Using robotic aircraft and intelligent surveillance systems for orange hawkweed detection

Abstract

Remote sensing using robotic aircraft (either Unmanned Aerial Vehicles (UAVs) or remotely piloted) can be an efficient and cost-effective way of collecting geo-spatial information over large areas. Furthermore, the large amounts of data collected by these systems can be handled by intelligent software systems that are able to autonomously classify the data. The Australian Centre for Field Robotics (ACFR) has been using aerial robots for environmental monitoring and has developed algorithms to support weed detection and mapping projects. The algorithm research at the ACFR has led to various intelligent detection and mapping software systems for accurate terrain mapping, vegetation segmentation and detection of different invasive species. The ACFR recently completed detecting and mapping of orange hawkweed (Hieracium aurantiacum subsp. N geli and Peter) at two different sites in Kosciuszko National Park, New South Wales. This paper presents an update of recent developments of the autonomous weed detection research program for orange hawkweed and a discussion on the current operational constraints and algorithm limitations to be addressed to support future large scale implementation.