UPM Institutional Repository

Comprehensive review of drones collision avoidance schemes: challenges and open issues


Citation

Rezaee, Mohammad Reza and Abdul Hamid, Nor Asilah Wati and Hussin, Masnida and Ahmad Zukarnain, Zuriati (2024) Comprehensive review of drones collision avoidance schemes: challenges and open issues. IEEE Transactions on Intelligent Transportation Systems, 25 (7). pp. 6397-6426. ISSN 1524-9050; eISSN: 1558-0016

Abstract

In the contemporary landscape, the escalating deployment of drones across diverse industries has ushered in a consequential concern, including ensuring the security of drone operations. This concern extends to a spectrum of challenges, encompassing collisions with stationary and mobile obstacles and encounters with other drones. Moreover, the inherent limitations of drones, namely constraints on energy consumption, data storage capacity, and processing power, present formidable obstacles in developing collision avoidance algorithms. This review paper explores the challenges of ensuring safe drone operations, focusing on collision avoidance. We explore collision avoidance methods for UAVs from various perspectives, categorizing them into four main groups: obstacle detection and avoidance, collision avoidance algorithms, drone swarm, and path optimization. Additionally, our analysis delves into machine learning techniques, discusses metrics and simulation tools to validate collision avoidance systems, and delineates local and global algorithmic perspectives. Our evaluation reveals significant challenges in current drone collision prevention algorithms. Despite advancements, critical UAV network and communication challenges are often overlooked, prompting a reliance on simulation-based research due to cost and safety concerns. Challenges encompass precise detection of small and moving obstacles, minimizing path deviations at minimal cost, high machine learning and automation expenses, prohibitive costs of real testbeds, limited environmental comprehension, and security apprehensions. By addressing these key areas, future research can advance the field of drone collision avoidance and pave the way for safer and more efficient UAV operations. © 2000-2011 IEEE.


Download File

[img] Text
112894.pdf - Published Version
Available under License Creative Commons Attribution.

Download (9MB)
Official URL or Download Paper: https://ieeexplore.ieee.org/document/10477874

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1109/TITS.2024.3375893
Publisher: Institute of Electrical and Electronics Engineers
Keywords: Collision avoidance; Drone collision; Drone swarm; Uav navigation; Unmanned aerial vehicles (uav)
Depositing User: Ms. Azian Edawati Zakaria
Date Deposited: 28 Oct 2024 07:57
Last Modified: 28 Oct 2024 07:57
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/TITS.2024.3375893
URI: http://psasir.upm.edu.my/id/eprint/112894
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item