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In this paper, we study the problem of map compression, that is compressing a given pointset map in the context of robotic mapping and localization applications. In particular, we are interested in grammar-based compression techniques that represent the input data by a context-free grammar generating only that data. A a central contribution, we present a grammar-based map compression framework, as...
Obtaining a compact representation of a given pointset map built by mapper robots is a critical issue for recent SLAM applications. This “map compression” problem is explored from a novel viewpoint of dictionary-based map compression techniques in the paper. The primary contribution of the paper is on the use of geometric priors within a dictionary-based map compression framework. An efficient map...
Obtaining a compact representation of a largesize pointset map built by mapper robots is a critical issue for recent SLAM applications. This “map compression” problem is explored from a novel perspective of dictionary-based map compression in the paper. The primary contribution of the paper is proposal of an incremental scheme for simultaneous mapping and map-compression applications. An incremental...
Obtaining a compact representation of a large-size pointset map built by mapper robots is a critical issue for recent SLAM applications. This “map compression” problem is explored from a novel perspective of dictionary-based map compression in the paper. The primary contribution of the paper is proposal of an incremental scheme for simultaneous mapping and map-compression applications. An incremental...
Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in the context of lightweight information sharing as well as Kolmogorov complexity. This map compression problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is proposal of the dictionary-based map compression...
Obtaining a compact representation of a large-size map built by mapper robots is a critical issue for information sharing in robotic sensor networks. In the paper, this map compression problem is explored from a novel perspective of lossless data compression. The primary contribution of the paper is the proposal of an efficient dictionary-based map compression approach employing RANSAC map-matching...
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