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Reliable Piece-picking Warehouse Robots in the U.S.

Image credit: mit.edu

To create robots that are capable of identifying an object, picking it up, and placing it somewhere else requires the latest technology in machine intelligence and robotic manipulation. Hence, U.S. researchers have developed robotic piece-picking systems which combine unique gripper designs with Artificial Intelligence (AI) and machine vision to help companies sort products and get orders out the door.

The robotic system is helping companies respond to two broad trends that have transformed retail operations. The first trend is the explosion of e-commerce, which has been accelerated during the COVID-19 pandemic. The other is a shift to just-in-time inventory fulfilment, in which pharmacies, grocery stores, and apparel companies restock items based on what has been purchased that day or week to improve efficiency.

The robot fleet also collects data that helps the robot to 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.

Rather than looking at just the performance of a single operation, e-commerce firms can modify or overhaul the operational flow throughout the warehouse. The goal is to eliminate variability as far upstream as is feasible, making a simpler, streamlined process.

At the core of this robotic 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 robotic system also utilises an end-of-arm tool that combines suction with novel underactuated fingers, which gives the robots more flexibility than robots relying solely on suction cups or simple pinching grippers. The data the robots collect are also used to improve reliability over time and shed light on warehouse operations for customers.

The data can be used to give people insights into their inventory, how they are storing their inventory, and how they are structuring tasks both upstream and downstream. Therefore, the researchers will have great actionable insights as to what may be a source of future problems.

This year, the company is introducing the third version of its picking robot, which ships with standardised integration and safety features in an attempt to make deploying piece-picking robots easier for warehouse operators. The robot systems can be drop-shipped worldwide and get up and running with minimal customisation.

Robotic systems can be utilised in different fields, including in the military. As reported by OpenGov Asia, The Defense Advanced Research Projects Agency (DARPA) is inviting small businesses to submit innovative research concepts in the technical domains of Electronics, Information Systems. In particular, DARPA is interested in understanding the feasibility of SQUad Intelligent Robotic Radio Enhancing Links (SQUIRREL) and are looking for proposals for small, lightweight, low-power robotic devices.

DARPA expects SQUIRREL solutions will use climbing, flying or hybrid robots to form a self-positioning 3D mesh network that can maintain small-squad communications through a combination of repositioning, frequency selection and beamforming, or focusing a signal toward a receiver. These devices should be quiet, difficult to observe and unlikely to be detected or intercepted.

SQUIRREL advances a DARPA project called LANdroids, which used small ground-based robotic radio relay nodes to configure and maintain mesh networks that were capable of reasoning about their positions relative to each other and individual warfighters.

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