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Multisensor SLAM for Indoor Navigation

Bleier, Michael (2013) Multisensor SLAM for Indoor Navigation. DLR-Interner Bericht. 572-2013/07. Diploma. Friedrich-Alexander-Universität Erlangen-Nürnberg. 96 S. (Unpublished)

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Affordable RGB-D sensors, such as Microsoft Kinect or ASUS Xtion Pro Live, have become a popular choice for gesture recognition and 3D reconstruction. However, in applications for Simultaneous Localization and Mapping (SLAM) the limited range and field of view of these sensors poses a challenge with respect to achieving accurate visual odometry. This thesis presents a multisensor setup for the Rollin’ Justin service robot platform and an approach to robust 3D mapping that is suitable for indoor navigation. Via calibration of multiple sensors the measurements can be projected into a common reference coordinate system for further processing. Matching the combined data provides better motion estimates than establishing the robot pose based on the measurements of the individual sensors. Furthermore, different algorithms for RGB-D frame alignment and techniques for minimizing the accumulated drift are studied. A tree-based map structure and signed distance fields allows one to integrate noisy measurements efficiently and store large areas with a low memory footprint. Moreover, the drift of frame-to-frame registration can be minimized through pose refinement by tracking the sensor frame against the map representation. The approach is validated by comparison to state-of-the-art methods on publicly available ground truth data and experiments on the Rollin’ Justin service robot.

Item URL in elib:https://elib.dlr.de/85578/
Document Type:Monograph (DLR-Interner Bericht, Diploma)
Title:Multisensor SLAM for Indoor Navigation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bleier, Michaelmichael.bleier (at) dlr.deUNSPECIFIED
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:96
Keywords:Multisensor SLAM, Kinect
Institution:Friedrich-Alexander-Universität Erlangen-Nürnberg
Department:Lehrstuhl für Mustererkennung (Informatik 5)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - On-Orbit Servicing [SY]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Autonomy and Teleoperation
Deposited By: Leidner, Daniel
Deposited On:16 Dec 2013 14:55
Last Modified:16 Dec 2013 14:55

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