Abstract. The development of robots that learn from experience is a relentless challenge confronting artificial intelligence today. This paper describes a robot learning method whi...
This paper discusses how a robot can develop its state vector according to the complexity of the interactions with its environment. A method for controlling the complexity is prop...
End-effector control of robots using just remote camera views is difficult due to lack of perceived correspondence between the joysticks and the end-effector coordinate frame. Thi...
Aditya Nawab, Keshav Chintamani, R. Darin Ellis, G...
We show how Embedded Graph Grammars (EGGs) are used to specify local interaction rules between mobile robots in a natural manner. This formalism allows us to treat local network to...
John-Michael McNew, Eric Klavins, Magnus Egerstedt
Abstract. This article discusses the issues of adaptive autonomous navigation as a challenge of artificial intelligence. We argue that, in order to enhance the dexterity and adapti...