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    Genetic Algorithm-Based Unmanned Aerial Vehicle (UAV) Path Planning in Dynamic Environments for Disaster Management
    (Institute of Electrical and Electronics Engineers Inc., 2025) Wijerathne V.R; Theekshana W.G.P; Prabhanga K.G.B.; De Silva K.P.C; Wijayasekara, S; Weerathunga, I; Hansika, M. M.D.J.T
    Unmanned Aerial Vehicles (UAVs) hold immense potential in disaster management by enabling rapid response, real-time aerial reconnaissance, and improved situational awareness without endangering human lives. This research proposes a real-time UAV path-planning system based on a Hierarchical Recursive Multiagent Genetic Algorithm (HR-MAGA). Unlike traditional methods that struggle with adaptability in dynamic 3D environments, our system employs localized waypoint updates to reduce the computational cost of full-path recalculations. A multi-objective fitness function guides the optimization process by balancing safety, energy efficiency, altitude smoothness, turbulence resistance, and travel time. Additionally, the system integrates a decoupled real-time collision avoidance module for immediate response to sudden threats. While obstacle detection is abstracted in this study, the framework is designed to be easily integrated with real-time sensing technologies such as LiDAR for dynamic obstacle awareness. Experimental evaluations show a 20-30% improvement in path efficiency and a 40% increase in convergence speed compared to conventional genetic algorithms, highlighting the system's adaptability and robustness in disaster response scenarios.
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    Dual-Channel OOK (D-COOK) Modulation for UAV-Assisted Mixed THz/VLC Systems
    (Institute of Electrical and Electronics Engineers Inc., 2025-06) Rajahrajasingh, H; Jayakody, D. N.K; Muthuchidambaranathan P; Tsiftsis, T.A
    This paper investigates a dual-hop UAV-assisted communications system that integrates Terahertz (THz) and Visible Light Communication (VLC) over a decode-and-forward (DF) relay that bridges the THz and VLC segments. The VLC channel is modelled to account for additive background noise and deterministic fading, while the THz link is subject to path loss, absorption loss, and pointing errors. A comparative analysis with Free Space Optics (FSO)-VLC and Radio Frequency (RF)-VLC systems highlights the superior performance of the THz-VLC system, especially at high signal-to-noise ratios (SNR), in terms of BER and outage probability. Furthermore, a novel modulation technique is proposed that enables increased data rates. Performance evaluation of the proposed modulation scheme further validates the effectiveness of the system.
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    PublicationOpen Access
    A QUADCOPTER WITH AUTOMATED TAKE-OFF AND LANDING ON MOBILE ROBOT PLATFORM
    (SHEFFIELD HALLAM UNIVERSITY ENGINEERING PROGRAM, 2016-12) Sandaruwan, B. A. S; Mithun, S; Rathnayake, R. M. K. M; Liyanage, M. H
    In this thesis, a controller is designed for an off the shelf quadcopter to give it the ability to autonomously takeoff, hover at a given altitude, follow and land on a mobile robot platform. This is a small part of a much bigger system which is a quadcopter and a mobile robot combined fully autonomous surveillance system. This system has the ability to navigate and complete a given task without any human interaction. Different types of sensor are used to determine the position of the quadcopter in 3D space. A PID controller is implemented to keep the quadcopter at a given altitude. Different types of sensors and technologies were used to achieve our target. A discrete PID controller will be used to hold the altitude of the quadcopter. Real-time image processing is used to determine the position of the quadcopter relative to the mobile robot platform. An ideal quadcopter simulation and a 3D simulation of the task is done to understand in detail how a quadcopter works and how to controller it the way we desire. Kalman filter is used to produce accurate and precious angular data of the quadcopter. The project is separated into several parts and divided among all the members of the group. The simulation of the complete system and the implementation of the takeoff, altitude holding and landing algorithms for the test system are done by me. Determining the position of the quadcopter using image processing and design and implementation of the Mobile robot platform is done by Rathnayake R.M.K.M. Implementation of Kalman filter to be used with Gyro and accelerometer sensors and the simulation of an ideal quadcopter model in Matlab is done by S. Mithun.