UAV Guidance for Fire Challenge of MBZIRC Contest - Window Flythrough and Indoor Flight Simulation



Abstract:

This thesis deals with the guidance of an unmanned multirotor aircraft for autonomous flight into buildings and autonomous indoor exploration. This research was motivated by the firefighting challenge of the Mohamed Bin Zayed International Robotic Challenge 2020. The main focus of this work is placed on window detection from 2D LiDAR data, fusion of the obtained detections with 3D depth camera data, and path planning for safe flight through the detected window and inside the building. A combination of line extraction algorithms is used for window detection from the LiDAR data. A Kalman filter-based estimator is used for filtering and fusion of the individual detections. A state machine generating line trajectories with constant velocity is used for guiding the UAV through the detected window. A wall following algorithm producing local trajectories based on a single laser scan is used for guiding the UAV inside the building. The proposed algorithms were extensively verified in simulations and real-world experiments under normal visibility conditions and in a smoke-filled environment.

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