A lot of the stuff we use today is largely made by robots—arms with multiple degrees of freedom positioned along conveyor belts that move in a spectacle of precisely synchronized motions. All this motion is usually programmed by hand, which can take hundreds to thousands of hours. Google’s DeepMind team has developed an AI system called RoboBallet that lets manufacturing robots figure out what to do on their own.
Traveling salesmen
Planning what manufacturing robots should do to get their jobs done efficiently is really hard to automate. You need to solve both task allocation and scheduling—deciding which task should be done by which robot in what order. It’s like the famous traveling salesman problem on steroids. On top of that, there is the question of motion planning; you need to make sure all these robotic arms won’t collide with each other, or with all the gear standing around them.
At the end, you’re facing a myriad of possible combinations where you’ve got to solve not one but three computationally hard problems at the same time. “There are some tools that let you automate motion planning, but task allocation and scheduling are usually done manually,” says Matthew Lai, a research engineer at Google DeepMind. “Solving all three of these problems combined is what we tackled in our work”.
