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31 pages, 2271 KB  
Article
An MDAO Method for Assessing Benefits of Variable Cycle Engines in the Conceptual Design of Supersonic Civil Aircraft
by Chao Yang and Xiongqing Yu
Aerospace 2026, 13(5), 399; https://doi.org/10.3390/aerospace13050399 - 22 Apr 2026
Abstract
The Variable Cycle Engine (VCE) is a key enabling technology for addressing the economic and environmental challenges of next-generation supersonic civil aircraft. This paper presents a multidisciplinary design analysis and optimization (MDAO) approach to quantitatively assess the potential benefits of Variable Cycle Engines [...] Read more.
The Variable Cycle Engine (VCE) is a key enabling technology for addressing the economic and environmental challenges of next-generation supersonic civil aircraft. This paper presents a multidisciplinary design analysis and optimization (MDAO) approach to quantitatively assess the potential benefits of Variable Cycle Engines (VCE) in the conceptual design of supersonic civil aircraft. In this approach, component-level models of a conventional Mixed-Flow Turbofan (MFTF) and a double-bypass VCE with a Core Driven Fan Stage (CDFS) are integrated into the MDAO process. Employing a multi-point optimization strategy, the engine design parameters and off-design control schedules are first determined. Subsequently, for each given engine design (MFTF and CDFS VCE), the airframe geometry parameters are optimized to minimize the aircraft Maximum Take-off Weight (MTOW). The application of this approach is illustrated through a case study of a medium-sized supersonic civil transport. The results indicate that, under the assumption of identical weights for the VCE and the MFTF, the design with the VCE reduces the MTOW by 2.8%, block fuel consumption by 5.7%, and total mission Nitrogen Oxides (NOx) emissions by 24.2% compared to the design with the MFTF. Additionally, lateral noise and flyover noise during the take-off phase are decreased by 2.2 EPNdB and 1.9 EPNdB, respectively. To account for the potential weight increase caused by the structural complexity of the VCE, a parametric weight sensitivity analysis is conducted. Results show that the VCE retains its advantages in MTOW, fuel efficiency, noise, and emissions for weight penalty factors up to 1.15. Full article
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38 pages, 454 KB  
Review
Conducting Evaluations in the Context of Tertiary Prevention of Youth Crime: Reflections from the Youth Endowment Fund
by Daniel K. Acquah, Claryn S. J. Kung and Rain M. Sherlock
Behav. Sci. 2026, 16(5), 626; https://doi.org/10.3390/bs16050626 - 22 Apr 2026
Abstract
Serious youth violence is a public health issue nationally in the UK and internationally. The Youth Endowment Fund (YEF) was established in March 2019, with a £200 million endowment and a ten-year mandate, with a mission to prevent children and young people from [...] Read more.
Serious youth violence is a public health issue nationally in the UK and internationally. The Youth Endowment Fund (YEF) was established in March 2019, with a £200 million endowment and a ten-year mandate, with a mission to prevent children and young people from becoming involved in violence. This article gives an overview of YEF’s successes and challenges to date, focusing specifically on the experience of evaluating tertiary interventions. After providing an overview of YEF’s approach to funding and evaluation, the article summarises YEF’s work focused on tertiary prevention, including: work to test interventions already being implemented in the UK; adapting and evaluating evidence-based interventions from other jurisdictions in the UK; innovations in a group approach to carrying out evaluations; and embedding a focus on racial equity in tertiary prevention. Next, the article discusses the design issues involved in high-quality evaluation of tertiary prevention, including the scale required and the processes for obtaining consent from young people to participate in evaluations. The article then documents the many challenges and lessons learned from implementing tertiary prevention evaluations, especially focusing on the recruitment and retention of young people. Finally, the article discusses the lessons and places them in a wider context. Full article
22 pages, 33614 KB  
Article
Spatiotemporal Optimization of Observation Geometry for Wave-Induced Bias in the Kuroshio Region Using the KaDOP Model and Five Years of Hourly ERA5 Reanalysis Data
by Saichao Cao, Yongsheng Xu, Hanwei Sun and Weiya Kong
Remote Sens. 2026, 18(9), 1265; https://doi.org/10.3390/rs18091265 - 22 Apr 2026
Abstract
Ocean surface currents (OSCs) are central to upper ocean dynamics and air–sea exchange, yet their retrieval from spaceborne synthetic aperture radar (SAR) is limited by wave-induced bias (WB). WB arises from the inherent motion of the scattering facets and from long-wave hydrodynamic and [...] Read more.
Ocean surface currents (OSCs) are central to upper ocean dynamics and air–sea exchange, yet their retrieval from spaceborne synthetic aperture radar (SAR) is limited by wave-induced bias (WB). WB arises from the inherent motion of the scattering facets and from long-wave hydrodynamic and tilt modulations, and is therefore jointly controlled by sea state and radar viewing geometry. This study develops an observation geometry optimization framework. Five years of hourly ERA5 wind and wave reanalysis data over the Kuroshio are used as a representative ensemble of sea states to drive the KaDOP model, and an exhaustive grid search over line-of-sight (LOS) azimuth (0–360°) and incidence angle (20–60°) is performed to identify, for each location and season, the viewing geometry that minimizes the time-mean WB. These local optima are then summarized as mission-level metrics, including the minimum achievable WB, the coverage meeting prescribed WB thresholds, and the spatial coherence of the preferred LOS azimuth and incidence angle. Finally, the theoretical minima are compared with the fixed left-looking geometry of the Luojia-2 (LJ-2) satellite along a 213 km × 6 km observation corridor and with Gaofen-3 (GF-3) viewing geometries at four representative locations in the Kuroshio. Across these validation cases, the optimized geometry reduces mean absolute WB by about 20–60% for LJ-2 and 20–80% for GF-3, providing quantitative constraints for future SAR mission design targeting OSCs. Full article
(This article belongs to the Section Ocean Remote Sensing)
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20 pages, 291 KB  
Review
A Review of GRACE/GRACE-FO Satellite Gravimetry Applications in Earthquake Activity Monitoring
by Haoyan Wu, Ye Wu, Guanwen Gu, Shunji Wang, Xinglong Lin, Xianzi Wang and Zhengxin Hong
Appl. Sci. 2026, 16(9), 4066; https://doi.org/10.3390/app16094066 - 22 Apr 2026
Abstract
Earthquakes induce significant mass redistribution, generating temporal gravity variations detectable by GRACE and GRACE-FO missions. However, the capability of different gravity field recovery strategies, particularly spherical harmonic (SH) and mass concentration (MASCON) solutions, to capture coseismic signals remains insufficiently quantified. This study investigates [...] Read more.
Earthquakes induce significant mass redistribution, generating temporal gravity variations detectable by GRACE and GRACE-FO missions. However, the capability of different gravity field recovery strategies, particularly spherical harmonic (SH) and mass concentration (MASCON) solutions, to capture coseismic signals remains insufficiently quantified. This study investigates coseismic gravity changes associated with three Mw 9.0-class earthquakes, including the 2004 Sumatra–Andaman, 2010 Maule, and 2011 Tohoku events, using both SH and MASCON products and theoretical dislocation models. Spectral analysis indicates that recovered signals are dominated by long-wavelength components, while short-wavelength deformation is strongly attenuated. SH products exhibit higher sensitivity to large-scale mass redistribution but are more affected by striping noise and leakage, whereas MASCON products provide improved stability at the cost of signal attenuation. Overall, these findings highlight fundamental limitations of current GRACE-derived products in fully recovering coseismic deformation signals and emphasize the need for improved signal separation strategies. Full article
26 pages, 399 KB  
Article
Anti-Art Poetics: Paul Celan’s “Meridian” Speech
by Shuwei Zhang
Arts 2026, 15(5), 86; https://doi.org/10.3390/arts15050086 - 22 Apr 2026
Abstract
Paul Celan’s speech the “Meridian” addresses the fundamental question of how poetry can be possible in a world “after Auschwitz.” In contrast to the Platonic aesthetic system and classical art traditions, Celan draws upon Büchner’s concept of “Hostility to Art.” Amid the paradox [...] Read more.
Paul Celan’s speech the “Meridian” addresses the fundamental question of how poetry can be possible in a world “after Auschwitz.” In contrast to the Platonic aesthetic system and classical art traditions, Celan draws upon Büchner’s concept of “Hostility to Art.” Amid the paradox of “the impossibility of writing” and “the loneliest loneliness,” Celan embraces the mission of “struggling with the German language,” speaking through a wounded mouth to reclaim a lost home for art. He employs a “grayer language” that distrusts beauty and turns toward truth, approaching a “meridian” of language in a way both “art-less” and “art-free.” On this “meridian,” Celan engages in a secret dialogue of poetry and thought with Others such as Mallarmé, Adorno, Nietzsche, and Heidegger, seeking to return to a realm that is at once uncanny and oriented toward the human. Full article
(This article belongs to the Section Visual Arts)
197 KB  
Proceeding Paper
Overview of Research on Multi-Robot Teams for Space Applications in Europe
by Malte Wirkus, Wiebke Brinkmann and Carlos J. Perez del Pulgar Mancebo
Eng. Proc. 2026, 133(1), 30; https://doi.org/10.3390/engproc2026133030 - 21 Apr 2026
Abstract
Multi-robot systems (MRSs) are promising solutions for complex tasks because different capabilities can be distributed among several systems, resulting in simpler systems, redundancy, and scalability opportunities. This makes MRSs well-suited for planetary and space operation missions. This work reviews and categorizes several approaches [...] Read more.
Multi-robot systems (MRSs) are promising solutions for complex tasks because different capabilities can be distributed among several systems, resulting in simpler systems, redundancy, and scalability opportunities. This makes MRSs well-suited for planetary and space operation missions. This work reviews and categorizes several approaches to multi-robotic teams in Europe into an adapted and extended classification scheme from the MRS literature. This paper presents the classification scheme and interprets the results of the literature review to identify research trends within the European space robotics community and pinpoint research gaps. Full article
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27 pages, 2636 KB  
Article
A Deployment-Oriented Real-Time Transformer Detector and Benchmark for Maritime Search and Rescue Under Severe Sea Clutter
by Zhonghao Wang, Xin Liu, Wenlong Sun, Qixiang Liu, Yijie Cai and Yong Hu
Remote Sens. 2026, 18(8), 1258; https://doi.org/10.3390/rs18081258 - 21 Apr 2026
Abstract
Maritime search and rescue (SAR) is a time-critical public safety mission that increasingly relies on unmanned vehicles to localize persons overboard. However, reliable onboard perception is challenged by extreme scale variation and heavy sea clutter under strict latency and compute budgets. We present [...] Read more.
Maritime search and rescue (SAR) is a time-critical public safety mission that increasingly relies on unmanned vehicles to localize persons overboard. However, reliable onboard perception is challenged by extreme scale variation and heavy sea clutter under strict latency and compute budgets. We present R-DET, a deployment-oriented end-to-end Transformer detector built on the RT-DETR paradigm, featuring three rescue-oriented designs: (i) a lightweight backbone (Rescue-Net) preserving multi-scale cues, (ii) a bounded-cost global-context module (Rescue Attention) suppressing sea clutter, and (iii) an efficient fusion module (Rescue-FPN) injecting high-resolution details for tiny targets. We further introduce MarineRescue-8K, a benchmark collected from real maritime operations with a mission-aligned ignore region protocol that reduces the influence of non-critical clutter during optimization and evaluation. On MarineRescue-8K, R-DET achieves 84.1% mAP@0.5 with only 14.5 M parameters at 63.2 FPS (RTX 2080 SUPER), demonstrating a favorable accuracy–efficiency trade-off for deployment-oriented maritime SAR perception. Full article
(This article belongs to the Special Issue Advances in Remote Sensing Image Target Detection and Recognition)
22 pages, 5240 KB  
Article
Visual Localization for Deep-Sea Mining Vehicles During Operation
by Yangrui Cheng, Bingkun Wang, Xiaojun Zhuo, Kai Liu and Yingjie Guan
J. Mar. Sci. Eng. 2026, 14(8), 759; https://doi.org/10.3390/jmse14080759 - 21 Apr 2026
Abstract
Deep-sea mining operations demand continuous, drift-free positioning over multi-day missions—a requirement that traditional acoustic dead-reckoning systems struggle to meet due to cumulative error accumulation and frequent DVL bottom-lock loss in sediment plume environments. Inspired by Google Cartographer’s 2D grid mapping paradigm, we present [...] Read more.
Deep-sea mining operations demand continuous, drift-free positioning over multi-day missions—a requirement that traditional acoustic dead-reckoning systems struggle to meet due to cumulative error accumulation and frequent DVL bottom-lock loss in sediment plume environments. Inspired by Google Cartographer’s 2D grid mapping paradigm, we present a prior map-based visual localization framework that decouples offline mapping from real-time localization, fundamentally eliminating drift through absolute image registration against pre-built seabed mosaics. By integrating adaptive keyframe selection, Multi-Scale Retinex (MSR) enhancement, and the AD-LG deep feature matching architecture, our system constructs globally consistent seabed maps for absolute positioning. The framework leverages deformable convolutions and LightGlue to effectively mitigate challenges such as low texture and non-rigid distortion. Quantitative validation on tank simulation datasets demonstrates significant superiority over IMU-only and standard fusion schemes; qualitative deployment on real Pacific CCZ imagery confirms near-real-time operational feasibility on an embedded Jetson Orin NX platform. This system establishes visual navigation as a viable backup to acoustic systems, addressing a critical gap in deep-sea mining vehicle autonomy. Full article
(This article belongs to the Special Issue Advances in Underwater Positioning and Navigation Technology)
23 pages, 4408 KB  
Article
Measurement-Informed Latency Limits for Real-Time UAV Swarm Coordination
by Rodolfo Vera-Amaro, Alberto Luviano-Juárez, Mario E. Rivero-Ángeles, Diego Márquez-González and Danna P. Suárez-Ángeles
Drones 2026, 10(4), 310; https://doi.org/10.3390/drones10040310 - 21 Apr 2026
Abstract
Communication latency is one of the main factors limiting the practical scalability of unmanned aerial vehicle (UAV) swarms operating with distributed formation control. In real-time UAV missions, such as coordinated swarm navigation, autonomous inspection, and aerial monitoring, delayed information exchange directly affects formation [...] Read more.
Communication latency is one of the main factors limiting the practical scalability of unmanned aerial vehicle (UAV) swarms operating with distributed formation control. In real-time UAV missions, such as coordinated swarm navigation, autonomous inspection, and aerial monitoring, delayed information exchange directly affects formation stability and operational safety. In practical aerial networks, inter-UAV communication latency is influenced by stochastic effects including jitter, burst delays, and multi-hop propagation, which are rarely captured by the simplified deterministic delay assumptions commonly adopted in analytical formation-control studies. This paper introduces a measurement-informed stochastic delay model and a communication–control delay-feasibility framework that jointly account for per-link latency behavior, multi-hop delay accumulation, and controller-level delay tolerance. The proposed framework is evaluated using an attractive–repulsive distance-based potential field (ARD–PF) formation controller, for which the maximum admissible end-to-end delay is quantified as a function of swarm size and inter-UAV separation. The delay model is calibrated and validated using more than 15,000 in-flight communication delay samples collected from a multi-UAV LoRa platform operating under realistic flight conditions. The results show that different mechanisms limit swarm operation under different operating scenarios. In some configurations, stochastic communication latency becomes the dominant constraint, whereas in others, formation geometry or network load determines the feasible operating region. Based on these elements, the proposed framework characterizes delay-feasible operating regions and predicts the maximum feasible swarm size under distributed formation control and realistic multi-hop communication latency. Full article
(This article belongs to the Special Issue Low-Latency Communication for Real-Time UAV Applications)
14 pages, 1358 KB  
Article
Per-Span Microwave-Frequency Fiber Interferometry for Amplified Transmission Links Employing High-Loss Loopbacks
by Georgios Aias Karydis, Menelaos Skontranis, Christos Simos, Iraklis Simos, Thomas Nikas, Charis Mesaritakis and Adonis Bogris
Sensors 2026, 26(8), 2551; https://doi.org/10.3390/s26082551 - 21 Apr 2026
Abstract
The use of long-distance transoceanic cables equipped with high-loss loopbacks enables distributed sensing with a resolution determined by amplifier spacing, typically in the order of 50–100 km. Microwave-frequency fiber interferometry is a promising trans-mission technique for investigating long links supported by periodic optical [...] Read more.
The use of long-distance transoceanic cables equipped with high-loss loopbacks enables distributed sensing with a resolution determined by amplifier spacing, typically in the order of 50–100 km. Microwave-frequency fiber interferometry is a promising trans-mission technique for investigating long links supported by periodic optical amplification. In this paper, we propose a variant of this technique that ensures compatibility with links containing high-loss loopbacks, thereby transforming the integrated sensing approach into a distributed one. We highlight the critical modifications required to overcome challenges associated with the detection of multiple return signals, and we conduct a proof-of-principle experiment using a two-loop configuration. We demonstrate the concept by detecting and localizing low-frequency (<10 Hz) events—whether human-generated or induced by fiber stretchers—with span-level resolution. This validates the potential of the modified microwave-frequency interferometry approach for transoceanic cable monitoring in scenarios where high-loss loopbacks are present. We also present a theoretical analysis that evaluates the limits of the technique across different frequency ranges, in comparison with optical interferometry methods based on high-spectral-purity fiber lasers. The analysis shows that for long amplifier spacings (~100 km), micro-wave-frequency fiber interferometry exhibits a signal-to-noise ratio advantage at sub-Hz frequencies (<0.1 Hz) compared to state-of-the-art optical interferometers. Full article
(This article belongs to the Special Issue Advances in Optical Fibers Sensing and Communication)
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8 pages, 378 KB  
Proceeding Paper
2U CubeSat Design to Provide Space-Based ICNS Services
by Alex Ganau and Amilcar Rincon Charris
Eng. Proc. 2026, 133(1), 24; https://doi.org/10.3390/engproc2026133024 - 20 Apr 2026
Abstract
This project focuses on the development of a 2U CubeSat intended for potential integration into an LEO constellation. The CubeSat is designed to deliver space-based CNS services, supporting the evolving needs of next-generation airspace and global communication networks. The primary objective is to [...] Read more.
This project focuses on the development of a 2U CubeSat intended for potential integration into an LEO constellation. The CubeSat is designed to deliver space-based CNS services, supporting the evolving needs of next-generation airspace and global communication networks. The primary objective is to enhance global connectivity and demonstrate how compact satellite platforms can contribute to modern ICNS systems. By leveraging the flexibility, scalability, and cost-efficiency of CubeSat technology, the mission aims to validate the role of small satellites in delivering reliable and responsive CNS capabilities. This approach provides a foundation for future advancements in satellite constellations tailored for airspace management and communication services. Full article
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19 pages, 2395 KB  
Article
Dynamic Region Planning and Profit-Adaptive Collaborative Search Strategies for Multi-Robot Systems
by Zeyu Xu, Kai Xue, Ping Wang and Decheng Kong
Systems 2026, 14(4), 450; https://doi.org/10.3390/systems14040450 - 20 Apr 2026
Abstract
Multi-Robot Systems (MRS) demand optimal spatial resource configuration to ensure systemic efficiency in mission-critical applications. Conventional paradigms rely on rigid coverage-first principles, prioritizing exhaustive spatial scanning over rapid target discovery, thereby compromising systemic responsiveness. To bridge this gap, this study proposes the Attraction [...] Read more.
Multi-Robot Systems (MRS) demand optimal spatial resource configuration to ensure systemic efficiency in mission-critical applications. Conventional paradigms rely on rigid coverage-first principles, prioritizing exhaustive spatial scanning over rapid target discovery, thereby compromising systemic responsiveness. To bridge this gap, this study proposes the Attraction of Unknown area Centroid for Exploration (AUCE) architecture, a centralized framework designed to simultaneously optimize global exploration efficiency and early-stage target discovery rates. The control framework incorporates a dynamic region planning strategy that adaptively modulates the systemic search focus based on the specific field of view of autonomous agents, alongside an optimized S-shaped trajectory pattern to establish a rigorous balance between localized path simplicity and global coverage. A versatile profit function synthesizing constant and time-varying coefficient strategies explicitly regulates the systemic trade-off between accelerated early-stage target discovery and global path cost minimization. Quantitative simulations demonstrate that AUCE significantly outperforms established methods by mitigating redundant path costs and generating a distinct front-loading effect to accelerate target localization. Subsequent evaluations confirm the framework’s computational scalability in expanded swarms and its systemic adaptability when navigating static obstacles. Full article
(This article belongs to the Section Systems Theory and Methodology)
31 pages, 1487 KB  
Article
Deep Reinforcement Learning-Based Dual-Loop Adaptive Control Method and Simulation for Loitering Munition Fuze
by Lingyun Zhang, Haojie Li, Chuanhao Zhang, Yuan Zhao, Shixiang Qiao and Hang Yu
Technologies 2026, 14(4), 239; https://doi.org/10.3390/technologies14040239 - 20 Apr 2026
Abstract
To address the poor adaptability and rigid initiation modes of the loitering munition fuze in complex environments and the inadequacy of single fuzzy control against strong interference, this paper proposes a dual-loop adaptive reconfiguration control method. The architecture integrates the Twin Delayed Deep [...] Read more.
To address the poor adaptability and rigid initiation modes of the loitering munition fuze in complex environments and the inadequacy of single fuzzy control against strong interference, this paper proposes a dual-loop adaptive reconfiguration control method. The architecture integrates the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with fuzzy logic. The inner loop uses TD3 to dynamically optimize fuzzy scaling factors based on real-time interference and state deviations. Concurrently, the outer loop utilizes a Fuze Readiness Index (FRI) and a finite state machine to manage real-time multi-modal mission switching (e.g., proximity, delay, and airburst) and reverse safety-state conversions. Co-simulations under non-stationary composite interference show that the proposed method reduces the burst height RMSE by 82.4% and 61.6% compared with the fixed-threshold and standard fuzzy baselines under the considered non-stationary composite interference setting, respectively. The false alarm rate (FAR) is reduced to 0.15%, and the reconfiguration response time under sudden interference is shortened to 12 ms. Even under extreme conditions, such as 400 ms sensor signal loss, the relative error remains within 5%. These simulation results demonstrate the potential of the proposed architecture to improve precision, responsiveness, and robustness under dynamic interference conditions and show good robustness to intermittent observation loss within the simulated operating envelope. Full article
31 pages, 1360 KB  
Article
Optimizing Post-Earthquake Relief with Combined Ground and Air Routing: ε-Constraint and NSGAII-Nearest Neighbor Approaches
by Sogol Mousavi, Mohammadreza Taghizadeh-Yazdi and Seyed Mojtaba Sajadi
Systems 2026, 14(4), 449; https://doi.org/10.3390/systems14040449 - 20 Apr 2026
Abstract
In the wake of an earthquake, severe infrastructure disruption and limited access to affected areas pose serious challenges to the relief process. Therefore, developing efficient models for vehicle allocation and routing plays a crucial role in reducing response time and improving operational efficiency. [...] Read more.
In the wake of an earthquake, severe infrastructure disruption and limited access to affected areas pose serious challenges to the relief process. Therefore, developing efficient models for vehicle allocation and routing plays a crucial role in reducing response time and improving operational efficiency. In this study, a multi-objective routing model is proposed for a hybrid ground–air transportation system, where trucks are responsible for covering accessible areas and drones are deployed to serve inaccessible locations. The model’s objectives include reducing service time, distance travel, total cost, and fuel consumption. To solve the model, the ε-constraint (epsilon-constraint) approach is used for small-scale problems, and a heuristic approach combining the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and the nearest neighbors concept is used for large-scale problems. The computational results show that the proposed hybrid system can reduce response time and significantly improve cost and fuel consumption compared to the ground fleet-only scenario through the optimal assignment of routes and drone missions. The proposed hybrid model resulted in a reduction of approximately 15% in total cost, 12% in service time, and nearly 10% in fuel consumption compared to using the ground fleet alone. These findings demonstrate the effectiveness and efficiency of the proposed framework in post-crisis relief operations. Full article
(This article belongs to the Special Issue Simulation and Digital Twins in Humanitarian Supply Chain Management)
27 pages, 10819 KB  
Article
A Task Allocation Cooperative Execution Method for Resource-Constrained UAVs in Complex Scenarios
by Liangbin Zhang, Weisheng Chen and Jing Chang
Drones 2026, 10(4), 307; https://doi.org/10.3390/drones10040307 - 20 Apr 2026
Abstract
Dynamic task allocation for UAV swarms in complex scenarios is often complicated by uncertain object discovery, potential UAV loss, as well as stringent battery and execution resource limitations. These resource constraints critically affect UAV survivability and mission success but are frequently neglected in [...] Read more.
Dynamic task allocation for UAV swarms in complex scenarios is often complicated by uncertain object discovery, potential UAV loss, as well as stringent battery and execution resource limitations. These resource constraints critically affect UAV survivability and mission success but are frequently neglected in existing studies. This paper develops an auction-based dynamic task allocation for resource-constrained UAV swarms conducting cooperative monitoring and interception missions in dynamic scenarios. Task priority is incorporated to prioritize high-urgency areas and identified objects, and a threshold-based cooperative engagement strategy is proposed to facilitate multi-UAV coordination for interception missions beyond individual UAV capabilities. Meanwhile, battery-aware resource allocation is adopted to improve utilization during cooperative operations. Simulation results across scenario scales and resource configurations demonstrate that the proposed method significantly improves UAV survivability while maintaining competitive mission completion rates, proving its effectiveness for resource-constrained UAV swarm operations. Full article
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