

Whether you're running robotic or manual depalletizing at receiving, mixed-case palletizing at order fulfillment, layer palletizers at the end of a production line, or pallet build and load verification at shipping, Roboflow sees every case, layer, pallet, and load, guides the pick and the place, verifies the build, and turns every pallet into a record, from receiving to the truck.
Depalletizing and Inbound:
Palletizing and Outbound:
Cells, Safety, and Systems Integration:
What is depalletizing and palletizing vision with Vision AI?
Depalletizing and palletizing vision with vision AI uses cameras over inbound pallets, palletizing cells, and shipping docks and deep-learning models to detect and segment every case and object on a pallet, sequence and locate picks for robotic and manual depalletizing, detect slip sheets, wrap, and damage before the pick, verify inbound pallets against the ASN, verify every placed case and layer against the build plan during palletizing, detect overhang, leaning, and instability as the load builds, and verify the finished pallet against the order with an image record. It guides the robot and the operator, holds the pallet when something is wrong, and feeds pick data, build verification, and load records into WMS, WCS, robot controllers, and PLCs. For the pick-point guidance details of a robotic depalletizing cell, see robotic depalletizing vision system; for tracking pallets through the building, see pallet tracking.
Can it verify a pallet build well enough to catch what the customer will reject?
Yes. Retail and distribution customers reject pallets for reasons that are visible: wrong case count, wrong SKU mix, cases placed label-in so the scanner cannot read them, overhang past the pallet edge, leaning or unstable loads, crushed bottom cases, and missing or misplaced pallet labels. Vision verifies each of those against the build plan and the order as the pallet is built and again when it is finished, with a photo of the load as shipped attached to the shipment record, which is what settles a chargeback dispute. Models are trained on your case mix, your pallet patterns, and your customers' compliance requirements, and the finished-pallet check runs at the wrapper or the dock on the cameras already there.
Can it integrate with our WMS, robot controllers, and PLCs?
Yes. Roboflow Inference runs on an edge device at the cell or the dock and exposes a standard API and common industrial protocols, so pick data, build verification, load records, and exceptions flow into your existing systems: WMS and WCS platforms like Manhattan, Blue Yonder, and Körber, robot controllers from FANUC, ABB, KUKA, and Yaskawa and their palletizing software, PLCs from Allen-Bradley and Siemens for cell and conveyor control, ASN and receiving systems, and shipping and compliance records, through REST, MQTT, OPC UA, discrete I/O, and direct database writes. PLC-level integration holds the pallet when a case is out of place or a person is in the cell, and every event carries pallet ID, order or ASN, cell or dock, case count and SKU mix, timestamp, exception class, and the image, with a full record behind every pallet received and every pallet shipped.