Case Studies
Real-world use cases from businesses leveraging Luxonis for smarter vision systems.
Proven applications for
Logistics & Warehousing
These are the field-proven scenarios where OAK consistently fits best.
Autonomous Forklifts
Detect pallets, racks, lanes, and nearby workers in real time so autonomous forklifts can move safely through busy warehouse environments.
Recommended device
OAK 4 D
OAK-D S2 PoE
Why Choose Luxonis
Find out what advantages our products offer specifically for your industry.
Active vision for hard surfaces
ToF and active stereo help preserve reliable depth on reflective packaging, low-texture cartons, and dim warehouse scenes where passive depth often struggles.
On-device edge inference
Real-time scanning, tracking, and perception stay responsive on the camera instead of waiting on congested Wi-Fi or overloaded backend systems.
Open Source ecosystem
Use our open source DepthAI Library to quickly deploy standard machine vision use cases, and then add additional functionality and customization as your environment demands it.
Cost Efficient
Ditch costly and closed traditional machine vision systems for affordable, performant, and flexible OAK ecosystem.
Precise Dimensioning
Combine ToF and high resolution stereo sensors to accurately dimension boxes, parcels, pallets, shelves, and empty spaces.
Simplified fleet operations
Manage warehouse camera fleets remotely with device health monitoring, updates, and deployment visibility that scale beyond a single facility.
PoE-ready deployment
PoE simplifies long cable runs, fixed scanner installs, and rugged deployments across docks, cells, and fulfillment infrastructure.
Active vision for hard surfaces
ToF and active stereo help preserve reliable depth on reflective packaging, low-texture cartons, and dim warehouse scenes where passive depth often struggles.
Reflective packaging support
Better low-light perception
Works on sparse texture
Validate faster with prebuilt examples
Start with apps, reference implementations, and ready-to-evaluate models that help you prove an OAK-powered workflow before building everything from zero.
Industry Examples
References that show how OAK fits measurement, warehouse automation, and robot-assisted logistics workflows.
Devlog
Box measurement with AI and ToF
A practical reference for depth-driven volumetric measurement in parcel workflows.
Devlog
High frame rate neural networks at 480 FPS
A useful reference for fast-moving parcels, sortation flows, and other logistics scenarios where very high frame rates improve tracking reliability.
Hub Apps
Quick validation tools for dimensioning, code reading, and proof-of-concept warehouse workflows.
OAK Examples
Engineering building blocks that map directly to sortation, mobile robotics, and warehouse perception.
Final PoC
Barcode Detection Conveyor Belt
A ready-made starting point for package scanning and routing workflows.
PoC
Box Measurement
A practical baseline for parcel sizing and dimensional warehouse validation.
Strong starting point
Spatial Detections
Use 3D detections as a base for shelf interaction, obstacle awareness, and parcel handling.
Strong starting point
Collision Avoidance
A useful starting point for autonomous warehouse vehicles and robot safety loops.
Model Zoo
Ready-to-evaluate models for barcode reading, package segmentation, QR workflows, and warehouse-safety deployments.
Model Zoo
Barcode Detection
A practical barcode-reading model for conveyor, parcel-routing, and warehouse scanning workflows.
Model Zoo
Box Instance Segmentation
Useful for isolating parcels cleanly before dimensioning, tracking, or robotic handling.
Model Zoo
QRDet
A strong QR-code baseline for routing labels, tote identification, and warehouse automation.
Model Zoo
PPE Detection
A useful safety model for worker-awareness workflows in shared warehouse environments.