Inspecting and Picking up Objects

Would seem to lead to the ability to generalize picking up objects in a complex domain, such as the home or office.   I had thought this was solved long ago, but when we looked at this for picking systems, discovered it was not the case.    Generalizing a key goal of human vision and its application to dexterity in robotic systems.

Robots can now pick up any object after inspecting it

Breakthrough CSAIL system suggests robots could one day be able to see well enough to be useful in people’s homes and offices.  

By Adam Conner-Simons | Rachel Gordon | CSAIL 

Humans have long been masters of dexterity, a skill that can largely be credited to the help of our eyes. Robots, meanwhile, are still catching up.

Certainly there’s been some progress: For decades, robots in controlled environments like assembly lines have been able to pick up the same object over and over again. More recently, breakthroughs in computer vision have enabled robots to make basic distinctions between objects. Even then, though, the systems don’t truly understand objects’ shapes, so there’s little the robots can do after a quick pick-up.  

In a new paper, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), say that they’ve made a key development in this area of work: a system that lets robots inspect random objects, and visually understand them enough to accomplish specific tasks without ever having seen them before.

The system, called Dense Object Nets (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 — a valuable skill for the kinds of machines that companies like Amazon and Walmart use in their warehouses.
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