We apply the auxiliary particle filter algorithm of Pitt and Shephard (1999) to the problem of robot localization. To deal with the high-dimensional sensor observations (images) ...
We generalize several recent works on nonlinear observers for aided attitude heading reference systems: we propose a symmetry-preserving nonlinear observer which merges the most co...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
In most models of computation, a device performs some type of process, and only some final output is regarded as the result. In adding an observer to such a device, one can obtain ...
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...