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.
That’s what MIT spinoff RightHand Robotics has incorporated 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,” says RightHand Robotics co-founder Lael Odhner ’04, SM ’06, PhD ’09. “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 broad trends that have transformed retail operations. One is the explosion of e-commerce, which only accelerated during the Covid-19 pandemic. The other is a shift to just-in-time inventory fulfillment, in which pharmacies, grocery stores, and apparel companies restock items based on what’s been purchased that day or week to improve efficiency.
The robot fleet also collects data that help RightHand Robotics 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 can help 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 says. “The goal is to eliminate variability as far upstream as is feasible, making a simpler, streamlined process.”
Pushing the limit
Odhner completed his PhD in the lab of Harry Asada, MIT’s Ford Professor of Engineering in the Department of Mechanical Engineering, who Odhner says encouraged students to develop a broad familiarity with robotics research. Colleagues also frequently shared their work in seminars, giving Odhner a well-rounded view of the field.
“Asada is a very well-known robotics researcher, and his early work, as well as the projects I worked on with him, are very much fundamental to what we’re doing at RightHand Robotics,” Odhner says.
In 2009, Odhner was part of the winning team in the DARPA Autonomous Robotic and Manipulation Challenge. Many of the com
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