A mobile robot exploring an unknown environment has no absolute frame of reference for its position, other than features it detects through its sensors. Using distinguishable landmarks is one possible approach, but it requires solving the object recognition problem. In particular, when the robot uses two-dimensional laser range scans for localization, it is difficult to accurately detect and localize landmarks in the environment (such as corners and occlusions) from the range scans. In this paper, we develop two new iterative algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment, that avoid the above problems. The first algorithm is based on matching data points with tangent directions in two scans and minimizing a distance function in order to solve the displacementbetween the scans. The second algorithm establishes correspondences between points in the two scans and then solves the point-to-point least-squares probl...

Getting robots to do complex tasks is very difficult. The robot must not only be able to navigate through the world and execute various primitive tasks such as "go forwards by 5 cm" and "take a picture", but also support the specification and execution of complex behaviors, which requires reasoning about goals and actions. The occurrence of exogenous events and runtime failures, and having incomplete information of the environment have long been two major problems encountered by most robots operating in the real world. In this thesis, we develop an approach to building robust high-level control modules using the ConGolog language and prioritized interrupts to handle exogenous events and runtime failures. Such a module is implemented and tested on a mobile robot in a real environment for a mail delivery task. We also develop a knowledge-based approach to guide search for people in the presence of incomplete knowledge. iv Acknowledgments First of all, I would like to thank my thesis su...