Picking up an object is only part of the problem. The picture shows a gripper spilling a glass of water. After the object is grasped, some purpose must be accomplished. If the water were wine and needed to go from a pitcher into a glass, it would be inportant not to spill it onto the floor or table, and that the robot's 'fingers' not get into the wine. While this is an interesting line of research, I can't see it replacing purpose-built grippers yet.
Ann, this might mark me out as a bit wierd, but I think about this a lot. Whenever I put the silverware away I thnk to myself, how would I program a robot to do this?
What really strikes me about this, and some other situations I have seen, is that people are programming robots to do things using a fairly simple vision system along with memory (a database) and an algorithm. This contrasts with robotics approaches that use all kinds of complex sensors. In many cases they are trying to automate something we do with our simple sensors naturally. Interesting.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.