Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones

A multimodal sensory array to accurately position aerial multicopter drones with respect to pipes has been studied, and a solution exploiting both LiDAR and vision sensors has been proposed. Several challenges, including detection of pipes and other cylindrical elements in sensor space and validation of the elements detected, have been studied. A probabilistic parametric method has been applied to segment and position cylinders with LIDAR, while several vision-based techniques have been tested to find the contours of the pipe, combined with conic estimation cylinder pose recovery. Multiple solutions have been studied and analyzed, evaluating their results. This allowed proposing an approach that combines both LiDAR and vision to produce robust and accurate pipe detection. This combined solution is validated with real experimental data.

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