The system, called "Dense Object Nets" (DON), looks at objects as collections of points that serve as "visual road-maps" of sorts, which lets robots better understand and manipulate items, and allows them to pick up a specific object among a clutter of similar objects.
Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) trained the system to look at objects as a series of points that make up a larger coordinate system. It can then map different points together to visualize an object's 3-D shape, similar to how panoramic photos are stitched together from multiple photos.
After training, if a person specifies a point on a object, the robot can take a photo of that object, and identify and match points to be able to then pick up the object at that specified point. This is a valuable skill for the kinds of machines that companies like Amazon and Walmart use in their warehouses.