Control Engineering
MARCH 17, 2023
Researchers in Arkansas and two other states will be using a $5 million grant to increase use of artificial intelligence and robotics in chicken processing to reduce waste in deboning and detect pathogens. Robotics are fit for repetitive tasks but don’t do well with the precision needed to cut up chicken products.”
Automation Mag
NOVEMBER 22, 2022
And this is how machine vision can help discrete manufacturing, enabling them with automation,” Montanari explains. You need very well-trained labour to inspect parts in manufacturing and discrete industries,” he explains. “If With the introduction of artificial intelligence, it’s going to be very different.
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Control Engineering
OCTOBER 10, 2023
Learning Objectives Understand the advantages of an integrated robot, artificial intelligence and machine vision package to better enable robotic item picking. AI-enabled robot insights Integrating a robot, artificial intelligence and a machine vision can more quickly enable robotic item picking.
Control Engineering
AUGUST 11, 2023
The engineering and runtime environment for PLCs, motion control, and IoT applications empowers engineers to program in the languages they know best or best fit the application. Workloads generated in the cloud, including modern versions of artificial intelligence (AI) and analytics, can be migrated toward the edge.
Control Engineering
APRIL 2, 2023
There’s also been a concerted effort to make agriculture smarter as a whole by using big data and artificial intelligence (AI) to help predict what will happen and create more sustainable and better crops. There’s a lot riding on farmers’ ability to fight weeds, which can strangle crops and destroy yields.
Control Engineering
APRIL 10, 2023
Researchers from MIT’s Improbable Artificial Intelligence Lab, part of the Computer Science and Artificial Intelligence Laboratory (CSAIL), have developed a legged robotic system that can dribble a soccer ball under the same conditions as humans.
Control Engineering
APRIL 27, 2023
Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have introduced a method for robust flight navigation agents to master vision-based fly-to-target tasks in intricate, unfamiliar environments.
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