Plant Protection Unmanned Aerial Vehicle Research Articles

Popularization of plant protection UAVs and farmers’ income increases: a quasinatural experiment

ABSTRACT The long-term stability of a developing country hinges on the imperative to increase farmers’ incomes. Based on county-level data from China from 2009 to 2019, we use the implementation of a pilot policy that subsidizes plant protection unmanned aerial vehicles (UAVs) as a quasinatural experiment to examine the impact of popularizing plant protection UAVs on farmers’ incomes. The results show that the popularization of plant protection UAVs may significantly increase farmers’ incomes via mechanisms that include not only labor transfer and agricultural productivity improvements but also unique mechanisms related to green agricultural development. The marginal income-increasing effect of the popularization of plant protection UAVs is higher in counties with farmers with high incomes, in major grain-producing areas and in areas with plains. In addition, the popularization of plant protection UAVs has a significant positive spatial spillover effect on farmers’ incomes in neighboring counties. We provide not only an empirical reference for the popularization of plant protection UAVs in China but also new ideas for compensating for the shortcomings of China’s agricultural mechanization and realizing the strategy of increasing farmers’ incomes and rural revitalization. More importantly, we provide Chinese wisdom for promoting agricultural development and farmers’ incomes in other developing countries.

Effects of Varying Planting Patterns on Wheat Aphids’ Occurrence and the Control Effect of Pesticide Reduction Spraying Process by Unmanned Aerial Vehicle

A walnut–wheat intercropping pattern is practiced widely in southern Xinjiang to alleviate the contradiction between the lack of cultivated land resources and to increase economic value. Previous studies have confirmed that an alley cropping pattern could change the microclimate by supplying additional ecological functions such as windbreak, light interception, water conservation, etc. Cereal aphids (including Sitobion avenae, Rhopalosiphum padi, Metopolophium dirhodum, etc.) are commonly spread pests that harm wheat plants. But, the difference in population numbers between local patterns is still unknown. Pesticide reduction is the national strategy in China to alleviate the contraction between the demand of grain yield and environment protection. Plant protection-unmanned aerial vehicles (UAV) spraying pesticides are the most efficient method to control pests. However, compared to traditional artificial spraying method, how the UAV spraying method affect the control effect of reduced concentration pesticide is unclear. In order to address this problem, we conducted field investigations at Zepu county in southern Xinjiang to test the difference between walnut–wheat intercropping and wheat monocropping patterns for three consecutive years. And, we employed the field experiments to ensure the effectiveness of the reduced concentration common pesticides through the UAV spraying method. In conclusion, we conducted a comparison of the control effects of two spraying methods under conditions of reduced pesticide usage. Our findings revealed that the population of cereal aphids was larger in the intercropping pattern compared to the monocropping pattern. Although the control effect of the reduced treatment was lower than the regular dosage, some treatments still demonstrated sufficient capability to eliminate aphids, particularly when considering the effect within major varieties. Additionally, the use of the UAV spraying method exhibited a satisfactory effect when compared to the traditional artificial spraying method.

A flight control system for quadrotor plant protection UAV based on RBF-PID algorithm

As a powerful tool for modern agricultural protection, unmanned aerial vehicle (UAV) has the advantages of good adaptability and high efficiency in spraying and other operations compared with traditional manual operations The attitude and control of plant protection UAV are greatly affected by external factors during operation. However, the traditional proportional-integral-derivative (PID) controller commonly used at present cannot adapt to the complex environment because of the fixed parametersTherefore, a more sensitive method is needed to achieve adaptive balance of the aircraft attitude. In this paper, we establish the dynamic mathematical model of quadrotor UAV, and the influence of air resistance and rotational torque is considered in the process. Adopting the combined control method of Radial Basis Function (RBF) neural network and PID, the dynamic tuning of system control parameters is achieved through the self-learning of neural network and the feature of nonlinear mapping. The control system not only has the advantages of simple PID control structure and clear physical meaning, but also has the ability of neural network self-learning and adaptation. Matlab/Simulink was used as the experimental platform to respectively simulate the RBF-PID control system and the traditional PID control system. The simulation results show that the control system based on RBF-PID algorithm has a shorter response time and stronger robustness, which enhances the systems self-adaptability

A Three-Dimensional Full-Coverage Operation Path Planning Method for Plant Protection Unmanned Aerial Vehicles Based on Energy Consumption Modeling

With the rapid development of precision agriculture technology worldwide, plant protection unmanned aerial vehicles (UAVs) have been widely applied in the prevention and control of agricultural pests and diseases due to their advantages such as unrestricted terrain, strong maneuverability, hover capability, and high operational efficiency. In view of the fact that most of the current path planning methods for plant protection UAVs are mainly applicable to large fields with relatively flat terrain, and there is a lack of three-dimensional path planning methods applicable to hilly orchards, as well as a lack of intuitive evaluation of the advantages and disadvantages of the paths by utilizing the amount of energy consumption, this paper proposes a three-dimensional (3D) path planning method for plant protection UAVs in hilly orchards. The method utilizes the three-dimensional (3D) coordinates of the operational area obtained from a realistic 3D model of the area, and determines the 3D operational path through the use of Boustrophedon Cellular Decomposition and the height variations of the operational area. Based on the induced power used by the plant protection UAV for flight and the power needed to overcome wind resistance, combined with the change of the load of the plant protection UAV and the supply situation, the relative energy consumption model of the plant protection UAV is constructed. Then, by optimizing the operational heading angle (1–180°), the 3D path with the minimum relative energy consumption is obtained. Through a simulation test, it is demonstrated that the path with the minimum relative energy consumption (operational heading angle of 133°) reduces the average relative energy consumption by 62.44% and 47.21% compared to the path with the maximum relative energy consumption (operational heading angle of 51°) and the average relative energy consumption, respectively. This proves the feasibility of the proposed path planning method in hilly orchard environments and provides a reference for the application of plant protection UAVs in such orchards.

Analysis of the research progress on the deposition and drift of spray droplets by plant protection UAVs

Plant protection unmanned aerial vehicles (UAVs), which are highly adapted to terrain and capable of efficient low-altitude spraying, will be extensively used in agricultural production. In this paper, single or several independent factors influencing the deposition characteristics of droplets sprayed by plant protection UAVs, as well as the experimental methods and related mathematical analysis models used to study droplet deposition and drift, are systematically investigated. A research method based on farmland environmental factors is proposed to simulate the deposition and drift characteristics of spray droplets. Moreover, the impacts of multiple factors on the droplet deposition characteristics are further studied by using an indoor simulation test system for the spraying flow field of plant protection UAVs to simulate the plant protection UAVs spraying flow field, temperature, humidity and natural wind. By integrating the operation parameters, environmental conditions, crop canopy characteristics and rotor airflow, the main effects and interactive effects of the factors influencing the deposition of spray droplets can be explored. A mathematical model that can reflect the internal relations of multiple factors and evaluate and analyze the droplet deposition characteristics is established. A scientific and effective method for determining the optimal spray droplet deposition is also proposed. In addition, this research method can provide a necessary scientific basis for the formulation of operating standards for plant protection UAVs, inspection and evaluation of operating tools at the same scale, and the improvement and upgrading of spraying systems.

Application Progress of UAV-LARS in Identification of Crop Diseases and Pests

Disease and pest stress is one of the important threats to crop growth and development, which have a very adverse impact on crop yield and quality every year, even leading to crop failure. Currently, the use of plant protection unmanned aerial vehicles (UAVs) for pesticide spraying is the most effective means of controlling crop diseases and pests. However, the areas where crop pests and diseases occur are often presented in “point-like” or “patchy” forms, and the UAV’s full-coverage spraying method results in a great waste of pesticides. Therefore, there is an urgent need to research a method for identifying the area of diseases and pest stress to achieve precise targeted spraying, in order to reduce the amount of pesticides used and improve their utilization. By analyzing the low-altitude remote sensing images of crop fields taken by UAVs, real-time pesticide spraying prescription maps can be generated to meet the demand for precise targeted spraying. This review focuses on the actual needs of precise targeted spraying by plant protection UAVs. Firstly, the RS monitoring mechanism of crop diseases and pests by UAVs is studied. Secondly, a comprehensive investigation of the literature on UAV Low-altitude Remote Sensing (UAV-LARS) technology for monitoring and identifying crop diseases and pests is conducted, summarizing the research progress in monitoring and identifying crop diseases and pests, especially in wheat, cotton, and rice. Finally, the key issues to be addressed and the future development direction of UAV-LARS monitoring of crop diseases and pests are proposed.

Remaining useful life prediction of weighted k-out-of-n systems based on dynamic random weights of importance

With the increasing complexity of various industrial systems, the reliability assessment and remaining useful life prediction of weighted k-out-of-n systems considering stochastic correlation have become a concern in the field of reliability. The components’ varying locations and operating environments result in fluctuating reliability and different impacts on normal system operation. In this study, the Birnbaum importance of components is modeled for a weighted k-out-of-n continuous degradation system consisting of different types of components with stochastic correlation. Furthermore, a reliability model and a remaining useful life prediction model based on kernel diffeomorphism estimation with dynamic random weights of Birnbaum importance are developed for weighted k-out-of-n systems. First, the component state reliability model is established by a nonparametric method of adaptive kernel diffeomorphism estimation. Second, the multivariate copula function is used to characterize the stochastic correlation of different types of component degradation. In addition, the Birnbaum importance model with stochastic correlation of components was developed using Akaike Information Criterion for copula function preference. A remaining useful life prediction model for the weighted k-out-of-n continuous degradation system is established considering the dynamic random weights of Birnbaum importance measures. Finally, the validity and accuracy of the proposed weighted k-out-of-n system remaining useful life model are verified using a cluster of plant protection unmanned aerial vehicles.

Design and Experiment of Ecological Plant Protection UAV Based on Ozonated Water Spraying

With the development of pesticide substitution technology, ozonated water has been gradually applied in agricultural plant protection. This paper describes our development of an ecological plant protection unmanned aerial vehicle (UAV) that can produce and spray ozonated water while flying. Firstly, this paper carries out the design of the ozonated water system, including the selection of the ozone generator and the gas-liquid mixing method. Secondly, the conceptual design method of the ecological plant protection UAV is introduced, including total weight estimation, propulsion system selection, layout and structure design, battery modeling, center of gravity evaluation, and control system. Then, static analysis was computed in ANSYS Workbench on the UAV fuselage. Finally, the field test verified that the hovering time of the UAV could reach the design requirement of 10 min when it was fully loaded. The effective spraying width (with a height of 2 m and a speed of 3 m/s) is 5.25 m. The UAV was used to spray ozonated water with a concentration of 17 ppm continuously once a day; on day 7, the control effect could reach 76.4% and the reduction rate of the larvae population was 59.3%. Therefore, spraying ozonated water with a concentration of 17 ppm every day by using the ecological plant protection UAV can effectively control broccoli diamondback moth larvae and achieve the control effect of traditional pesticides (Chlorantraniliprole SC).

Productivity model and experiment of field crop spraying by plant protection unmanned aircraft.

Traditional agricultural production requires numerous human and material resources; however, agricultural production efficiency is low. The successful development of plant protection unmanned aerial vehicles (UAVs) has changed the operation mode of traditional agricultural production, saving human, material, and financial resources and significantly improving production efficiency. To summarize the process of improving the productivity of plant protection UAVs, this study established a productivity calculation model of UAVs based on the time composition of the UAV agricultural plant protection process, including spraying, turning, replenishment, and transfer times. The time required for the unmanned aircraft application process was counted through years of tracking the application process of eight different plant protection unmanned aircraft. Plot lengths of 100, 300, 500, 700, 1,000, 1,500, 2,000, 2,500, 3,000, and 3,500 m were established to calculate the theoretical productivity. The results showed that the productivity of different types of plant protection UAVs increased with an increase in plot length in the range of 100 to 1,500 m; however, when the plot length reached a certain value, the productivity growth rate slowed down or even decreased slightly. Simultaneously, based on the working area per 10,000 mu, the recommended plot length and the number of configured models for different models were recommended. If the plant protection UAV was distinguished by electric and oil power, the time utilization rate of electric plant protection UAVs was 72.7%, and the labor productivity was 56.4 mu/person·h. In contrast, the time utilization rate of the heavy load oil-powered plant protection unmanned aircraft was 86%, and the labor productivity was 63.5 mu/person ·h. This study can support plant protection UAV enterprises to optimize equipment efficiency, provide evaluation methods for the operation efficiency assessment of plant protection UAVs, provide a reference for the selection of plant protection UAVs, and provide a basis for field planning.

Optimization-Design and Atomization-Performance Study of Aerial Dual-Atomization Centrifugal Atomizer

The aerial atomizer is the most essential component of the plant protection UAV (unmanned aerial vehicle). However, the structural optimization of existing aerial atomizers lacks comprehensive consideration of spray parameters and structural parameters, and there is a shortage of available atomizer spray models, resulting in the unstable effect of UAV application. In our previous work, an aerial dual-atomization centrifugal atomizer was developed. In order to obtain an aerial atomizer with good atomization effect and its atomization model, structural optimization at different rotation speeds and flow rates of the atomizer, and its atomization performance, are studied in this paper. Firstly, with the droplet volume median diameter (VMD) and spectral width (SRW) as the evaluation index, through the single-factor, Plackett–Burman and Box–Behnken tests, the influence of rotation speed, flow rate, tooth number and tooth shape were studied. The regression models of the droplet VMD and SRW were established using multiple quadratic regression fitting of the test data. Secondly, in order to achieve the lowest droplet VMD and SRW, the response surface method and post-hoc multiple comparison method were used to obtain the optimized structure of the atomizer’s rotation ring at different rotation speeds (600–7000 r/min) and flow rates (500–1000 mL/min). Lastly, with the effective swath width (ESW) of the optimized atomizer as the evaluation index, through the Box–Behnken test, the influence of rotation speed, flow rate and spray height were studied. The multiple quadratic regression model of ESW was established with the test data. The test results indicated that rotation speed, flow rate and tooth number had a significant effect on droplet VMD and SRW; tooth shape had no significant effect on the droplet VMD and SRW, however, the square tooth shape had the best atomization effect; and rotation speed, flow rate and spray height had a significant effect on ESW. The optimized structural parameters were tooth shape: square, and tooth number: 20. The determination coefficient R2 of the regression model of VMD, SRW and ESW were 0.9976, 0.9770 and 0.9974, respectively, which indicates that the model was accurate, and can evaluate and predict the spray effect. This paper provides an optimized dual-atomization centrifugal atomizer, and its regression models of VMD, SRW and ESW for UAV applications can provide a reference for efficient UAV spraying.

Numerical Simulation and Analysis of Droplet Drift Motion under Different Wind Speed Environments of Single-Rotor Plant Protection UAVs

Unmanned aerial vehicles (UAVs) have been widely used in plant protection, and the mechanism of droplet deposition drift while spraying with the 3WQF120-12 produced by Quanfeng Aviation, a representative model of single-rotor plant protection UAVs in China, still requires more research. This study used a combination of computational fluid dynamics (CFD) and wind tunnel experiments to analyze the droplet deposition drift pattern of the 3WQF120-12 single-rotor plant protection UAV. The CFD modeling of the nozzle was confirmed to be feasible using wind tunnel experiments. Pearson correlation analysis was performed between experimental and simulated values, and multiple correlation coefficients reached above 0.89, which is a robust correlation. In this study, CFD simulations were performed to simulate the drift of UAV spray droplets under the rotor wind field and the combined effect of front and side winds. The deposition of droplets at different heights was simulated. The UAV’s spraying conditions at different flight speeds, side wind magnitudes, and spraying heights were evaluated. According to the CFD simulation results of the 3WQF120-12 plant protection UAV, the recommended flight height is 1–3 m, the recommended flight speed is below 3 m/s, and the recommended ambient wind speed is within 3 m/s. The simulation results were verified by the field test, and the trend of the field experimental data and CFD simulation results are qualitatively consistent to verify the reasonableness and feasibility of the simulation’s data. The simulated results were similar to the curves and spray area of the field test results at operating heights of 1.5 m and 3.5 m.

Operation quality control of rapeseed strip aerial seeding system via under-constrained seeding technique

Due to the strong aerodynamic disturbance induced by high-speed rotating rotors and under-constrained seeding condition, it is difficult to control the width of landing seeds in target area during the aerial seeding process. In this study, based on the multi-rotor plant protection unmanned aerial vehicle (UAV) platform, the strategy of under-constrained seeding at a low dropping height is employed to realize the strip aerial seeding of rapeseed. Firstly, the spatial-temporal characteristics of downwash flow field in forward flight state are verified via the high-fidelity computational fluid dynamics method. Afterwards, the migration mechanism of falling seeds and operation parameter optimization are investigated by employing the gas-solid coupling simulation technique. Finally, flight experiments are carried out based on multi-rotor UAV platform to verify the validity of simulation results, where the image processing technique is used to accurately obtain the coordinates and distribution characteristics of landing seeds. The result indicates that the strip effect could be further improved with a higher flight speed and lower dropping height, for instance, the strip width of 95 % landing seeds could be controlled within 81.1 mm when the flight speed and dropping height are 3.5 m/s and 0.5 m respectively. The research results can provide a suggestion for scientific setting of operation parameters of aerial seeding system.

Design and validation of a multi-objective waypoint planning algorithm for UAV spraying in orchards based on improved ant colony algorithm.

Current aerial plant protection with Unmanned Aerial Vehicles (UAV) usually applies full coverage route planning, which is challenging for plant protection operations in the orchards in South China. Because the fruit planting has the characteristics of dispersal and irregularity, full-coverage route spraying causes re-application as well as missed application, resulting in environmental pollution. Therefore, it is of great significance to plan an efficient, low-consumption and accurate plant protection route considering the flight characteristics of UAVs and orchard planting characteristics. This study proposes a plant protection route planning algorithm to solve the waypoint planning problem of UAV multi-objective tasks in orchard scenes. By improving the heuristic function in Ant Colony Optimization (ACO), the algorithm combines corner cost and distance cost for multi-objective node optimization. At the same time, a sorting optimization mechanism was introduced to speed up the iteration speed of the algorithm and avoid the influence of inferior paths on the optimal results. Finally, Multi-source Ant Colony Optimization (MS-ACO) was proposed after cleaning the nodes of the solution path. The simulation results of the three test fields show that compared with ACO, the path length optimization rate of MS-ACO are 3.89%, 4.6% and 2.86%, respectively, the optimization rate of total path angles are 21.94%, 45.06% and 55.94%, respectively, and the optimization rate of node numbers are 61.05%, 74.84% and 75.47%, respectively. MS-ACO can effectively reduce the corner cost and the number of nodes. The results of field experiments show that for each test field, MS-ACO has a significant optimization effect compared with ACO, with an optimization rate of energy consumption per meter of more than 30%, the optimization rate of flight time are 46.67%, 56% and 59.01%, respectively, and the optimization rate of corner angle are 50.76%, 61.78% and 71.1%, respectively. The feasibility and effectiveness of the algorithm were further verified. The algorithm proposed in this study can optimize the spraying path according to the position of each fruit tree and the flight characteristics of UAV, effectively reduce the energy consumption of UAV flight, improve the operating efficiency, and provide technical reference for the waypoint planning of plant protection UAV in the orchard scene.

Numerical simulation of the spatial and temporal distributions of the downwash airflow and spray field of a co-axial eight-rotor plant protection UAV in hover

The downwash airflow of a multi-rotor unmanned aerial vehicle (UAV) in hover can improve the penetration rate of droplets in the canopy of fruit trees, but the uncertain distribution of the downwash airflow can also lead to the generation of uneven distribution of droplets. With a co-axial eight-rotor plant protection UAV as the research object, the computational fluid dynamics (CFD) method is adopted in this study to establish the coupled flow field model of the downwash airflow and the two-phase flow model of airflow-droplets in hover. The spatial and temporal distribution law of the downwash airflow is analyzed, and the impact of the motion law of the droplets in the spray field is investigated. The results show that the downwash airflow shifts from an unsteady state to a steady state over time. Various wind vortices such as wake vortex, ground diffusion airflow, and vortex ring are generated during the evolution process, with a “negative velocity channel” of downwash airflow velocity identified in the central region under the rotors. The farther the airflow is from the rotor, the larger the area field of wake vortex airflow. Consequently, there is a gradual coupling of the left and right adjacent wake vortices from mutual independence, with the “spiral effect” of the downwash wind field offset by the mutual coupling of the upper and lower rotors of the UAV. When the installation position of the nozzle falls within the below-rotor region, the distribution of droplet deposition becomes more penetrative than the central axis installation position of the nozzle. It indicates that the below-rotor installation position of the nozzle can prevent droplets from entering into the coupling region of the trailing vortex, which reduces droplet drift. According to the field test, the measurement and simulation results of the downwash air velocity are consistent, with the minimum and maximum relative error reaching 4% and 29%.

Airflow characteristics of rotorcraft plant protection UAV operating in rice fields

Rotorcraft unmanned aerial vehicles (UAVs) cause movement of the rice crop which is an important indicator of the effectiveness of spray applications. A method of acquiring images of the effects of airflow on the spray target by video aerial photography and computer vision to process the images was examined to obtain the characteristic information in rice fields; the dimensions of the disturbed area of crop, the so-called “rice vortex”. Orthogonal experiments were designed to investigate the three factors of take-off mass, flying height and flight speed of the plant protection to assess the four indices of trailing distance, trailing stability, area and shape of the rice vortex. The results show that the influence of the three factors on the vortex trailing distance and its stability was in the order of flight speed, flight altitude and take-off mass. The effects on the vortex area and vortex shape were speed > mass > height. Analysis and discussion of the characteristics and morphological features of the airflow targets revealed that the greater the distance and longer the duration of the trailing vortex, the more easily the rice vortex was disturbed and dissipated, and the lower its stability. Changes in the shape of the rice vortex mainly occur in its length, and changes in width are smaller. The results provide a data collection method and basis for further development of flight parameter-airflow target-application effect models. The four parameters of the trailing distance, stability, vortex area, and vortex shape constitute technical parameters suitable for assessing the effects of rotorcraft plant protection UAVs operating in rice fields.

Research on Dynamic Scheduling Model of Plant Protection UAV Based on Levy Simulated Annealing Algorithm

The plant protection unmanned aerial vehicle (UAV) scheduling model is of great significance to improve the operation income of UAV plant protection teams and ensure the quality of the operation. The simulated annealing algorithm (SA) is often used in the optimization solution of scheduling models, but the SA algorithm has the disadvantages of easily falling into local optimum and slow convergence speed. In addition, the current research on the UAV scheduling model for plant protection is mainly oriented to static scenarios. In the actual operation process, the UAV plant protection team often faces unexpected situations, such as new orders and changes in transfer path costs. The static model cannot adapt to such emergencies. In order to solve the above problems, this paper proposes to use the Levi distribution method to improve the simulated annealing algorithm, and it proposes a dynamic scheduling model driven by unexpected events, such as new orders and transfer path changes. Order sorting takes into account such factors as the UAV plant protection team’s operating income, order time window, and job urgency, and prioritizes job orders. In the aspect of order allocation and solution, this paper proposes a Levy annealing algorithm (Levy-SA) to solve the scheduling strategy of plant protection UAVs in order to solve the problem that the traditional SA is easy to fall into local optimum and the convergence speed is slow. This paper takes the plant protection operation scenario of “one spray and three defenses” for wheat in Nanjing City, Jiangsu Province, as an example, to test the plant protection UAV scheduling model under the dynamic conditions of new orders and changes in transfer costs. The results show that the plant protection UAV dynamic scheduling model proposed in this paper can meet the needs of plant protection UAV scheduling operations in static and dynamic scenarios. Compared with SA and greedy best first search algorithm (GBFS), the proposed Levy-SA has better performance in static and dynamic programming scenarios. It has more advantages in terms of man-machine adjustment distance and total operation time. This research can provide a scientific basis for the dynamic scheduling and decision analysis of plant protection UAVs, and provide a reference for the development of an agricultural machinery intelligent scheduling system.

Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach

With the development of aviation agricultural technology, the number of farmers adopting the use of drones in daily agricultural activities is growing rapidly in recent decades. Among these, a large portion constitutes agricultural drones being used in pest control and crop protection practices, e.g. agriculture spraying of pesticides. Spraying pesticides with drones have proven to be faster than other traditional methods. On the downside, flight time and range of Unmanned Aerial Vehicles (UAV) are often limited. Thus, a proper arrangement of flight height and velocity will greatly improve spraying efficiency. A new strategy to optimize the flight parameters, i.e. flight height and flight velocity, for fixed-wing UAV with a 3D simulation-based approach together with an automatic optimization algorithm was proposed in this study. To find the optimal parameters for a UAV to fly and spray under certain environmental conditions, a three-dimensional model of the target crop was established first, followed by a detailed simulation of droplet spraying. As a demonstration case, a grass model was developed and used as the target plant, and a physics-based method was used to simulate realistically the movement of the droplets in the air as well as the interaction between the droplets and the plant to obtain the droplet deposition rate under the specified operating parameters. Furthermore, the standard Particle Swarm Optimization (PSO) algorithm was used to optimize the UAV operating parameters to obtain the best operating parameters. The results indicate that using the standard PSO algorithm to optimize the operating parameters of the drone could significantly improve the deposition rate and find the best operating parameters. Keywords: unmanned aerial vehicle, droplet deposition, 3D simulation, particle swarm optimization algorithm DOI: 10.25165/j.ijabe.20231601.6581 Citation: Xu L F, Yang Z Z, Huang Z S, Ding W L, Buck-Sorlin G. Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach. Int J Agric & Biol Eng, 2023; 16(1): 66–72.

Development Status and Key Technologies of Plant Protection UAVs in China: A Review

Plant protection unmanned aerial vehicles (UAVs) play a crucial role in agricultural aviation services. In recent years, plant protection UAVs, which improve the accuracy and eco-friendliness of agricultural techniques, have been used to overcome the shortcomings of traditional agricultural operations. First, this paper introduces the development scale, main types, and operation scenarios of China’s plant protection UAVs. Subsequently, the key technologies of plant protection UAVs, such as precision autonomous flight control, pesticide spraying, drift control, and spraying quality measurement technologies, are reviewed. Next, the emergent technologies of plant protection UAVs are studied and analyzed with a focus on better spray effects, calculation models of droplet drift, controllable droplet size atomization technology, droplet drift detection technology, and droplet deposition quality detection technology in the application of plant protection UAVs. Moreover, the technologies of plant protection UAV application are summarized and future research prospects are presented, offering ideas for follow-up research on the key technologies of plant protection UAVs and encouraging agricultural production management to move toward better efficiency, eco-friendliness, and accuracy.

Key Technology Progress of Plant-Protection UAVs Applied to Mountain Orchards: A Review

With precision agriculture developing rapidly worldwide, water-saving, energy-saving, environment-friendly, and efficient agricultural production activities are effective ways to address human needs for agricultural products under the conditions of intensifying climate change, limited available arable land resources, and rapid population growth. Ground-based plant-protection machinery applied to large fields has difficulty solving the pest and disease prevention needs of mountain orchards since they feature undulating topography changes and low standardization of orchards. Unmanned aerial vehicles (UAVs) have broad development prospects in pest control in mountain orchards because of their advantages of not being restricted by terrain, strong maneuverability, and hover ability. This paper reviews the recent development of plant-protection UAVs from three perspectives, i.e., positioning and navigation technology, flight attitude control technology, and route planning in mountain orchards. We highlight that the future research should focus on following technology development, including (1) positioning navigation technology with high positioning accuracy and strong anti-interference capability, (2) intelligent control technology with high dynamic stability and better calculation accuracy, and (3) the optimization of the route-planning algorithm covering multiple constraints and the cluster cooperative operation scheme of plant-protection UAVs applicable to mountain orchards. These reviewed results could provide a reference for the future development of plant-protection UAVs, which will become the focus of future research.

Stereoscopic plant-protection system integrating UAVs and autonomous ground sprayers for orchards.

For orchard plant protection, conventional large machines and small sprayers are practically restricted by either narrow planting intervals with dense leaves or their inadequate penetration power, which leads to an unsatisfactory effect of spray. This paper proposes a stereoscopic plant-protection strategy that integrates unmanned air and ground sprayers to spray different parts of canopies to improve uniformity. In order to verify the proposal, a stereoscopic plant-protection system (SPS) was developed, consisting of a small swing-arm sprayer and a T16 plant-protection Unmanned Aerial Vehicle (UAV). Then, optimal operation parameters were determined by Computational Fluid Dynamics (CFD) and orthogonal experiments, and the uniformity was finally quantified by trials. CFD and orthogonal experiments showed that a swing-arm angle of 60° and a forward speed of 0.4 m/s were optimal for the ground sprayer, whilst a height of 2.0 m from the top of canopies and a forward speed of 1.0 m/s were appropriate for the UAV. The trial results showed that the density of vertical droplet deposition varied from 90 to 107 deposits/cm2 in canopies, and the uniformity was 38.3% higher than conventional approaches. The uniformity of top, bottom, inside and outside canopies was significantly improved. Meanwhile, the density of droplet deposition on both sides of leaves in all test points exceeded 25 deposits/cm2, able to meet the standard of spray. This study provides a practical approach for uniform pesticide spray to large-canopy fruit trees. Moreover, the high flexibility of plant-protection UAVs and the significant trafficability of small swing-arm sprayers can solve the problem of large machine entering and leaving orchards.