Continuous hand-eye calibration using 3D points
(2017) 2017 IEEE 15th International Conference on Industrial Informatics (INDIN)- Abstract
- The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods. The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary... (More)
- The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods. The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary hand-eye transformation. We show that it is superior in accuracy and robustness compared to traditional approaches. Second, we decrease the dependency on the calibration object to a single 3D-point by using a similar formulation based on the equation of translation which is much less affected by the estimation error of the calibration object's orientation. Moreover, it makes the estimation of the orientation obsolete while taking advantage of the higher accuracy and robustness from the first solution, resulting in a versatile method for continuous hand-eye calibration. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/09d903dc-880d-4efc-8c6f-0be83498335f
- author
- Grossmann, Bjarne and Krüger, Volker LU
- publishing date
- 2017
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- continuous hand-eye calibration, calibration algorithms, noisier estimation methods, necessary hand-eye transformation, calibration object pose estimation, single 3D-point, calibration object orientation error estimation
- host publication
- Proceedings of IEEE 2017, 15th International Confference on Industrial Informatics (INDIN)
- publisher
- IEEE Press
- conference name
- 2017 IEEE 15th International Conference on Industrial Informatics (INDIN)
- conference location
- Emden, Germany
- conference dates
- 2017-07-24 - 2017-07-26
- external identifiers
-
- scopus:85041226045
- ISBN
- 978-1-5386-0838-8
- 978-1-5386-0837-1
- DOI
- 10.1109/indin.2017.8104791
- language
- English
- LU publication?
- no
- id
- 09d903dc-880d-4efc-8c6f-0be83498335f
- date added to LUP
- 2019-05-16 21:29:12
- date last changed
- 2024-07-23 16:33:20
@inproceedings{09d903dc-880d-4efc-8c6f-0be83498335f, abstract = {{The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods. The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary hand-eye transformation. We show that it is superior in accuracy and robustness compared to traditional approaches. Second, we decrease the dependency on the calibration object to a single 3D-point by using a similar formulation based on the equation of translation which is much less affected by the estimation error of the calibration object's orientation. Moreover, it makes the estimation of the orientation obsolete while taking advantage of the higher accuracy and robustness from the first solution, resulting in a versatile method for continuous hand-eye calibration.}}, author = {{Grossmann, Bjarne and Krüger, Volker}}, booktitle = {{Proceedings of IEEE 2017, 15th International Confference on Industrial Informatics (INDIN)}}, isbn = {{978-1-5386-0838-8}}, keywords = {{continuous hand-eye calibration; calibration algorithms; noisier estimation methods; necessary hand-eye transformation; calibration object pose estimation; single 3D-point; calibration object orientation error estimation}}, language = {{eng}}, publisher = {{IEEE Press}}, title = {{Continuous hand-eye calibration using 3D points}}, url = {{http://dx.doi.org/10.1109/indin.2017.8104791}}, doi = {{10.1109/indin.2017.8104791}}, year = {{2017}}, }