UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters

João P Matos-Carvalho,Raúl T Rato,André Mora,Ricardo Mendonça,José M Fonseca

doi:10.1007/978-3-030-17771-3_7

Abstract

Knowing how to identify terrain types is especially important in the autonomous navigation, mapping, decision making and detect landings areas. A recent area is in cooperation and improvement of autonomous behavior between robots. For example, an unmanned aerial vehicle (UAV) is used to identify a possible landing area or used in cooperation with other robots to navigate in unknown terrains. This paper presents a computer vision algorithm capable of identifying the terrain type where the UAV is flying, using its rotors’ downwash effect. The algorithm is a fusion between the frequency Wiener-Khinchin adapted and spatial Empirical Mode Decomposition (EMD) domains. In order to increase certainty in terrain identification, machine learning is also used. The system is validated using videos acquired onboard of a UAV with an RGB camera.

Highlights

Nowadays, Unmanned Aerial Vehicles (UAVs) have a huge impact in the area of research and industry
The task of the UAV is to cooperate with the Unmanned Surface Vehicle (USV) so that it reaches its intended destination
With an RGB camera mounted on the UAV it is possible to receive the images from the outside from the effect of the downwash caused by the UAV

Summary

Introduction

Nowadays, Unmanned Aerial Vehicles (UAVs) have a huge impact in the area of research and industry. In the area of industry, being a lightweight and low-power robot, it can be used in various situations, such as precision agriculture, emergency landings and rescue missions. In this case, the task of the UAV is to cooperate with the Unmanned Surface Vehicle (USV) so that it reaches its intended destination. This effect is only felt at low altitudes and has unique effects on the terrain (e.g. the circular wave effect on the water terrain)

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Conclusion