We introduce the new denizens of the mobile robotics lab and give an overview of our software system for mobile robot control.   Some of the key problems in mobile robotics arise from the inherent uncertainties involved in sensing and acting in the real world. Our control system makes extensive use of probabilistic methods in order to deal with these uncertainties. We focus on probabilistic methods for mobile robot localization and map building. The first problem is the estimation of a robot’s position within its environment, and the second problem is the task of building a model of a robot's environment using sensor information collected by the robot. We introduce and demonstrate the application of efficient Monte Carlo methods to these problems. Furthermore, we discuss directions for future research. From the Series:CSE Colloquia - 2001