File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

주경돈

Joo, Kyungdon
Robotics and Visual Intelligence Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.conferencePlace CA -
dc.citation.endPage 288 -
dc.citation.startPage 281 -
dc.citation.title IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 -
dc.contributor.author Park, Jinsun -
dc.contributor.author Shin, Ukcheol -
dc.contributor.author Shim, Gyumin -
dc.contributor.author Joo, Kyungdon -
dc.contributor.author Rameau, Francois -
dc.contributor.author Kim, Junhyeok -
dc.contributor.author Choi, Dong-Geol -
dc.contributor.author Kweon, In So -
dc.date.accessioned 2024-01-31T23:36:11Z -
dc.date.available 2024-01-31T23:36:11Z -
dc.date.created 2020-11-05 -
dc.date.issued 2019-11-05 -
dc.description.abstract In this paper, we present a multi-camera sensor system along with its control algorithm for automated visual inspection from a moving vehicle. To accomplish this task, we propose a unique hardware configuration consisting of a frontal stereo vision system, six lateral cameras motorized to tilt, and a GPS/IMU sensor mounted on the roof of a car. From the frontal stereo system, we detect electric poles and estimate their corresponding 3D positions. Based on this 3D estimation, the tilt angles of the motorized lateral cameras are controlled in real-time to capture high resolution images of the equipment - typically installed a few meters above the road surface. In addition, inertial odometry information from the GPS/IMU module is utilized for pose estimation, object localization, and re-identification among cameras. Experimental results demonstrate the efficiency and robustness of our system for automated electric equipment maintenance, which can reduce human effort significantly. © 2019 IEEE. -
dc.identifier.bibliographicCitation IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019, pp.281 - 288 -
dc.identifier.doi 10.1109/IROS40897.2019.8968085 -
dc.identifier.issn 2153-0858 -
dc.identifier.scopusid 2-s2.0-85081163740 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/78920 -
dc.language 영어 -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title Vehicular Multi-Camera Sensor System for Automated Visual Inspection of Electric Power Distribution Equipment -
dc.type Conference Paper -
dc.date.conferenceDate 2019-11-04 -

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.