Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8647
Title: Path Planning and Collision Avoidance with Artificial Intelligence for a Quadrotor UAV
Authors: Karahan M.
Kasnakoğlu, Coşku
Keywords: A-star algorithm
artificial intelligence
obstacle avoidance
optimization
path planning
Quadrotor
UAV
Antennas
Collision avoidance
MATLAB
Motion planning
A-Star algorithm
Collisions avoidance
Condition
Noisy conditions
Obstacles avoidance
Optimisations
Quad rotors
Short-path
Trajectory optimization
Unmanned aerial vehicles (UAV)
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Karahan, M., & Kasnakoglu, C. Path Planning and Collision Avoidance with Artificial Intelligence for a Quadrotor UAV. In 2021 International Conference Automatics and Informatics (ICAI) (pp. 163-166). IEEE.
Abstract: Artificial intelligence has brought new features to unmanned aerial vehicles. Path planning, trajectory optimization and obstacle avoidance are some of the features that artificial intelligence brings to drones. In this study, path planning optimization and collision avoidance with artificial intelligence for an unmanned aerial vehicle are emphasized. Path planning and collision avoidance simulations were performed using MATLAB software under ideal conditions and under noisy conditions. It is shown that the unmanned aerial vehicle finds the shortest path on maps with various obstacles. © 2021 IEEE.
Description: 2021 International Conference Automatics and Informatics, ICAI 2021 -- 30 September 2021 through 2 October 2021 -- -- 175600
URI: https://doi.org/10.1109/ICAI52893.2021.9639807
https://hdl.handle.net/20.500.11851/8647
ISBN: 9781665426619
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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