Subramanian Sundaram, a biological engineer affiliated with both Boston University and Harvard has been looking into the current state of robot hands and proposed ideas regarding where new research might be heading. He has published a Perspective piece in the journal Science outlining the current state of robotic hand engineering.
Sundaram suggests that machine learning appears likely to play a major role in improving the robot hand, as well—along with the brain that controls it. It might be possible to teach a robot how to react to being handed a hot potato, for example, by giving it examples of people responding to them. In like manner, robots might learn how to crack open a walnut, apply nail polish or brush dirt off another part of the robot body simply by watching YouTube videos.
Biological Engineer suggests there are three broad themes that might provide a roadmap of sorts for future robot hand research: emphasizing tactile sensor capabilities over the lifetime of a robot, addressing longevity of the data that is collected, and perhaps the most difficult, addressing the myriad of sensations that are expected of hands—being able to identify a cold coin dropped into the hand in the dark, for example.
Source: Techxplore
