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.
| 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 |


