Design and Test of Quantitative Fertilizer Feeding Device for Point-Applied Fertilization Device

Aiming at the suboptimal local path, slow convergence speed, and many inflection points in the path planning of fruit and vegetable picking robots in complex environments, a global planning method combining particle swarm optimization (PSO) algorithm and A* algorithm was proposed. Firstly, Manhattan distance was taken as a heuristic function of global programming based on the A* algorithm. Secondly, the step size of PSO was adjusted to optimize the path, shorten the path length, and reduce the number of inflection points. Finally, the planned path of the fruit and vegetable picking robot was smoothed so that it could steadily move along a smoother driving path in real scenarios. The experimental results show that compared with the traditional PSO algorithm, the hybrid algorithm based on the improved A* algorithm and PSO algorithm achieves a smoother path and fewer folding points. In comparison with the PSO algorithm, moreover, this algorithm can guarantee the path generation efficiency and the global optimum. In the end, the effectiveness of the proposed method was verified by shortening the path length and reducing the accumulative number of inflection points.

Path Planning of Fruit and Vegetable Picking Robots Based on Improved A* Algorithm and Particle Swarm Optimization Algorithm

2023

Design and Experiment of Impeller Type Variable Fertilizer Discharger Device Based on Edem Simulation

WANG,

CHE,

WAN

et al. 2023

Aiming at the problem of poor uniformity and stability of fertilizer discharge caused by the operation of the fertilizer discharger in the variable fertilization operation of rice. Combined with the agronomic requirements of deep fertilization on the northeast side, an impeller type variable side deep fertilizer was designed. According to the change of the prescription map, change the adjustment factors to achieve reasonable fertilization. Based on EDEM simulation, using the fertilizer discharge stability and uniformity coefficient of variation as indicators, under different impeller blades, different impeller speeds and different fertilizer discharge port angles, a secondary orthogonal rotation combination test was carried out, using Design-Expert. V8.0.6.1 is analyzed and tested, the regression equation and the response surface diagram are obtained, the interaction between the influencing factors is analyzed, and the best combination is determined. It is concluded that the stability and uniformity coefficient of variation of fertilizer discharge have reached the quality evaluation index of fertilization machinery According to technical specifications, the coefficient of variation of stability is 0.67%~2.85%, and the coefficient of variation of uniformity is 2.7%~16.4%. When the number of blades is 6, the fan angle of the fertilizer outlet is 35.7°, and the impeller speed is 18.85 r·min-1, the minimum variation coefficient of stability is 0.67%, and the minimum variation coefficient of uniformity is 2.1%. The bench test results are basically consistent with the optimal combination of simulation, and meet the design requirements.

Design and Testing of a Variable Fertilization System Based on Soil Nutrient Detection

LIU,

KONG,

JIE

et al. 2024

In order to solve the problems of low correlation between variable fertilizer application system and soil nutrient content detection and insufficient real-time performance, a variable fertilizer application system based on real-time soil nutrient content detection was developed. This paper describes the structure, working principle and design of key components of the soil information acquisition and fertilizer application system. It includes the simulation and analysis of fertilizer application using the discrete element method and the selection of curved blade fertilizer application discs. The system uses STM32F429IGT6 microcontroller and ROS higher-level computer for decision making. The device detects soil nutrients in real time, adjusts the fertilizer motor speed accordingly, and runs autonomously along the planned path. The decision coefficient R^2 between the fertilizer application rate and the speed of the fertilizer application wheel is not less than 0.97, and the relative error between the actual fertilizer application rate and the theoretical fertilizer application rate is up to 5.91%, with the maximum value of the coefficient of variation (CV) of 10.18%. The indoor bench test shows that the relative error between the actual fertilizer application rate and the target fertilizer application rate within a single operating grid is up to 6.2%, with the maximum value of CV being 6.64%. The field test in the orchard showed that the maximum relative error between the actual fertilizer application and the target fertilizer application in a single operation grid was 6.3%, and the maximum value of CV was 12.34%, and the fertilizer application was completed in the operation grid, which demonstrated that the device was able to realize real-time and accurate variable fertilizer application according to the soil nutrient information.