A Guidance, Navigation, and Control Architecture for a Co-operative Autonomous Offshore System

Abstract

In recent years, researchers have widely used autonomous systems in marine environment exploration and exploitation. The main reasons for this are the amount of unknown and unexplored areas (in oceans, seas, and lakes) and the extensive range of autonomous vehicle applications. Autonomous offshore systems include unmanned surface vehicles (USVs) and autonomous underwater vehicles (AUVs) as primary offshore vehicles; their guidance, navigation, and control (GNC) architectures play a significant role in algorithm development. The ultimate goal of this research is to solve the design, modeling, and implementation challenges of a path-following algorithm with obstacle avoidance as the GNC architecture for a co-operative autonomous offshore system formed by a USV and AUV.

First, this thesis concentrates on developing a mathematical model based on non­linear equations of motion, using system identification (SI) and parameter estimation techniques and validating the USV and AUV models with field test data. Second, this thesis also provides a comprehensive analysis of various guidance and control methods focusing on the path-following and obstacle avoidance algorithms. The GNC architecture uses a modular and multi-layer approach allowing for the fast check of the GNC algorithms for both USV and AUV platforms. This architecture includes all obstacle detection, path-following, and control algorithms. Then, the results show the implementation challenges in simulation and field test control scenarios. These results present the capabilities and adequate performance of the developed GNC architecture for an individual vehicle operation in the autonomous offshore system. Finally, a GNC architecture for the complete co-operative autonomous offshore system is designed and implemented based on the development of the USV and AUV. The co-operative system implementation includes decentralized control techniques, allowing for the fusion of information obtained from the individual vehicles. Additionally, the decentralized control allows for exchanging the necessary information with other components of the co-operative system.