Browse Topic: Unmanned aerial vehicles
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
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
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
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.
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
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.
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
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.
How does one of the biggest birds in the world spend so much time in the air?
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.
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.
ABSTRACT The development of a coupled computational structural dynamics (CSD) and electrodynamic suspension (EDS) system was critical in modeling and predicting the aeromechanics of MagLev Aero's (MLA) propulsion system, ensuring safe testing and proving viability of levitated rotors for vertical lift systems. This advancement validates the feasibility of this enabling technology in applications of uncrewed aerial systems (UAS) with high hover lift efficiencies. This paper explores the implementation of an electromagnetic motor hub on a large-root-cutout, slowed rotor system with a specific focus on the impacts on aeromechanics: loads, performance, vibrations, and aeroelastic stability. The performance benefits of a large-root-cutout system, with an external or internal rotor, are well known; however, the mechanisms to implement such a design have been impractical. The development of an EDS motor bearing enables previously unattainable configurations like large-root-cutout and tip
ABSTRACT In this work, a vision-based solution is developed to address the challenge of landing on a ship deck with precision and accuracy. For an autonomous landing, it is important to have a fast and accurate pose estimation system along with a reliable control strategy. This research uses fractal ArUCo markers instead of multiple separate markers to allow smooth pose estimation at different heights. Pose estimates are further improved using an Extended Kalman Filter, and a tracking algorithm then uses these estimates to guide the landing. A four degree-of-freedom (roll, pitch, heave and sway) simulator platform was built and used to validate the algorithm. The accuracy of the vision system is compared against that of a motion capture system. Real-world experiments were performed on different quadrotors to demonstrate tracking and landing on the platform with sway, roll, and pitch motions. The results show that the system is efficient and reliable in achieving safe and successful
ABSTRACT This paper presents a distributed algorithm to track a desired target while fostering the emergence of a swarm formation and providing obstacle avoidance capability to deal with unknown scenarios. The proposed approach is based on the merge between a Flight Management System for global path planning and the definition of virtual forces through a custom Artificial Potential Field to prevent drones collisions between each other, with external objects and to provide cohesion of the swarm configuration. Each drone independently computes its global route and adjusts its path based on an optimal control action to minimize a potential energy function induced by its neighbors and obstacles. This approach results in a high cost-effective strategy to enhance UAVs autonomy level by managing a large group of drones, guaranteeing a low cost per unit thanks to the low computational effort and low-budget sensor suit while providing all the capabilities to accomplish the desired mission.
ABSTRACT To document noise characteristics and provide validation data for acoustic modeling of rotor systems appropriate for eVTOL/UAM aircraft, the authors performed an outdoor static test of a subscale 5-blade proprotor. The testing was carried out as part of a program to demonstrate feasibility and overall performance of a quiet proprotor system in support of the eVTOL industry. The authors designed a low-tip speed proprotor to approximate performance required by a 4-5 passenger UAM vehicle. A driving design feature was low-tip speed operation (Mtip ˜0.27) at system disk loadings of 7 to 8 psf (˜3.7 N/m2). The test article was designed as a ground adjustable pitch 5-blade proprotor, with aerodynamic and acoustic data collected in outdoor static hover testing. The test article diameter of 3 feet (0.91 m) represented a scale factor of approximately 30% to 40% compared to vehicles currently in operation or development. The aerodynamic performance in hover was consistent with other
ABSTRACT The Rotor Blown Wing (RBW) is a tailsitter Vertical Takeoff and Landing (VTOL) Unmanned Aerial System (UAS) configuration that leverages cutting-edge autonomous flight controls through Sikorsky's MATRIX™ technology to create a highly capable, efficient, and scalable technology platform. By combining the benefits of fixed- and rotary-wing aircraft, the RBW configuration eliminates the need for traditional UAS launch and recovery infrastructure. This paper describes the RBW-5 prototype, a 100-pound, dual 5-foot diameter proprotor demonstrator, and discusses the comprehensive evaluation of its design and operability through a combination of flight tests, wind tunnel experiments, and computational fluid dynamics (CFD) simulations. The results demonstrate the maturity of the UAS and highlights key accomplishments of the RBW-5 program, including successful autonomous takeoff and landing and transitions between hover and forward flight, the extraction of critical "blown-physics
ABSTRACT A simulation framework is essential for the development of a hybrid-electric tilt-wing aircraft such as Dufour Aerospace's Aero2 drone. The tilt-wing design with its complex interaction effects between the propellers and the aerodynamic surfaces presents unique modeling challenges, especially during early stages of development when only limited data is available. Furthermore, a delicate balance between accuracy and performance must be found while keeping complexity low to allow for rapid development. This paper introduces a modular design approach for a simulation framework, details the aero-propulsive models and shows ways to validate them using flight data and a system identification approach. By implementing models that capture all relevant effects, the framework helps building a deeper understanding for the dynamics of individual systems, serves as a basis for the design of the flight controller and offers capabilities for pilot training and hardware testing.
ABSTRACT This paper presents a multi-aircraft Markov decision process congestion game to resolve multi-aircraft near midair collisions (NMACs) for small unmanned aerial vehicles (sUAVs). Two key features of this framework are: 1) it leverages the concept of strategic equilibria from game theory to define optimality in multi-aircraft near midair encounters and 2) it extends the existing NMAC metrics to stochastic formulations via the occupancy measure of a Markov decision process. This game-theoretic approach decomposes the classically centralized air traffic control objective to multiple objectives that correspond to each aircraft within the NMAC, and as result, provides an aircraft-centric notion of optimality and safety that is well-suited for distributed conflict resolutions in multi-aircraft NMACs. In addition to modeling multi-aircraft as a game, stochastic metrics that extend the deterministic notions of NMACs are explored. The safety and optimality of the Nash equilibrium multi
ABSTRACT Precision flight in windy conditions is a common challenge for multirotor UAS. It is especially challenging for in contact tasks that require high-precision positioning and good disturbance rejection capabilities. Such tasks include landing on high-voltage powerlines for in-contact inspections. This paper presents the implementation of small lateral thrusters to improve the lateral position hold ability of a large power line inspection UAS in windy conditions. Arranged in antagonistic pairs on each side, the lateral thrusters handle the high-frequency but smaller-amplitude wind turbulence components with a frequency split control. Using an identified model of the UAS flight dynamics alongside flight data in high-wind conditions, a control architecture with a frequency split in the lateral axis was optimized to increase the disturbance rejection. Experimental tests showed a 67% reduction in lateral position error with the proposed approach in high-wind conditions.
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