For most people, the task of identifying an object, picking it up, and placing it somewhere else is trivial. For robots, it requires the latest in machine intelligence and robotic manipulation.

RightHand Robotics — a Somerville, MA-based spinoff from Massachusetts Institute of Technology (MIT) — has incorporated both machine intelligence and advances in robotic manipulation into its robotic piece-picking systems, which combine unique gripper designs with artificial intelligence and machine vision to help companies sort products and get orders out the door.

“If you buy something at the store, you push the cart down the aisle and pick it yourself. When you order online, there is an equivalent operation inside a fulfillment center,” said RightHand Robotics co-founder Lael Odhner. “The retailer typically needs to pick up single items, run them through a scanner, and put them into a sorter or conveyor belt to complete the order. It sounds easy until you imagine tens of thousands of orders a day and more than 100,000 unique products stored in a facility the size of 10 or 20 football fields, with the delivery expectation clock ticking.”

RightHand Robotics is helping companies respond to two trends that have transformed retail operations: the explosion of e-commerce, which only accelerated during the COVID-19 pandemic, and a shift to just-in-time inventory fulfillment, in which retailers restock items based on what’s been purchased to improve efficiency.

The robot fleet also collects data that help RightHand improve its system over time and enable it to learn new skills such as more gentle or precise placement. Process and performance data feed into the company’s fleet management software, which helps customers understand how their inventory moves through the warehouse and identify bottlenecks or quality problems.

“The idea is that rather than looking at just the performance of a single operation, e-commerce firms can modify or overhaul the operational flow throughout the warehouse,” Odhner said.

Pushing the Limit

At the core of the company’s solution is the idea of using machine vision and intelligent grippers to make piece-picking robots more adaptable. The combination also limits the amount of training needed to run the robots, equipping each machine with what the company equates to hand-eye coordination.

The systems give people insights into their inventory, how they’re storing their inventory, and how they’re structuring tasks both upstream and downstream of any picking. (Credit: MIT)

RightHand Robotics also utilizes an end-of-arm tool that combines suction with novel underactuated fingers, which Odhner said gives the robots more flexibility than robots relying solely on suction cups or simple pinching grippers. “Sometimes, it actually helps you to have passive degrees of freedom in your hand — passive motions that it can make and can’t actively control,” Odhner said of the robots. “Very often, those simplify the control task. They take problems from being heavily over-constrained and make them tractable to run through a motion planning algorithm.”

The data the robots collect are also used to improve reliability over time and shed light on warehouse operations. “We can give people insights into their inventory, how they’re storing their inventory, and how they’re structuring tasks both upstream and downstream of any picking we’re doing,” Odhner said. “We have very good insight as to what may be a source of future problems and we can feed that back to customers.”

Odhner noted that warehouse fulfillment could grow to be a much larger industry if throughput were improved. “As consumers increasingly value the option of shopping online, more and more items need to get into a growing number of ‘virtual’ carts. The availability of people near order fulfillment centers tends to be a limiting factor for e-commerce growth. All of that is really indicative of a massive economic inefficiency and that’s essentially what we’re trying to address,” Odhner said. “We are taking the least engaging tasks in the warehouse — things like sorter induction where you’re just picking, scanning, and putting something on a belt all day long — and we’re working to automate those tasks to the point where you can take your people and direct them to things that are going to be more directly felt by the customer.”

Odhner also said more automated fulfillment centers offer improved measures to protect worker health and safety such as ergonomic stations where goods are brought to workers for specialized tasks and increased social distancing. Rather than reducing the number of people employed in a warehouse, he said, “Ultimately, what you want is a system with people working in roles like quality control, overseeing the robots.”

Robots Made Easy

This year, the company is introducing the third version of its picking robot, which ships with standardized integration and safety features in an attempt to make deploying piece-picking robots easier for warehouse operators.

“People may not necessarily grasp the enormity of our progress in productizing this autonomous system in terms of ease of integration, configuration, safety, and reliability but it is huge because it means that our robot systems can be drop-shipped pretty much worldwide and get up and running with minimal customization,” Odhner said. “There is no reason why this can’t just come in a box or on a pallet and be set up by anyone. That’s our big vision.”

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Motion Design Magazine

This article first appeared in the August, 2021 issue of Motion Design Magazine.

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