Kindred is set to bring its AI-powered robotic system designed to automate the small parcel induction process to market, with the aim of assisting parcel, post, and e-commerce fulfilment companies alleviate capacity shortages and increase efficiency.
Named Induct, the system is built on Kindred’s proprietary CORE/AutoGrasp AI platform. It is a high-speed work cell that identifies items and determines how to handle them, a process known as induction.
It accurately picks, manoeuvres, and places items onto a moving belt, bomb bay, or tilt sorter. The platform combines AI-powered machine vision, grasping, and manipulation algorithms to handle parcels of varying size, fragility, and materials.
“AI and reinforcement learning is in Kindred’s DNA and embedded in all our products. Those capabilities enabled us to quickly solve the engineering challenge of automating induction – a more challenging process than picking and sorting due to the unstructured and unpredictable dynamics of handling parcels,” said Anne Marie Neatham, chief operating officer, Kindred.
The Induct in-feed system separates items from a chute onto a series of belts, dividing and unstacking pieces into two organised streams. Using Adaptive Motion Control, two synchronised robotic arms pick up each item at the precise speed and grip required for its shape and weight and place it on a free space on the moving sorter. Built-in scanners capture barcodes as items move down the sorter, regardless of orientation.
The solution can grasp and manoeuvre items up to 4kg (8lb) with a variety of shapes, surface textures, and materials, both rigid packaging and loose plastic. It is also designed to induct with throughput of 1,600 – 2,000 picks per hour (PPH).
Induct is built to fit within the confines of most induction workstations with a footprint of 2.7m by 1.4m (8 feet 10 inches by 4 feet 6 inches).
Numerous Induct work cells can perform collaboratively along the same fulfilment line for maximum productivity and integrate with many different communication protocols, customisations, and customer and warehouse management systems. Kindred’s integration team can develop customised screens for cycle reporting, performance statistics, and parameter configuration.
Additionally, Kindred developed several new algorithms to enable the Induct system to accurately achieve sortation, induction, and singulation regardless of the item, dimensions, characteristics, or orientation. Integrated into Kindred’s CORE/AutoGrasp reinforcement learning platform, these capabilities can now be deployed in any future Kindred products.
