Simultaneous Localization and Mapping with Infinite Planes

Michael Kaess
Journal Article, In IEEE Intl. Conf. on Robotics and Automation, May, 2015

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Simultaneous localization and mapping with in- finite planes is attractive because of the reduced complexity with respect to both sparse point-based and dense volumetric methods. We show how to include infinite planes into a least- squares formulation for mapping, using a homogeneous plane parametrization with a corresponding minimal representation for the optimization. Because it is a minimal representation, it is suitable for use with Gauss-Newton, Powell’s Dog Leg and incremental solvers such as iSAM. We also introduce a relative plane formulation that improves convergence. We evaluate our proposed approach on simulated data to show its advantages over alternative solutions. We also introduce a simple mapping system and present experimental results, showing real-time mapping of select indoor environments with a hand-held RGB- D sensor.

author = {Michael Kaess},
title = {Simultaneous Localization and Mapping with Infinite Planes},
journal = {In IEEE Intl. Conf. on Robotics and Automation},
year = {2015},
month = {May},
} 2018-11-12T12:36:42-04:00