Browse Topic: Unmanned aerial vehicles

Items (993)
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
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
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
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.
How does one of the biggest birds in the world spend so much time in the air?
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.
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
This SAE Aerospace Recommended Practice (ARP) describes terminology specific to unmanned systems (UMSs) and definitions for those terms. It focuses only on terms used exclusively for the development, testing, and other activities regarding UMSs. It further focuses on the autonomy and performance measures aspects of UMSs and is based on the participants’ earlier work, the Autonomy Levels for Unmanned Systems (ALFUS) Framework, published as NIST Special Publication 1011-I-2.0 and NIST Special Publication 1011-II-1.0. This Practice also reflects the collaboration results with AIR5665. Terms that are used in the community but can be understood with common dictionary definitions are not included in this document. Further efforts to expand the scope of the terminology are being planned.
AS-4JAUS Joint Architecture for Unmanned Systems Committee
The development of drones has raised questions about their safety in case of high-speed impacts with the head. This has been recently studied with dummies, postmortem human surrogates and numerical models but questions are still open regarding the transfer of skull fracture tolerance and procedures from road safety to drone impacts. This study aimed to assess the performance of an existing head FE model (GHBMC M50-O v6.0) in terms of response and fracture prediction using a wide range of impact conditions from the literature (low and high-speed, rigid and deformable impactors, drones). The fracture prediction capability was assessed using 156 load cases, including 18 high speed tests and 19 tests for which subject specific models were built. The GHBMC model was found to overpredict peak forces, especially for rigid impactors and fracture cases. However, the model captured the head accelerations tendencies for drone impacts. The formulation of bone elements, the failure representation
Pozzi, ClémentGardegaront, MarcAllegre, LucilleBeillas, Philippe
Researchers have created a 98-milligram sensor system — about one tenth the weight of a jellybean or less than one-hundredth of an ounce — that can ride aboard a small drone or an insect, such as a moth, until it gets to its destination. Then, when a researcher sends a Bluetooth command, the sensor is released from its perch and can fall up to 72 feet — from about the sixth floor of a building — and land without breaking. Once on the ground, the sensor can collect data, such as temperature or humidity, for almost three years.
In the future, autonomous drones could be used to shuttle inventory between large warehouses. A drone might fly into a semi-dark structure the size of several football fields, zipping along hundreds of identical aisles before docking at the precise spot where its shipment is needed.
The Science and Technology Directorate's (S&T) National Urban Security Technology Laboratory (NUSTL) recently brought together emergency responders from across the nation to test unmanned aircraft systems (UAS) from the Blue UAS Cleared List. By providing an aerial vantage point, and creating standoff distance between responders and potential threats, UAS can significantly mitigate safety risks to responders by allowing them to assess and monitor incidents remotely. U.S. Department of Homeland Security, Washington, D.C. In November 2024, the U.S. Department of Homeland Security's (DHS) National Urban Security Technology Laboratory (NUSTL) teamed up with Mississippi State University's (MSU) Raspet Flight Research Laboratory, and DAGER Technology LLC, to conduct an assessment on selected models of cybersecure “Blue UAS.” The drones, including models from Ascent AeroSystems, Freefly Systems, Parrot Drones, Skydio, and Teal Drones, are cybersecure and commercially available to assist
In February, the Joint Interagency Field Experimentation (JIFX) team at the Naval Postgraduate School (NPS) executed another highly collaborative week of rapid prototyping and defense demonstrations with dozens of emerging technology companies. Conducted alongside NPS’ operationally experienced warfighter-students, the event is a win-win providing insight to accelerate potential dual-use applications.
Da Jiang Innovations (DJI)’s AeroScope drone detection platform has proven to be an effective security tool for military and law enforcement. It identifies and tracks drones in real time, providing AeroScope users with information like flight status, path and pilot location for drones up to 50 kilometers away. This data stream enables users to make fast and informed responses as soon as possible, mitigating the potentially harmful effects of consumer drones in and around public spaces, government facilities, infrastructure and other no-fly zones.
As the capabilities of unmanned aerial systems continue to evolve rapidly in response to the tactical and strategic necessities of the modern battlefield, the U.S. Army Aeromedical Research Laboratory is exploring a unique approach to improving their operational effectiveness – by focusing on the protection and performance of UAS operators.
With the exponential rise in drone activity, safely managing low-flying airspace has become challenging — especially in highly populated areas. Just last month an unauthorized drone collided with a ‘Super Scooper’ aircraft above the Los Angeles wildfires, grounding the aircraft for several days and hampering the firefighting efforts.
In November 2024, the U.S. Department of Homeland Security’s (DHS) National Urban Security Technology Laboratory (NUSTL) teamed up with Mississippi State University’s (MSU) Raspet Flight Research Laboratory, and DAGER Technology LLC, to conduct an assessment on selected models of cybersecure “Blue UAS.” The drones, including models from Ascent AeroSystems, Freefly Systems, Parrot Drones, Skydio, and Teal Drones, are cybersecure and commercially available to assist emergency responders with their public safety operations.
This document defines a set of standard application layer interfaces called JAUS Autonomous Capabilities 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 Autonomous Behaviors Services represent the platform-independent capabilities commonly found in platforms across domains, including air, maritime, and ground. At present five (5) services are defined in this document. These services are: Comms Lost Policy Manager: Detect and recover from loss of communications with a control station Retrotraverse: Return along a path previously traveled Self-Righting: Attempt to recover from a tip over condition Cost Map 2D: Provides information about the current operating environment of the platform Path Reporter: Provides information about the previous or future planned path of the platform
AS-4JAUS Joint Architecture for Unmanned Systems Committee
The SAE Aerospace Information Report AIR5315 – Generic Open Architecture (GOA) defines “a framework to identify interface classes for applying open systems to the design of a specific hardware/software system.” [sae] JAUS Service (Interface) Definition Language defines an XML schema for the interface definition of services at the Class 4L, or Application Layer, and Class 3L, or System Services Layer, of the Generic Open Architecture stack (see Figure 1). The specification of JAUS services shall be defined according to the JAUS Service (Interface) Definition Language document.
AS-4JAUS Joint Architecture for Unmanned Systems Committee
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