Google Robotics Learn Ping Pong
The Robotics team at Google has taught a robotic arm to play 300+ ping pong shot rallies with other people. While you may not be a big table tennis fan, the same techniques could be used to train robots to perform other “dynamic, high acceleration tasks” that require close human-robot interaction (like a surgical assist maybe).
Table tennis was chosen because it requires both fast and precise movements in a structured game that occurs in a fixed and predictable environment - this makes it a great set up for exploring human-robot interaction and reinforcement learning techniques (where the robot learns from doing).
What Does It Solve?
What problems does this model of robot learning really solve? The team explained that if you don’t have a good robot policy (a set of rules for the robot) to begin with, then you can’t collect high-quality data on how people will interact with it. But, without a human behavior model to start with, you can’t come up with the robot policy in the first place. It's the old "chicken-or-the-egg" dilemma. Their alternative solution was to train a robot in the real-world from human interaction – a process that could take a long time (and people can get hurt by swinging robotic arms).
Researchers sidestepped this limitation by using a simplified model of human behavior as a starting point and then trained the robot both with a simulation and a by interacting with real human. With each subsequent iteration in the process, both the human behavior model and the robot policy were refined.
Teaching robots to play games might seem trivial, but addressing these kinds of robot training problems potentially has real-world applications. What other tasks could robots learn faster and better from interacting dynamically with humans?
Even if Googles current ping pong robotic project only leads to a future table tennis robot “coach” able to adapt its play style according to the skill level of the human student – it’s a testament to how fast the field of robotics and machine learning are progressing.
See Full Article Table Tennis: A Research Platform for Agile Robotics
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