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2020 | OriginalPaper | Chapter

Low-Cost RGB-D-SLAM Experimental Results for Real Building Interior Mapping

Authors : Jean Motsch, Yves Bergeon, Václav Křivánek

Published in: Modelling and Simulation for Autonomous Systems

Publisher: Springer International Publishing

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Abstract

Robot navigation inside a building relies on efficient localization of the device for motion planning. Mapping is also to be considered, and, along with high-end and costly solutions, low-cost devices prove to be useful. Therefore, this article presents well known low-cost solutions, with a methodology tailored for the mapping of a complex building floor. It takes care of the limitations of the sensor with some post-processing added to obtain beautiful point cloud as results of the experiments. Data acquired during an intensive campaign of measures by a trainee are presented. Finally, the analysis of the results shows the impact of the point cloud’s size and the storage needed.

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previous chapter Kinematic Model of a Specific Robotic Manipulator

next chapter Deep Learning Algorithms for Vehicle Detection on UAV Platforms: First Investigations on the Effects of Synthetic Training

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http://wiki.ros.org/openni_launch/Tutorials/BagRecordingPlayback.

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Title: Low-Cost RGB-D-SLAM Experimental Results for Real Building Interior Mapping
Authors: Jean Motsch
Yves Bergeon
Václav Křivánek
Publisher: Springer International Publishing
Book: Modelling and Simulation for Autonomous Systems
Print ISBN: 978-3-030-43889-0

Electronic ISBN: 978-3-030-43890-6

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-43890-6_4

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