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‘Breakthrough’ robot can make decisions based on what it sees
Published:  21 January, 2021

Robotics experts at the UK’s Manufacturing Technology Centre (MTC) in Coventry have developed a flexible industrial robot that, they say, has the decision-making capabilities of a human operator. Using a combination of machine learning and visual recognition, the robot can be taught to make assembly decisions based on components put in front of it. The MTC is hailing this as “a breakthrough development” which could save manufacturers the costs of expensive fixed tooling.

In trials, the MTC's system achieved a 99% detection rate and demonstrated that it was possible to swap an input tray and change the component mix with little effect on performance.

“We now have a blueprint for developing and implementing intelligent vision systems to industrial problems in an effective way, opening up potential applications in human-robot collaboration,” says the MTC's chief automation officer, Mike Wilson. “We have eliminated the need for part fixtures as this system can adapt to new layouts without reprogramming. Completely traceable decision-making allows errors to be addressed quickly and effectively, and the system can be trained to apply to any new assembly process.”

Most industrial automation technology is programmed to perform a given task and is unable to accept input variations. Changing the process can require a major investment in fixturing and reprogramming.

The new system is trained to recognise components and assembly variables and to retrieve solutions from its database. It combines a robot operating system with a collaborative robot and low-cost vision sensors.

“Giving robots the decision-making capability of a human operator can dramatically improve their productivity and flexibility in variable conditions,” explains senior MTC research engineer, Mark Robson. “Our demonstrator project shows how machine learning can be applied to achieve this.

The MTC's intelligent robotic assembly system in action

“This work has shown that deep-learning-based vision can provide robots with a robust ability to find and work with objects,” he adds. “The MTC has demonstrated methods to overcome the challenges in translating this ability into the physical domain of robotics which will enable the use of other machine-learning algorithms in industrial solutions."

The Centre has developed a demonstrator to show manufacturers how its technology can be used to create low-cost, reactive assembly systems. The demonstrator mimics a typical electronic assembly operation involving multiple components.

The MTC was founded by the University of Birmingham, Loughborough University, the University of Nottingham and TWI. It aims to provide a competitive environment to bridge the gap between university-based research and the development of innovative manufacturing solutions, in line with the UK Government’s manufacturing strategy. The MTC is part of the High Value Manufacturing Catapult, supported by Innovate UK.

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