Scientists from Cornell University have developed a way for robots to identify physical interactions just by analyzing a user’s shadows. Their ShadowSense system uses an off-the-shelf USB camera to capture the shadows produced by hand gestures on a robot’s skin. Algorithms then classify the movements to infer the user’s specific interaction. Study lead author Guy Hoffman said the method provides a natural way of interacting with robots without relying on large and costly sensor arrays: Touch is such an important mode of communication for most organisms, but it has been virtually absent from human-robot interaction. One of the reasons is that full-body touch used…
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