MIT researchers built a soft robotic gripper that uses embedded cameras and deep learning to enable high-resolution tactile sensing and “proprioception” (awareness of positions and movements of the body). | Credit: MIT CSAIL
One of the hottest topics in robotics is the field of soft robots, which utilizes squishy and flexible materials rather than traditional rigid materials. But soft robots have been limited due to their lack of good sensing. A good robotic gripper needs to feel what it is touching (tactile sensing), and it needs to sense the positions of its fingers (proprioception). Such sensing has been missing from most soft robots.
In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with new tools to let robots better perceive what they’re interacting with: the ability to see and classify items, and a softer, delicate touch.
Editor’s Note: This article was reprinted with permission from MIT News.
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