Logistics video data for physical AI
Plan logistics video around picking, packing and sorting, with useful task boundaries, shipment privacy and observable completion criteria.
Logistics footage becomes useful when it captures the decisions and object movements inside a defined workflow. Picking, packing and sorting may look similar at a distance, but each has different start conditions and completion criteria. Define the workflow, the item references and the required viewpoint before collecting long stretches of warehouse activity.
The camera should observe an approved operation without changing the way the site controls movement or handles goods. For early protocol testing, authorized demonstration items and non-sensitive labels can make the relevant actions easier to inspect without exposing real shipment information.
Tasks to include in the brief
Picking from a location
Show the source shelf or bin, the selected item and the destination tote. Include ordinary reselection or hesitation when it helps explain the choice, without revealing customer-specific instructions.
Packing a parcel
Capture positioning approved items, arranging packaging and closing the carton. State whether the objective concerns action order, spatial arrangement or the visible completion of the packing sequence.
Sorting into containers
Use documented categories and visible destinations. Similar-looking items can test discrimination, but the intended category should be supplied as context rather than guessed from the video afterward.
Returning an item
Record an approved return-to-location sequence. A wrong initial position followed by a natural correction can provide useful recovery behavior when the final location is observable and authorized.
Capture requirements
- Preserve the full handoff between source, hand and destination. A close view of the item alone may lose the bin choice that gives the action meaning.
- Record item dimensions, packaging type and declared task context separately. Do not rely on reading operational labels or internal screens to reconstruct the workflow.
- Vary shelf arrangements, container shapes, object appearance and ordinary lighting within approved areas. Retain session identifiers to distinguish coverage from repeated footage of one station.
- Define completion visibly: item placed, carton closed or object returned. A movement that leaves the frame should not automatically receive a successful placement label.
Useful annotation layers
- Useful labels include reach, pick, inspect, transfer, place, fold and close. Track a consistent object reference across the sequence when the research objective requires identity persistence.
- Record declared item classes and destination rules separately from visual observations. A model seeing a barcode does not establish the shipment’s correct business destination.
- Human video supplies no measured robot grasp pose, load weight, inventory truth or conveyor control signal. Dedicated telemetry and task-specific validation need a separate brief.
Permissions, boundaries and exclusions
- Keep addresses, order numbers, shipping barcodes, customer names and internal stock systems out of view unless their specific capture has been approved and appropriately scoped.
- Do not enter vehicle routes, climb storage equipment, change lifting practices or interfere with active conveyors for recording. The workplace’s existing operating arrangements take precedence over camera coverage.
- Avoid capturing unrelated employees or commercial partners. Do not stage dropped loads, blocked aisles or misrouted real shipments to create negative examples.