Preface

This edited volume is a collection of reviewed and relevant research chapters concerning the latest developments within the autonomous vehicles field of study.

The book includes scholarly contributions by various authors and has been edited by an ex‐ pert pertinent to the vehicle autonomy field of research.

Each contribution comes as a separate chapter complete in itself but directly related to the book's topics and objectives.

The book's nine chapters are as follows:


The target audience comprises scholars and specialists in the field.

**IntechOpen**

#### **Chapter 1 Provisional chapter**

#### **Autonomous Underwater Vehicle Guidance, Navigation, and Control Autonomous Underwater Vehicle Guidance, Navigation, and Control**

DOI: 10.5772/intechopen.80316

Timothy Sands and Kevin Bollino Timothy Sands and Kevin Bollino

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.80316

#### **Abstract**

A considerable volume of research has recently blossomed in the literature on autonomous underwater vehicles accepting recent developments in mathematical modeling and system identification; pitch control; information filtering and active sensing, including inductive sensors of ELF emissions and also optical sensor arrays for position, velocity, and orientation detection; grid navigation algorithms; and dynamic obstacle avoidance among others. In light of these modern developments, this article develops and compares integrative guidance, navigation, and control methodologies for the Naval Postgraduate School's Phoenix, a submerged autonomous vehicle. The measure of merit reveals how well each of several methodologies cope with known and unknown disturbance currents that can be constant or harmonic while maintaining safe passage distance from underwater obstacles, in this case submerged mines.

**Keywords:** submersible vehicles, ocean research, obstacle avoidance, guidance, navigation, and control, linear quadratic optimal control, approximated optimal control, reduced-order observers, MIMO, SIMO
