G<sup>2</sup>o: A general framework for graph optimization
Published: May 1, 2011
Abstract
Many popular problems in robotics and computer vision including various types of simultaneous localization and mapping (SLAM) or bundle adjustment (BA) can be phrased as least squares optimization of an error function that can be represented by a graph. This paper describes the general structure of such problems and presents g 2 o, an open-source...
Paper Details
Title
G<sup>2</sup>o: A general framework for graph optimization
Published Date
May 1, 2011
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