A Storage-Saving Quadtree-Based Multibeam Bathymetry Map Representation Method

With the rapid advancement of simultaneous localization and mapping (SLAM) technology, collaboration several autonomous underwater vehicles (AUVs) in large-scale seafloor imaging has become a trending topic. Electromagnetic waves are difficult to transfer underwater, only viable method communication is acoustic transmission, but its bandwidth limited. Therefore, how compress process multibeam bathymetry maps so that AUVs can acquire gathered by other an important topic study. This study presents representation approach for based on quadtree structure. In comparison girding approach, sparse pseudo-input Gaussian processes (SPGPs) method, octree-based quadtree-based suggested this preserves precision while compressing storage space. Experiments utilizing field data validate performance proposed technique, method’s ability space towards AUV cooperative SLAM’s scenario.