Using a combination of machine learning and visual recognition, the robot can be taught to make assembly decisions based on the components put in front of it, in a breakthrough development which could save manufacturers the costs of expensive fixed tooling.
A flexible industrial robot with the decision-making capability of a human operator has been developed at the MTC.
Using a combination of machine learning and visual recognition, the robot can be taught to make assembly decisions based on the components put in front of it, in a breakthrough development which could save manufacturers the costs of expensive fixed tooling.
Now the MTC has developed a flexible automation demonstrator to show manufacturers how the robotics can be used to create a low cost, reactive assembly system. The demonstrator mimics a typical electronic assembly using multiple components and combines a robot operating system with a collaborative robot and low-cost vision sensors.
In trials, the MTC’s system returned a 99 per cent successful detection rate and demonstrated that it was possible to swap the input tray and change the component mix with little effect on performance.
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