Enhancing Autonomy and Decision-Making Capabilities of an Obstacle Avoidance System for Autonomous Underwater Vehicles Operating Under Ice

Today's marine science requires the collection of data in extreme environments, including polar oceans and under ice. AUVs are often employed for these tasks, granting access to areas not reachable with conventional ship-based sampling methods. The availability of a reliable obstacle avoidance system is of paramount importance to enable AUV operations in these complex environments, whose continuous evolution and limited predictability pose additional challenges to marine autonomous operations. An autonomous vehicle must be able to promptly and adequately react to the challenges that a dynamic environment presents to maintain its own safety and the integrity of the precious data it collects. Despite the large interest that obstacles avoidance has received, the problem still presents open questions and areas for improvement. The project will focus on the development of robust and reliable algorithms and processes to enable an underwater vehicle to effectively detect its surrounding environment based on the information provided by onboard sensors (such as ranging or imaging sonars), and to use that knowledge to guarantee its safety to successfully complete autonomous missions. The candidate will be required to contribute to and develop innovative solutions to tackle the diverse aspects of the problem