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Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision

Müller, Marcus Gerhard and Steidle, Florian and Schuster, Martin and Lutz, Philipp and Maier, Moritz and Stoneman, Samantha and Tomic, Teodor and Stürzl, Wolfgang (2018) Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision. In: IEEE International Conference on Intelligent Robots and Systems. IROS 2018, 01-05 Oct 2018, Madrid, Spain.

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Abstract

The here presented flying system uses two pairs of wide-angle stereo cameras and maps a large area of interest in a short amount of time. We present a multicopter system equipped with two pairs of wide-angle stereo cameras and an inertial measurement unit (IMU) for robust visual-inertial navigation and time-efficient omni-directional 3D mapping. The four cameras cover a 240 degree stereo field of view (FOV) vertically, which makes the system also suitable for cramped and confined environments like caves. In our approach, we synthesize eight virtual pinhole cameras from four wide-angle cameras. Each of the resulting four synthesized pinhole stereo systems provides input to an independent visual odometry (VO). Subsequently, the four individual motion estimates are fused with data from an IMU, based on their consistency with the state estimation. We describe the configuration and image processing of the vision system as well as the sensor fusion and mapping pipeline on board the MAV. We demonstrate the robustness of our multi-VO approach for visual-inertial navigation and present results of a 3D-mapping experiment.

Item URL in elib:https://elib.dlr.de/122805/
Document Type:Conference or Workshop Item (Speech)
Title:Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Müller, Marcus GerhardMarcus.Mueller (at) dlr.deUNSPECIFIED
Steidle, FlorianFlorian.Steidle (at) dlr.deUNSPECIFIED
Schuster, MartinMartin.Schuster (at) dlr.dehttps://orcid.org/0000-0002-6983-3719
Lutz, Philippphilipp.lutz (at) dlr.deUNSPECIFIED
Maier, MoritzMoritz.Maier (at) dlr.deUNSPECIFIED
Stoneman, SamanthaSamantha.Stoneman (at) dlr.deUNSPECIFIED
Tomic, Teodorteodor.tomic (at) gmail.comUNSPECIFIED
Stürzl, WolfgangWolfgang.Stuerzl (at) dlr.deUNSPECIFIED
Date:2018
Journal or Publication Title:IEEE International Conference on Intelligent Robots and Systems
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Status:Published
Keywords:MAV; UAV; visual odometry; multiple cameras; robust state estimation; 3D mapping; robust visual-inertial navigation; ultra-wide FOV stereo vision; robotic
Event Title:IROS 2018
Event Location:Madrid, Spain
Event Type:international Conference
Event Dates:01-05 Oct 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):Vorhaben Intelligente Mobilität
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Müller, Marcus Gerhard
Deposited On:07 Dec 2018 17:24
Last Modified:31 Jul 2019 20:20

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