Autonomous Vision-Guided High-Precision Firefighting using Unmanned Aerial Vehicles

This paper presents a novel, precise, and fast framework for autonomous aerial forest fire fighting using unmanned aerial vehicles (UAVs) to extinguish a line of fires by most efficiently utilizing the on-board camera. Autonomous aerial firefighting algorithms using UAVs have been proven to be promising in early wildfire suppression. However, UAVs/drones have limited payloads, which do not allow them to carry as much retardant as fixed-wing aircraft do. Hence, firefighting drones should release the retardant in a way that accurately extinguishes wildfire and efficiently suppresses the line of fires. In this work, a DJI M300 RTK drone mounted on which a RGB camera and a 3D-printed water tanker are mounted and utilized to extinguish a line of fires in an outdoor experimental environment. A line of fires has been set up using firepits, whose GPS locations are known. The optimal path along which a drone should approach and release the retardant to extinguish the fire line is calculated using the RANSAC algorithm, as well as the in-motion dropping mission starting point. Nonetheless, due to errors in the drone's onboard GPS sensor, the drone does not exactly position itself at the starting point. In fact, in the proposed method, the drone uses on-board camera images to adjust itself and get aligned with the retardant-releasing line as it is supposed based on prediction, followed by approaching the fire line and releasing the retardant. The testing results show efficient and accurate suppression of fire spots whose video verification is provided at https://www.youtube.com/watch?v=ZP2KoxtwAsg.