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Home Technology Robotics

FANUC Unveils 5 Robotic Systems for Warehouse Automation at MODEX 2026

2026/03/30
in Robotics, Technology
0 0
FANUC Unveils 5 Robotic Systems for Warehouse Automation at MODEX 2026

According to www.newswire.ca, FANUC America will demonstrate five high-performance robotic systems targeting warehousing, logistics, and supply chain operations at MODEX 2026, held April 13–16 at the Georgia World Congress Center in Atlanta.

CRX-30iA + OTTO 600 AMR: First Integrated Mobile Manipulator Demo

New to FANUC’s MODEX lineup is the CRX-30iA mobile manipulator, paired with the OTTO 600 Autonomous Mobile Robot (AMR) from Rockwell Automation. This fully integrated system performs palletizing in warehouse, fulfillment, and distribution environments—replacing ergonomically taxing manual tasks while sustaining high throughput. The CRX-30iA operates at its top collaborative speed, and the AMR travels up to 2 meters per second.

AI-enhanced perception tools enable dynamic adaptation: payload estimation, box-locating vision (via robot-mounted 3DV/400 sensor), and barcode-based decision logic allow real-time responses to variable box sizes, pallet conditions, and routing needs. Safety is maintained through an intelligent architecture using area scanners and smart speed control—slowing automatically when workers approach, enabling fenceless collaboration.

The demonstration includes:

  • CRX-30iA palletizing from quarter pallets to full pallets
  • AMR transporting multiple boxes simultaneously to build full pallets
  • iRVision barcode scanning for routing, sorting, and verification
  • Full repalletizing and depalletizing sequences (quarter to full pallet)
  • AI-assisted perception for dynamic box recognition, precise positioning, and adaptive palletizing logic

Three Additional Real-World Logistics Demonstrations

FANUC will also showcase three other production-ready solutions:

  • Interactive Box Scanning: Featuring the CRX-10iA collaborative robot, with hands-on programming via free-hand teach, drag-and-drop interface, and a custom Tablet Teach Pendant; uses 3DV/200 vision sensor for label inspection and barcode reading.
  • Tote Consolidation: Using the M-10/12-14D industrial robot, combining 2D iRVision cameras (for bin barcode reading), 3DV/600 3D sensor (to locate items), and an integrated RFID reader to identify and consolidate SKUs into totes—an intelligent identification workflow for complex e-commerce fulfillment.
  • Flexible Palletizing and Depalletizing: Featuring the M-710/50-26D robot equipped with 3DV/1600 3D vision sensor and FANUC iPC Box, powering the AI Box Locator tool to detect boxes—even under challenging, low-contrast or irregular stacking patterns—and execute precise depalletizing, repalletizing, and slip-sheet handling between layers.

“MODEX is where the supply chain industry comes to see what’s next, and FANUC’s products and technologies show how we can help customers solve their toughest fulfillment and logistics challenges.” — Jim Cooper, General Manager, U.S. General Industry Sales, FANUC America

This MODEX 2026 presence reflects broader industry momentum toward integrated, AI-augmented intralogistics. According to MHI and Deloitte’s 2024 Annual Industry Report, 82% of supply chain leaders now deploy or plan to deploy AMRs within two years, and 71% cite labor shortages as the top driver. FANUC’s integration of collaborative robotics with Rockwell’s OTTO platform aligns with growing adoption of vendor-agnostic interoperability standards such as VDA 5050 and MassRobotics AMR Interoperability Framework—mirroring similar integrations recently demonstrated by Locus Robotics with Boston Dynamics’ Stretch and by Amazon Robotics with KION Group’s Dematic systems. For practitioners, these demonstrations signal a shift from isolated automation islands toward coordinated, perception-driven workflows—where real-time vision, payload-aware motion planning, and safety-certified autonomy converge to reduce reliance on fixed infrastructure and manual intervention.

Source: www.newswire.ca

Compiled from international media by the SCI.AI editorial team.

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