Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones
Yedilkhan D. Kyzyrkanov A.E. Kutpanova Z.A. Aljawarneh S. Atanov S.K.
December 2024KeAi Communications Co.
Journal of Electronic Science and Technology
2024#22Issue 4
The growing field of urban monitoring has increasingly recognized the potential of utilizing autonomous technologies, particularly in drone swarms. The deployment of intelligent drone swarms offers promising solutions for enhancing the efficiency and scope of urban condition assessments. In this context, this paper introduces an innovative algorithm designed to navigate a swarm of drones through urban landscapes for monitoring tasks. The primary challenge addressed by the algorithm is coordinating drone movements from one location to another while circumventing obstacles, such as buildings. The algorithm incorporates three key components to optimize the obstacle detection, navigation, and energy efficiency within a drone swarm. Firstly, the algorithm utilizes a method for calculating the position of a virtual leader, acting as a navigational beacon to influence the overall direction of the swarm. Secondly, the algorithm identifies observers within the swarm based on the current orientation. To further refine obstacle avoidance, the third component involves the calculation of angular velocity using fuzzy logic. This approach considers the proximity of detected obstacles through operational rangefinders and the targets location, allowing for a nuanced and adaptable computation of angular velocity. The integration of fuzzy logic enables the drone swarm to adapt to diverse urban conditions dynamically, ensuring practical obstacle avoidance. The proposed algorithm demonstrates enhanced performance in the obstacle detection and navigation accuracy through comprehensive simulations. The results suggest that the intelligent obstacle avoidance algorithm holds promise for the safe and efficient deployment of autonomous mobile drones in urban monitoring applications.
Drone swarms , Fuzzy logic , Intelligent solution , Smart city , Urban monitoring
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Department of Computer Engineering, Astana IT University, Astana, 010000, Kazakhstan
Department of Computer and Software Engineering, L. N. Gumilyov Eurasian National University, Astana, 010000, Kazakhstan
Department of Automation and Control Systems, L. N. Gumilyov Eurasian National University, Astana, 010000, Kazakhstan
Department of Software Engineering, Jordan University of Science and Technology, Irbid, 22110, Jordan
Department of Computer Engineering
Department of Computer and Software Engineering
Department of Automation and Control Systems
Department of Software Engineering
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