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Analysing visual-inertial odometry algorithms for the localization of industrial autonomous mobile robots in intralogistics and manufacturing
Citation Link: https://doi.org/10.15480/882.13741
Other Titles
Analyse visueller Odometrie-Algorithmen für die Lokalisierung von autonomen mobilen Industrierobotern in der Intralogistik und Fertigung
Publikationstyp
Conference Paper
Date Issued
2024-09-26
Sprache
English
Author(s)
Krishnamurthy, Aishwarya
Adamanov, Asan
Rose, Hendrik Wilhelm
Küstner, David
TORE-DOI
Journal
Citation
20. Fachkolloquium Logistik, 2024
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
WGTL
Peer Reviewed
true
The use of Autonomous Mobile Robots (AMR) plays asignificant role inthe automation of intralogisticsprocesses. For safe operation and navigation, high locali-zation accuracy is required. Common AMR systems rely oncost-intensive sensors such as LIDAR scanners. To en-able widespread use of AMRs the industry alternative so-lutions are required. This study explores stereo camera-based visual SLAM as a cost-effective alternative to con-ventional 3D LIDAR-based localization solutions for an industrial robot application. Using Stereolabs ZED 2I and Intel RealSense D455 cameras with ORB-SLAM3 and OpenVINS algorithms, we evaluated Mean Absolute Pose Error (APE) and Root Mean Square Pose Error (RPE). The highest accuracy was achieved with the ZED 2I with OpenVINS with an APE of 0.17m and an RPE of 0.02m while the use of a RealSense D455 showed an APE of 0.33m with an RPE of 0.02m
DDC Class
600: Technology
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