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by RugnirViking
1201 days ago
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a common example from my robotics experience (mainly mobile robots) has been getting something powerful enough to run our image recognition/interpreting sensor data. We often have something like several microprocessors (think:arduino equivalent running c++ or c) which run all the motor control etc and a high level system (used to often be raspberry pi, now more often nvidia jetson nano) listening to all of those and using most of it's computing power on some kind of sensor data, usually image recognition or processing TOF camera/lidar/radar data etc. We often have to optimise hard to get a couple of cycles or "frames" per second with these, which really puts limitations on how robots respond (250ms delay is veeeery noticable, especially if it's in obstacle avoidance - relatively common) |
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Researchers at US Berkeley came out with the algorithm they named SpeedFolding in October of last year. Watch https://youtu.be/UTMT2WAUlRw?t=511 and then realize that linked excerpt is sped up 9x.
If we had 9x faster compute we could have laundry folding robots which is one thing, but that amount of compute would enable robots to do tons more tasks in industry.