Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Informatics in Control, Automation and Robotics |
| Herausgeber/-innen | Joaquim Filipe, Oleg Gusikhin, Jurek Sasiadek, Kurosh Madani |
| Erscheinungsort | Cham |
| Seiten | 43-58 |
| Seitenumfang | 16 |
| ISBN (elektronisch) | 978-3-319-26453-0 |
| Publikationsstatus | Veröffentlicht - 2016 |
Publikationsreihe
| Name | Lecture Notes in Electrical Engineering |
|---|---|
| Band | 370 |
| ISSN (Print) | 1876-1100 |
| ISSN (elektronisch) | 1876-1119 |
Abstract
This paper describes two methods to determine the homogeneous transformation of a projector with respect to the robot hand. Since the projector itself has no exteroceptive capabilities, a camera is rigidly attached to the robot base or placed in the environment to detect the projected pattern. The camera’s extrinsic calibration parameters can be simultaneously solved, which is shown by the second method. Self-calibration implies that any kind of calibration tool may be omitted. For calibration, the robot hand has to make at least two movements around nonparallel rotational axes. At each robot configuration, correspondences between the camera and the projector are established to recover the transformation between them, up to an unknown scale factor. The system is described by the common known formulations AX = XB and AX = ZB. Both can be arranged in a linear form with respect to the unknown extrinsic parameters and scale factors, and solved in least square sense. Further optimization allows to refine all intrinsic and extrinsic parameters.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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Informatics in Control, Automation and Robotics. Hrsg. / Joaquim Filipe; Oleg Gusikhin; Jurek Sasiadek; Kurosh Madani. Cham, 2016. S. 43-58 (Lecture Notes in Electrical Engineering; Band 370).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Full Self-calibration of a Hand-Mounted Projector Using Structured Light
AU - Wieghardt, Christian S.
AU - Wagner, Bernardo
PY - 2016
Y1 - 2016
N2 - This paper describes two methods to determine the homogeneous transformation of a projector with respect to the robot hand. Since the projector itself has no exteroceptive capabilities, a camera is rigidly attached to the robot base or placed in the environment to detect the projected pattern. The camera’s extrinsic calibration parameters can be simultaneously solved, which is shown by the second method. Self-calibration implies that any kind of calibration tool may be omitted. For calibration, the robot hand has to make at least two movements around nonparallel rotational axes. At each robot configuration, correspondences between the camera and the projector are established to recover the transformation between them, up to an unknown scale factor. The system is described by the common known formulations AX = XB and AX = ZB. Both can be arranged in a linear form with respect to the unknown extrinsic parameters and scale factors, and solved in least square sense. Further optimization allows to refine all intrinsic and extrinsic parameters.
AB - This paper describes two methods to determine the homogeneous transformation of a projector with respect to the robot hand. Since the projector itself has no exteroceptive capabilities, a camera is rigidly attached to the robot base or placed in the environment to detect the projected pattern. The camera’s extrinsic calibration parameters can be simultaneously solved, which is shown by the second method. Self-calibration implies that any kind of calibration tool may be omitted. For calibration, the robot hand has to make at least two movements around nonparallel rotational axes. At each robot configuration, correspondences between the camera and the projector are established to recover the transformation between them, up to an unknown scale factor. The system is described by the common known formulations AX = XB and AX = ZB. Both can be arranged in a linear form with respect to the unknown extrinsic parameters and scale factors, and solved in least square sense. Further optimization allows to refine all intrinsic and extrinsic parameters.
KW - Motion estimation
KW - Pattern projection
KW - Self-calibration
KW - Structured light system
UR - http://www.scopus.com/inward/record.url?scp=84952778205&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-26453-0_3
DO - 10.1007/978-3-319-26453-0_3
M3 - Conference contribution
SN - 9783319264516
T3 - Lecture Notes in Electrical Engineering
SP - 43
EP - 58
BT - Informatics in Control, Automation and Robotics
A2 - Filipe, Joaquim
A2 - Gusikhin, Oleg
A2 - Sasiadek, Jurek
A2 - Madani, Kurosh
CY - Cham
ER -