The Next-Generation Solution of Intra-Logistics Fulfillment
with Siemens, Universal Robots, and Zivid
The webinar will have two sessions to accommodate everyone around the globe - choose above the one that best suits your time zone.
Discover the cutting-edge advancements in intra-logistics fulfillment offered by Siemens, Universal Robots, and Zivid.
The demanding world of warehouse automation has been at the vanguard of robotic automation deployment for many years. Modern fulfillment centers are alive with automated transport of thousands or millions of SKUs (stock-keeping units). While automation thrives in these centers, one stubborn problem has remained: reliable picking of all items, regardless of opacity, transparency, shape, or size.
Live from UR's headquarters in Denmark, the event will introduce a solution for logistics and e-commerce automation made possible by Siemens, Universal Robots, and Zivid. Together, they show how easily you can integrate and deploy a powerful picking solution with the right partners.
Agenda:
- Background and challenges of the industry
- The role of 3D vision and its limitations
- The solution
- Live demo
- Audience Q&A with Universal Robots, Siemens and Zivid
About the technologies:
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Siemens: SIMATIC Robot Pick AI is a pre-trained, deep learning-based vision software for piece-picking robot applications and beyond. It enables robots to perform previously manual-only tasks, such as picking and placing unknown objects, empowering the industry.
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Universal Robots: The UR20 offers the longest reach of all UR's heavy payload cobots. Thanks to its incredibly small footprint, this industrial collaborative robot enables you to automate more applications where heavy objects must be lifted over a longer distance.
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Zivid: Designed to optimize your robot's performance in pick & place applications, the Zivid 2+ M130 camera can see everything in the bin without compromising on speed. This is the first 3D camera in the world that can image transparent surfaces, making it ideal for order fulfillment tasks.
