Autonomous Flying into Buildings in a Firefighting Scenario

Abstract

We propose an approach enabling an Unmanned Aerial Vehicle (UAV) to autonomously enter a target building through an open window. We use a fusion of depth camera and 2D Light Detection and Ranging (LiDAR) data for window detection and continuous estimation of its position, orientation, and size. The proposed algorithms are capable of running both with and without available a priori information. The obtained detections are utilized for planning collision-free trajectories through the target window. We use a sensor fusion algorithm for robust altitude estimation from laser rangefinder data while flying over ground with inconsistent elevation. Particular focus is given to the transition between outdoor and indoor environments and vice-versa to achieve the required reliability of UAV state estimation. The proposed approach has been verified in multiple real-world experiments, where the UAV was able to successfully enter and leave the target building both under normal conditions and under decreased visibility conditions in a smoke-filled environment.