets them side by side, with each status as the site states it.

No. No dataset on the off-the-shelf pages is listed for lobby or common-area cleaning. One stereo dataset, S2, names hotels among its environments alongside bed making, but it lists no lobby or common-area task, so this is custom collection. The row is Ready to deploy, and the collection is scoped to a written spec, on demand.

Every episode links to a signed contributor release through a documented consent chain, and the consent record is part of the delivery. Faces, plates and screens are detected and irreversibly blurred at ingest, and a reviewer confirms the result before anything ships. Clips that cannot be de-identified are discarded. The anonymization record is delivered with the data.

The site treats room turnover as back-of-house work and describes guest-facing capture as a different bystander picture, but it states no separate lobby rule. Settle in the spec when capture happens and who may be in frame.

Delivery formats are RLDS, LeRobot and WebDataset, plus HDF5, zarr and Rerun .rrd. The first three are the training-loader formats; HDF5 and zarr carry arrays for custom pipelines, and Rerun .rrd gives a multi-stream synchronized playback file for review. The sixth table below sets each against what its official documentation states. The site states one task instruction per episode as the language data for a Firsthand capture.

Every batch is validated against signed accept criteria before it ships, with a reject log, and delivery is rolling, per validated batch.

Where coverage is already deep, the first validated batch lands in a median of 48 hours from signed spec. Thin environments typically take three to four weeks, because vetting operators there is the bottleneck, and we quote that timeline up front.

The site does not state whether hotel lobbies count as deep or thin coverage, so the timeline is quoted against your spec. On-demand top-ups run against the same spec and accept criteria after each training run.

You describe the work your policy needs: which chores, the start state and the end state, and the setting. We turn that into a written spec covering the steps, the environment, the capture tier, annotation depth, the bystander rules and accept criteria, then quote reach, timeline and price against that document before any capture begins. The last table below lists each element.

A Spec Pilot, a small and fast first batch, can prove the spec and the accept criteria before you scale volume. Billing is per validated hour, a reject log ships with every batch, and rejected items are recaptured at our cost.