Model-based Guidance, Navigation and Control architecture for an Autonomous Underwater Vehicle

Abstract

This article studies the design, modeling, and implementation of a model-based Guidance, Navigation, and Control (GNC) architecture for an Autonomous Underwater Vehicle (AUV). First, effective simulation modeling is developed using a theoretical six-degree-of-freedom (6DoF) dynamic model. Then, this study considers two GNC algorithms (simple and advanced). The simple GNC algorithm considers three different kinds of PID controllers (velocity, velocity-position, and position), and the advanced GNC algorithm enables path-following and data acquisition and processing from an underwater sensor. The path following is based on the position control using a unique PID controller and obtains its waypoints from a wall detection algorithm. This wall detection algorithm uses a mechanical imaging sonar as the main perception sensor. Finally, an implementation challenge in two control scenarios is addressed to validate the designed GNC architecture and to carry out model-verification of the position PID controller.