Search Results (42)

This paper investigates the energy efficiency and positional stability of two types of ultralight unmanned aerial vehicles (UAVs)—bicopter and quadcopter—both with mass below 250 g, under varying flight conditions. The study is motivated by increasing interest in low-weight drones due to their regulatory flexibility and application potential in constrained environments. A comparative methodology was adopted, involving the construction of both UAV types using identical components where possible, including motors, sensors, and power supply, differing only in propulsion configuration. Experimental tests were conducted in wind-free and wind-induced environments to assess power consumption and stability. The data were collected through onboard blackbox logging, and positional deviation was tracked via video analysis. Results show that while the quadcopter consistently demonstrated lower energy consumption (by 6–22%) and higher positional stability, the bicopter offered advantages in simplicity of frame design and reduced component count. However, the bicopter required extensive manual tuning of PID parameters due to the inherent instability introduced by servo-based control. The findings highlight the potential of bicopters in constrained applications, though they emphasize the need for precise control strategies and high-performance servos. The study fills a gap in empirical analysis of energy consumption in lightweight bicopter UAVs. Full article

This study investigates the electromagnetic performance of two carbon fiber monopole antennas integrated into a UAV copter frame, with emphasis on design adaptation, impedance matching, and propagation behavior. A comprehensive experimental campaign was conducted to characterize key parameters such as center frequency, bandwidth, gain, VSWR, and S₁₁. Both antennas exhibited dual-band resonance at approximately 381 MHz and 1.19 GHz, each achieving a 500 MHz bandwidth where VSWR ≤ 2. The modified antenna achieved a minimum reflection coefficient of –14.6 dB and a VSWR of 1.95 at 381.45 MHz, closely aligning with theoretical predictions. Gain deviations between measured (0.15–0.19 dBi) and calculated (0.19 dBi) values remained within 0.04 dB, while received power fluctuations did not exceed 1.3 dB under standard test conditions despite the composite material’s finite conductivity. Free-space link-budget tests at 0.5 m and 2 m of separation revealed received-power deviations of 0.9 dB and 1.3 dB, respectively, corroborating the Friis model. Radiation pattern measurements in both azimuth and elevation planes confirmed good directional behavior, with minor side lobe variations, where Antenna A displayed variations between 270° and 330° in azimuth, while Antenna B remained more uniform. A 90° polarization mismatch led to a 15 dBm signal drop, and environmental obstructions caused losses of 9.4 dB, 12.6 dB, and 18.3 dB, respectively, demonstrating the system’s sensitivity to alignment and surroundings. Additionally, signal strength changes observed in a Two-Ray propagation setup validated the importance of ground reflection effects. Small-scale fading analysis at 5 m LOS indicated a Rician-distributed envelope with mean attenuation of 53.96 dB, σ_dB = 5.57 dB, and a two-sigma interval spanning 42.82 dB to 65.11 dB; the fitted K-factor confirmed the dominance of the LOS component. The findings confirm that carbon fiber UAV frames can serve as effective directional antenna supports, providing proper alignment and tuning. These results support the future integration of lightweight, structure-embedded antennas in UAV systems, with potential benefits in communication efficiency, stealth, and design simplification. Full article

The motion of a copter with a suspended payload in a vertical plane is considered. The payload has a spherical shape and contains a concentric spherical cavity partially filled with ideal liquid. The system is subjected to horizontal stationary wind. The aerodynamic load on the payload is described within the framework of a quasi-steady approach. The dynamics of the liquid are simulated using the phenomenological pendulum model. The points of this study are the controllability and observability of a stationary flight of a copter with the payload. A control strategy is proposed, which aims to bring the system from a certain initial state to a certain final state, such that the center of mass of the copter moves along a given sufficiently smooth curve. The control is designed to ensure the suppression of oscillations of the payload and the liquid along the entire trajectory. 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 light composite rotor blades with acceptable load carrying capacity is an essential issue to be dealt with in the design of relatively large copter-type drones. In this paper, a method is established to determine the quasi-static blade load carrying capacity which is vital to drone reliability. The proposed method, which provides a systematic procedure to determine blade load carrying capacity, consists of three parts, namely, a procedure to determine the distributed quasi-static blade aerodynamic load via the Blade Element Momentum (BEM) approach, a finite element-based failure analysis method to identify the actual blade failure mode, and an optimization method to determine the actual blade load carrying capacity. The experimental failure characteristics (failure mode, failure thrust, failure location) of two types of composite sandwich rotor blades with different skin lamination arrangements have been used to verify the accuracy of the theoretical results obtained using the proposed load carrying capacity determination method. The skin lamination arrangement for attaining the optimal blade-specific load carrying capacity and the blade incipient rotational speed for safe drone operation has been determined using the proposed method. Full article

Enhancements to the analytical method for the determination of tricyclazole in rice samples have been applied to monitor residues during unmanned aerial spraying. The acetonitrile extraction technique QuEChERS was improved by the incorporation of ethyl acetate and 0.1% formic acid, which significantly elevated the recovery rates. Furthermore, the purification process was refined by integrating both primary–secondary amine (PSA) and C18 in the dSPE method, achieving a substantial improvement in reducing matrix effects (MEs) and increasing recovery efficiency. The optimized method demonstrated an impressive % ME value at −3.1%, with a limit of quantitation (LOQ) established at 0.01 mg/kg, and recovery rates between 94.7 and 95.6% at 0.01, 0.1, and 2 mg/kg. Using two types of adjuvants (stickers) during multi-copter spraying markedly improved the initial tricyclazole deposition on rice panicles, with residue levels initially increasing from 0.35 mg/kg to between 0.68 and 1.60 mg/kg. Residues in hulled rice at harvest (10 days post-application) remained well below the maximum residue limit (MRL) of 0.7 mg/kg, ranging from 0.02 to 0.11 mg/kg, thus affirming the safety and efficacy of adjuvants in residue management. Full article

Marine aerosol particles can act as cloud condensation nuclei and influence the atmospheric boundary layer by scattering solar radiation. The interaction of ocean waves and coral reefs may affect the distribution and size of marine aerosol particles. Measuring this effect has proven challenging. Here, we tested the hypothesis that the distribution and size of marine aerosol particles would vary over three distinct zones (i.e., coral lagoon, surf break, and open water) near One Tree Island in the Great Barrier Reef, which is approximately 85 km off the east coast of Australia. We used a modified DJI Agras T30 drone fitted with a miniaturised scanning electrical mobility sizer and advanced mixing condensation particle counter to collect data on aerosol size distribution between 30 and 300 nm at 20 m above the water surface. We conducted 30 flights over ten days during the Austral summer/autumn of 2023. The fitted bimodal lognormal curves indicate that the number concentrations for aerosols below 85 nm diameter are more than 16% higher over the lagoon than over open water. The average mean mode diameters remained constant across the different zones, indicating no significant influence of breaking waves on the detected aerosol size modes. The most influential explanatory variable for aerosol size distribution was the difference between air temperature and the underlying sea surface, explaining around 40% of the variability. Salinity also exhibited a significant influence, explaining around 12% of the measured variability in the number concentration of aerosols throughout the campaign. A calculated wind stress magnitude did not reveal significant variation in the measured marine aerosol concentrations. Overall, our drone-based aerosol measurements near the water surface effectively characterise the dynamics of background marine aerosols around One Tree Island Reef, illustrating the value of drone-based systems for providing size-dependent aerosol information in difficult-to-access and environmentally sensitive areas. Full article

This paper presents an overview on the state of the art in copter drones and their components. It starts by providing an introduction to unmanned aerial vehicles in general, describing their main types, and then shifts its focus mostly to multirotor drones as the most attractive for individual and research use. This paper analyzes various multirotor drone types, their construction, typical areas of implementation, and technology used underneath their construction. Finally, it looks at current challenges and future directions in drone system development, emerging technologies, and future research topics in the area. This paper concludes by highlighting some key challenges that need to be addressed before widespread adoption of drone technologies in everyday life can occur. By summarizing an up-to-date survey on the state of the art in copter drone technology, this paper will provide valuable insights into where this field is heading in terms of progress and innovation. Full article

In the expeditiously evolving discipline of autonomous aerial robotics, the efficiency and precision of drone control deliveries have become predominant. Different control strategies for UAV systems have been thoroughly investigated, yet PID controllers still receive significant consideration at various levels in the control loop. Although fractional-order PID controllers (FOPID) have greater flexibility than integer-order PID (IOPID) controllers, they are approached with caution and hesitance. This is due to the fact that FOPID controllers are more computationally intensive to tune, as well as being more challenging to implement accurately in real time. In this paper, we address this problem by developing and implementing a surrogate-based analysis and optimization (SBAO) of a relatively high-order approximation of FOPID controllers. The proposed approach was verified through two case studies; a simulation quadrotor benchmark model for waypoint navigation, and a real-time twin-rotor copter system. The obtained results validated and favored the SBAO approach over other classical heuristic methods for IOPID and FOPID. Full article

A dataset of aerial urban traffic images and their semantic segmentation is presented to be used to train computer vision algorithms, among which those based on convolutional neural networks stand out. This article explains the process of creating the complete dataset, which includes the acquisition of the images, the labeling of vehicles, pedestrians, and pedestrian crossings as well as a description of the structure and content of the dataset (which amounts to 8694 images including visible images and those corresponding to the semantic segmentation). The images were generated using the CARLA simulator (but were like those that could be obtained with fixed aerial cameras or by using multi-copter drones) in the field of intelligent transportation management. The presented dataset is available and accessible to improve the performance of vision and road traffic management systems, especially for the detection of incorrect or dangerous maneuvers. Full article

Understanding the atmospheric conditions in remote areas contributes to assessing local weather phenomena. Obtaining vertical profiles of the atmosphere in isolated locations can introduce significant challenges for the deployment and maintenance of equipment, as well as regulatory obstacles. Here, we assessed the potential of consumer drones equipped with lightweight atmospheric sensors to collect vertical meteorological profiles off One Tree Island (Great Barrier Reef), located approximately 85 km off the east coast of Australia. We used a DJI Matrice 300 drone with two InterMet Systems iMet-XQ2 UAV sensors, capturing data on atmospheric pressure, temperature, relative humidity, and wind up to an altitude of 1500 m. These flights were conducted three times per day (9 a.m., 12 noon, and 3 p.m.) and compared against ground-based weather sensors. Over the Austral summer/autumn, we completed 72 flights, obtaining 24 complete sets of daily measurements of atmospheric characteristics over the entire vertical profile. On average, the atmospheric temperature and dewpoint temperature were significantly influenced by the time of sampling, and also varied among days. The mean daily temperature and dewpoint temperature reached their peaks at 3 p.m., with the temperature gradually rising from its morning low. The mean dewpoint temperature obtained its lowest point around noon. We also observed wind speed variations, but changes in patterns throughout the day were much less consistent. The drone-mounted atmospheric sensors exhibited a consistent warm bias in temperature compared to the reference weather station. Relative humidity showed greater variability with no clear bias pattern, indicating potential limitations in the humidity sensor’s performance. Microscale temperature inversions were prevalent around 1000 m, peaking around noon and present in approximately 27% of the profiles. Overall, the drone-based vertical profiles helped characterise atmospheric dynamics around One Tree Island Reef and demonstrated the utility of consumer drones in providing cost-effective meteorological information in remote, environmentally sensitive areas. Full article

Simulation platforms are critical and indispensable tools for application developments of unmanned aerial vehicles (UAVs) because the UAVs are generally costly, have certain requirements for the test environment, and need professional licensed operators. Thus, developers prefer (or have) to test their applications on simulation platforms before implementing them on real machines. In the past decades, a considerable number of simulation platforms for robots have been developed, which brings convenience to developers, but also makes them hard to choose a proper one as they are not always familiar with all the features of platforms. To alleviate this dilemma, this paper provides a survey of open-source simulation platforms and employs the simulation of a multi-copter UAV swarm as an example. The survey covers seven widely used simulators, including Webots, Gazebo, CoppeliaSim, ARGoS, MRDS, MORSE, and USARSim. The paper outlines the requirements for multi-copter UAV swarms and shows how to select an appropriate platform. Additionally, the paper presents a case study of a UAV swarm based on Webots. This research will be beneficial to researchers, developers, educators, and engineers who seek suitable simulation platforms for application development, (not only multi-copter UAV swarms but also other types of robots), which further helps them to save expenses for testing, and speed up development progress. Full article

As a modern technological trend, unmanned aerial vehicles (UAVs) are extensively employed in various applications. The core purpose of condition monitoring systems, proactive fault diagnosis, is essential in ensuring UAV safety in these applications. In this research, adaptive health monitoring systems perform blade balancing fault diagnosis and classification. There seems to be a bidirectional unpredictability within each, and this paper proposes a hybrid-based transformed discrete wavelet and a multi-hidden-layer deep neural network (DNN) scheme to compensate for it. Wide-scale, high-quality, and comprehensive soft-labeled data are extracted from a selected hovering quad-copter incorporated with an accelerometer sensor via experimental work. A data-driven intelligent diagnostic strategy was investigated. Statistical characteristics of non-stationary six-leveled multi-resolution analysis in three axes are acquired. Two important feature selection methods were adopted to minimize computing time and improve classification accuracy when progressed into an artificial intelligence (AI) model for fault diagnosis. The suggested approach offers exceptional potential: the fault detection system identifies and predicts faults accurately as the resulting 91% classification accuracy exceeds current state-of-the-art fault diagnosis strategies. The proposed model demonstrated operational applicability on any multirotor UAV of choice. Full article

The actuator, which generally consists of motors, electrical regulations, and propellers, is the key component of the quadrotor Unmanned Aerial Vehicle. During the operation of the UAV, actuators are prone to degrade performance and even cause serious failure, which affects the service quality and flight safety of Unmanned Aerial Vehicles. Therefore, timely and accurate monitoring and evaluation of the health condition of actuators is of great significance to ensure the mission reliability of UAVs. This paper proposes an Adaptive Two-stage Unscented Kalman Filter-based actuator health assessment method for Quadcopter Unmanned Aerial Vehicles. Firstly, a state space equation is established based on dynamic analysis to characterize the degradation mechanism of the actuator. Then, by modifying the Two-stage Unscented Kalman Filter algorithm, the Adaptive Two-stage Unscented Kalman Filter algorithm is constructed by combining the filter divergence criterion and the covariance matching technique to implement the health assessment of actuators. Finally, experiments are carried out for different degradation scenarios to verify the effectiveness of the proposed method. Full article

Copter-type UAVs (unmanned aerial vehicles) or drones are expected to become more and more popular for deliveries of small goods in urban areas. One strategy to reduce the risks of drone collisions is to constrain their movements to a drone road system as far as possible. In this paper, for reasons of scalability, we assume that path-planning decisions for drones are not made centrally but rather autonomously by each individual drone, based solely on position/speed/heading information received from other drones through WiFi-based communications. We present a system model for moving drones along a straight road segment or tube, in which the tube is partitioned into lanes. We furthermore present a cost-based algorithm by which drones make lane-switching decisions, and evaluate the performance of differently parameterized versions of this algorithm, highlighting some of the involved tradeoffs. Our algorithm and results can serve as a baseline for more advanced algorithms, for example, including more elaborate sensors. Full article