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Color obstacle detection algorithm using AR drone 2.0 in a controlled environment

Author(s)
Faiber Robayo Betancourt Departamento de Ingeniería Electrónica, Facultad de Ingeniería, Universidad Surcolombiana,Neiva, Huila,Colombia
Daniel Suescún-Díaz Departamento de Ciencias Naturales, Avenida Pastrana, Universidad Surcolombiana,Neiva, Huila,Colombia
Abstract
This work presents an obstacle detection algorithm using quadrotor AR. Drone 2.0 in a controlled environment with programming in OpenCV, ROS (Robot Operating System), and Python. The algorithm is based on the color object feature to determine it as an obstacle. It is the first step for future work where the drone is allowed to perform autonomous flights and obstacle avoidance. The ROS development environment makes it possible to adjust both the drone's linear and angular speed. The OpenCV management library allows processing the image obtained in real-time thanks to the cv_bridge package. The obstacle detection scenario is simulated using ROS-Gazebo, and then the algorithm is implemented in a real controlled environment. The results obtained were good; an obstacle detection system was successfully implemented using open-source tools.
Publication Details
Page(s) 352-357
DOI DOI not available
Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 18, Issue: 4, Year: 2023

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Keywords
ROS, Algorithm, Drone, Python, OpenCV
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