Strategies for Autonomous Robot to Inspect Pavement Distresses
Date Issued
2010
Date
2010
Author(s)
Tseng, Yuan-Hsu
Abstract
Distress inspection is an important task in pavement maintenance. Because pavement inspection requires tremendous human resources, many investigators start developing automatic and robotic inspection methods to increase the efficiency and accuracy. In this research, we specific focus on developing strategies for executing the inspection tasks using robots. We developed three strategies. The first strategy is random-walk. Robot surveys randomly in a confined environment. The second strategy is random-walk with map recording. Robot randomly wanders with recording the information it has gone through. The third one adds the vision capacity to the robot. Robot determines inspection path reactively based on the visual information.
To validate the three strategies, we developed a test field in a virtual environment. This test field includes 5 type of distress, including an alligator crack, a patching, a breaking hole, a rectangular manhole and a circular manhole. We also developed a virtual robot which can autonomously navigate in the test field. We then implemented the three survey strategies in the robot and compare their performances with traditional longitudinal survey method. The results show that using the first strategy, we can increase frequency for passing the distresses; it means that robot can detect and collect data more times than traditional longitudinal survey. The results of the second strategy show that we can increase the repeatability by using map recording to guide random-walk. The results of third strategy show that the robot can find more distresses in a certain amount of time; it means that we can improve survey efficiency by adding vision capacity to adjust motion path when distresses detected.
Subjects
distress
robotic
strategies
random-walk
map
vision
virtual environment
Type
thesis
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