Adaptive deep perception methods for autonomous surface vehicles

The project’s overarching goal is to develop the next-generation maritime environment perception methods, which will harvest the power of end-to-end trainable deep models. The models will address the challenges essential for safe USV operation like general obstacle detection, long-term tracking with re-identification, implicit detection of hazardous areas and sensor fusion for improved detection. Particular focus will be placed on the adaptivity of the models and self-supervised tuning to new environments. New multisensor datasets are planned to be recorded to facilitate this research.