Search Results (69)

In the process of plant protection for fruit trees using rotary-wing UAVs, challenges such as droplet drift, insufficient canopy penetration, and low agrochemical utilization efficiency remain prominent. Among these, the uncertainty in the spatio-temporal distribution of downwash airflow is a key factor contributing to non-uniform droplet deposition and increased drift. To address this issue, we developed a wind field numerical simulation model based on an improved hierarchical leaf density model to clarify the spatio-temporal characteristics of downwash airflow, the scale of turbulence regions, and their effects on internal canopy airflow under varying flight altitudes and different rotor speeds. Field experiments were conducted in orchards to validate the accuracy of the model. Simulation results showed that the average error between the simulated and measured wind speeds inside the canopy was 8.4%, representing a 42.11% reduction compared to the non-hierarchical model and significantly improving the prediction accuracy. The coefficient of variation (CV) was 0.26 in the middle canopy layer and 0.29 in the lower layer, indicating a decreasing trend with an increasing canopy height. We systematically analyzed the variation in turbulence region scales under different flight conditions. This study provides theoretical support for optimizing UAV operation parameters to improve droplet deposition uniformity and enhance agrochemical utilization efficiency. Full article

The downwelling light sensor (DLS) is the industry-standard solution for generating UAV-based digital orthophoto maps (DOMs). Current mainstream DLS correction methods primarily rely on angle compensation. However, due to the temporal mismatch between the DLS sampling intervals and the exposure times of multispectral cameras, as well as external disturbances such as strong wind gusts and abrupt changes in flight attitude, DLS data often become unreliable, particularly at UAV turning points. Building upon traditional angle compensation methods, this study proposes an improved correction approach—FIM-DC (Fitting and Interpolation Model-based Data Correction)—specifically designed for data collection under clear-sky conditions and stable atmospheric illumination, with the goal of significantly enhancing the accuracy of reflectance retrieval. The method addresses three key issues: (1) field tests conducted in the Qingpu region show that FIM-DC markedly reduces the standard deviation of reflectance at tie points across multiple spectral bands and flight sessions, with the most substantial reduction from 15.07% to 0.58%; (2) it effectively mitigates inconsistencies in reflectance within image mosaics caused by anomalous DLS readings, thereby improving the uniformity of DOMs; and (3) FIM-DC accurately corrects the spectral curves of six land cover types in anomalous images, making them consistent with those from non-anomalous images. In summary, this study demonstrates that integrating FIM-DC into DLS data correction workflows for UAV-based multispectral imagery significantly enhances reflectance calculation accuracy and provides a robust solution for improving image quality under stable illumination conditions. Full article

In this paper, we study an unmanned aerial vehicle (UAV)-enabled maritime communication system, where a single rotary-wing UAV is dispatched to communicate with multiple moving vessel users. We formulate the energy efficiency optimization problem with a propulsion energy consumption model by jointly considering the UAV transmit power, flight trajectory, and flight velocity. The problem is a non-convex fractional programming problem, which makes it difficult to obtain the optimal solution. To solve this problem, we propose an efficient algorithm utilizing the successive convex approximation techniques and Dinkelbach (SCAD) algorithm. In particular, we divide the original problem into three involved sub-problems that can be solved by adopting alternate optimization. In order to satisfy the constraint of maximum UAV flight velocity, we obtain a modified flight trajectory by matching the UAV positions. Numerical results demonstrate the effectiveness of the proposed scheme which effectively improves the energy efficiency for UAV communication. Meanwhile, the SCAD shows an outstanding performance in terms of energy efficiency for a long-duration flight. Full article

A newly designed tilt-wing unmanned aerial vehicle (Tilt-wing UAV) requires a unified control strategy across rotary-wing, fixed-wing, and transition modes, introducing significant challenges. Existing control strategies typically rely on accurate modeling or extensive parameter tuning, which limits their adaptability to dynamically changing flight configurations. Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. To address this challenge, we propose Temporal Sequence Constrained Q-learning (TSCQ), an offline RL framework that integrates an encoder–decoder with recurrent networks to capture temporal dependencies. The policy is further constrained within an offline dataset collected via hardware-in-the-loop simulation using a variational autoencoder, and a sequence-level prediction mechanism is introduced to ensure temporal consistency across action trajectories, thereby mitigating extrapolation error while preserving data fidelity. Experimental results demonstrate that TSCQ significantly outperforms gain scheduling, Model Predictive Control (MPC), and Batch-Constrained Q-learning (BCQ), reducing the RMSE of pitch angle by up to 53.3% and vertical velocity RMSE by approximately 33%. These findings underscore the potential of data-driven, safety-aware offline RL paradigms to enable robust and generalizable control strategies for tilt-wing UAVs. Full article

This paper explores unconventional configurations of rotary-wing unmanned aerial vehicles (UAVs), focusing on designs that transcend the limitations of traditional ones. Through innovative rotor arrangements, refined airframe structures, and novel flight mechanisms, these advanced designs aim to significantly enhance performance, versatility, and functionality. Rotary-wing UAVs that deviate markedly from conventional models in terms of mechanical topology, aerodynamic principles, and movement modalities are rigorously examined. These unique UAVs are categorized into four distinct groups based on their mechanical configurations and dynamic characteristics: (1) UAVs with tilted or tiltable propellers, (2) UAVs featuring expanded mechanical structures, (3) UAVs with morphing multirotor capabilities, and (4) UAVs incorporating groundbreaking aerodynamic concepts. This classification establishes a structured framework for analyzing the advancements in these innovative designs. Finally, key challenges identified in the review are summarized, and corresponding research outlooks are derived to guide future development in rotary-wing drone technology. Full article

The Third Pole region contains vast glaciers, and changes in these glaciers profoundly affect the lives and development of billions of people. Therefore, accurate glacier monitoring in this region is of great scientific and practical significance. Unmanned Aerial Vehicles (UAVs) provide high-resolution observation capabilities and flexible deployment options, effectively overcoming certain limitations associated with traditional in situ and satellite remote sensing observations. Thus, UAV technology is increasingly gaining traction and application in the glaciology community. This review systematically analyzed studies involving UAV technology in Third Pole glaciology research and determined that relevant studies have been performed for a decade (2014–2024). Notably, after 2020, the number of relevant manuscripts has increased significantly. Research activities are biased toward the use of rotary-wing UAVs (63%) and ground control point (GCP) correction methods (67%). Additionally, there is strong emphasis on analyzing glacier surface elevation, surface velocity, and landform evolution. These activities are primarily concentrated in the Himalayan region, with relatively less research being conducted in the western and central areas. UAV technology has significantly contributed to glaciology research in the Third Pole region and holds great potential to enhance the monitoring capabilities in future studies. Full article

Quad-tilt-wing (QTW) Unpiloted Aerial Vehicles (UAVs) combine the vertical takeoff and landing capabilities of rotary-wing designs with the high-speed, long-range performance of fixed-wing aircraft, offering significant advantages in both civil and military applications. The unique configuration of QTW UAVs presents complex control challenges due to nonlinear dynamics, strong coupling between translational and rotational motions, and significant variations in aerodynamic characteristics during transitions between flight modes. To address these challenges, this study develops an optimal control framework tailored for real-time operations. A State-Dependent Riccati Equation (SDRE) approach is employed for attitude control, addressing nonlinearities, while a Linear Quadratic Regulator (LQR) is used for position and velocity control to achieve robustness and optimal performance. By integrating these strategies and utilizing the inverse dynamics approach, the proposed control system ensures stable and efficient operation. This work provides a solution to the optimal control complexities of QTW UAVs, advancing their applicability in demanding and dynamic operational environments. Full article

The hybrid unmanned aerial vehicle combines the vertical take-off and landing and hover abilities of rotary-wing UAVs with the high-speed cruise and long-endurance capabilities of fixed-wing UAVs, expanding the flight envelope and application areas. The designed controller must handle the highly nonlinear dynamics and variable actuators resulting from this combination. Furthermore, the performance of the controller is also influenced by uncertainties in model parameters and external disturbances. To address these issues, a unified robust disturbance rejection control based on fixed-time stability theory is proposed for attitude control. A fixed-time disturbance observer is utilized to estimate composite disturbances without some strict assumptions. Based on this observer, a nonsingular chattering-free fixed-time integral sliding mode control law is introduced to ensure that tracking errors converge to the origin within a fixed time. In addition, an optimized control allocator based on the weighted least squares method is designed to handle the overactuation of a dual-system hybrid UAV. Finally, numerical simulations and hardware-in-the-loop experiments under different flight modes and disturbance conditions are carried out, and compared with nonlinear dynamic inverse and the nonsingular terminal sliding mode control based on a finite-time observer, the developed controller enhances attitude angle tracking accuracy and disturbance rejection performance. Full article

Hover-capable unmanned aerial vehicles (UAVs), including rotary-wing UAVs such as unmanned helicopters, multi-rotor drones, and tilt-rotor UAVs, are widely employed due to their hovering capabilities. In recent years, tilt-rotor aircraft, which offer both vertical takeoff and landing as well as rapid maneuverability, have increasingly become a research focus. This paper first proposes a design concept for a flying-wing configuration tilt-rotor tri-rotor UAV, detailing the selection of airfoils and the calculation of aerodynamic parameters. To address the specific operational requirements and flight characteristics of this UAV, a specialized tilting mechanism was developed, and a flight control system was designed and implemented using classical PID control methods. Finally, a prototype of the tilt-rotor tri-rotor UAV was fabricated and subjected to flight tests. The results from both simulations and flight tests confirmed that the UAV met the design performance criteria and that the control method was effective. Full article

The development of unconventional and hybrid unoccupied aerial vehicles (UAVs) has gained significant momentum in recent years, with many designs utilizing small fans or rotary blades for vertical take-off and landing (VTOL). However, these systems often inherit the limitations of traditional helicopter rotors, including susceptibility to aerodynamic inefficiencies and mechanical issues. Additionally, achieving a seamless transition from VTOL to fixed-wing flight mode remains a significant challenge for hybrid UAVs. A novel approach is the reciprocating airfoil (RA) or reciprocating wing (RW) VTOL aircraft, which employs a fixed-wing configuration driven by a reciprocating mechanism to generate lift. The RA wing is uniquely designed to mimic a fixed-wing while leveraging its reciprocating motion for efficient lift production and a smooth transition between VTOL and forward flight. Despite its advantages, the RA wing endures substantial stress due to the high inertial forces involved in its operation. This study presents an optimized structural design of the RA wing through wing topology optimization and finite element analysis (FEA) to enhance its load-bearing capacity and stress performance. A comparative analysis with existing RA wing configurations at maximum operating velocities highlights significant improvements in the safety margin, failure criteria, and overall stress distribution. The key results of this study show an 80.4% reduction in deformation, a 43.8% reduction in stress, and a 78% improvement in safety margin. The results underscore the RA wing’s potential as an effective and structurally stable lift mechanism for RA-driven VTOL aircraft, demonstrating its capability to enhance the performance and reliability of next-generation UAVs. Full article

Geophysical surveys, a means of analyzing the Earth and its environments, have traditionally relied on ground-based methodologies. However, up-to-date approaches encompass remote sensing (RS) techniques, employing both spaceborne and airborne platforms. The emergence of Unmanned Aerial Vehicles (UAVs) has notably catalyzed interest in UAV-borne geophysical RS. The objective of this study is to comprehensively review the state-of-the-art UAV-based geophysical methods, encompassing magnetometry, gravimetry, gamma-ray spectrometry/radiometry, electromagnetic (EM) surveys, ground penetrating radar (GPR), traditional UAV RS methods (i.e., photogrammetry and LiDARgrammetry), and integrated approaches. Each method is scrutinized concerning essential aspects such as sensors, platforms, challenges, applications, etc. Drawing upon an extensive systematic review of over 435 scholarly works, our analysis reveals the versatility of these systems, which ranges from geophysical development to applications over various geoscientific domains. Among the UAV platforms, rotary-wing multirotors were the most used (64%), followed by fixed-wing UAVs (27%). Unmanned helicopters and airships comprise the remaining 9%. In terms of sensors and methods, imaging-based methods and magnetometry were the most prevalent, which accounted for 35% and 27% of the research, respectively. Other methods had a more balanced representation (6–11%). From an application perspective, the primary use of UAVs in geoscience included soil mapping (19.6%), landslide/subsidence mapping (17.2%), and near-surface object detection (13.5%). The reviewed studies consistently highlight the advantages of UAV RS in geophysical surveys. UAV geophysical RS effectively balances the benefits of ground-based and traditional RS methods regarding cost, resolution, accuracy, and other factors. Integrating multiple sensors on a single platform and fusion of multi-source data enhance efficiency in geoscientific analysis. However, implementing geophysical methods on UAVs poses challenges, prompting ongoing research and development efforts worldwide to find optimal solutions from both hardware and software perspectives. Full article

As a fundamental part of water management, water sampling treatments have recently been integrated into unmanned aerial vehicle (UAV) technologies and offer eco-friendly, cost-effective, and time-saving solutions while reducing the necessity for qualified staff. However, the majority of applications have been conducted with rotary-wing configurations, which lack range and sampling capacity (i.e., payload), leading scientists to search for alternative designs or special configurations to enable more comprehensive water assessments. Hence, in this paper, the conceptual design of a novel long-range and high-capacity WIGE UAV capable of autonomous water sampling is presented in detail. The design process included a vortex lattice solver for aerodynamic investigations, while analytical and empirical methods were used for weight and dimensional estimations. Since the mission involved operation inside maritime traffic, potential obstacle avoidance scenarios were discussed in terms of operational safety, and the aim was for autonomous trajectory tracking performance to be improved by means of a stochastic optimization algorithm. For this purpose, an artificial intelligence-integrated concurrent engineering approach was applied for autonomous control system design and flight altitude determination, simultaneously. During the optimization, the stability and control derivatives of the constituted longitudinal and lateral aircraft dynamic models were predicted via a trained artificial neural network (ANN). The optimization results exhibited an aerodynamic performance enhancement of 3.92%, and a remarkable improvement in trajectory tracking performance for both the fly-over and maneuver obstacle avoidance modes, by 89.9% and 19.66%, respectively. Full article

This paper considers a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV). By tilting its propellers, the aircraft can transition from rotary-wing (RW) multirotor mode to fixed-wing (FW) mode and vice versa. A novel architecture of a neural network-based controller (NNC) is presented. An “imitative learning” approach is employed to train the NNC to mimic the response of an expert but computationally expensive model predictive controller (MPC). The resulting NNC approximates the MPC’s solution while significantly decreasing the computational cost. The NNC is trained on the longitudinal axis. Successful simulations and real flight tests prove that the NNC is suitable for the longitudinal axis control of a complex nonlinear system such as the tilt-rotor VTOL UAV through a sequence of transitions between the RW mode to the FW mode, and vice versa, in a forward flight. Full article

The atmospheric boundary layer is a crucial transitional region connecting the surface with the free atmosphere, playing a bridging role in land-sea-air interactions and the interactions between different atmospheric layers. This study utilizes rotary-wing UAVs, high-resolution lidar, and WRF simulation data to analyze the vertical distribution characteristics of temperature, humidity, wind speed, and wind direction boundary layer over the Mount Si’e region in 4–6 April 2024. The results indicate that the boundary layer temperature decreases with increasing altitude, reaching up to 18°C, while humidity decreases with height, dropping to as low as 35%. Daytime wind speeds range from 4 to 8 m/s, decreasing to 2 to 4 m/s at night. The boundary layer height can reach up to 900 m during the day and drops to 100–200 m at night, showing distinct diurnal variation characteristics. UAV observations are in good agreement with lidar and WRF simulation results, highlighting the application value of UAVs in high temporal and spatial resolution boundary layer studies. The study also reveals the significant impact of complex terrain on boundary layer characteristics, providing scientific insights into the dynamic and thermal processes of the boundary layer and offering reference value for improving regional weather forecasting and numerical simulations. Full article

Tilt-duct Unmanned Aerial Vehicles (UAV) combine the high-speed efficiency of fixed-wing aircrafts with vertical takeoff and landing (VTOL) and the hover capabilities of rotary-wing aircrafts while maximizing the advantages of ducted fans in terms of noise reduction, efficiency, and safety, making it a pivotal direction for the future of aviation such as urban air mobility. This paper concentrates on the design and optimization of the primary structures of a laboratory-designed reference tilt-duct UAV. Firstly, the general data of the reference tilt-duct UAV are presented. According to the load conditions, the overall structural layout design for the wing, fuselage, and empennage is carried out, where special attention has been paid to account for the requirements of VTOL/hover and cruise flight modes. Based on the structural layout, finite element models (FEM) are established and static analyses are performed. The results indicate that the design can fulfill the structural requirements during a flight mission. Furthermore, based on the Method of Feasible Directions (MFD) algorithm, we have carried out the optimization of the composite wing box that incorporates manufacturing constraints. Via optimization, the total mass of the wing box is reduced by 38.6%, i.e., from 3.73 kg to 2.29 kg. The results indicate that the combination of composite materials with a tilt-duct configuration holds significant potential for future high-efficiency and environmentally friendly aviation. Full article