Photogrammetric Characterization of Robot Positioning Accuracy and Repeatability

  • Additive manufacturing enables the development of low-cost, self-built robotic systems; however, their performance is typically not characterized by validated metrics. The paper presents a photogrammetric concept intended for system-independent application to characterize planar positioning accuracy and repeatability without access to internal controller data. The method is based on a Raspberry Pi 4 camera system, image processing in Python 3.12.0 and OpenCV 4.12.0, and a universal additively manufactured robot tool attachment. Two position estimation strategies are investigated: a marker-based approach using ArUco markers and a markerless blob-analysis method based on a ruby sphere. Camera calibration is evaluated using different patterns, with a compact CharUco board exhibiting the lowest RMS reprojection error (~1 px). Experimental validation follows selected elements of ISO 9283:1998 and comprises 30 repetitions at five target poses for linear and axial motion strategies. The results show lower positional deviations for marker-based methods compared to the markerless approach, with a two-marker configuration yielding the lowest mean deviation under the investigated conditions. Sub-millimeter positioning accuracy and repeatability are achieved, and linear motion exhibits lower repeatability deviations than axial motion. The proposed approach provides a cost-effective and flexible solution for external robot characterization, particularly suited for self-built and resource-constrained systems.

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Metadaten
URN:urn:nbn:de:kobv:526-opus4-21775
Publisher DOI:https://doi.org/10.3390/robotics15050086
Author:Sebastián ChajónORCiD, Jörg Reiff-StephanORCiDGND, Norman GüntherORCiD
ISSN:2218-6581
Parent Title (English):Robotics
Document Type:Article
Language:English
Year of Publication:2026
Volume:15
Issue:5
Article Number:86
Publisher:MDPI
Publishing Institution:Technische Hochschule Wildau
Tag:image processing; photogrammetry; robot characterization
Version:Version of Record
Source:Chajón, S.; Reiff-Stephan, J.; Günther, N. Photogrammetric Characterization of Robot Positioning Accuracy and Repeatability. Robotics 2026, 15, 86. https://doi.org/10.3390/robotics15050086
Faculties an central facilities:Fachbereich Ingenieur- und Naturwissenschaften
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 006 Spezielle Computerverfahren
6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 629 Andere Fachrichtungen der Ingenieurwissenschaften
Funding:Publikationsfonds der TH Wildau
Licence (German): Creative Commons - CC BY - Namensnennung 4.0 International
Release Date:2026/05/04
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