In order to achieve an autonomous vessel, it is important how to organize the map. The map is required to be fine when navigating in confined space but to be coarse when navigating in sparse space to save memory consumption and computation time. However switching between fine and coarse maps may cause discontinuities of navigation. In this paper, we propose a concept that integrates coarse and fine maps without switching between them named SEAMLESS. To resolve the ambiguity near the map boundary and optimize the number of map grids, our approach integrates the wide area maps and the narrow area maps with depth-optimized Quad Trees according to each sensor's distance error and self-positioning error. The concept has been demonstrated in real environment on our vessel with multi-modal system which generates both wide and narrow area maps based on obstacle detection.
