Technical innovations in artificial intelligence and robotics have unlocked massive potential for retailers to automate the handling of diverse Stock Keeping Units (SKUs) in the order fulfillment process with human-like flexibility at high speed.
Traditional bin picking methods have given way to order fulfillment picking approaches, moving the complexity of the process from the hardware to the software. This is important because of the physical modifications required to meet supply chain variability today.
Furthermore, the pressure on distribution centers to transport materials quickly to meet customer expectations is so great that the implementation of intelligent technologies is necessary for companies to stay competitive and to provide reliable service.
For nearly a decade, Universal Logic, Inc. has tackled these complex issues and technological advances, integrating artificial intelligence (AI), sensing and robotics into automated solutions. As the need for on-time delivery accelerates, there will be more demand for robotic solutions that can handle environmental changes in real-time.
Universal Logic’s AI software platform, Neocortex®, enables robotic cells to handle the item diversity, container variation and process changes required for piece-picking order fulfillment without additional engineering or programming.
In 2016, Yaskawa Motoman collaborated with Universal Logic, Inc. to design and introduce the Neocortex® Goods to Robot (G2R) Cell, a complete, pre-engineered adaptive picking solution that uses intelligent 3D vision and interactive motion control to identify and handle unsorted items with a level of speed and accuracy that exceeds human ability. This workcell is the first plug-and-play robotic solution targeting high-mix / high-volume applications scaled to a human form factor.
Hob Wubbena, Vice President of Universal Logic Inc., recently shared the whitepaper, Achieving Reliable Flexibility @ Speed® in Robotics Order Fulfillment. This whitepaper discusses how the innovations in artificial intelligence and robotics are meeting the three requirements necessary for success in automating order fulfillment: flexibility, reliability and speed.