Self-Learning Robot Hands Adapt to Grasp Objects

Anew grasp system with robotic hands works without previously knowing the characteristics of objects, learning by trial and error. The robot features two hands based on human hands in terms of both shape and mobility. The robot brain for the hands has to learn how everyday objects like pieces of fruit or tools can be distinguished on the basis of their color or shape, as well as what matters when attempting to grasp the object; for example, a banana can be held, and a button can be pressed. The system learns to recognize such possibilities as characteristics, and constructs a model for interacting with and re-identifying the object.