Universal Robots and RightHand Robotics deliver a piece-picking world record | Robotics

MODEX 2018, the largest supply chain event in the Americas, was the scene of a remarkable demo as

RightHand Robotics, a leader in robotic piece-picking solutions, drove a team of automation partners to set a world : Over the duration of the show at the Georgia Congress center in Atlanta, 131,072 items were successfully picked and placed. The work cells, all showcasing UR robots with RightHand Robotics’ RightPick machine learning software and grippers, were featured in five exhibitor booths at MODEX, demonstrating how robotic piece-picking increases the value of their respective solutions for e-commerce fulfillment and intralogistics.

What are the benefits of the RightPick application with UR robots? Watch MODEX exhibitors explain.

“We wanted to set a benchmark for piece-picking performance, and the show was a fantastic opportunity for it. We are grateful to our partners: Eurosort, Vecna Robotics, White Systems, and Universal Robots for helping us establish this record,” says Yaro Tenzer, co-founder of RightHand Robotics. “Our robots handle a wide range of everyday items at high throughput rates, delivering the reliability required by our customers. Sharing the final results from our MODEX fleet is a fun way to illustrate this point.”

RightHand’s team of four deployment engineers set up multiple work cells at the show in a day.

Utilizing collaborative robots from Universal Robots, the cells were integrated with sortation systems, automated storage and retrieval systems (AS/RS) and mobile robots at partner booths across both halls at the exhibition. “We are pleased that our collaborative robots were the workhorses behind this record performance,” says Esben Østergaard, CTO at Universal Robots. Depending on the workflow, the RightHand systems achieved pick rates up to 1,000 units per hour across an assortment of items, including products that the system had never seen before. “Robotic piece-picking is easy to deploy and can provide predictable capacity for our customers and those of our integration partners,” adds Tenzer.


Warehouse processes such as order fulfillment require the ability to recognize and pick a wide range of items that are different sizes, weights, and materials, often jumbled together in bins. While traditional industrial robots usually stay bolted down in protective cages, dedicated to one handling task only, the RightPick solution with Universal Robots effectively address this automation challenge with flexible implementation and low upfront cost.

RightPick is a hardware-enabled software solution that handles the key task of picking individual items in a variety of workflows within e-commerce order fulfillment centers, distribution centers and other warehouse and production environments. With RightPick, businesses can reduce costs and improve reliability of the fulfillment process for pharmaceuticals, electronics, grocery, apparel, and many other industries. Unlike traditional factory robots, RightPick handles tens of thousands of different items using a machine learning backend coupled with an intelligent gripper that works in concert with the UR cobots.

RightHand Robotics co-founder Leif Jentoft, PhD refers to RightPick’s flexible grasping capabilities as the “holy grail” in robotics technology: “RightPick enabled piece-picking delivers ‘The Three Rs’ – range of items, rate of picking, and reliability of the customer getting what they ordered,” he says. RightPick can run on any robot arm, but the company chose Universal Robots as they can safely work side-by-side with humans in warehouse environments. “To have collaborative arms as user-friendly as the UR systems gives us a very accessible solution,” says RightHand Robotics business development team member, Nadia Cheng, PhD. “I was super impressed by how easy it was to use, and how elegant the whole process was.”

RightPick enables validated picking and placement of the industry’s widest range of items (SKUs) regardless of orientation – including items the system has not seen before, eliminating the need for 3D CAD models of new SKUs. Utilizing machine learning, the system becomes increasingly more intelligent, expanding the range of pickable SKUs and first-pick success, as well as pick and place validation capabilities.

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