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New innovations in AI make vision-guided robotics easier to deploy

POSTED 12/06/2023

As manufacturers look to increase their productivity and cope with labor shortages, AI is seen as a path to improvement. 

But deploying AI is not always easy. Manufacturing solutions have had “AI” labels attached to them, while only providing incremental improvements. Other AI-labelled solutions are complicated to install. Apera AI CEO Sina Afrooze

One area where AI has helped make significant improvements in productivity and ease-of-use is with vision-guided robotics. 

“Apera has learned from its customers over the past year that the benefits of using AI for robotic guidance are clear. But they wanted more control over the implementation of AI into their robotic cells. That’s what we’ve introduced—user control over pick points, gripping strategy and simulation tools. These innovations all make vision-guided robotics easier to use.”

In the past year, Apera AI has installed its vision systems at the factories of more than 10 Fortune 500 manufacturers. These vision systems touch billions of dollars of manufacturing value. 

“We have made significant leaps in the past six months that make AI-powered vision easier to use. Engineers can choose pick points on the part and define clearances around the robot and gripper. Custom end-of-arm tools can be incorporated into the vision program. And these adjustments can now be tested in a complete simulation using the fully built cell before being moved into production. People approving automation spending said they wanted less risk before spending on automation, and we’ve delivered,” adds Afrooze.

With the release of a new version of Vue, its robotic vision software, Apera AI is helping industrial manufacturers deploy AI more easily. Neural networks train manufacturers’ parts over around 1 million simulated cycles. With a ready vision program generated by AI, an automation engineer can now take control. Specialized vision expertise is of lower importance by using AI.

Robotic cells using AI-powered vision are hitting human-like levels of object recognition and productivity. Software can now recognize objects in randomized bins and provide complete path planning to the robot at the same speed a person could make the decision—0.3 seconds. Vision systems are no longer a bottleneck to robotic productivity.

“We see a future where robots can take on increasingly complex tasks and perform with human intelligence. Automation and robotics engineers will play an important role in those deployments. This leap with Vue will make it easier for them to succeed,” Afrooze concludes.

 

Image: Engineers can deploy custom end-of-arm tools or off-the-shelf grippers to handle complex parts. Engineers can choose the best gripping strategy based on the AI-generated vision program.

Engineers can deploy custom end-of-arm tools or off-the-shelf grippers to handle complex parts. Engineers can choose the best gripping strategy based on the AI-generated vision program.

 

 

 

 

 

 

 

 

Image: A pre-deployment simulation environment ensures that the combination of robot, gripper, objects and operating environment will perform as expected.

A pre-deployment simulation environment ensures that the combination of robot, gripper, objects and operating environment will perform as expected.