If you've ever seen a live robot manipulation demo, you've almost certainly noticed that the robot probably spends a lot of time looking like it's not doing anything. It's tempting to say that the robot is "thinking" when this happens, and that might even be mostly correct: odds are that you're watching some poor motion-planning algorithm try and figure out how to get the robot's arm and gripper to do what it's supposed to do without running into anything. This motion planning process is both one of the most important skills a robot can have (since it's necessary for robots to "do stuff"), and also one of the most time and processor intensive. At the RSS 2016 conference this week, researchers from the Duke Robotics group at Duke University in Durham, N.C., are presenting a paper about "Robot Motion Planning on a Chip," in which they describe how they can speed up motion planning by three orders of magnitude while using 20 times less power. How? Rather than using general purpose CPUs and GPUs, they instead developed a custom processor that can run collision checking across an entire 3D grid all at once.
Jun-21-2016, 19:01:00 GMT