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AI-Powered Robotic Vision Integrated Into Universal Robots’ UR+ Ecosystem

Apera AI has announced the integration of its AI-powered robotic vision into the Universal Robots’ UR+ ecosystem. The Vue robotic vision software adds powerful bin picking, assembly, packaging, and machine tending capabilities to UR cobots.

Apera AI’s Vue robotic vision software is now available on the UR+ ecosystem offered by Universal Robots, the world’s leading cobot manufacturer. The two companies have tested and certified that Vue software integrates seamlessly with the full range of UR cobots.

Vue software uses artificial intelligence and machine learning for robotic path planning, grasp intelligence and collision avoidance. These capabilities are integral for fast and repeatable performance in manufacturing applications such as bin picking, assembly, packaging, machine tending, sorting, and palletizing.

Vue software provides industry-leading performance, with a total vision cycle time as low as 0.3 seconds (3 Hz). Using Vue, robots can move faster in identifying and grasping objects, therefore achieving higher productivity versus competing vision solutions.

“Vue from Apera is one of the best UR+ vision systems I have seen. The robot guidance is very effective for bin picking, feeding machines and more. Our shared customers will find that Apera AI’s sales team is both knowledgeable and responsive.,” said Christopher Savoia, Regional Head of UR+ Americas, Universal Robots.

“Universal Robots has a strong reputation for usability. Apera AI fits with that approach since we remove the custom programming that’s typical of vision integration projects. Our systems also operate in ambient light with no special cameras or sensors. We can even simulate performance in a full digital twin before the customer commits to spending,” said Manuel Sordo, Chief Revenue Officer at Apera AI.

Apera AI’s proprietary technology focuses on the use of artificial intelligence to train robots to find the most pickable object in randomized situations. An AI neural network is trained to understand all the properties of an object, including its geometry, finishes and how it can be handled.

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