Details
Originalsprache | Englisch |
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Titel des Sammelwerks | 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) |
Herausgeber/-innen | Lino Marques, Majid Khonji, Jorge Dias |
Herausgeber (Verlag) | IEEE Computer Society |
Seiten | 341-347 |
Seitenumfang | 7 |
ISBN (elektronisch) | 978-1-6654-0390-0 |
ISBN (Print) | 978-1-6654-0391-7, 978-1-6654-0389-4 |
Publikationsstatus | Veröffentlicht - 2020 |
Veranstaltung | 2020 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR) - virtual event Dauer: 4 Nov. 2020 → 6 Nov. 2020 |
Publikationsreihe
Name | IEEE International Symposium on Safety, Security and Rescue Robotics |
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ISSN (Print) | 2374-3247 |
ISSN (elektronisch) | 2475-8426 |
Abstract
An accurate geometric calibration between the subsystems of a mobile platform is essential for a multitude of applications. The laser scanner is of particular relevance for tasks such as localization and mapping, as well as for object-and obstacle detection. Thus, the calibration between a laser scanner and a manipulator is of particular interest for mobile manipulation and relevant for the use in industrial applications, disaster szenarios or search-and-rescue missions. In this paper, we present a probabilistic method for geometric calibration of a manipulator and a 2D laser scanner. In contrast to state-of-the-art procedures, the presented method takes into account the uncertainties of the measurements of the laser scanner and of joints which is propagated through the kinematic chain of the manipulator. Furthermore, our approach provides an estimate of the uncertainty of the resulting calibration. The method does not require any additional sensors and constitutes an accurate and easy-to-apply solution. The approach is validated with data of simulation and real experiments. We show in numerous monte carlo simulations that considering the uncertatinties improves the accuracy by 50.2% in translation and 44.3% in rotation compared to a state-of-the-art procedure. The plausibility of the estimated calibration is validated by real experiments. Furthermore, the provided uncertainty of each calibration parameter indicates whether recalibration is required.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Angewandte Informatik
- Ingenieurwesen (insg.)
- Maschinenbau
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Mathematik (insg.)
- Steuerung und Optimierung
- Sozialwissenschaften (insg.)
- Sicherheitsforschung
Zitieren
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- BibTex
- RIS
2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). Hrsg. / Lino Marques; Majid Khonji; Jorge Dias. IEEE Computer Society, 2020. S. 341-347 9292604 (IEEE International Symposium on Safety, Security and Rescue Robotics).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Probabilistic Calibration of a Manipulator and a 2D Laser Scanner
AU - Alberts, Jan
AU - Kleinschmidt, Sebastian P.
AU - Wagner, Bernardo
PY - 2020
Y1 - 2020
N2 - An accurate geometric calibration between the subsystems of a mobile platform is essential for a multitude of applications. The laser scanner is of particular relevance for tasks such as localization and mapping, as well as for object-and obstacle detection. Thus, the calibration between a laser scanner and a manipulator is of particular interest for mobile manipulation and relevant for the use in industrial applications, disaster szenarios or search-and-rescue missions. In this paper, we present a probabilistic method for geometric calibration of a manipulator and a 2D laser scanner. In contrast to state-of-the-art procedures, the presented method takes into account the uncertainties of the measurements of the laser scanner and of joints which is propagated through the kinematic chain of the manipulator. Furthermore, our approach provides an estimate of the uncertainty of the resulting calibration. The method does not require any additional sensors and constitutes an accurate and easy-to-apply solution. The approach is validated with data of simulation and real experiments. We show in numerous monte carlo simulations that considering the uncertatinties improves the accuracy by 50.2% in translation and 44.3% in rotation compared to a state-of-the-art procedure. The plausibility of the estimated calibration is validated by real experiments. Furthermore, the provided uncertainty of each calibration parameter indicates whether recalibration is required.
AB - An accurate geometric calibration between the subsystems of a mobile platform is essential for a multitude of applications. The laser scanner is of particular relevance for tasks such as localization and mapping, as well as for object-and obstacle detection. Thus, the calibration between a laser scanner and a manipulator is of particular interest for mobile manipulation and relevant for the use in industrial applications, disaster szenarios or search-and-rescue missions. In this paper, we present a probabilistic method for geometric calibration of a manipulator and a 2D laser scanner. In contrast to state-of-the-art procedures, the presented method takes into account the uncertainties of the measurements of the laser scanner and of joints which is propagated through the kinematic chain of the manipulator. Furthermore, our approach provides an estimate of the uncertainty of the resulting calibration. The method does not require any additional sensors and constitutes an accurate and easy-to-apply solution. The approach is validated with data of simulation and real experiments. We show in numerous monte carlo simulations that considering the uncertatinties improves the accuracy by 50.2% in translation and 44.3% in rotation compared to a state-of-the-art procedure. The plausibility of the estimated calibration is validated by real experiments. Furthermore, the provided uncertainty of each calibration parameter indicates whether recalibration is required.
UR - http://www.scopus.com/inward/record.url?scp=85099455840&partnerID=8YFLogxK
U2 - 10.1109/SSRR50563.2020.9292604
DO - 10.1109/SSRR50563.2020.9292604
M3 - Conference contribution
SN - 978-1-6654-0391-7
SN - 978-1-6654-0389-4
T3 - IEEE International Symposium on Safety, Security and Rescue Robotics
SP - 341
EP - 347
BT - 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
A2 - Marques, Lino
A2 - Khonji, Majid
A2 - Dias, Jorge
PB - IEEE Computer Society
T2 - 2020 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)
Y2 - 4 November 2020 through 6 November 2020
ER -