Butler PickPal

Autonomous Fulfillment For E-Commerce Warehouses

GreyOrange BUTLER


Robotics verandert de manier waarop logistiek en supply chains over de gehele wereld worden geoptimaliseerd.

Butler Pickpal concept : “Automatisch  order picking robot technologie voor in het magzaijn”.

Today, supply chains are under enormous pressure to keep up with ever-increasing consumer demands. Rapid e-commerce adoption, same-day delivery and omni-channel operations place many new demands on warehouses operations. As a response to this, supply chain executives tend to build bigger warehouses, increase their workforce or add complex technology to achieve some productivity gains. Even with additional investments, the problems cannot always be solved.


PickPal is an automated picking systems in warehouse. It works seamlessly with GreyOrange Butler Goods-to-Person System for automated piece picking in warehouses. This robotic picking can pick, process, consolidate, and prepare orders in warehouses.

The system is best fit for e-commerce warehouse automation as it works collaboratively with a human operator to fulfill orders, increasing picking productivity from the same workstation. This automated picking systems in warehouse from Grey Orange works seamlessly & efficiently with the Butler goods-to-person system

Logaps, Butler, GreyOrange

Works seamlessly & efficiently with the Butler goods-to-person system

The Butler PickPal can work as a fully automated picking systems in warehouse. Alternatively, you can also work along side human operator to deliver accelerated and improved picking performance with up to 2x productivity gains. The system delivers:

  • Higher Picking Efficiency
  • Lower cost per shipment
  • Reduces pilferage and miss-pick due to human error


How Butler PickPal Works?

Butler PickPal is an automated picking systems in warehouse. It works seamlessly and efficiently with the Butler Goods-to-Person system. Also, it processes and consolidates multiple orders simultaneously.

  • Items are accurately identified from the MSU using sophisticated machine vision algorithms.
  • Identified items are accurately grasped from a densely packed MSU using a collaborative robotic arm and a set of complaint grippers.
  • Items are dropped in totes, corrugated boxes after the barcode scan which is sent for packing.