/Simultaneous Localization and Mapping with Infinite Planes

Simultaneous Localization and Mapping with Infinite Planes

Michael Kaess
Journal Article, Carnegie Mellon University, 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.

BibTeX Reference
author = {Michael Kaess},
title = {Simultaneous Localization and Mapping with Infinite Planes},
journal = {In IEEE Intl. Conf. on Robotics and Automation},
year = {2015},
month = {May},