Yu-Xuan Zhou¹, Kai-Qing Zhou^1,*, Wei-Lin Chen¹, Zhou-Hua Liao¹, Di-Wen Kang^1,2

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.075099 - 10 February 2026

Abstract The Pigeon-Inspired Optimization (PIO) algorithm constitutes a metaheuristic method derived from the homing behaviour of pigeons. Initially formulated for three-dimensional path planning in unmanned aerial vehicles (UAVs), the algorithm has attracted considerable academic and industrial interest owing to its effective balance between exploration and exploitation, coupled with advantages in real-time performance and robustness. Nevertheless, as applications have diversified, limitations in convergence precision and a tendency toward premature convergence have become increasingly evident, highlighting a need for improvement. This review systematically outlines the developmental trajectory of the PIO algorithm, with a particular focus on its core… More >

Gang Hou^1,#, Aifeng Liu^1,#, Tao Zhao¹, Wenyuan Wei², Bo Li¹, Jiancheng Liu^3,*, Siwen Wei^4,5,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.073202 - 10 February 2026

Abstract Cooperative multi-UAV search requires jointly optimizing wide-area coverage, rapid target discovery, and endurance under sensing and motion constraints. Resolving this coupling enables scalable coordination with high data efficiency and mission reliability. We formulate this problem as a discounted Markov decision process on an occupancy grid with a cellwise Bayesian belief update, yielding a Markov state that couples agent poses with a probabilistic target field. On this belief–MDP we introduce a segment-conditioned latent-intent framework, in which a discrete intent head selects a latent skill every K steps and an intra-segment GRU policy generates per-step control conditioned on More >

Cosmin Dumitru, Emanuel Pantelimon, Alexandru Guzu, Georgian Nicolae^*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072749 - 10 February 2026

Abstract Unmanned aerial vehicles (UAVs), especially quadcopters, have become indispensable in numerous industrial and scientific applications due to their flexibility, low cost, and capability to operate in dynamic environments. This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking, object detection, precision landing, and real-time telemetry via long-range communication protocols. The system integrates an onboard flight controller running real-time sensor fusion algorithms, a vision-based detection system on a companion single-board computer, and a telemetry unit using Long Range (LoRa) communication. Extensive flight tests were conducted to validate the system’s More >

Nur Afikah Juhari, Khairul Nizam Tahar^*

Revue Internationale de Géomatique, Vol.35, pp. 1-11, 2026, DOI:10.32604/rig.2026.070991 - 19 January 2026

Abstract The use of Unmanned Aerial Vehicles (UAVs) in photogrammetry has grown rapidly due to enhanced flight stability, high-resolution imaging, and advanced Structure from Motion (SfM) algorithms. This study investigates the potential of UAVs as a cost-effective alternative to Terrestrial Laser Scanners (TLS) for 3D building reconstruction. A 3D model of Bangunan Sarjana was generated in Agisoft Metashape Professional v.2.0.2 using 492 aerial images captured at flying altitudes of 40, 50, and 60 m. Ground control points were established using GNSS (RTK-VRS), and Total Station measurements were employed for accuracy validation. The results indicate that the 60 More >

Yanan Liu^1,*, Suhao Wang^1,*, Lei Cao¹, Pengfei Wang¹, Zheng Zhang², Shuo Qiu¹, Ruchan Dong¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072710 - 12 January 2026

Abstract Unmanned Aerial Vehicles (UAVs) in Flying Ad-Hoc Networks (FANETs) are widely used in both civilian and military fields, but they face severe security, trust, and privacy vulnerabilities due to their high mobility, dynamic topology, and open wireless channels. Existing security protocols for Mobile Ad-Hoc Networks (MANETs) cannot be directly applied to FANETs, as FANETs require lightweight, high real-time performance, and strong anonymity. The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity, high security, and low overhead in high dynamic and resource-constrained scenarios. To address these challenges, this paper proposes an Anonymous Authentication… More >

Yonghua Huo^1,2, Ying Liu^1,*, Anni Jiang³, Yang Yang³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072681 - 12 January 2026

Abstract With the advent of sixth-generation mobile communications (6G), space–air–ground integrated networks have become mainstream. This paper focuses on collaborative scheduling for mobile edge computing (MEC) under a three-tier heterogeneous architecture composed of mobile devices, unmanned aerial vehicles (UAVs), and macro base stations (BSs). This scenario typically faces fast channel fading, dynamic computational loads, and energy constraints, whereas classical queuing-theoretic or convex-optimization approaches struggle to yield robust solutions in highly dynamic settings. To address this issue, we formulate a multi-agent Markov decision process (MDP) for an air–ground-fused MEC system, unify link selection, bandwidth/power allocation, and task… More >

Minghui Li¹, Hongbo Li^1,*, Jiaqi Zhu², Xupeng Zhang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072406 - 12 January 2026

Abstract To address the challenge of real-time detection of unauthorized drone intrusions in complex low-altitude urban environments such as parks and airports, this paper proposes an enhanced MBS-YOLO (Multi-Branch Small Target Detection YOLO) model for anti-drone object detection, based on the YOLOv8 architecture. To overcome the limitations of existing methods in detecting small objects within complex backgrounds, we designed a C2f-Pu module with excellent feature extraction capability and a more compact parameter set, aiming to reduce the model’s computational complexity. To improve multi-scale feature fusion, we construct a Multi-Branch Feature Pyramid Network (MB-FPN) that employs a… More >

Qian Yu^1,2, Gui Zhang^2,*, Ying Wang¹, Xin Wu², Jiangshu Xiao², Wenbing Kuang¹, Juan Zhang²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072172 - 12 January 2026

Abstract Detecting small forest fire targets in unmanned aerial vehicle (UAV) images is difficult, as flames typically cover only a very limited portion of the visual scene. This study proposes Context-guided Compact Lightweight Network (CCLNet), an end-to-end lightweight model designed to detect small forest fire targets while ensuring efficient inference on devices with constrained computational resources. CCLNet employs a three-stage network architecture. Its key components include three modules. C3F-Convolutional Gated Linear Unit (C3F-CGLU) performs selective local feature extraction while preserving fine-grained high-frequency flame details. Context-Guided Feature Fusion Module (CGFM) replaces plain concatenation with triplet-attention interactions to… More >

Sai Xu^1,*, Jun Liu^1,*, Shengyu Huang¹, Zhi Li²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071865 - 12 January 2026

Abstract In scenarios where ground-based cloud computing infrastructure is unavailable, unmanned aerial vehicles (UAVs) act as mobile edge computing (MEC) servers to provide on-demand computation services for ground terminals. To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs, this paper presents PER-MATD3, a multi-agent deep reinforcement learning algorithm with prioritized experience replay (PER) into the Centralized Training with Decentralized Execution (CTDE) framework. Specifically, PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution, while leveraging a shared replay buffer with More >

Mohammed Alnusayri¹, Ghulam Mujtaba², Nouf Abdullah Almujally³, Shuoa S. Aitarbi⁴, Asaad Algarni⁵, Ahmad Jalal^2,6, Jeongmin Park^7,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071804 - 12 January 2026

Abstract This paper presents a unified Unmanned Aerial Vehicle-based (UAV-based) traffic monitoring framework that integrates vehicle detection, tracking, counting, motion prediction, and classification in a modular and co-optimized pipeline. Unlike prior works that address these tasks in isolation, our approach combines You Only Look Once (YOLO) v10 detection, ByteTrack tracking, optical-flow density estimation, Long Short-Term Memory-based (LSTM-based) trajectory forecasting, and hybrid Speeded-Up Robust Feature (SURF) + Gray-Level Co-occurrence Matrix (GLCM) feature engineering with VGG16 classification. Upon the validation across datasets (UAVDT and UAVID) our framework achieved a detection accuracy of 94.2%, and 92.3% detection accuracy when More >