Unmanned surface vessel (USV) systems for bridge inspection : final report.
-
2016-08-01
Details
-
Creators:
-
Corporate Creators:
-
Contributors:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final report
-
Corporate Publisher:
-
Abstract:The use of unmanned surface vehicles (USVs) for bridge inspection has been explored. The following issues were considered: (1) the requirements of and ; current techniques utilized in on-water bridge inspection; (2) USV design and configuration considerations for USV-based bridge inspection; (3) use of ; acoustic sensing techniques for imaging underwater bridge structures and channel bottom features; (4) the control and dynamic positioning of USVs for ; bridge inspection; (5) the use of advanced robotics techniques for improving vehicle navigation under bridges and the mapping of bridge features; and lastly, ; (6) recommendations for the addition of standard operating procedures to accommodate the use of USVs for bridge inspection. A proof of concept system ; was developed and tested using an existing USV at Florida Atlantic University (FAU) outfitted with a real-time imagining sonar. Field experiments were ; conducted with the system at several sites near the city of Carrabelle, Florida and in Dania Beach, Florida. Live demonstrations of the system were also ; conducted at the 2015 Florida Automated Vehicles Summit. The system was able to autonomously collect images of bridge structures, both underwater and ; at the waterline, by traversing a series of preprogrammed waypoints along a bridge and station-keeping at locations of interest. The results of the field tests ; and background literature survey are presented, and a set of recommendations for use of USV-based bridge inspection systems is given. It is suggested that ; the application of advanced robotics techniques for Human-Robot-Interaction and autonomous mapping/imaging can improve the preliminary inspection ; approach implemented during this study.
-
Format:
-
Funding:
-
Download URL:
-
File Type:
-
Collection(s):
-
Main Document Checksum:urn:sha256:911c79998888cae197e02366bf8c6f631f6178e33f8445037ff3d63e6e49a214