Frontiers in Marine Research Robotics

Overview

Abstract

Marine robotics have evolved substantially since the early days of autonomous underwater vehicles which meant a multimillion-dollar vehicle always accompanied by a surface vehicle. An early step forward in scientific vehicles was the development of the buoyancy-driven autonomous underwater vehicles which could stay at sea for months and traverse large distances and depths down to 1000m, albeit slowly. Critical needs exist for vehicles that can map, image and characterize the sea bottom, and for intelligent fleet management schemes. The mesophotic (below diver accessible depths) and the deep ocean are poorly known regions. Thus, design of a new types of vehicles capable of terrain following, obstacle avoidance and navigational learning are essential to fill gaps in our knowledge of the deeper ocean. The need extends not only to the shallower depths, but to the very deep ocean (77% of the ocean is deeper than 4000 meters) which is extremely difficult to explore and map via existing approaches such as surface ships and ROVs. A second area of high need is effective fleet management. The integration of autonomous aquatic vehicle fleets with oceanographic models and AI is essential to improve our understanding of the ocean.

Biography

Professor Jones' (see Twitter) research interests include bio-optical oceanography, physical-biological interactions, coastal processes, and coastal ocean observing systems. He has been involved in studying the dynamics of physical and biological interactions in a variety of environments throughout the world. Development of instrument systems and implementation of ocean observing networks has been a major technological thrust of his efforts. At KAUST he has extended these efforts to understand the physical and biogeochemical processes within the Red Sea, the interaction of the open sea with the coastal coral reef systems, and developing a basis for managing future use of the Red Sea. He is currently leading efforts in the implementation of a "Smart Reef" observational network and in development of a new fit-for-purpose autonomous vehicle for benthic imaging and characterization.