An Unmanned Vehicle Inspection System for Airport Runways

Foreign objects on the airport runway can affect the takeoff of the plane and seriously endanger the safety of people's lives and property. The existing solutions for these foreign bodies on the runway of the airport is manual cleaning during the take-off interval of the aircraft, but this method has high labor cost, low efficiency and poor reliability. In this paper, an unmanned vehicle inspection system for airport runways is introduced to address the above problems, which is used to detect runway foreign objects at airport runways. This paper introduces the hardware configuration of the unmanned vehicle and its software functions such as automatic cruise and path planning in detail, and briefly introduces the foreign object detection function. Among them, a new aggregated Euclidean clustering method suitable for sub-regional adaptive thresholds of fused point clouds is proposed when performing lidar point cloud clustering. Experiments show that this method can greatly improve the effect of point cloud clustering for obstacles detection.