Depalletizing and Palletizing Vision AI

See every case on every pallet in and out, guide the pick, verify the build, and catch the load that will lean before it leaves the dock.
Shipping container with OCR output

Depalletizing and Palletizing Vision AI Across Receiving, Fulfillment, Production, and Shipping

Deploy Anywhere, Run Everywhere

Run depalletizing and palletizing vision on the cameras at your cells and docks and an edge device on-site, on-prem, air-gapped, in your VPC, or via API, wherever your receiving, palletizing, and shipping operations need it.

One Platform, Full Adoption

Tools every warehouse and plant team can adopt, from cell operators and dock leads to controls engineers, robotics integrators, and operations management, no separate ML team required to ship and own pallet models.

Secure, Compliant, and Audit-Ready

Data stays safe with SOC 2 Type II compliance, encrypted data, and an uptime SLA, with an image record of every pallet received and shipped that supports receiving discrepancies, customer compliance, and chargeback disputes.
Mixed-Case Segmentation & Pick Sequencing
Slip Sheet, Wrap & Damage Detection
Inbound Pallet vs. ASN Verification
Layer-by-Layer Build Verification
Overhang, Lean & Stability Detection
Finished Pallet & Load Records
Mixed-Case Segmentation & Pick Sequencing
Slip Sheet, Wrap & Damage Detection
Inbound Pallet vs. ASN Verification
Layer-by-Layer Build Verification
Overhang, Lean & Stability Detection
Finished Pallet & Load Records
Mixed-Case Segmentation & Pick Sequencing
Slip Sheet, Wrap & Damage Detection
Inbound Pallet vs. ASN Verification
Layer-by-Layer Build Verification
Overhang, Lean & Stability Detection
Finished Pallet & Load Records
Mixed-Case Segmentation & Pick Sequencing
Slip Sheet, Wrap & Damage Detection
Inbound Pallet vs. ASN Verification
Layer-by-Layer Build Verification
Overhang, Lean & Stability Detection
Finished Pallet & Load Records

Talk to a Vision AI engineer who's shipped vision on a live palletizing cell.

Bring us your toughest depalletizing or palletizing problem and we'll map a working solution.
  • Solution architecture for robotic and manual depalletizing at receiving, mixed-case and layer palletizing, and pallet build and load verification at shipping, alongside existing robot vision and WMS
  • Live demo on your cell or dock camera footage or pallet images, with the load type, mixed inbound, outbound build, or finished pallet, that costs you the most stoppages or chargebacks
  • Deployment options: existing cameras and an edge device at the cell or dock, on-prem, air-gapped, or VPC, with integration into WMS, WCS, robot controllers, and PLCs
  • ROI modeling against cell stoppages and manual intervention, receiving discrepancies, customer chargebacks and rejected pallets, rebuild labor, and manual depal ergonomics
  • We will connect you with an AI subject matter expert on our team based on your answers.
    What challenges would you like to solve with vision AI?
    Where will you run vision AI?
    Are you replacing a current solution with AI or will this be a new solution?
    How many detections do you anticipate per month?
    Describe the business problem you would like to solve.
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    Guide Every Pick, Verify Every Build, and Record Every Pallet, with Vision AI

    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:

    • Detect and segment every case, bag, tote, and tray on an inbound pallet, mixed or uniform, known SKU or never seen before, and give the robot or the operator the pick sequence and pick points for the top layer
    • Detect slip sheets, tier sheets, stretch wrap remnants, banding, and damaged or open cases before the pick, so the gripper takes the case and not the sheet
    • Verify inbound pallet contents against the ASN or PO by counting cases and reading labels, so a short or a wrong SKU is caught at receiving rather than at putaway

    Palletizing and Outbound:

    • Verify every placed case against the build plan during palletizing, position, orientation, label-out, and layer pattern, so a case out of place is corrected before the next layer is built on it
    • Detect overhang, leaning, gaps, crushed cases, and unstable stacks as the load builds, and hold the pallet before the wrapper or the forklift makes it worse
    • Verify the finished pallet, case count, SKU mix, height, wrap, corner boards, and label placement, against the order before it leaves the dock, with an image record of the load as shipped

    Cells, Safety, and Systems Integration:

    • Guide robotic depalletizers and palletizers with 2D and 3D vision on the cell's own cameras, and monitor manual stations for cycle time, ergonomics, and pick errors
    • Detect people inside the cell, pallets out of position, and obstructions on the conveyor, so the cell stops for the right reason and restarts without a walk
    • Push pick data, build verification, load records, and exceptions into WMS, WCS, robot controllers, and PLCs through API integration, with an image behind every pallet in and out

    More About Depalletizing and Palletizing Vision

    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.

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