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

增强冰下自主水下航行器避障系统的自主性和决策能力

• 批准号: 2757066
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2757066
• 关键词: Enhancing; Autonomy; Decision; Making; Capabilities

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

当今的海洋科学需要在极端环境下收集数据，包括极地海洋和冰下。 AUV 通常用于执行这些任务，允许进入传统船基采样方法无法到达的区域。可靠的避障系统的可用性对于在这些复杂环境中实现 AUV 操作至关重要，其不断发展和有限的可预测性给海洋自主操作带来了额外的挑战。自动驾驶车辆必须能够及时、充分地应对动态环境带来的挑战，以维护自身的安全和所收集的宝贵数据的完整性。尽管避障引起了人们极大的兴趣，但该问题仍然存在悬而未决的问题和需要改进的领域。该项目将重点开发稳健可靠的算法和流程，使水下航行器能够根据机载传感器（例如测距或成像声纳）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地成功完成自主任务。候选人将被要求做出贡献并开发创新的解决方案来解决问题的各个方面