Edge-based approach to estimate the drift of a helicopter during flight

Abstract

The Institute of Flight Systems at the German Aerospace Center (DLR) site in Braunschweig Germany has set its goal into making helicopter flying as safe as possible. The new DLR research project "Rettungshubschrauber 2030" addresses the topic of aiding helicopter rescue missions. Research will be conducted to increase the safety of these missions as well as to enable the conduct of missions in circumstances where nowadays a helicopter would not be allowed to operate. One aspect of this research is to increase or maintain the situational awareness of the pilot by processing data from camera images. The presented paper will focus on the field of visual odometry. Most of the publications on this topic use techniques that are only working with satisfying reliability in a very restricted environment, i.e. in good weather conditions. It shall be surveyed, if an edge-based approach for extracting features is a possible alternative or addition to established feature extractors. In the following paper, two algorithms for edge-extraction will be compared: An algorithm that is based on Hough transform and an algorithm that is based on the Douglas-Peucker-Method. They will be tested on their ability to detect a sufficient amount of features in camera images as well as on their computational complexity. Then, their ability to detect the drift of a helicopter will be surveyed on recorded data from flight tests with the Advanced Control Technology/Flying Helicopter Simulator (ACT/FHS) of the DLR. Their performance will be tested on the base of reference data from the ACT/FHS which have been recorded by the use of a highly accurate INS/DGPS system. Finally, a short outlook in form of a first comparison of well established feature extractors and the presented algorithms will be shown on a recorded scene with raindrops covering the lens of the camera.