Development of a hybrid autonomous underwater vehicle for benthic monitoring

Abstract:

This paper reports the initial development of a man-portable hybrid autonomous underwater vehicle that combines the best characteristic of AUV and ROV, good hydrodynamics and high stability in the water column. This architecture allows navigation close to the sea bed to get images and benthic samples. The electronics is based on FPGA and ARM processor development boards. The algorithms for Guidance, Navigation, Control, Computer Vision, Bayesian Networks and Deep Neural Networks were coded by VHDL blocks and C/C++ scripts that run on a Linux Embedded System. The Inertial Navigation System complemented by GPS is implemented by an Extended Kalman Filter described by VHDL blocks working with 64 bit arithmetic floating point and CORDIC algorithm. The main purpose of this hardware-software architecture is to allow the execution of some ROV complex tasks with human operators like identify sites of scientific interest and make parking strategies to collect underwater samples. Experimental results from sea trials are shown.

Año de publicación:

2018

Keywords:

• Remotely Operated Vehicle (ROV)
• Navigation and Control (GNC)
• Field programmable gate array (FPGA)
• Guidance
• Deep Neural Networks (DNN)
• Autonomous Underwater Vehicles (AUV)

Fuente:

google

scopus