Tompkins Robotics, a Raleigh, N.C.-based division of Tompkins International, and RightHand Robotics, Somerville, Mass., announced a collaboration that will combine t-Sort, what is dubbed to be the world’s first portable, automated sortation system, with RightPick, a robotic piece-picking system, to provide flexibility and throughput for e-commerce and omni-channel fulfillment.

“The response from customers visiting our recently re-launched Emerging Technology Center to see these two systems working together has been extremely positive,” says Mike Futch, president of Tompkins Robotics. “Integrating RightHand’s best-in-class, piece-picking technology with Tompkins Robotics’ t-Sort provides a solution that can flexibly scale from a small operation in the backroom of a supercenter or mall anchor store to dedicated fulfillment center application, processing millions of units a day.”

Tompkins Robotics offers the patented automated sortation system, t-Sort, in North America and Europe. This new and innovative robotic technology performs much like a conventional tilt tray or crossbelt sorter. However, it uses completely independent robots. This difference provides any-to-any flow from induct stations to divert points in a modular system that is easy to reconfigure as business scales or to accommodate seasonal peaks.

“With t-Sort, Tompkins Robotics is delivering innovation to help retailers growing their e-commerce platforms or leveraging existing store footprint in an omni-channel business model,” says Leif Jentoft, co-founder of RightHand Robotics. “Combined with our ability to deliver the 3Rs of robotic piece-picking – range of products, rate and reliability – with our RightPick AI software, we believe, provides a welcome new set of options to our customers. We have recently installed t-Sort in our RightHand Robotics Demo Center and have already scheduled visits.”

RightPick is a combined software and hardware solution that handles the key task of picking individual items for e-commerce order fulfillment. RightPick handles hundreds of thousands of different items using a machine learning backend, coupled with an intelligent gripper that works in concert with robotic arms.