Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
In this paper, we present techniques that allow one or multiple mobile robots to efficiently explore and model their environment. While much existing research in the area of Simul...
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
A dynamic layer representation is proposed in this paper for tracking moving objects. Previous work on layered representations has largely concentrated on two-/multiframe batch fo...
— Automatically synthesizing behaviors for robots with articulated bodies poses a number of challenges beyond those encountered when generating behaviors for simpler agents. One ...