In this work, a monocular camera-based obstacle avoidance system was designed to improve autonomous operation of quadcopters in dynamic environments, already hindered by sensors’ heavyweight and processing and energy requirements. The work underwent two stages. First, the system dynamics were modeled, linearized, and controlled using PD controllers. Then, an optic flow-based hybrid obstacle avoidance algorithm was developed. The algorithm consisted of three approaches that account for avoiding frontal and peripheral objects, while aiming to the final position. The developed system was tested in a challenging scenario that mimics a real forest using Webots simulator. Results demonstrated an 85% success rate of avoiding obstacles. Cases of system failure resulted due to the linearization constraint which blocked ad hoc aggressive behaviour.
2nd Mosharaka International Conference on Smart Systems and Technologies (MIC-Smart 2021)
Congress
2021 Global Congress on Electrical Engineering (GC-ElecEng 2021), 10-12 December 2021, Valencia, Spain
Pages
29-34
Topics
Computer Vision Image Processing for Machine Vision
ISSN
2227-331X
DOI
BibTeX
@inproceedings{1170ElecEng2021,
title={Optic Flow-based Vision System for Autonomous and Collision-free Navigation of Micro Aerial Vehicles },
author={Zayd Khashshan, and Moudar Zgoul},
booktitle={2021 Global Congress on Electrical Engineering (GC-ElecEng 2021)},
year={2021},
pages={29-34},
doi={}},
organization={Mosharaka for Research and Studies}
}
