Development and Validation of Embedded System Architecture for Shallow-Water Based H-AUV

Abstract Autonomous underwater vehicles (AUVs) have gained enormous popularity over the years and are employed extensively in various industries, including bio-research, subsea industries, and military applications. Most of the available commercial AUVs are very expensive and complex. This makes it unsuitable to be used for civilian applications. On the other hand, recent technological advancements have made it possible to have highly capable sensors at acceptable prices as an alternative to expensive commercial vehicles. In this paper, an embedded system-based multi-sensor hardware architecture for an H-configured AUV, called H-AUV, is designed and developed with low-cost, power-efficient, real-time controllers with a small footprint for data acquisition and sensors. These parameters play an important role for designing and developing energy-efficient autonomous vehicles. Significantly, auto navigation is a very important mechanism for AUVs, which includes auto heading control and depth keeping control techniques developed, deployed, and tested in the H-AUV. Additionally, the denoise filters such as moving average, exponential, and dynamic linear Kalman filter (KF) have been exercised and validated for heading and depth control of an H-AUV. It was found that the dynamic KF is very efficient and performs with 88% accuracy in the heading and depth control mechanisms. The KF is also found to perform with 98% accuracy for surface navigation of the H-AUV. Finally, an indigenous graphical user interface has been developed for data telemetry, command, and logging in autonomous and manual modes through wired and wireless communication. The proposed development and validation of an efficient and low-cost H-AUV shall support academic researchers for subsea applications.