An Integrated Vision System for Vegetation Detection in Autonomous Ground Vehicles

Duong V. Nguyen, Lars Kuhnert, and Klaus D. Kuhnert

Keywords

Vegetation Detection, Autonomous Navigation, 2D3D Imaging, TimeofFlight Sensor, 2D3D Feature Fusion

Abstract

Autonomous Ground Vehicle (AGV) has been investigated in large amount researches of robotics but a safe navigation system is still infeasible in complex outdoor environments. One of the biggest challenges is to deal with the presence of vegetation on the vehicle’s way where the decision-making framework usually applied for indoor contexts or rigid objects fails totally. Therefore, this paper addresses a solution for vegetation detection which lets the vehicle fully exploit its mobility capability outside. For that aim, we introduce the use of a new vision system integrated from Photonic Mixer Device (PMD) and CMOS camera, so called Zess-Multicam. Whereby, chlorophyll-rich vegetation is marked by evaluating the reflectance of the modulated near infrared (NIR) given by PMD sensor and the red channel of the CMOS sensor while the color descriptors used also supplement to result a more robust vegetation classifier. Finally we will show the out-performance of this approach in comparison with more conventional approaches under real-time constraint.

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