Soft Robotics’ SuperPick Addresses Complexity, Variability in the Unstructured Environment of Reverse Logistics

Soft Robotics' SuperPick Polybag Picking System automates the handling, scanning, and loading of returned polybagged items.

The ability to quickly pick a wide range of objects has proven to be elusive for robots. This has led to the development of vision-guided systems and complex machine-learning algorithms to handle different shapes, materials, and orientations. Soft Robotics has reduced some of that complexity with its compliant grippers, which take inspiration from octopus tentacles and are based on the work of Harvard University researcher George Whitesides.

Bedford, Mass.-based Soft Robotics’ mGrip gripper kits enable companies to assemble the best configurations of soft fingers for their robotics applications. These include picking and packaging in e-commerce order fulfillment, consumer goods, medical and pharmaceuticals, and food handling.

Reverse logistics and product returns are particularly challenging for retailers, with up to 30% of online orders sent back. Soft Robotics’ SuperPick system works with unstructured, heterogenous bins of products without requiring prior training of stock-keeping units (SKUs), and it integrates with existing warehouse management systems (WMS).

The SuperPick Polybag Picking System uses 3D vision in combination with so grippers to singulate and scan polybags, which traditional automation has had difficulty handling.