SoilGrids TM (hereafter SoilGrids) is a system for global digital soil mapping that uses state-of-the-art machine learning methods to map the spatial distribution of soil properties across the globe. doi: 10.1016/j.isprsjprs.2020.03.008.We are collecting information on SoilGrids’ user base to improve the products and better understand their uses. SLAM aided forest plot mapping combining terrestrial and mobile laser scanning. Shao J., Zhang W., Mellado N., Wang N., Jin S., Cai S., Yan G. Multi-Modal Signal Analysis for Underwater Acoustic Sound Processing Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Halifax, NS, Canada. Talebpour F., Mozaffari S., Saif M., Alirezaee S. Bio-inspired monocular drone SLAM Proceedings of the Conference on System Engineering for Constrained Embedded Systems Budapest, Hungary. Heterogeneous Collaborative Mapping for Autonomous Mobile Systems.Ĭatal O., Verbelen T., Wang N., Hartmann M., Dhoedt B. University of Windsor Windsor, ON, Canada: 2022.
A review on map-merging methods for typical map types in multiple-ground-robot SLAM solutions. We also present the results based on hierarchical map fusion to merge six individual maps at once in order to constrict a consistent global map for SLAM.Ĭollaborative SLAM feature-base map merging heterogeneous on-board sensors occupancy grid maps. It is shown that the presented method is suitable for identifying geometrically consistent features across various mapping conditions, such as low overlapping and different grid resolutions. Further, a global grid fusion strategy based on the Bayesian inference, which is independent of the order of merging, is also provided. We also present a procedure to verify and accept the correct transformation to avoid ambiguous map merging. This article presents an effective feature-based map fusion approach that includes processing the spatial occupancy probabilities and detecting features based on locally adaptive nonlinear diffusion filtering. Such map fusion requires solving the unknown initial correspondence problem. These maps can be exchanged and integrated among robots to reduce the overall exploration time, which is the main advantage of the collaborative systems. One of the most frequently used approaches to represent collaborative mapping are probabilistic occupancy grid maps.
0 kommentar(er)
