Search Results (124)

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

Rotator cuff tears are common in individuals over 40, and physical therapy is often prescribed post-surgery. However, access can be limited by cost, convenience, and insurance coverage. CuffLink is a telehealth rehabilitation system that integrates the Strengthening and Stabilization System mechanical exerciser with the interACTION mobile health platform. The system includes a triple-axis accelerometer (LSM6DSOX + LIS3MDL FeatherWing), a rotary encoder, a VL530X time-of-flight sensor, and two wearable BioMech Health IMUs to capture upper-limb motion. CuffLink is designed to facilitate controlled, home-based exercise while enabling clinicians to remotely monitor joint function. Concurrent validity and test–retest reliability were used to assess device accuracy and repeatability. The results showed moderate to good validity for shoulder rotation (ICC = 0.81), device rotation (ICC = 0.94), and linear tracking (from zero: ICC = 0.75 and RMSE = 2.41; from start: ICC = 0.88 and RMSE = 2.02) and good reliability (e.g., RMSEs as low as 1.66 cm), with greater consistency in linear tracking compared to angular measures. Shoulder rotation and abduction exhibited higher variability in both validity and reliability measures. Future improvements will focus on manufacturability, signal stability, and force sensing. CuffLink supports accessible, data-driven rehabilitation and holds promise for advancing digital health in orthopedic recovery. 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

Complex air pollution, including particulate matter and ozone, is a significant environmental issue in China, with volatile organic compounds (VOCs) as key precursors. Traditional ground-based monitoring methods struggle to capture the vertical distribution and changes of pollutants in the troposphere. To address this, we developed a vertical monitoring and sampling platform using a quadcopter unmanned aerial vehicle (UAV). The platform, equipped with lightweight quartz sampling canisters and miniaturized sensors, collects air samples for VOC analysis and vertical data on meteorological parameters and particulate matter. Performance tests showed the quartz canisters had less than 15% adsorption loss, with sample storage stability exceeding 80% over three days. Sensor data showed strong correlations with standard instruments (R² > 0.80). Computational fluid dynamics simulations optimized the sampler’s inlet position and ascertained that ascending flight mitigates rotor-induced air recirculation. Field campaigns were conducted at six sites along the Chengdu Metropolitan Circle Ring Expressway. Vertical data from 0~300 m revealed particulate matter concentrations peaked at 50~70 m. Near-surface VOCs were dominated by alkanes, while aromatics were found concentrated at 150~250 m, indicating significant regional transport influences. The results confirmed the platform’s effectiveness for pollutant distribution analysis. 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

The energy consumption of rotary-wing unmanned aerial vehicles has become an important factor restricting their long-term application. This article focuses on decoupling the motion channel and reducing control energy consumption, and proposes a decoupling controller based on dynamic inversion for the complete dynamics of quadcopter unmanned aerial vehicles. Firstly, we design a direct closed-loop feedback controller for the z-channel to exhibit second-order linear dynamic characteristics with adjustable parameters. Then, the specific functions of pitch angle and yaw angle are combined as virtual control variables for the comprehensive decoupling design of the x-direction and y-direction, so that the x-channel and y-channel also exhibit independent parameter-adjustable second-order linear dynamic characteristics. Next, by solving the actual control variables, a fast convergence system is dynamically formed by the deviation between the virtual control variables and their actual values, ensuring that the specific function combination of pitch angle and yaw angle quickly converges to the expected value. Finally, the effectiveness and low energy consumption control characteristics of the decoupling control scheme were demonstrated through simulation comparison with other control methods (such as classical PID) in terms of energy consumption. 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

This study details the design and testing of a custom test rig for evaluating the performance of both open and shrouded rotors. The rig includes a two-axis load cell that is directly connected to the rotor to measure the rotor thrust separated from the total thrust when testing shrouded rotors and ensure accurate torque measurements, independent of external structural influences. Moreover, a main load cell is used to measure the total thrust for both configurations (open and shrouded rotor), as it is connected to the entire setup. Rotor RPM is monitored by capturing the voltage frequency from the BLDC motor, controlled using a Pololu Maestro Controller through the electronic speed controller. A shunt resistance is used to calculate the current through the electric Brushless Direct Current (BLDC) motor and by measuring the voltage, the electric power is calculated. By combining both mechanical and electrical power measurements, the BLDC motor’s efficiency is calculated. Automated data collection is conducted using National Instruments DAQ systems, with averaged measurements of thrust, torque, RPM, current, and voltage. Two rotors are tested to obtain performance data for both open and shrouded configurations. Additionally, a computational study is carried out to account for the aerodynamic effects of the rig’s structural elements. Uncertainty analysis is employed to assess the reliability of the experimental results by quantifying the numerical errors associated with both random and systematic errors encountered during the rotor’s performance evaluation. Full article

Picking fruits from tall fruit trees manually is laborious and inefficient. Rotary-wing drones, a low-altitude carrier platform, can enhance the picking efficiency for tall fruit trees when combined with picking robotic arms. However, during the operation of rotary-wing drones, the wind field changes dramatically, and the center of gravity of the drone shifts at the moment of picking, leading to poor aerodynamic stability and making it difficult to achieve optimized attitude control. To address the aforementioned issues, this paper constructs a drone and wind field testing platform and employs the Lattice Boltzmann Method and Large Eddy Simulation (LBM-LES) algorithm to solve the high-dynamic, rapidly changing airflow field during the transient picking process of the drone. The aerodynamic structure of the drone is optimized by altering the rotor spacing and duct intake ratio of the harvesting drone. The simulation results indicate that the interaction of airflow between the drone’s rotors significantly affects the stability of the aerodynamic structure. When the rotor spacing is 2.8R and the duct ratio is 1.20, the lift coefficient is increased by 11% compared to the original structure. The test results from the drone and wind field experimental platform show that the rise time ($t_r$) of the drone is shortened by 0.3 s, the maximum peak time ($t_p$) is reduced by 0.35 s, and the adjustment time ($t_s$) is accelerated by 0.4 s. This paper, by studying the transient wind field of the harvesting drone, clarifies the randomness of the transient wind field and its complex vortex structures, optimizes the aerodynamic structure of the harvesting drone, and enhances its aerodynamic stability. The research findings can provide a reference for the aerodynamic optimization of other types of drones. 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