Browse Topic: Unmanned aerial vehicles

Items (1,155)
This study presents a comprehensive methodology for optimizing critical UAV structural nodes—specifically Arm Clamps, Landing Gear, and Motor Mounts—using Generative Design (GD) tailored for Fused Filament Fabrication (FFF) with PLA+. Traditional “plate-and-standoff” UAV constructions often utilize orthogonal geometries that induce stress concentrations and fail to leverage the geometric freedom of additive manufacturing. Furthermore, reliance on expensive CNC machining or injection molding creates supply chain bottlenecks for custom or short-run UAV production. While FFF offers geometric freedom, applying it to structural airframe parts introduces challenges regarding anisotropy, layer adhesion, and material brittleness. This research optimizes these components for standard commercial 3D printers by strictly enforcing manufacturing constraints, including a 40-degree maximum overhang and a 0.4 mm nozzle size, to ensure printability without internal support structures. A significant
Krishna Bansal, Vaibhav
Automatic Dependent Surveillance–Broadcast (ADS-B) has become a cornerstone of modern aviation, revolutionizing Air Traffic Management (ATM) through its ability to continuously transmit real-time flight data—including GPS-derived position, altitude, and velocity. Since its widespread operational deployment over the past decade, ADS-B has significantly enhanced situational awareness, improved safety, extended surveillance coverage into previously unmonitored airspace, and enabled more efficient aircraft routing and separation. However, despite its many advantages, the fundamental design of ADS-B introduces notable security vulnerabilities. Because ADS-B signals are unencrypted and unauthenticated, malicious actors can inject fraudulent broadcasts, creating the illusion of non-existent aircraft. Such spoofing attacks can trigger false cockpit alerts and distract pilots during critical phases of flight. The current ADS-B data format prioritizes simplicity to accommodate a broad range of
Chikkegowda, KanthaShetty, RameshKhan, KalimullaSahoo, Subhransu
Worldwide, engineers are exploring the possibility of using polymer composites in their quest for lightweight materials. In this study, injection moulding was used to develop a biodegradable polymer PLA composite containing 20 wt.% vetiver fibers (VFs) and 2 wt.% nano-silica (nSiO2) obtained from pearl millet, which is sustainable. Materials need machining as secondary operation that required joining. Desirability analysis was used to examine and optimize machining (drilling) studies that were designed with Taguchi's design (L9 orthogonal array). Surface roughness (SR) and delamination factor (Fd) were taken as outputs, while spindle speed (SS), feed rate (FR), and drill diameter (DD) were the inputs. Drilling studies were performed on a single vertical machining center (VMC). ANOVA identifies that the FR had the most decisive influence on SR (F=559.24, p=0.001785), followed by DD and SS. FR is the dominant contributor to Fd (F=379, p=0.00263), followed by SS and DD. At low SS and high
Senthilkumar, N.
Dynamic soaring is a flight technique that exploits wind shear for sustained flight. It is commonly observed in birds such as albatrosses and holds significant potential for unmanned aerial vehicle (UAV) missions. Previous research has primarily focused on trajectory generation using direct optimal control or differential flatness. This paper proposes an enhancement to the existing six-degree-of-freedom (6-DOF) trajectory generation method based on differential flatness. The proposed formulation includes sideslip and accounts for all stability and control derivatives. A Vortex Lattice Method (VLM) solver is then used to compute steady aerodynamic forces and moments, which are compared against the constant-derivative-based trajectories. To assess the validity of the constant-derivative assumption, a 6-DOF UAV model is simulated in a dynamic soaring orbit with stability augmentation provided by a Linear Quadratic Regulator (LQR). The observed divergence in this simulation highlights the
Swaminathan, Bharath
This paper addresses the critical challenge of fault-tolerant control in autonomous multi-copters, particularly under conditions of one or two rotor failures a scenario that often leads to severe instability and a complete loss of directional control due to unbalanced torque and resultant autorotation. Existing advanced control strategies, including optimal approaches such as LQR, typically require precise system modeling and state estimation, which are difficult to achieve in real-world, dynamic failure scenarios. Alternative methods like fuzzy logic, sliding mode control, and gain-scheduling either lack robust generalization or are impractical for enumerating all possible failure cases. In this work, a hybrid control framework integrating Physics Informed Neural Networks (PINN) with a standard PID controller is proposed for fault-tolerant operation of autonomous multi-copters subject to multiple actuator failures. PINNs incorporate governing physical laws as regularization in their
Charapalle, SamruddhiVenugopalan, NandagopalanNerkundram Muralidharan, ArunSundararaj, Laveen
Unmanned Aircraft Systems (UAS) are increasingly deployed in diverse missions, and maintaining heading stability in the presence of unpredictable wind disturbance is a significant challenge. This paper proposes a novel model reference adaptive gain-scheduled PID (Proportional-Integral-Derivative) control framework tailored for the heading control of flapping-wing UAS (ornithopter) operating under dynamic wind conditions. The control architecture integrates an estimated wind disturbance value and adaptively tunes the PID gains by minimizing the error between the actual system response and a desired reference model. Gain scheduling mechanism uses airspeed, yaw rate, and estimated wind magnitude to ensure stability. The proposed method is validated on a 6-DOF UAS simulation model subjected to dynamic wind and temperature variation profiles. Comparative results show improved heading accuracy, responsiveness, and robustness over conventional fixed-gain and static gain-scheduled PID
M V, ArunaMelissa, Arul
Unmanned Aerial Vehicles (UAVs) demand structural materials that are lightweight, strong, impact-resistant, and durable in diverse environments. The synthetic fiber reinforced polymer composites have varying mechanical performance depending on the fiber matrix interfacial properties. This research analyzes the influence of Graphene Oxide (GO) nano fillers on mechanical properties of composites. Firstly, the epoxy resin was modified by incorporating different weight percentage of Graphene Oxide. This resin was used to make an composite laminate using different materials (Carbon, Glass and combination of these fibers). Then the composites were put through the tensile, compression, flexural tests. The synthetic fiber reinforced polymer composites have a significant improvement in mechanical properties due to the addition of Graphene Oxide.
Manoharan, DineshLangford, PeterM.K., PadmanabhanR, PrithvirajRajkumar, SubbiahKarthikeyan, RavikumarVeeramuthu, BalasubramaniyanGunaseelan, JohnT, Thangaraj
Bird accidental collision with overhead transmission lines poses a threat to the ecology of rare bird populations. This article analyzes the warning measures to prevent birds from accidental collisions at home and abroad. In response to the low efficiency of manual installation and the poor static warning effect in preventing birds from accidental collisions with overhead transmission lines, the visual characteristics of birds are analyzed. A drone-based automatic installation flash-type bird accidental collision warning device is proposed, which includes a fixture, a disc, and a luminous circuit. The fixture can be carried and installed on the overhead line by a drone and can be easily disassembled. The disc adopts eye-catching colors and has a hollow structure to reduce wind resistance load. The luminous circuit includes solar panels, charge and discharge control circuits, flicker control circuits, batteries, and luminous components. The drone suspension warning device test was
Wang, JianWang, XiulongLiu, BinLi, DanyuXu, Xunjian
This paper presents a multi-physics modeling approach for a hybrid propulsion system designed for High-Altitude Long-Endurance Unmanned Aerial Vehicles (HALE UAVs), integrating solid oxide fuel cells (SOFCs), lithium-ion batteries, and a jet engine. A dynamic model was developed to analyze the coupled characteristics of pressure, temperature, and power under steady-state conditions. Simulation results demonstrate that the internally integrated system achieves efficient fuel and waste heat recovery, delivering a net power output of 300–700 kW, sufficient to meet the operational demands of HALE UAVs. Key innovations include a heat exchanger maintaining SOFC stack inlet temperatures above 850 K for optimal performance and a compressor-fan subsystem enhancing gas compression efficiency. Experimental validation confirmed the accuracy of the SOFC model, with simulated electrical characteristics aligning closely with empirical data. The proposed hybrid system addresses limitations in specific
Zhang, LinZhang, DiZhao, LuluLi, Xi
Unmanned Aerial Vehicles (UAVs) are widely used for inspecting transmission towers. However, traditional waypoint planning relies heavily on manual experience. This leads to low efficiency, incomplete coverage, and a lack of standardization. Facing these problems, this paper proposes an intelligent generation method based on Hierarchical Reinforcement Learning (HRL). This method achieves end-to-end automation, converting raw point cloud data directly into an optimal set of waypoints. Preprocess and grid the point cloud data to build a model of the coverage area. Then design a hierarchical framework to break down the complex planning task. This framework divides the task into high-level waypoint selection and low-level pose optimization. Specifically, the high-level part uses a Deep Q-Network (DQN) to learn the best sequence of waypoints. The low-level part uses Q-learning tables to optimize the pitch and yaw angles for each point. Meanwhile, design a reward function to maximize
Cui, ShichengLin, ShizhongShao, ZhanChen, RuiduanLi, XingyuLuo, He
This document defines a set of standard application layer interfaces called JAUS Environment Sensing Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Environment Sensing Services represent typical environment sensing capabilities commonly found across all domains and types of unmanned systems in a platform-independent manner. At present, twelve services are defined in this document: Range Sensor: Determine the proximity of objects in the platform’s environment Visual Sensor: Provides common configuration and setup for different types of imaging systems Digital Video: A type of Visual Sensor that manages digital video Analog Video: A type of Visual Sensor that manages analog video Still Image: A type of Visual Sensor that manages and encodes individual digital images Digital Audio Sensor: Provides common configuration and setup for different types of audio streams
AS-4JAUS Joint Architecture for Unmanned Systems Committee
Army researchers recently developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. Army Research Laboratory, Adelphi, MD Researchers at the U.S. Army Combat Capabilities Development Command, or DEVCOM, Army Research Laboratory (ARL) harnessed bottom-up Soldier innovation to develop an experimental 3D-printed small unmanned aerial system, or drone, that was demonstrated at the inaugural U.S. Army Best Drone Warfighter Competition in Huntsville, Alabama. Known as the Soldier Portable Autonomous Reconnaissance Transitioning Aircraft, or SPARTA, the drone was developed at DEVCOM ARL in collaboration with Soldiers. By incorporating Soldier feedback early in the design process and leveraging ARL's world-class research facilities, researchers developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. ARL is actively working to partner the technology
MyDefence has officially opened its U.S. counter uncrewed aircraft systems (C UAS) manufacturing and innovation facility in Oklahoma City, marking a major step in the company's expansion of its North American production footprint. The latest MyDefence facility, which became operational in February, strengthens the company's ability to support U.S. and allied defense customers with domestically produced counter drone technologies while reinforcing supply chain resilience, regulatory compliance, and lifecycle support. The opening comes amid rapid growth in the scale, diversity, and technical sophistication of uncrewed aerial system threats. Advances in autonomy, range, payload integration, and - critically -radio frequency (RF) employment have increased demand for counter UAS solutions that can evolve as quickly as the threat itself.
Researchers recently helped Skydio, the leading U.S. drone manufacturer, demonstrate compliance to the Federal Aviation Administration's rules for safe flights over people and vehicles. Virginia Polytechnic Institute and State University, Blacksburg, VA Operators using a drone from the leading manufacturer in the U.S. can now conduct missions over people and vehicles much easier and with even greater confidence in their safety. In January, the Federal Aviation Administration (FAA) accepted a declaration of compliance for such flights for the parachute-equipped Skydio X10 drone from Skydio, a San Mateo, California-based company that supplies its drones to customers in public safety, utilities, and national security. The acceptance came as the result of working with Virginia Tech's Mid-Atlantic Aviation Partnership (MAAP) and Center for Injury Biomechanics to complete their FAA-approved means of compliance testing.
On a clear afternoon over a contested airspace, a drone suddenly appears on radar. Within seconds, more follow, and they're small, fast, and unpredictable. For the U.S. Army's air and missile defense operators, every moment counts. The difference between mission success and mission failure is measured in milliseconds. During that brief window, sensors must connect instantly, embedded systems must process floods of data at the edge, and command links must hold steady even under electronic interference.
Traditionally, ground vehicle design is based on identifying engineering solutions that fulfil the requirements and specifications put forth by the stakeholders. Although a vehicle is a single entity, it is composed of many subsystems and thousands of parts that must operate together in unison to meet all design goals. A System of Systems (SoS) design approach enables the consideration of subsystem performance within a framework of overall system operation, which includes possible tradeoffs. This collaborative approach to subsystem and primary system design draws upon modelling, optimization, tradespace analysis and virtual studies. In this paper, a system of system design approach will be investigated for a collection of multi-domain vehicles assembled to undertake coordinated search and rescue operations on land and water. A host ground vehicle, an unmanned aerial drone, an unmanned marine drone and an unmanned tracked vehicle constitute the family of multi-domain vehicles which will
Somanchi, AnangAbeynayake, ChandimaDeshmukh, MrunalSuresh, JohirRamnath, SatchitTurner, CameronSchmid, MatthiasCastanier, Matthew P.Rapp, StephenJaczkowski, Jeffrey J.Wagner, John
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages—sensor acquisition, video encoding, data transmission, decoding, and display—undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software
Indrakanti, Rama Kiran Kumar
The exponentially growing complexity of engineering systems, such as robotic systems, autonomous vehicles, and unmanned aerial vehicles, require sophisticated control strategies that can efficiently coordinate system operation in various environments. The traditional control design approaches present significant challenges for control engineers to keep up with the increasing complexity and changing requirements. To advance embedded control system design, a paradigm shift from traditional development approaches toward more structured, systematic methodologies that can manage the multi-domain nature of control systems is critically needed. Model-based design approach is emerging as a solution for this demand. Model-based design approach uses a system model for control system development, from requirements capture to control system design, implementation, and testing. It provides an integrated environment for design, implementation, automatic code generation, and validation, which allows
Repaka, SindhuraChen, Bo
The modern battlefield is increasingly characterized by the use of small drones. As such, military vehicles must now be designed to account for this threat. This paper presents a model-based systems engineering approach to identify vehicle vulnerabilities and generate new vehicle requirements to mitigate them. This approach uses a standard set of System Modeling Language diagrams. A vehicle’s primary roles are captured in a series of use cases. Each use case is characterized by a sequence of activities performed by the vehicle. These activity sequences are captured in an activity diagram, which are used to wargame how a drone can exploit the vehicle at each phase. Each potential exploitation is assigned likelihood and severity scores, which feed into a risk index. This risk index is then used to prioritize each vulnerability. From these vulnerabilities, a set of operational requirements are derived, which then informs the development of system requirements. As the system matures, the
Ells, AlecWerntz, BrysonSaulsberry, TaylorWilkinson, CooperMittal, Vikram
Fires in Urban high-rise structures and industrial areas pose significant challenges to traditional firefighting methods. Traditional firefighting methods often struggle to address the challenges posed by height, accessibility and rapid response. In such a scenario innovative technologies become vital for effective and efficient methods. This project introduces an unmanned aerial vehicle designed to suppress fire on high-rise building by using drone technologies and robotics. The drone is equipped with a stereo camera which will detect fire and measure its coordinates with the help of algorithms fed on the companion computer raspberry pi. Upon receiving the coordinates, the drone will station itself at a predetermined distance from the fire. The drone will adjust itself in the vertical direction for proper ejection of water at the fire. The water will be ejected through a nozzle integrated with the drone, which is connected to the pump at the ground via hose. This drone solution
R, AbhiramSadique, AnwarPV, AnuragJ, Harisankar VA, Geethuvs, Amarnath
The growing environmental, economic, and social challenges have spurred a demand for cleaner mobility solutions. In response to the transformative changes in the automotive sector, manufacturers must prioritize digital validation of products, manufacturing processes, and tools prior to mass production. This ensures efficiency, accuracy, and cost-effectiveness. By utilizing 3D modelling of factory layouts, factory planners can digitally validate production line changes, substantially reducing costs when introducing new products. One key innovation involves creating 3D models using point cloud data from factory scans. Traditional factory scanning processes face limitations like blind spots and periodic scanning intervals. This research proposes using drones equipped with LiDAR (Light Detection and Ranging) technology for 3D scanning, enabling real-time mapping, autonomous operation, and efficient data collection. Drones can navigate complex areas, access small spaces, and optimize
Narad, Akshay MarutiC H, AjheyasimhaVijayasekaran, VinothkumarFasge, Abhishek
Current world conflicts have proven that drones are now indispensable tools in modern warfare. Whether for reconnaissance, loitering munitions, or asymmetric tactics that exploit vulnerabilities in conventional defenses, unmanned aerial systems (UAS) are redefining the rules of engagement.
In complete darkness, through smoke, glare and fog, thermal infrared (IR) imaging is indispensable for modern defense and autonomous systems. Enabling autonomous vehicles (AVs) to detect pedestrians or threats at night or providing critical sensing capabilities for unmanned aerial vehicles and counter-UAS operations, thermal imaging has become the essential “eyes” when visible camera systems fail.
Without reliability and signal integrity, aerospace communications risk severe signal degradation and reduced security, posing risks to both personnel and mission-critical data. These challenges are particularly critical for applications that depend on military aircraft, satellite communications, and unmanned aerial vehicles (UAVs). As global demand for real-time data continues to surge, communication infrastructure requires regular maintenance and upgrades to maintain secure and reliable performance.
Unmanned Aerial Vehicles (UAVs) offer high efficiency, low cost, and strong mobility, making them well-suited for traffic vehicle detection. However, dense targets, rapid scene changes, and small object sizes in aerial videos reduce detection accuracy, which in turn affects the precision of speed extraction algorithms. To address these issues, this paper proposes a speed extraction method that integrates an improved You Only Look Once Version 11 (YOLOv11) with the Deep Simple Online and Realtime Tracking (DeepSORT) algorithm. On the detection side, several architectural enhancements are introduced. A Haar wavelet-based HWD downsampling module preserves fine-grained details, a CSK2_m multi-scale convolution block with a CCFM feature fusion structure strengthens cross-scale representation, and an additional detection head at the P2 layer improves the recall of tiny objects in complex scenes. Extensive experiments on a hybrid dataset constructed from VisDrone2019 and a custom UAV dataset
Ye, XinCheng, XiaoxuanLi, Xiangdong
This study examines the issue of frequent traffic accidents leading to congestion and subsequent accidents. Timely investigation and management of these incidents is essential for effectively addressing this problem. This study aims to utilize Unmanned Aerial Vehicle (UAV) technology to improve the efficiency of assessing and investigating traffic accidents. We propose a bi-objective spatial optimization model based on identifying high-risk accident locations. This model combines coverage and median objectives within a service area, taking into account coverage requirements and optimizing site distribution. We also propose a constraint-based process to generate a Pareto frontier to help identify various alternative UAV station location scenarios. The model was validated using real traffic accident data from Nanning City, resulting in a UAV station configuration solution that reduces accident response time and improves assessment efficiency by considering multi-objective trade-offs
Li, QiulingWan, QianLiu, QianqianSun, Ke
Identifying objects within images taken by unmanned aerial vehicles poses specific difficulties due to the aerial viewpoint, limited resolution, significant scale variation, and densely distributed targets. These issues hinder accurate identification, particularly of small objects. To mitigate these problems, we developed MSDFYOLO, a innovative architecture built upon YOLOv11, which integrates several structural and functional enhancements tailored for UAV-based imagery. Specifically, we develop the C3K2-GGCA module, an attention-based mechanism embedded in the backbone to better capture spatial dependencies and improve feature extraction. In addition, a lightweight attention strategy is employed to reduce complexity. We further introduce a small-object detection enhancement layer, an improved C2PSA module with deeper fusion between semantic and spatial features, and a multi-scale feature concatenation mechanism to strengthen information integration. To improve training stability and
Zhou, XingzhongLiu, QianHuang, Hanming
In the future battlefield, logistics UAVs will play an increasingly important role. The development of logistics UAVs abroad is rapid. Sort out the current development status of logistics UAVs in countries such as the United States, Russia, Israel, and Ukraine, including mission tasks, functional characteristics, and main performance indicators. In addition, the future technological trends of logistics UAVs are studied and predicted. Firstly, diversification of functions, which logistics UAVs will achieve diversified functions in the future, such as material transportation, aerial refueling, unmanned mother aircraft, and transfer of wounded personnel; Secondly, intelligent commendation and control, which logistics UAVs pursue the optimal efficiency in the four steps of ordering, dispatching, delivering, and evaluating in the “food delivery” mode; Finally, resource collaboration. In the collaborative logistics mode of “free riding”, logistics UAVs over a wide area are interconnected
Zhai, JundaLiu, DaweiBai, QiangqiangHua, JinxingWang, XiaoyueYang, JianZou, XiaoyingGao, Yuxuan
Objective:Methods:Results:Conclusion:
Sun, KeWan, QianLiu, QianqianLi, Qiuling
Augustine's Law predicts “In the year 2054, the entire defense budget of the United States will purchase just one aircraft. This aircraft will have to be shared by the Air Force and Navy three days each per week except for leap year, when it will be made available to the Marines for the extra day.” While the world is not on course for the $800 billion aircraft as Augustine predicted, the aerospace & defense industry must take steps to bring new technology to the battlefield without the $800 billion price tag. The development of robotic aircraft or drones is one way to deliver new capability faster for less cost.
From satellites and commercial aircraft to uncrewed aerial vehicles (UAVs), the reliability of aerospace and defense electronics depends on their ability to perform flawlessly in extreme conditions. While stresses such as altitude changes, vacuum, vibration, moisture and chemical exposure have the potential to wreak havoc on electronic components, conformal coatings have become essential to providing protection in the midst of these challenges. Applied as thin, lightweight films that follow the contours of printed circuit boards (PCBs) and components, conformal coatings create a barrier between the electronics and the harsh environments in which they must perform. The coatings' ability to provide dielectric insulation, chemical protection and moisture resistance ensures that mission-critical electronics remain functional on the ground, in the sea, in flight or in orbit.
The geological disasters along the Sichuan-Tibet Highway are frequent, and the traffic environment is complex. Traditional disaster reconnaissance methods struggle to meet the timeliness and accuracy requirements of emergency response. With the development of unmanned aerial vehicle (UAV) technology, it has significant advantages in rapid disaster information acquisition and complex terrain coverage. Considering the large elevation fluctuations, variable climate, and limited communication conditions in the study area, this paper focuses on UAV disaster reconnaissance in complex mountainous environments. By systematically summarizing and categorizing existing UAV disaster reconnaissance methods, this paper designs a UAV disaster reconnaissance system and applies it in practical engineering projects, providing technical support for disaster reconnaissance and emergency management along the Sichuan-Tibet Highway.
Wu, GuorongXu, HuayanChen, YunjinTang, LuweiMo, ShiyingLuo, ShuzhaoHuang, ZiyangLiu, Xianxin
Two-stroke engines represent an attractive solution for aviation industry applications (UAVs, VTOL aircraft, and ultralight aircraft) due to their compact size, high power-to-weight ratio, reduced number of moving parts, and the ability to operate with different fuels. This work presents a 0D/1D methodology for simulating the gas exchange, combustion, and unsteady flow of a two-stroke aviation engine. The scavenging and combustion processes, as well as the unsteady flow within the induction and exhaust systems, are investigated using a 0D/1D modeling approach. This study is motivated by the need to assess the accuracy of such models in predicting engine performance. For this purpose, the thermo-fluid dynamic code GASDYN has been applied and enhanced. The proposed 0D model is embedded into a 1D fluid-dynamic code for simulating the entire engine system. To characterize the baseline configuration, which includes tangential ports that facilitate a loop-scavenging process, computed results
Cerri, TarcisioGiussani, AlessandroLucchini, TommasoMarinoni, AndreaMontenegro, GianlucaOnorati, Angelo
Rotary engines offer a highly attractive solution for uncrewed aerial vehicles (UAVs) and portable power generation, thanks to their compact design, high power-to-weight ratio, fewer moving parts, and ability to operate on multiple fuels. Despite their promising advantages, these engines still require significant improvements to match the efficiency and lifespan of traditional reciprocating internal combustion engines. In particular, fuel consumption is impacted by heat losses due to the high surface-to-volume ratio of the combustion chamber, as well as the unfavorable interaction between the rotor and stator, which slows down flame propagation. To address these challenges, computational fluid dynamics (CFD) has become an important tool for the study and optimization of Wankel engines, providing insight into how fuel efficiency is influenced by the complex interactions between combustion chamber design, flame dynamics, flow characteristics, and turbulence distribution. This work
Lucchini, TommasoGianetti, GiovanniRamognino, FedericoCerri, TarcisioMarmorini, LucaButtitta, Marco
There is a significant shift toward the electrification of military systems as defense chiefs worldwide look to secure operational advantage across land, sea, and air. From ground vehicles to naval vessels, fighter jets to autonomous drones, senior officials, and planners are eager to accelerate the adoption of batteries, hybrid electric systems, and other sustainable technologies — thereby improving the performance of major platforms.
Forest fire prevention and control agencies in São Carlos, in the interior of the state of São Paulo, Brazil, will soon have help from the sky to detect fires more quickly and combat them before they grow out of control and cannot be extinguished.
A Modular Open Systems Approach (MOSA) for command and control (C2) of autonomous vehicles equipped with sensor and defeat mechanisms enhances force protection against unmanned aerial systems (UAS), swarm, and ground-based robotic threats with current technology while providing an adaptable framework able to accommodate technological advances. This approach emphasizes modularity, which allows for independent upgrades and maintenance; interoperability, which ensures seamless integration with other systems; and scalability, which enables the system to grow and adapt to increasing threats and new technologies – all of which are essential for managing complex, dynamic, and evolving operational threats from UAS, swarm, and ground-based robots. The proposed systems approach is designed around component-based modules with standardized interfaces, ensuring ease of integration, maintenance, and upgrades. The integration of diverse sensors through plug-and-play capabilities and multi-sensor
Davidson, JeremyDrewes, PeterGraham, RogerHaider, EricPhillips, Michael
Drones, or Unmanned Aerial Vehicles (UAVs) pose an increasing threat to military ground vehicles due to their precision strike capabilities, surveillance functions, and ability to engage in electronic warfare. Their agility, speed, and low visibility allow them to evade traditional defense systems, creating an urgent need for advanced AI-driven detection models that quickly and accurately identify UAV threats while minimizing false positives and negatives. Training effective deep-learning models typically requires extensive, diverse datasets, yet acquiring and annotating real-world UAV imagery is expensive, time-consuming, and often non-feasible, especially for imagery featuring relevant UAV models in appropriate military contexts. Synthetic data, generated via digital twin simulation, offers a viable approach to overcoming these limitations. This paper presents some of the work Duality AI is doing in conjunction with the Army’s Program Executive Office Ground Combat Systems (PEO GCS
Mejia, FelipeShah, SunilYoung, Preston C.Brunk, Andrew T.
The emergence of SUAS as a threat vector introduces significant challenges in surveillance and defense due to their potential for low cross section and high speeds, defeating or evading many existing detection and tracking capabilities. This paper presents two algorithms—one for detection and one for tracking—developed for event cameras, which offer substantial improvements in temporal resolution, dynamic range, and low-light performance compared to traditional imaging systems, all of which are critical for effective UAS defense. These advancements address current limitations in using event cameras and pave the way for a new generation of robust robotic vision based on event cameras.
Anthony, DavidChambers, DavidTowler, Jerry
As weather-related catastrophes and urban vulnerabilities intensify, there is a growing interest in AI-driven tools for predicting weather patterns and disaster response. Engineers at Texas A&M University have developed CLARKE (Computer vision and Learning for Analysis of Roads and Key Edifices) — a system that uses drone imagery and artificial intelligence to rapidly assess damage after hurricanes and floods.
High-altitude uncrewed aircraft can remain in the lower stratosphere for extended periods, performing a wide range of Earth observation and communications tasks – from monitoring shipping lanes and supporting disaster response to providing internet access. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) has now taken an important step in the development of its own high-flying solar aircraft by successfully completing a Ground Vibration Test (GVT) on its innovative HAP-alpha high-altitude platform. Extensive ground trials took place at DLR’s National Experimental Test Center for Unmanned Aircraft Systems in Cochstedt, Germany. Further tests will follow and the first low-altitude flight trial is planned for 2026, subject to ideal weather conditions.
Mathematician hopes to harness principles of dynamic soaring for long-distance flights. University of Cincinnati, Cincinnati, OH How does one of the biggest birds in the world spend so much time in the air? Albatrosses have 11-foot wingspans that carry them across oceans. But it's how they use these wings that makes them world-class flyers, according to a University of Cincinnati aerospace engineering professor.
How does one of the biggest birds in the world spend so much time in the air?
The German Aerospace Center's (DLR) solar-powered high altitude platform (HAP) has completed ground vibration testing, in preparation for low altitude flight testing planned for 2026. German Aerospace Center (DLR), Cologne, Germany High-altitude uncrewed aircraft can remain in the lower stratosphere for extended periods, performing a wide range of Earth observation and communications tasks - from monitoring shipping lanes and supporting disaster response to providing internet access. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) has now taken an important step in the development of its own high-flying solar aircraft by successfully completing a Ground Vibration Test (GVT) on its innovative HAP-alpha high-altitude platform. Extensive ground trials took place at DLR's National Experimental Test Center for Unmanned Aircraft Systems in Cochstedt, Germany. Further tests will follow and the first low-altitude flight trial is planned for 2026, subject to ideal
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