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“Simultaneous Localization and Mapping with Infinite Planes” by M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Seattle, WA), May 2015, pp. 4605-4611.
Simultaneous localization and mapping with infinite 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.
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BibTeX entry:
@inproceedings{Kaess15icra,
author = {M. Kaess},
title = {Simultaneous Localization and Mapping with Infinite Planes},
booktitle = {Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA},
pages = {4605-4611},
address = {Seattle, WA},
month = may,
year = {2015}
}