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Amazon Develops Algorithm to Improve Collaboration Between Robots and Humans

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Amazon has identified a financially beneficial way for robots and humans to coexist, and it’s saving the online enterprise half a billion dollars per year. Using robots to bring shelves of inventory to associates to pick up customer orders cuts down the distance travelled by robots and decreases the company’s storage footprint.

A common fear is that artificial intelligence (AI) and robotics will put Americans out of work, but that may not be the case. New research in the INFORMS Journal on Applied Analytics is using the science of operations research (OR) to enable humans and robots to work together more effectively.

The study shows the work done to redesign the robotic picking algorithm used in Amazon Robotics (AR) fulfilment centres (FCs).

“Rather than associates going to the product shelves to pick for a customer order shipment or stow new inventory, robots bring shelves of inventory to associates who are at workstations either picking or stowing items,” said Russell Allgor of Amazon.

The picking algorithm decides which specific units of inventory on which pods should be picked to fulfil customer order shipments. The algorithm reduced the distance travelled by pods by 62% without negative operational impact. This has now been implemented in all Amazon Robotics FCs, such as Amazon Inventory Management

“This improvement reduced the number of drives required in AR FCs by 31%, which amounted to half a billion dollars in savings,” continued Allgor.

Allgor, alongside his co-authors Tolga Cezik and Daniel Chen, both of Amazon, says that by implementing AR FCs as the standard for new fulfilment centres, Amazon has also reduced their storage footprint by about 29% when compared with non-AR FCs. This translates to more efficient use of space and a more productive human workforce.

Jeetu Mirchandani, the director of software development at Amazon Fulfillment Technology said: “With a focus on algorithmic efficiency and effectiveness, operations research has been able to shorten the overall development time necessary for wide-scale deployment while increasing the overall performance of a critical robotic system used within Amazon.

“The algorithmic improvements have enabled sustained improvements in operational efficiency and have played a key role in accelerating Amazon’s fulfilment operations, enabling humans and robots to work together efficiently.”

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