Strategies for autonomous robots to inspect pavement distresses

Abstract The distress survey is an important task for pavement maintenance and rehabilitation (MR (2) Strategy II: random survey with map recording (R + M); (3) Strategy III: random survey with map recording and vision guidance (R + M + V). To validate these three strategies, we developed a test field in a virtual environment. The test field included five distress types, including an alligator crack, a small patching, a pothole, a rectangular manhole and a circular manhole. We also developed a virtual robot to navigate the test field autonomously. The three survey strategies were then implemented by the virtual robot and their performances were compared with the current traffic-directional survey strategy.

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