Reliable Robot Localization

Preface

In the field of mobile robotics, navigation is the building block of any autonomous mission. It involves several competencies, which are perception of the environment, localization of the robot with respect to a given reference frame, the cognition leading to a set of trajectory decisions and control of the actuators to achieve these decisions. The localization problem has given a tremendous impetus to the development of new technologies and algorithms, such as global navigation satellite systems (GNSSs) or a variety of Kalman filters. The challenges raised by this localization imply a wide variety of contexts, sensors and uncertainties that still gather a large part of the robotic community today.

This book focuses on a new approach to deal with the localization problem. It finds its inspiration in the challenges raised by strong uncertainties and perception difficulties present in underwater robotics. Furthermore, for safety reasons related to surface navigation or risks of collision with the seabed, it is crucial to consider the quality of position estimates. Emergent set-membership methods allow us to define reliable bounds on uncertainties in computations; this book explains how to apply these tools to mobile robots. The illustrations are related to underwater robotics, but the concepts remain fully valid for other applications involving dynamical systems.

This book is expected to be useful for students and researchers in the areas of mobile robotics, nonlinear ...