Human toddlers are inspiring new approaches to robot learning

It’s an exciting time for robotic learning. Organizations have spent decades building complex datasets and pioneering different ways to teach systems to perform new tasks. It seems we’re on the cusp of some real breakthroughs when it comes to deploying technology that can adapt and learn on the fly.

The past year, we’ve seen a large number of fascinating studies. Take VRB (Vision-Robotics Bridge), which Carnegie Mellon University showcased back in June. The system is capable of applying learnings from YouTube videos to different environments, so a programmer doesn’t have to account for every possible variation.

Last month, Google’s DeepMind robotics team showed off its own impressive work, in the form of RT-2 (Robotic Transformer 2). The system is able to abstract away minutia of performing a task. In the example given, telling a robot to throw away a piece of trash doesn’t require a programmer to teach the robot to identify specific pieces of trash, pick it up and throw it away in order to perform a seemingly simple (for humans, at least) task.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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