A novel augmented reality and reinforcement learning empowered communication framework for underwater unmanned autonomous vehicle.

ABSTRACT: These days, autonomous uncrewed underwater vehicles (UUVs) play a crucial role in marine exploration, surveillance, and environmental monitoring. However, their communication and object identification are key challenges due to high latency, limited bandwidth, and security vulnerabilities. Traditional UUV frameworks have distinct limitations and pose challenges for dynamic communication in critical environments. To address the above issue, this paper presents a novel augmented reality and reinforcement learning-enabled communication framework for UUAV applications to improve communication quality, enhance object detection, and identify system vulnerabilities. In this framework, we propose adaptive augmented reality and reinforcement learning scheduling strategies (AARLSS) to optimize commun

SUBMITTER: Lakhan A 

PROVIDER: S-EPMC12905303 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature