The implementation of unmanned vessels will evidently come with its own legal challenges. One of the most crucial of these is the identification of the role and status of the shore-based controller (SBC) for the purposes of determining liability. Different liability regimes apply different legal principles in this regard. This article will explore these issues from the perspective of English law and Scandinavian law.
Abstract: In recent years, the development of ground robots with human-like perception capabilities has led to the use of multiple sensors, including cameras, lidars, and radars, along with deep learning techniques for detecting and recognizing objects and estimating distances. This paper proposes a computer vision-based navigation system that integrates object detection, segmentation, and monocular depth estimation using deep neural networks to identify predefined target objects and navigate towards them with a single monocular camera as a sensor. Our experiments include different sensitivity analyses to evaluate the impact of monocular cues on distance estimation. We show that this system can provide a ground robot with the perception capabilities needed for autonomous navigation in unknown indoor environments without the need for prior mapping or external positioning systems. This technique provides an efficient and cost-effective means of navigation, overcoming the limitations of other navigation techniques such as GPS-based and SLAM-based navigation. Graphical Abstract: [Figure not available: see fulltext.]