Methods for the formal verification and specification of systems are a critical tool for the
development of correct systems, and they have been applied to the design of hardware …

Localization is the problem of determining the position of a mobile robot from sensor data.
Most existing localization approaches are passive, ie, they do not exploit the opportunity to …

This dissertation investigates the use of hierarchy and problem decomposition as a means
of solving large, stochastic, sequential decision problems. These problems are framed as …

Autonomous mobile robots need very reliable navigation capabilities in order to operate
unattended for long periods of time. We present a technique for achieving this goal that uses …

This dissertation explores fundamental issues in e ective and safe navigation of mobile
indoor robots. In particular, we will look at the problem of self-localization and aspects of …

This research investigates behavioral diversity in learning robot teams. Behavioral diversity
refers to the extent to which individual agents assume distinct behavioral roles in a group …

Recently there has been a good deal of interest in using techniques developed for learning
from reinforcement to guide learning in robots. Motivated by the desire to find better robot …

A partially observable Markov decision process (POMDP) is a model of planning and control
that enables reasoning about actions with stochastic effects and observations that provide …

High-level control systems are designed to enable mobile robots to successfully perform
complex missions such as office delivery and survillance tasks. For that purpose they have …

In recent years, researchers in AI planning have been trying to extend the classic planning
paradigm to handle uncertainty and partial goal satisfaction. This dissertation focuses on the …