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Obstacle detection and avoidance system performed with drone using ROS and python

Author(s)
Karen Cerón Departamento de Ingeniería Electrónica, Facultad de Ingeniería, Universidad Surcolombiana,Neiva, Huila,Colombia
David Reina Departamento de Ingeniería Electrónica, Facultad de Ingeniería, Universidad Surcolombiana,Neiva, Huila,Colombia
Faiber Robayo Betancourt Departamento de Ingeniería Electrónica, Facultad de Ingeniería, Universidad Surcolombiana,Neiva, Huila,Colombia
Abstract
The AR Drone 2.0 obstacle detection and avoidance system using ROS (Robot Operating System) as a development environment, OpenCV as a library for image processing, and Python as a programming language are presented. The algorithm is based on the object's color feature to determine whether it is an obstacle to allowing autonomous flights to the drone if the drone's battery charge level and its distance from the ground station are considered. The obstacle detection scenario is simulated using ROS-Gazebo, and then the algorithm is tested in a real controlled environment. It shows the proper functioning of the system, that is, it manages to detect a red object correctly and avoid it by the control actions implemented in the algorithm.
Publication Details
Page(s) 251-256
DOI DOI not available
Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 18, Issue: 3, Year: 2023

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Keywords
ROS, Algorithm, Hue Saturation Value, controlled environment, Drone
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