Details
Originalsprache | Englisch |
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Seiten | 197-203 |
Seitenumfang | 7 |
Publikationsstatus | Veröffentlicht - 30 Aug. 2017 |
Veranstaltung | 2017 18th International Conference on Advanced Robotics (ICAR) - Hong Kong Science and Technology Park, Hong Kong, China Dauer: 10 Juli 2017 → 12 Juli 2017 |
Konferenz
Konferenz | 2017 18th International Conference on Advanced Robotics (ICAR) |
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Kurztitel | ICAR |
Land/Gebiet | China |
Ort | Hong Kong |
Zeitraum | 10 Juli 2017 → 12 Juli 2017 |
Abstract
Rising automation requirements in manufacturing lead to an increasing demand for robot self-calibration. Self-calibration becomes a challenging task for mobile robots since the environment is dynamic, at least from the perspective of moving robots. This paper proposes a new self-calibration method by tracking the end-effector with the help of a head-mounted projector (see Fig. 1). Pseudorandom coded light is projected into the environment and single images are decoded. The pattern consists of checkerboard-like corner-primitives, which are detected by a camera-pair, mounted on the robot base. Triangulation yields the primitives' positions. The projector can be described as an inverse camera model, so its pose is determinable by taking the primitive points as reference. The extrinsic hand-projector and camera-robot transformations are given by the commonly known formula AX = ZB. Further optimization and the incorporation of the joint parameters allow the calibration of the manipulator. Self-calibration means that no sort of calibration object like a checkerboard is needed. Since the decoding is applied to single images, the environment is permitted to change, and the robot is allowed to move around freely during calibration. Experimental results of this method show a submillimeter accuracy of the proposed projector tracking as well as improvements of the robot's accuracy in its typical workspace.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Angewandte Informatik
- Ingenieurwesen (insg.)
- Maschinenbau
- Mathematik (insg.)
- Steuerung und Optimierung
Zitieren
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- BibTex
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2017. 197-203 Beitrag in 2017 18th International Conference on Advanced Robotics (ICAR), Hong Kong, China.
Publikation: Konferenzbeitrag › Paper › Forschung › Peer-Review
}
TY - CONF
T1 - Self-calibration of a mobile manipulator using structured light.
AU - Wieghardt, Christian Sebastian
AU - Wagner, Bernardo
N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions. Publisher Copyright: © 2017 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/8/30
Y1 - 2017/8/30
N2 - Rising automation requirements in manufacturing lead to an increasing demand for robot self-calibration. Self-calibration becomes a challenging task for mobile robots since the environment is dynamic, at least from the perspective of moving robots. This paper proposes a new self-calibration method by tracking the end-effector with the help of a head-mounted projector (see Fig. 1). Pseudorandom coded light is projected into the environment and single images are decoded. The pattern consists of checkerboard-like corner-primitives, which are detected by a camera-pair, mounted on the robot base. Triangulation yields the primitives' positions. The projector can be described as an inverse camera model, so its pose is determinable by taking the primitive points as reference. The extrinsic hand-projector and camera-robot transformations are given by the commonly known formula AX = ZB. Further optimization and the incorporation of the joint parameters allow the calibration of the manipulator. Self-calibration means that no sort of calibration object like a checkerboard is needed. Since the decoding is applied to single images, the environment is permitted to change, and the robot is allowed to move around freely during calibration. Experimental results of this method show a submillimeter accuracy of the proposed projector tracking as well as improvements of the robot's accuracy in its typical workspace.
AB - Rising automation requirements in manufacturing lead to an increasing demand for robot self-calibration. Self-calibration becomes a challenging task for mobile robots since the environment is dynamic, at least from the perspective of moving robots. This paper proposes a new self-calibration method by tracking the end-effector with the help of a head-mounted projector (see Fig. 1). Pseudorandom coded light is projected into the environment and single images are decoded. The pattern consists of checkerboard-like corner-primitives, which are detected by a camera-pair, mounted on the robot base. Triangulation yields the primitives' positions. The projector can be described as an inverse camera model, so its pose is determinable by taking the primitive points as reference. The extrinsic hand-projector and camera-robot transformations are given by the commonly known formula AX = ZB. Further optimization and the incorporation of the joint parameters allow the calibration of the manipulator. Self-calibration means that no sort of calibration object like a checkerboard is needed. Since the decoding is applied to single images, the environment is permitted to change, and the robot is allowed to move around freely during calibration. Experimental results of this method show a submillimeter accuracy of the proposed projector tracking as well as improvements of the robot's accuracy in its typical workspace.
KW - End-effector tracking
KW - Manipulator self-calibration
KW - Structured light
UR - http://www.scopus.com/inward/record.url?scp=85031679614&partnerID=8YFLogxK
U2 - 10.1109/icar.2017.8023518
DO - 10.1109/icar.2017.8023518
M3 - Paper
SP - 197
EP - 203
T2 - 2017 18th International Conference on Advanced Robotics (ICAR)
Y2 - 10 July 2017 through 12 July 2017
ER -