American engineers have developed a specially-designed computer processor which allows robots to plan their movements up to 10,000 times faster than existing approaches while consuming a small fraction of the power.
The researchers from Duke University in North Carolina say the new processor is fast enough to plan and operate in real time, and power-efficient enough to be used in large-scale manufacturing environments with thousands of robots.
"When you think about a car assembly line, the entire environment is carefully controlled so that the robots can blindly repeat the same movements over and over again," said George Konidaris, assistant professor of computer science and electrical and computer engineering at Duke.
"The car parts are in exactly the same place every time, and the robots are contained within cages so that humans don't wander past. But if your robot is using motion planning in real time and a part is in a different place, or there's some unexpected clutter, or a human walks by, it'll do the right thing."
The new processor has been designed to perform collision detection — the most time-consuming aspect of motion planning — such that the processor performs thousands of collision checks in parallel.
The technology works by breaking down the arm's operating space into thousands of 3D volumes called voxels. The algorithm then determines whether or not an object is present in one of the voxels contained within pre-programmed motion paths. Thanks to the specially designed hardware, the technology can check thousands of motion paths simultaneously, and then stitch together the shortest motion path possible using the "safe" options remaining.
"The state of the art prior to our work used high-performance, commodity graphics processors that consume 200 to 300 watts," said Konidaris. "And even then, it was taking hundreds of milliseconds, or even as much as a second, to find a plan. We're at less than a millisecond, and less than 10 watts. Even if we weren't faster, the power savings alone will add up in factories with thousands, or even millions, of robots."
Konidaris also notes that the technology opens up new ways to use motion planning.
"Previously, planning was done once per movement, because it was so slow," said Konidaris, "but now it is fast enough that it could be used as a component of a more complex planning algorithm, perhaps one that sequences several simpler motions or plans ahead to reason about the movement of several objects."
[A robot picks up an object while navigating around piles of boxes. Image: Duke University]
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