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2018 | OriginalPaper | Chapter

Block Matching Based Obstacle Avoidance for Unmanned Aerial Vehicle

Authors : Adomas Ivanovas, Armantas Ostreika, Rytis Maskeliūnas, Robertas Damaševičius, Dawid Połap, Marcin Woźniak

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

Unmanned aerial vehicles (UAVs) are becoming very popular now. They have a variety of applications: search and rescue missions, crop inspection, 3D mapping, surveillance and military applications. However, many of the lower-end UAV do not have obstacle avoidance systems installed, which can lead to broken equipment or people may get injured. In this paper, we describe the design of low-cost UAV with computer vision based obstacle avoidance system. We used Block Match (BM) and Semi Global Block Match (SGBM) algorithms for detection of obstacles in stereo images. We constructed custom UAV platform, and demonstrated the effectiveness of UAV with an obstacle avoidance system in real-world field testing conditions.

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Title: Block Matching Based Obstacle Avoidance for Unmanned Aerial Vehicle
Authors: Adomas Ivanovas
Armantas Ostreika
Rytis Maskeliūnas
Robertas Damaševičius
Dawid Połap
Marcin Woźniak
Publisher: Springer International Publishing
Book: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-91252-3

Electronic ISBN: 978-3-319-91253-0

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-91253-0_6

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