AI Helps Warehouse Robots Pick Up New Tricks

#News(IoTStack) [ via IoTGroup ]

Some of the biggest names in artificial intelligence, including two godfathers of the machine learning boom, are betting that clever algorithms are about to transform the abilities of industrial robots.
Geoffrey Hinton and Yann LeCun, who shared this year’s Turing Prize with Yoshua Bengio for their work on deep learning, are among the AI luminaries who have invested in Covariant.ai, a startup developing AI technology for warehouse bin-picking bots.
Covariant.ai has developed a platform that consists of off-the-shelf robot arms equipped with cameras, a special gripper, and plenty of computer power for figuring out how to grasp objects tossed into warehouse bins.
The company, emerging from stealth Wednesday, announced the first commercial installations of its AI-equipped robots: picking boxes and bags of products for a German electronics retailer called Obeta.
Workplace robots are still incredibly dumb and clumsy, and teaching them to grasp unfamiliar objects or those with complex shapes remains a holy grail of AI and robotics research.
In recent years, a number of companies have sprung up offering robots that use simpler algorithms to perform useful warehouse tasks, including limited product picking.
Covariant.ai has not yet developed a robot as dextrous or adaptable as a human, but it has apparently succeeded in applying an exotic research technology, called reinforcement learning, to an industrial setting.
It is hard for robots to learn in the real world without making mistakes, and commercial robot installations require extreme levels of reliability.
Abbeel pioneered the application of machine learning to robotics, and he made a name for himself in academic circles in 2010 by developing a robot capable of folding laundry (albeit very slowly).
Covariant uses a range of AI techniques to teach robots how to grasp unfamiliar objects.

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