How a new generation of grippers with improved 3D perception and tactile sensing is learning to manipulate a wide variety of objects
This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.
While robots have prepared entire breakfasts since 1961, general manipulation in the real world is arguably an even more complex problem than autonomous driving. It is difficult to pinpoint exactly why, though. Closely watching the 1961 video suggests that a two-finger parallel gripper is good enough for a variety of tasks, and that it is only perception and encoded common sense that prevents a robot from performing such feats in the real world. Indeed, a recent Science article reminded us that even contact-intensive assembly tasks such as assembling a piece of furniture are well within the realm of current industrial robots. The real problem is that the number of possible manipulation behaviors is very large, and the specific behaviors required to prepare a club sandwich aren’t necessarily the same as those required to assemble a chair.