PhD student Lucas Manuelli helped to develop a system that uses advanced computer vision to enable a Kuka robot to pick up virtually any object. (Tom Buehler/CSAIL)

Students at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) developed Dense Object Nets (DON), a system that lets robots inspect random objects and visually understand them enough to accomplish specific tasks without ever having seen them before.

DON looks at objects as collections of points that serve as sort of visual roadmaps. This approach lets robots better understand and manipulate items, and, most importantly, allows them to even pick up a specific object among a clutter of similar ones. DON could get a robot to grab onto a specific spot on an object, such as the tongue of a shoe. From that, it can look at a shoe it has never seen before, and successfully grab its tongue.

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