The alignment of two occupancy grid maps generated by SLAM algorithms is a quite researched problem, being an obligatory step either for unsupervised map merging techniques or for evaluation of OGMs (Occupancy Grid Maps) against a blueprint of the environment. This paper provides an overview of the existing automatic alignment techniques of two occupancy grid maps that employ pattern matching. Additionally, an alignment pipeline using local features and image descriptors is implemented, as well as a method to eliminate erroneous correspondences, aiming at producing the correct transformation between the two maps. Finally, map quality metrics are proposed and utilized, in order to quantify the produced map’s correctness. A comparative analysis was performed over a number of image processing and OGM-oriented detectors and descriptors, in order to identify the best combinations for the map evaluation problem, performed between two OGMs or between an OGM and a Blueprint map.
https://link.springer.com/article/10.1007/s10846-019-01053-7
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ISSEL at RSCy2025: Advancing Food Security & Sustainability with Cutting-Edge Tech!
We’re excited to participate in RSCy2025 and present our latest research on food security, sustainability, and digital innovation in agriculture! Our Contributions: • Best paper award : A hybrid Edge-to-Cloud Architecture towards low-code development of Read more…