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GraphSLAM

In robotics, GraphSLAM is a Simultaneous localization and mapping algorithm which uses sparse information matrices produced by generating a graph of… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous… Expand
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2017
2017
The general simultaneous localization and mapping (SLAM) problem aims at estimating the state of a moving platform simultaneously… Expand
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2016
2016
An extensive, precise and robust recognition and modeling of the environment is a key factor for next generations of Advanced… Expand
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2015
2015
To build consistent feature-based map for the environment, GraphSLAM forms the graph using the collected information, with poses… Expand
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2014
2014
The increasing use of Autonomous Underwater Vehicles (AUV) in industrial or scientific applications makes the vehicle… Expand
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2013
2013
This paper presents a robust solution to the mobile robotics data association problem based on solving the maximum clique problem… Expand
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Highly Cited
2011
Highly Cited
2011
The widespread deployment of wireless networks presents an opportunity for localization and mapping using only signal-strength… Expand
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Highly Cited
2011
Highly Cited
2011
Estimating a vehicles' own trajectory and generating precise maps of the environment are both important tasks for intelligent… Expand
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Highly Cited
2006
Highly Cited
2006
A robot exploring an environment can estimate its own motion and the relative positions of features in the environment… Expand
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Highly Cited
2006
Highly Cited
2006
This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent… Expand
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