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

今天的海洋科学需要在极端环境中收集数据，包括极地海洋和冰层下的数据。AUV经常被用于这些任务，允许进入传统的基于船舶的采样方法无法到达的区域。要使AUV能够在这些复杂的环境中作业，可靠的避障系统的可用性是至关重要的，这种环境的不断演变和有限的可预测性给海洋自主作业带来了额外的挑战。自动驾驶汽车必须能够迅速和充分地应对动态环境带来的挑战，以维护自己的安全和收集的宝贵数据的完整性。尽管避障引起了人们的极大兴趣，但这个问题仍然存在悬而未决的问题和有待改进的领域。该项目将专注于开发稳健可靠的算法和程序，使水下机器人能够根据机载传感器(如测距或成像声纳)提供的信息有效地检测其周围环境，并利用这些知识来保证其安全，成功完成自主任务。候选人将被要求为解决问题的不同方面做出贡献并开发创新的解决方案

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