Search Results (30)

This study introduces a novel, drone-based approach for the detection and classification of Greater Caribbean Manatees (Trichechus manatus manatus) in the Panama Canal Basin by integrating advanced deep learning techniques. Leveraging the high-performance YOLOv8 model augmented with Sliced Aided Hyper Inferencing (SAHI) for improved small-object detection, our system accurately identifies individual manatees, mother–calf pairs, and group formations across a challenging aquatic environment. Additionally, the use of AltCLIP for zero-shot classification enables robust demographic analysis without extensive labeled data, enhancing model adaptability in data-scarce scenarios. For this study, more than 57,000 UAV images were acquired from multiple drone flights covering diverse regions of Gatun Lake and its surroundings. In cross-validation experiments, the detection model achieved precision levels as high as 93% and mean average precision (mAP) values exceeding 90% under ideal conditions. However, testing on unseen data revealed a lower recall, highlighting challenges in detecting manatees under variable altitudes and adverse lighting conditions. Furthermore, the integrated zero-shot classification approach demonstrated a robust top-2 accuracy close to 90%, effectively categorizing manatee demographic groupings despite overlapping visual features. This work presents a deep learning framework integrated with UAV technology, offering a scalable, non-invasive solution for real-time wildlife monitoring. By enabling precise detection and classification, it lays the foundation for enhanced habitat assessments and more effective conservation planning in similar tropical wetland ecosystems. Full article

This study examines the aerodynamic performance of a joined-wing (JW) aircraft design based on the NASA Common Research Model (CRM), aiming to assess its potential for efficient commercial transport or cargo aircraft at transonic speed (Mach 0.85). The CRM wing, optimised for transonic flight, was transformed into a JW design featuring a high-aspect-ratio main wing. An initial parametric study using the vortex lattice minimum drag panel method identified viable designs. The selected JW configuration, comprising front and rear wings joined by a vertical fin, was analysed using ANSYS Fluent to understand flow interactions and aerodynamic performance. At an angle of attack (AoA) of −1°, the JW design achieved a peak lift-to-drag ratio (L/D) of 17.45, close to the CRM’s peak L/D of 19.64 at 2°, demonstrating competitive efficiency. The JW’s L/D exceeded the CRM’s between AoA −3° and 0.8°, but the CRM performed better above 0.8°, with differences decreasing at a higher AoA. Based on induced drag alone, the JW outperformed the CRM across AoA −3° to 8°, but flow complications restricted its L/D advantage to a small, low AoA range. A strong shock on the vertical fin’s inboard side due to high incoming flow speed delayed shock formation on the main wing near the joint. Optimising the vertical fin shape slightly improved L/D, suggesting potential for further enhancements or that other design factors significantly affect JW performance. This study provides insights into JW aerodynamics at transonic speeds, revealing its potential benefits and challenges compared to the CRM design. Full article

In recent years, unmanned aerial vehicle (UAV) formation flight has become an effective strategy for urban air mobility (UAM). However, close rotor separation during formation flight leads to complex aerodynamic interference between rotors, significantly affecting UAV flight performance and operational safety. This study systematically examines the effects of axial and lateral rotor separation on the rotor’s thrust performance through wind tunnel experiments. The tests simulate horizontal, vertical, and hovering states by generating relative airflow in the wind tunnel, focusing primarily on the thrust coefficient changes of the bottom rotor at various separations. The results are compared with a single rotor operating under the same conditions without wake interference. Additionally, computational fluid dynamics (CFD) simulations using the Fluent software were conducted to investigate the effect of wake interactions by analyzing the velocity flow field between the two rotors in different separations. Both the experimental and simulation results demonstrate that rotor aerodynamic performance is notably influenced by wake interactions. Under hovering and vertical states, substantial aerodynamic interference occurs in the region directly beneath the top rotor, within 1D ≤ $Z$ ≤ 3D. This interference gradually diminishes as the rotor separation increases. Additionally, the thrust coefficient of the bottom rotor decreases with increasing flight speed due to the wake, and at higher flight speeds, the wake tends to contract. When the lateral separation is X = 0D, the mid-sectional flow field of the two rotors exhibits symmetry; however, with lateral separation, the symmetry of the bottom rotor’s wake velocity field is disrupted. During the horizontal flight, the rotor wake tilts backward due to the relative airflow, and the extent of this influence is governed by both rotor rotational speed and flight velocity. Therefore, when UAVs operate in formation, it is crucial to account for these factors affecting aerodynamic performance, and rotor separation must be optimized to enhance flight safety and efficiency. Full article

The aerodynamic behavior of a square-shaped formation of four quadcopter UAVs flying in a swarm is investigated in detail through three-dimensional computer simulations utilizing Computational Fluid Dynamics (CFD) methodology. The swarm configuration comprises four UAVs positioned with two in the upper row and two in the lower row along the same propeller axes. The flow profile generated by the UAV propellers rotating at 10,000 revolutions per minute is analyzed parametrically using the Multiple Reference Frame (MRF) technique. UAVs within the swarm are positioned at 75 cm from the motion centers of adjacent propellers. This distance, the effects of horizontally and vertically positioned UAVs on each other, and the collective behavior of the swarm are thoroughly examined. Pressure, velocity, and turbulent kinetic energy values are meticulously analyzed. This research represents a milestone in understanding the aerodynamic characteristics of UAV swarms and the optimization of swarm performance. The findings highlight effective factors in swarm flights and their consequences for UAVs. Additionally, the article describes the “near-UAV phenomenon”. Furthermore, the methodology developed for CFD simulations provides an approach to analyzing close flight scenarios and evaluating their performance in various swarm configurations. These achievements contribute to the future development of UAV technology. Full article

Unmanned aerial vehicles (UAVs) equipped with magnetic airborne detectors (MADs) represent a new combination for underground or undersea magnetic anomaly detection. The electromagnetic interference (EMI) generated by a UAV platform affects the acquisition of weak magnetic signals by the MADs, which brings unique conceptual design difficulties. This paper proposes a systematic and integrated low-EMI design method for small, fixed-wing UAVs. First, the EMI at the MAD is analyzed. Second, sensor layout optimization for a single UAV is carried out, and the criteria for the sensor layout are given. To enhance UAV stability and resist atmospheric disturbances at sea, the configuration is optimized using an improved genetic algorithm. Then, three typical multi-UAV formations are analyzed. Finally, the trajectory is designed based on an analysis of its influence on EMI at the MAD. The simulation results show that the low-EMI design can keep MADs away from the EMI sources of UAVs and maintain flight stability. The thread-like formation is the best choice in terms of mutual interference and search width. The results also reveal the close relationship between the low-EMI design and flight trajectory. This research can provide a reference for the conceptual design and trajectory optimization of small, fixed-wing UAVs for magnetic anomaly detection. Full article

This paper presents a close-formation flight of two unmanned aerial vehicles (UAVs) and the aim of the study is to improve the understanding of the vortex effects between fixed-wing UAVs in a swarm using computational fluid dynamics (CFD) tools. To validate the numerical method, results of a variable-density wind tunnel test from the literature were used. This numerical CFD analysis was used to determine the lift coefficient (C_L) and the drag coefficient (C_D) values for a single UAV at various angles of attack. When examining the aerodynamic impact areas behind the UAV, the longitudinal distance between the two UAVs is not particularly effective for close flight. Therefore, CFD analyses were carried out on the two UAVs for both vertical and lateral distances. The optimum position for close-formation flight was identified using C_L/C_D ratios. The results of the analysis indicate that the most effective flights, across all lateral positions, occur when the two UAVs are vertically at the same height. In terms of aerodynamic efficiency, the most effective points for close-formation flight for wingspan b are at lateral distances of 0.875 b and 1 b. At these positions, flight efficiency can be increased by approximately 11.5%. Full article

This paper investigates the target fencing control problem of fixed-wing Unmanned Aerial Vehicle (UAV) swarms with collision avoidance and connectivity maintenance in obstacle environments. A distributed cooperative fencing scheme for maneuvering targets is proposed without predefined accurate formation. Firstly, considering that not all states of the target can be obtained by UAVs, a differential state observer is developed to estimate the target’s unknown speed and control input. Secondly, by constructing potential functions with fewer parameter adjustments, corresponding negative gradient terms are calculated to guarantee the flight safety and communication connectivity of the swarm. A distributed cooperative controller is designed using the self-organized theory and consensus control. Additionally, the stability of the closed-loop system with the controller is analyzed based on Lyapunov stability theory. Finally, numerical simulations are performed to illustrate the effectiveness of the proposed scheme. Full article

The non-contact close-proximity formation satellite (NCCPFS) is one of the technical solutions to improve the attitude performance, consisting of a payload module (PM) and a support module (SM). The non-contact Lorentz actuator (NCLA), as the core components of the NCCPFS, directly affect the attitude control performance of the entire satellite. In order to ensure the ultra-high attitude pointing performance and stability of the PM, an in-flight calibration method for the NCLAs based on minimum model error (MME) algorithm and Kalman filtering (KF) with cooperative control strategy is proposed in this article. In this method, the NCLAs generate a periodic nominal torque that causes the attitude of the PM to be periodically deflected. This periodic torque also reacts on the SM, and the SM counteracts this periodic torque through the flywheel to realize the cooperative tracking relative to the PM. Then, the gyroscope data are substituted into the MME algorithm to obtain the angular acceleration of the two modules, and the KF algorithm is adopted to observe the actual output torque of the NCLAs to complete the in-flight calibration of the NCLAs. Numerical simulation results show that the accuracy of the proposed calibration algorithm can reach about 8%, which proves the effectiveness of the proposed method. Full article

The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously. Full article

Formation path planning is a significant cornerstone for unmanned aerial vehicle (UAV) swarm intelligence. Previous methods were not suitable for large-scale UAV formation, which suffered from poor formation maintenance and low planning efficiency. To this end, this paper proposes a novel millisecond-level path planning method appropriate for large-scale fixed-wing UAV formation, which consists of two parts. Instead of directly planning paths independently for each UAV in the formation, the proposed method first introduces a formation control strategy. It controls the chaotic UAV swarm to move as a single rigid body, so that only one planning can obtain the feasible path of the entire formation. Then, a computationally lightweight Dubins path generation method with a closed-form expression is employed to plan feasible paths for the formation. During flight, the aforementioned formation control strategy maintains the geometric features of the formation and avoids internal collisions within the formation. Finally, the effectiveness of the proposed framework is exemplified through several simulations. The results show that the proposed method can not only achieve millisecond-level path planning for the entire formation but also excellently maintain formation during the flight. Furthermore, simple formation obstacle avoidance in a special case also highlights the application potential of the proposed method. Full article

This paper investigates a practical time-varying formation control method for quadrotors subjected to disturbances, uncertainties, and switching-directed topologies. A fully distributed formation control scheme is proposed using a linear-velocity independent position controller (LVIPC) and a nonsingular terminal sliding mode attitude controller (NTSMAC). A distributed observer is adopted to eliminate the measurement of linear-velocity states, and only local neighbor states are needed to realize formation flight. A time-varying nonsingular terminal sliding mode manifold is designed to suppress the reaching phase and ensure the finite-time convergence. Adaptive estimators are employed to remove the reliance on the prior knowledge of the upper bound of lumped uncertainties. It is then proven that all the closed-loop signals are bounded under the proposed method. Comparative experimental results based on a practical outdoor hardware solution are presented to confirm the effectiveness of the suggested control algorithm. Full article

Imagery from Unmanned Aerial Vehicles can be used to generate three-dimensional (3D) point cloud models. However, final data quality is impacted by the flight altitude, camera angle, overlap rate, and data processing strategies. Typically, both overview images and redundant close-range images are collected, which significantly increases the data collection and processing time. To investigate the relationship between input resources and output quality, a suite of seven metrics is proposed including total points, average point density, uniformity, yield rate, coverage, geometry accuracy, and time efficiency. When applied in the field to a full-scale structure, the UAV altitude and camera angle most strongly affected data density and uniformity. A 66% overlapping was needed for successful 3D reconstruction. Conducting multiple flight paths improved local geometric accuracy better than increasing the overlapping rate. The highest coverage was achieved at 77% due to the formation of semi-irregular gridded gaps between point groups as an artefact of the Structure from Motion process. No single set of flight parameters was optimal for every data collection goal. Hence, understanding flight path parameter impacts is crucial to optimal UAV data collection. Full article

Flow behavior and aerodynamic performance of a small-scale joined-wing unmanned aerial vehicle (UAV) was studied experimentally and numerically under various pitch and yaw angle combinations in subsonic flow conditions. Selected numerical results are compared against experimental results obtained using surface oil flow visualizations and force measurements, with additional simulations expanding the range of combined pitch and yaw configurations. Under zero-yaw conditions, increasing the pitch angle leads to the formation of symmetric ogive vortex roll-ups close to the fuselage and their significant interactions with the fore-wing. Additionally, contributions to lift and drag coefficients under zero-yaw conditions by the key UAV components have been documented in detail. In contrast, when the UAV is subjected to combined pitch and yaw, no clear evidence of such ogive vortex roll-ups can be observed. Instead, asymmetric flow separations occur over the fuselage’s port side and resemble bluff-body flow behavior. Additionally, these flow separations become more complex, and they interact more with the fuselage and fore- and aft-wings when the yaw angle increases. Lift and drag variations due to different pitch and yaw angle combinations are also documented. Finally, rolling and yawing moment results suggest that the present UAV possesses adequate flight stability unless the pitch and yaw angles are high. Full article

This paper designs a robust close-formation control system with dynamic estimation and compensation to advance unmanned aerial vehicle (UAV) close-formation flights to an engineer-implementation level. To characterize the wake vortex effect and analyze the sweet spot, a continuous horseshoe vortex method with high estimation accuracy is employed to model the wake vortex. The close-formation control system will be implemented in the trailing UAV to steer it to the sweet spot and hold its position. Considering the dynamic characteristics of the trailing UAV, the designed control system is divided into three control subsystems for the longitudinal, altitude, and lateral channels. Using linear active-disturbance rejection control (LADRC), the control subsystem of each channel is composed of two cascaded first-order LADRC controllers. One is responsible for the outer-loop position control and the other is used to stabilize the inner-loop attitude. This control system scheme can significantly reduce the coupling effects between channels and effectively suppress the transmission of disturbances caused by the wake vortex effect. Due to the cascade structure of the control subsystem, the correlation among the control parameters is very high. Therefore, sine-powered pigeon-inspired optimization is proposed to optimize the control parameters for the control subsystem of each channel. The simulation results for two UAV close formations show that the designed control system can achieve stable and robust dynamic performance within the expected error range to maximize the aerodynamic benefits for a trailing UAV. Full article

Hop-derived volatile organic compounds (VOCs) and their transformation products significantly impact beer flavour and aroma. Geraniol, a key monoterpene alcohol in hops, has been reported to undergo yeast-modulated biotransformation into various terpenoids during fermentation, which impacts the citrus and floral aromas of the finished beer. This study monitored the evolution of geraniol and its transformation products throughout fermentation to provide insight into differences as a function of yeast species and strain. The headspace concentration of VOCs produced during fermentation in model wort was measured using Solid-Phase Microextraction Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS). In the absence of yeast, only geraniol was detected, and no terpenoid compounds were detected in geraniol-free ferments. During fermentation, the depletion of geraniol was closely followed by the detection of citronellol, citronellyl acetate and geranyl acetate. The concentration of the products and formation behaviour was yeast strain dependent. SPME-GC/MS provided confidence in compound identification. PTR-ToF-MS allowed online monitoring of these transformation products, showing when formation differed between Saccharomyces cerevisiae and Saccharomyces pastorianus yeasts. A better understanding of the ability of different yeast to biotransform hop terpenes will help brewers predict, control, and optimize the aroma of the finished beer. Full article