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Warehouse Robotics

Break Through Supply Chain Blocks with Automated Container Unloading

Customers finding bare spots on grocery store shelves or waiting months instead of weeks for a furniture delivery are feeling the ripple effects of supply chain disruptions—with more shortages and delays anticipated as the holiday season approaches.

Much of the merchandise is out there, stalled in cargo ports loaded with shipping containers at unprecedented volumes. Labor shortages have slowed the pace of unloading containers and warehouses to a crawl, and ports on both U.S. coasts have required ships to idle at sea for days until space opens up in the yards. Those delays are straining the supply of cargo containers at a time when demand for goods is hardly slowing down—rather, U.S. imports are projected to rise through the end of the year.  

Why Warehouse Automation Needs Purpose-Built Computer Vision

On the surface, automated depalletizing looks relatively straightforward. A computer vision system identifies a box and then a robotic arm with a gripper lifts the box off a pallet and onto a conveyor belt. However, solving carton location and path planning to successfully unpack a pallet requires highly advanced perception and intelligent vision processing algorithms.

How Flexibility Simplifies Warehouse Automation

Over the past year, COVID-19 has put a huge strain on warehouse operations—making hiring and staffing a challenge, while simultaneously accelerating the demand for fast, effective e-commerce services. Even as social distancing restrictions lift, e-commerce adoption rates continue to rise dramatically, highlighting the need for ongoing solutions to fulfillment, shipping, and delivery challenges. The warehousing industry is primed for an automation boom to support this new landscape.