Learning has been a holy grail in robotics for decades. If these systems are going to thrive in unpredictable environments, they’ll need to do more than just respond to programming — they’ll need to adapt and learn. What’s become clear the more I read and speak with experts is true robotic learning will require a combination of many solutions.
Video is an intriguing solution that’s been the centerpiece of a lot of recent work in the space. Roughly this time last year, we highlighted WHIRL (in-the-Wild Human Imitating Robot Learning), a CMU-developed algorithm designed to train robotic …
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