Multi-robot map merging is an essential task for cooperative robot navigation. In the realistic case, the robots do not know the initial positions of the others and this adds extra challenges to the problem. Some approaches search transformation parameters using the local maps and some approaches assume the robots will observe each other and use robot to robot observations. This work extends a ...

We present a robust region segmentation method based on a pseudo-distance map (PDM) that uses a watershed algorithm as a segmentation tool. The PDM is a regularized version of a Euclidean distance map (EDM) directly computed from the edgestrength function (ESF) of an input image without edge detection, which involves a thresholding operation. This unavoidably causes useful region boundary infor...

This paper focuses on the application of triangulation and rubber-sheeting techniques to the problem of merging two digitized map files. The Census Bureau is currently developing a map merging procedure called conflation. Reproducibility, quality control, and a desire for mathematical consistency in conflation lead to a need for well-defined procedures. The Delaunay triangulation is well-define...

Merging is an important operation in the map generalization of land-cover and other coverages. We define structured geographic objects as collections adjacent areas with homogeneous semantics that are regularly arranged spatial structures. Existing studies have concentrated on unstructured objects, which will lead to ones losing part or even most typical characteristics during merging. Therefor...

This paper presents OntoShare, an automated ontology mapping and merging architecture for learning object retrieval and reuse. The architecture aims to offer contextual and robust ontology mapping and merging through hybrid unsupervised clustering techniques comprising of Formal Concept Analysis (FCA), Self-Organizing Map (SOM) and K-Means clustering incorporated with linguistic processing usin...

We address the problem of partitioning a volume image into a previously unknown number of segments, based on a likelihood of merging adjacent supervoxels. Towards this goal, we adapt a higher-order probabilistic graphical model that makes the duality between supervoxels and their joint faces explicit and ensures that merging decisions are consistent and surfaces of final segments are closed. Fi...

Controlled language is the primary challenge in merging heterogeneous databases of geologic information. Each agency or organization produces databases with different schema, and different terminology for describing the objects within. In order to make some progress toward merging these databases using current technology, we have developed software and a workflow that allows for the “manual sem...

The recent merging self-organizing map (MSOM) for unsupervised sequence processing constitutes a fast, intuitive, and powerful unsupervised learning model. In this paper, we investigate its theoretical and practical properties. Particular focus is put on the context established by the self-organizing MSOM, and theoretic results on the representation capabilities and the MSOM training dynamic ar...