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A Multi-Functional Robot For Civil I...
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ProQuest Information and Learning Co.
A Multi-Functional Robot For Civil Infrastructure Inspection.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
A Multi-Functional Robot For Civil Infrastructure Inspection./
作者:
Le, Tuan D.
面頁冊數:
1 online resource (63 pages)
附註:
Source: Masters Abstracts International, Volume: 56-05.
Contained By:
Masters Abstracts International56-05(E).
標題:
Robotics. -
電子資源:
click for full text (PQDT)
ISBN:
9780355051582
A Multi-Functional Robot For Civil Infrastructure Inspection.
Le, Tuan D.
A Multi-Functional Robot For Civil Infrastructure Inspection.
- 1 online resource (63 pages)
Source: Masters Abstracts International, Volume: 56-05.
Thesis (M.S.)
Includes bibliographical references
This thesis focuses on designing and building a robotic system for civil infrastructure inspections. The robot is equipped with two non-destructive-evaluation (NDE) types of sensors: a ground penetrating (GPR) sensor and two electrical resistivity (ER) sensors. For localization, the robot employs an extended Kalman filter (EKF)-based approach using global positioning system (GPS) signal. Differ from its predecessor, the currently built robot is capable of localizing and navigating in GPS-denied environments by using a visual-inertial odometry method with a stereo camera. In addition, the robot can build an elevation map of its surrounding areas using a PrimeSence camera for obstacle avoidance.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355051582Subjects--Topical Terms:
561941
Robotics.
Index Terms--Genre/Form:
554714
Electronic books.
A Multi-Functional Robot For Civil Infrastructure Inspection.
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Source: Masters Abstracts International, Volume: 56-05.
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Includes bibliographical references
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This thesis focuses on designing and building a robotic system for civil infrastructure inspections. The robot is equipped with two non-destructive-evaluation (NDE) types of sensors: a ground penetrating (GPR) sensor and two electrical resistivity (ER) sensors. For localization, the robot employs an extended Kalman filter (EKF)-based approach using global positioning system (GPS) signal. Differ from its predecessor, the currently built robot is capable of localizing and navigating in GPS-denied environments by using a visual-inertial odometry method with a stereo camera. In addition, the robot can build an elevation map of its surrounding areas using a PrimeSence camera for obstacle avoidance.
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Mode of access: World Wide Web
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click for full text (PQDT)
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