By placing a camera inside a robot, researchers can infer how the person is touching it and what the person’s intent is just by looking at the shadow images. | Credit: Cornell University
Cornell University researchers created a low-cost method for soft robots to detect a range of physical interactions, from pats to punches to hugs, without relying on touch at all. Instead, a USB camera located inside the robot captures the shadow movements of hand gestures on the robot’s skin and classifies them with machine-learning software.
The post How shadows can help robots understand human touch appeared on The Robot Report.
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