Document Type



Master of Science (MS)


Mechanical Engineering

First Advisor's Name

Dwayne McDaniel

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Leonel Lagos

Second Advisor's Committee Title

committee member

Third Advisor's Name

Ibrahim Tansel

Third Advisor's Committee Title

committee member


robot, autonomous, ros, slam, lidar, point, cloud, monitoring, infrastructure, mapping

Date of Defense



Actively monitoring infrastructure is key to detecting and correcting problems before they become costly. The vast scale of modern infrastructure poses a challenge to monitoring due to insufficient personnel. Certain structures, such as refineries, pose additional challenges and can be expensive, time-consuming, and hazardous to inspect.

This thesis outlines the development of an autonomous robot for structural-health-monitoring. The robot is capable of operating autonomously in level indoor environments and can be controlled manually to traverse difficult terrain. Both visual and lidar SLAM, along with a procedural-mapping technique, allow the robot to capture colored-point-clouds.

The robot is successfully able to automate the point cloud collection of straightforward environments such as hallways and empty rooms. While it performs well in these situations, its accuracy suffers in complex environments with variable lighting. More work is needed to create a robust system, but the potential time savings and upgrades make the concept promising.



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Included in

Robotics Commons



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