An air-assisted electrostatic nozzle uses a combination of air-assisted atomization and electrostatic spray technology. This article optimizes the existing air-assisted electrostatic nozzles in terms of structural design to obtain a higher charge-to-mass ratio and a smaller droplet size. The optimized air-assisted electrostatic nozzle was studied experimentally, and the effects of liquid pressure, air pressure and applied voltage on the droplet size and charge-to-mass ratio were investigated. Comparing the effects of air pressure, liquid pressure and applied voltage on the charge-to-mass ratio and droplet size, the relationship curves of the droplet size and charge-to-mass ratio under each voltage were fitted using the Rayleigh charge limit theory. For a higher CMR during the spray operation, applied voltages between 2.5 kV and 3 kV, an air pressure between 0.4 bar and 0.6 bar, and a liquid pressure of less than 0.9 bar could be chosen. The optimized air-assisted electrostatic nozzles not only have small droplets but also have high charge-to-mass ratios, reducing the need for pesticide use and thus protecting human health and the environment.

This paper presents the design of an intra-row obstacle avoidance shovel-type weeding machine. Theoretical analysis of intra-row weeding components guided the determination of the structures and parameters for key parts, including the signal acquisition mechanism, automatic obstacle avoidance mechanism, and weeding shovel. Furthermore, a hydraulic system was designed to support these functions. The design aims to optimize intra-row weeding operations, reduce labor costs, enhance weed control effectiveness, and prevent collisions between weeding equipment and grapevines. Through the construction of a mathematical model, the analysis determined the necessary minimum return speed of the hydraulic cylinder for the intra-row weeding shovel to avoid grapevines. We also established a reasonable range for the extension speed of the hydraulic cylinder to minimize areas missed during weeding. Further analysis showed that using the minimum return speed of the hydraulic cylinder effectively reduced missed weeding areas. A virtual prototype model of the weeding machine was created in ADAMS. Using the coverage rate of weeding operation as the evaluation index, single-factor simulation tests determined that the extension speed of the piston rod in the obstacle avoidance hydraulic cylinder and the forward speed of the weeding machine are the main influencing factors. The preset threshold of the control system, which triggered the automatic obstacle avoidance mechanism when the obstacle avoidance rod reached a specific angle (the “Angle Threshold”), was identified as a secondary influencing factor. Other factors were considered irrelevant. Hydraulic cylinder extension speed, weeding machine forward speed, and angle threshold were chosen as the influencing factors. Following the principles of a Box–Behnken experimental design, a quadratic regression combination experiment was designed using a three-factor, three-level response surface analysis method. The evaluation criterion focused on the coverage rate of weeding operation. A regression model was developed to determine the coverage rate of the weeding operation, identifying the optimal parameters as follows: obstacle avoidance hydraulic cylinder extension speed of 120 mm/s, forward speed of the weeding machine at 0.6 m/s, and an angle threshold of 18°. The optimized coverage rate of the weeding operation achieved 86.1%. This study serves as a reference for further optimization of intra-row weeding machines in vineyards and for other crops.

Based on the current issues of difficulty in clearing intra-row weeds in orchards, inaccurate sensor detection, and the inability to adjust the row spacing depth, this study designs an intelligent intra-row obstacle avoidance and weeding machine for orchards. We designed the weeding machine’s sensor device, depth-limiting device, row spacing adjustment mechanism, joystick-based obstacle avoidance mechanism, weeding shovel, and hydraulic system. The sensor device integrates non-contact sensors and a mechanical tactile structure, which overcomes the instability of non-contact detection and avoids the risk of collision obstacle avoidance by the weeding parts. The weeding shovel can be adapted to the environments of orchards with small plant spacing. The combination of the sensor device and the obstacle avoidance mechanism realizes flexible obstacle avoidance. We used Ansys Workbench to conduct static and vibration modal analyses on the chassis of the in-field weeding machine. On this basis, through topology optimization, the chassis quality of the weeding machine is reduced by 8%, which realizes the goal of light weight and ensures the stable operation of the machinery. To further optimize the weeding operation parameters, we employed the Box–Behnken design response surface analysis, with weeding coverage as the optimization target. We systematically explored the effects of forward speed, hydraulic cylinder extension speed, and retraction speed on the weeding efficiency. The optimal operational parameter combination determined by this study for the weeding machine is as follows: forward speed of 0.5 m/s, hydraulic cylinder extension speed of 11.5 cm/s, and hydraulic cylinder retraction speed of 8 cm/s. Based on the theoretical analysis and scenario simulations, we validated the performance of the weeding machine through field experiments. The results show that the weeding machine, while exhibiting excellent obstacle avoidance performance, can achieve a maximum weeding coverage of 84.6%. This study provides a theoretical foundation and technical support for the design and development of in-field mechanical weeding, which is of great significance for achieving intelligent orchard management and further improving fruit yield and quality.

In automated orchard operations, the straight-line locomotion stability of ground-based weeding robots is critical for ensuring path coverage efficiency and operational reliability. To address the response lag and high-frequency oscillations often observed in conventional PID and fixed-lookahead Pure Pursuit controllers, this study proposes an adaptive lookahead Pure Pursuit method incorporating angular velocity feedback. By dynamically adjusting the lookahead distance according to real-time attitude changes, the method enhances coordination between path curvature and robot stability. To enable systematic evaluation, three time-series-based metrics are introduced: mean absolute yaw error (MAYE), peak-to-peak fluctuation amplitude, and the standard deviation of angular velocity, with overshoot occurrences included as an additional indicator. Field experiments demonstrate that the proposed method outperforms baseline algorithms, achieving lower yaw errors (0.61–0.66°), reduced maximum deviation (≤3.7°), and smaller steady-state variance (<0.44°²), thereby suppressing high-frequency jitter and improving turning convergence. Under typical working conditions, the method achieved a mean yaw deviation of 0.6602°, a fluctuation of 5.59°, an angular velocity standard deviation of 10.79°/s, and 155 overshoot instances. The yaw angle remained concentrated around the target orientation, while angular velocity responses stayed stable without loss-of-control events, indicating a favorable balance between responsiveness and smoothness. Overall, the study validates the robustness and adaptability of the proposed strategy in complex orchard scenarios and establishes a reusable evaluation framework, offering theoretical insights and practical guidance for intelligent agricultural machinery optimization.

Variable-rate spray systems with canopy leaf area density information detection are an important approach to reducing pesticide usage in orchard management. In order to estimate the canopy leaf area density using ultrasonic sensors, this article proposed three parameter model equations based on ultrasonic echo peaks for canopy leaf area density estimation and verified the accuracy of the three parameter model equations using laboratory-simulated canopy and outdoor tree experiments. The orthogonal regression statistics results from the laboratory-simulated canopy experiment indicated that parameter ${\mathrm{V}}_{\mathrm{c}}$ is more suitable for canopy leaf area density estimation compared to parameter ${\mathrm{V}}_{\mathrm{a}}$ and ${\mathrm{V}}_{\mathrm{b}}$ when the density ranges from 0.54 to 5.4 ${\mathrm{m}}^2{\mathrm{m}}^{-3}$. The model equation from parameter ${\mathrm{V}}_{\mathrm{c}}$ has minor systematic errors, and the predicted and observed values of parameter ${\mathrm{V}}_{\mathrm{c}}$ have good agreement with the experimental conditions. The laboratory-simulated canopy and outdoor tree canopy leaf area density verification experiments of parameter ${\mathrm{V}}_{\mathrm{c}}$ were carried out, and the results indicated that the absolute value of the mean relative error is 5.37% in the laboratory-simulated canopy and 2.84% in outdoor tree experiments. The maximum absolute value of the relative error is 8.61% in the laboratory-simulated canopy and 14.71% in the outdoor tree experiments, and the minimum absolute value of the relative error is 3.21% in the laboratory-simulated canopy and 0.56% in the outdoor tree experiments. The laboratory-simulated canopy leaf area density verification results showed that the mean relative errors under canopy leaf area density 0.98 and 4.92 ${\mathrm{m}}^2{\mathrm{m}}^{-3}$ conditions are 6.29% and 5.82%, respectively, which is larger than the mean relative error under 2.95 ${\mathrm{m}}^2{\mathrm{m}}^{-3}$; nevertheless, these results proved that this model equation is applicable for canopy information detection and advanced pesticide application development in future.

The dynamic evaporation of single droplets was investigated under controlled conditions. In the evaporation process, a droplet was placed on a peach leaf surface. In this research, the relative humidity and temperature were kept constant, and the wind speeds and thiophanate-methyl concentrations varied. Based on these conditions, this study aimed to determine the droplets’ dynamic transforming characteristics, including the contact angle, the height of the droplets, and the evaporation rate. Five concentrations and five wind speeds were chosen, and pure water droplets at different wind speeds were used as a control group. All single droplets were generated by a syringe. The results showed that the pure water and thiophanate-methyl droplets’ evaporation mode was CCR (constant contact radius) mode. An increase in the wind speed accelerated the evaporation process, when the wind speed was 0 m/s, the evaporation was the longest, and the shortest evaporation was achieved with 2.0 m/s wind speed. An increase in wind speed enhanced the pure water droplets’ dynamic evaporation process with a maximum enhancement ratio of 3.44 times in the present work. Under the same conditions, the thiophanate-methyl droplets’ evaporation time was shorter than that of the pure water droplets. For thiophanate-methyl droplets, the higher the concentration, the shorter the dynamic evaporation process. A 1250 ppm thiophanate-methyl solution with 2.0 m/s wind speed, had an evaporation ratio that was 2.83 times greater than that measured with 0 m/s wind speed. These results could benefit farmers by suggesting that they should adjust the concentration of thiophanate-methyl depending on the wind speed in order to reduce pollution.