BIM-Aided Scanning Path Planning for Autonomous Surveillance UAVs with LiDAR

Abstract

An Unmanned Aerial Vehicle (UAV), equipped with a Light Detection And Ranging (LiDAR) scanner, can collect high-accuracy point cloud data of facilities in cluttered indoor environment. Recent developments in aerial robotics have demonstrated navigation through designated waypoints, yet little has been investigated on the trajectory to complete a full scan of the environment. This study develops an automated approach to integrate scan planning and trajectory generation of a LiDAR-carrying UAV. The proposed approach converts an as-designed Building Information Model (BIM) into an occupancy map, where a set of waypoints are generated with a greedy algorithm. The shortest collision-free path to traverse all the waypoints is computed with the A* algorithm and Genetic Algorithm (GA). After that, the straight-line segments are transformed into a minimum snap trajectory formed of piecewise polynomials. The planned trajectory is validated with both a MATLAB numerical solver and a Hardware-In-the-Loop (HIL) simulation in the Unreal Engine 4.