Grassland Fractional Vegetation Cover (FVC) must be effectively monitored because it can reflect the ecological situation of typical grasslands. However, there is a lack of research on ground sensing systems for typical grasslands. This study first designed an FVC detection test bench, and completed the strength verification of the device by establishing a finite element model and a virtual prototype model. With the reliable data support of the test bench, it was verified that there were optimal data points in the vegetation sample plot and the camera trajectory model for data acquisition was obtained. Based on the above theory and model, this study developed a mobile ground FVC perception device and a cell-based image cover estimation method. The device can adjust the camera while driving. The method includes detecting the vegetation area, acquiring the number of pixels, and calculating the number of pixels in the quadrat area. In the final field test, the average precision of the system was 90.0 %, the average recall was 90.3 %, and the average F1 was 90.1 %. At the same time, this study found that the system's accuracy for grasslands with the low FVC and the high FVC is better, up to 94.2 %. For 1 m2 and 0.5 m2 quadrats, the R2 obtained from the experiment was 0.89 and 0.92 respectively. Compared with similar studies, the perception system proposed in this study has better estimation accuracy and application potential. This study may contribute to grassland intelligence monitoring and grassland protection.

The study introduces an energy-efficient coverage path planning with tree bypassing navigation in hilly Camellia oleifera orchards. Firstly, a 3D grid map incorporating elevation was built to segment the workspace into rectangular flat and uneven sub-regions. Furthermore, an energy consumption model of the multifunctional platform for Camellia oleifera was developed. Secondly, to improve the energy efficiency, a long-edge row-wise strategy featuring tree bypassing was proposed for the flat sub-regions, with an improved A* ensuring efficient dead-end escape. For the uneven sub-regions, the terrain coverage was achieved through integrating contour-following and tree-bypassing arcs. Finally, a Manhattan-distance fitness function minimized inter-region travel, with optimal sequences and entries determined by a hybrid Genetic Algorithm and Tabu Search. Based on the results of algorithm simulations under convex slope, uniform slope, and slope-pit mixed terrains, the performance of the proposed energy-efficient coverage path planning model were evaluated in comparison with Greedy Genetic, Greedy, Spiral, and Boustrophedon algorithms. The results showed that the average pitch angle of the proposed algorithm was reduced by 75.00%, 75.68%, 71.88%, and 81.21% compared to Greedy Genetic, Greedy, Spiral, and Boustrophedon algorithms, respectively. Specifically, on the convex slope terrain, the proposed model obtained a total energy reduction of 14.46%, 12.41%, 6.8%, and 18.20% compared to the aforementioned algorithms, respectively. For the uniform slope terrain and the slope-pit mixed terrain, the reduction percentages were 1.71%, 2.3%, 13.42%, 25.74% and 11.2%, 11.12%, 14.29%, 14.47%, respectively. The results confirm that the proposed model has superior adaptability and energy efficiency in covering diverse terrain types.

Feeding and chopping are key operations in alfalfa harvesting, directly affecting silage quality and operational energy consumption. To address the problems of insufficient feeding stability, poor chopped length uniformity, and high specific energy consumption during direct alfalfa harvesting, a five-roller feeding–chopping device was designed. Based on the mechanical analyses of the feeding and chopping processes, the key structural parameters of the device were determined. Feeding speed, preload force, and rotational speed of chopping cylinder were selected as experimental factors, while standard grass length ratio, specific feeding and chopping energy consumption were used as evaluation indices. Single-factor experiments and a three-factor quadratic orthogonal rotatable combination experiment were conducted, and the operating mechanism was further analyzed using high-speed photography and torque sensor data. The single-factor experiments determined that the ranges of feeding speed, preload force, and rotational speed of chopping cylinder were 1–3 m/s, 900–1300 N, and 800–1200 r/min, respectively. The optimal parameter combination obtained from the quadratic regression equation was a feeding speed of 2 m/s, a preload force of 1090 N, and a rotational speed of chopping cylinder of 1010 r/min. Validation experiments were carried out under the optimal parameter combination, and the results were 90.34%, 0.86 kJ/kg, and 2.58 kJ/kg, respectively. The relative errors between the experimental results and the software-predicted values were all less than 10%. The results provide a theoretical basis and experimental support for parameter matching and low-energy optimization design of feeding–chopping devices for direct alfalfa harvesting.

With the development of smart agriculture, articulated tractors are increasingly applied in hilly and mountainous areas, where precise path tracking under lateral slippage remains a major challenge. Due to the articulated structure, the front and rear vehicle bodies exhibit different responses to terrain disturbances, making conventional single-point reference tracking insufficient for accurately describing whole-vehicle deviation. To address this issue, this study proposes a novel multi-point tracking deviation index that integrates the deviations of the front axle center, articulation point, and rear axle center. Based on this index, a systematic comparison of different reference points, including the centroid, incenter, and circumcenter of the characteristic triangle, is conducted through co-simulation experiments. The results demonstrate that the centroid yields the smallest whole-vehicle comprehensive deviation, achieving average deviations of 0.040 and 0.037 m under U-shaped and closed-curve paths, respectively, corresponding to reductions of 87% and 88% compared with the traditional articulation-point-based method. These findings indicate that the centroid provides the most balanced and robust reference point for articulated tractor path tracking under terrain-induced slippage, offering an effective trade-off between tracking accuracy and computational efficiency for autonomous operations in complex agricultural environments.

This study addresses the challenges of material blockage and inconsistent bale density during the feeding of high-moisture materials in round balers, focusing on hybrid foxtail millet chopped material as the research subject. The feeding mechanism of the round baler was simplified into a roller-belt feeding device to experimentally examine the flow characteristics of the material following pre-pressing and pre-compression stages. The feeding and scattering processes were divided into six representative dynamic stages. Using Matlab-based machine vision techniques, including Shi-Tomasi corner detection and the Kanade-Lucas-Tomasi optical flow method, the discrete motion behavior of the material during feeding was dynamically tracked and quantitatively analyzed. A comprehensive discreteness evaluation index was developed, incorporating metrics such as displacement direction consistency, spatial diffusion, and velocity variance. Complemented by discrete element method simulations, the study elucidated the material scattering mechanisms from both macroscopic and microscopic perspectives, revealing the discrete evolution patterns at each stage. Employing a Box-Behnken orthogonal experimental design, a regression model was constructed to relate key operational parameters to the discrete response, enabling the determination of optimal operating conditions that minimize material discreteness through parameter optimization. This research offers a novel methodological framework for analyzing the behavioral mechanisms of high-moisture bulk materials during conveying and forming processes and provides a theoretical basis for the optimized design of related agricultural machinery.

To achieve high speed and uniform mixed sowing of forage seeds, a novel mechanical-pneumatic seed metering device was designed. The system integrates a negative-pressure cone metering device for alfalfa seeds with an involute helix groove wheel device for oat seeds. Computational fluid dynamics was applied to optimise airflow distribution within the negative pressure cone, and the discrete element method was used to analyse seed movement in the groove wheel. A Box-Behnken design was employed to optimise key structural parameters, including base circle radius, involute polar angle, rotation speed, and helix angle. Bench tests were performed to assess sowing uniformity and relative error. Results showed that a cone inclination angle of 70 degrees provided stable airflow distribution, ensuring reliable suction performance. For the groove wheel mechanism, the optimal parameters were a base circle radius of 9 mm, an involute polar angle of 135 degrees, a rotation speed of 20 r min- 1, and a helix angle of 20 degrees, yielding a coefficient of variation of 13.08%. Further bench tests confirmed that at a rotation speed of 30 r min- 1 and a working pressure of 2500 Pa, the relative sowing error was maintained within 6.81%- 7.49%. These findings provide both theoretical and experimental insights for the design of efficient seed metering systems in mixed forage sowing.

Soil salinization poses severe threats to grassland ecological security and agricultural sustainability, readily triggering biodiversity loss, soil structure degradation, and productivity decline. Ameliorating saline soils is crucial for safeguarding agricultural and animal husbandry production and sustaining grassland ecosystems. Plasma biotreatment emerges as a novel green agriculture approach to enhance crop stress resistance and soil quality. This research investigates plasma treatment effects on alfalfa seed germination and growth under salt stress, specifically examining the correlative mechanisms between seed coat etching and germination efficacy. The methodology employed SEM-GLCM texture quantification to characterize seed coat micro-morphology. Through imbibition experiments, it elucidated regulatory mechanisms of plasma excitation parameters on the imbibition cycle. Systematic analysis of parameter impacts on physiological traits and field performance further determined cultivar-specific critical thresholds and optimal plasma parameter sets. Results demonstrated that plasma treatment significantly altered seed surface micro-morphology with cultivar-dependent responses. Plasma discharge power exerted notable regulatory effects on the imbibition cycle, where rational modulation of imbibition processes optimized germination and enhanced stress resistance. Under saline conditions, Zhongmu No. 4 treated at 100 W-18s exhibited maximum increases in plant height and stem diameter compared to the control, reaching 26.32% and 25.19%, respectively. This treatment further promoted efficient growth, optimized root architecture, and thereby improved physicochemical properties of saline soils. This work provides a theoretical foundation for plasma technology implementation in green agriculture and offers practical guidance for optimizing ecological remediation systems through further investigation into long-term effects on soil microbial communities and salt transport mechanisms.

Accurate estimation of Above-Ground Biomass (AGB) in natural grasslands is critical for ecosystem management, yet traditional satellite and unmanned aerial vehicle (UAV) remote sensing struggle to capture fine-scale vegetation details. To overcome these limitations, we developed "PraePercep-Y," an integrated ground-based robotic perception platform tailored for typical grasslands. Within this system, we systematically established a theoretical model for Fractional Vegetation Cover (FVC) estimation, determining that an optimal actual pixel area of 3 to 5 mm2 significantly enhances detection accuracy. Building upon this optimized data acquisition, we proposed the AGBT network for high-precision biomass inversion. The AGBT model is designed with a flexible dual-stream architecture that operates in two primary configurations: Mode 1 (RGB-based estimation), utilizing the Visual Stream to extract hierarchical RGB image features, and Mode 2 (Multi-sensor data fusion), which further integrates an Attribute Stream to encode vegetation height and FVC. To effectively fuse these modalities, we introduced a Cross-Modal Attention mechanism for semantic alignment and an Adaptive Weight Distribution strategy to dynamically adjust modality contributions. Validated through rigorous field experiments from 2022 to 2025 across 600 quadrats in Inner Mongolia, the system demonstrated superior performance. The AGBT model achieved strong predictive accuracy, with R2 values of 0.82 for Mode 1 (RGB-only) and 0.88 for Mode 2 (multi-sensor fusion). This study provides a highly accurate, automated methodological baseline for AGB assessment, significantly reducing manual labor and offering a scientific basis for grassland resource conservation.

To improve the soil loosening effects of degraded grasslands, this study investigates the performance of a bionic loosening shovel designed based on the claws of prairie zokor. A single-factor simulation test of the bionic loosening shovel was conducted using EDEM software to analyze the effects of loosening depth (H) and operating speed (V) on key parameters, including the ridge disturbance area (As), furrow disturbance area (Af), loosening resistance (Fr), and trench specific resistance (Fc). Additionally, field tests were performed to validate the simulation results of the bionic loosening shovel. The findings indicate that the difference ratio (Da1) between the simulated and test values for the bionic loosening shovel remained consistently low, confirming the reliability of the simulation model in predicting variations in response parameters. Furthermore, comparative field tests were conducted to evaluate the loosening performance of the bionic loosening shovel against standard loosening shovels (the diamond-shaped loosening shovel and the arrow-shaped loosening shovel). The results show that the bionic loosening shovel achieved the lowest values for As, Af, and Fr under the same operating parameters. However, its effect on improving Af was limited. These findings provide valuable technical support for the enhancement and optimization of loosening shovels for degraded grasslands.

The movement characteristics of mixed alfalfa and awnless brome seeds within a Venturi conveyor of an airblown centralized seeding system were studied by using the CFD-DEM coupling method. A Venturi conveyor with curved tube structure was designed based on the principle of the brachistochrone curve, and the impact of various structural and working parameters on seed movement characteristics and airflow distribution was investigated. The results showed that the stability and uniformity of seed supply and transport of designed curvilinear feed tube were better than that of conventional linear tube, and the 50 mm mixed tube design significantly reduced the number of collisions between seeds and the tube wall, thereby enhancing transport performance. For a 1:1 ratio of alfalfa to awnless brome seeds, the optimal airflow velocity ranged from 24 to 28 m/s, and the suitable seed feeding rate was 1500-3000 seeds/s. When the ratio was adjusted to 1:2, the suitable airflow velocity was between 20-24 m/s, and the suitable seed feeding rate was 3000-4500 seeds/s. Bench tests confirmed that the optimized Venturi conveyor effectively improved its operational performance. The study outcomes contribute to a better understanding of the motion characteristics of mixed seeds in Venturi tubes and lay the groundwork for further device structure optimization.

The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot. Compared to flat terrain, path tracking control on sloped terrain faces the obstacle of motion instability of the wheel-legged robot induced by the slope gravitational force component, which causes instantaneous steering center to offset. To address this problem, this study proposed a slope path tracking control algorithm by combining the methods of virtual sensing radar and two-level neural network. Firstly, the kinematic and dynamic models of the wheel-legged robot are deduced, from which the crucial factors affecting control accuracy of slope path tracking are recognized. Secondly, this study constructs the slope path tracking control algorithm, in which the virtual sensing radar is utilized to realize route perception, and the two-level neural network is employed to provide drive motors' speeds to adapt to path tracking on different slopes. Furthermore, the corresponding compensation methods of the identified impacting factors are embedded in the proposed algorithm, including the lateral tracking deviation factor, heading angle deviation factor, slope change factor, and slip rate factor. Finally, the co-simulation model of slope path tracking control is constructed, including the multi-body dynamic model of the wheel-legged robot in RecurDyn and the proposed slope path tracking algorithm complied by Python. Subsequently, the simulation tests of the wheel-legged robot are carried out under various slope angles and velocities. The results reveal that the proposed algorithm's effectiveness and accuracy are superior, with tracking errors reduced by more than 47.2% compared to an optimized pure pursuit algorithm.

The study focused on the granular fertilizer used in Camellia oleifera planting areas in Changsha City, Hunan, China, and aimed to determine the discrete element simulation parameters for the interaction between the fertilizer and the spreader, with the repose angle as the response variable. By employing the Box-Behnken response surface optimization method, a regression model for the repose angle was developed and optimized to identify the best parameter combination. This model was validated through physical repose angle tests. The research findings revealed specific coefficients for the interaction between fertilizer particles, as well as between fertilizer particles and a PVC board. The optimal parameter combination resulted in a simulated repose angle of 36.10°, with an error of 1.74

This study addresses the challenges of instability and rollover faced by agricultural machinery operating on complex hilly and mountainous terrains by proposing an active leveling system for an articulated unmanned tractor. The proposed system is an independent, vehicle-mounted swing platform that levels the equipment-carrying surface rather than the entire tractor body, facilitating modular retrofitting and enhancing operational safety on complex terrains. The system utilizes a hydraulic parallel-swing platform structure, equipped with a dual-axis tilt sensor to monitor the tractor's body tilt in real-time. In combination with a hydraulic drive system, the platform adjusts the tractor's posture to ensure stable operation on slopes of up to 30 degrees. The system's performance is evaluated through degrees of freedom analysis, inverse kinematic solution, dexterity analysis, and workspace evaluation. A multibody dynamics model is developed, and kinematic simulations are performed to verify its leveling capabilities. Co-simulations using Simulink and RecurDyn are employed to study the system's response and stability under complex terrain conditions, as well as the leveling accuracy of the pitch and roll angles. Finally, bench and field tests were conducted, demonstrating that leveling errors peak at extreme angles, with a maximum roll error of 1.17 degrees and a maximum pitch error of 0.87 degrees, meeting the precision requirements for angle control on uneven terrain.

Conditioning is a critical step in alfalfa hay harvesting, directly influencing its quality. A conditioning model was developed to identify the key factors affecting conditioning effectiveness. To address the issue of uneven stem damage caused by conventional conditioning rollers, a surface bump structure was designed. By arranging these bumps spatially, the rollers applied micro-rubbing actions to the alfalfa stems, thereby enhancing structural disruption. Parametric optimisation studies clarified how bump diameter, non-interference distance and helix angle influence stem disruption efficiency. The design was further refined using the finite element method. Subsequently, a Box-Behnken experimental design was employed to optimise three key operational parameters: feed rate, roller gap, and roller rotational speed. Drying tests were then conducted to compare the conditioning performance of different roller designs. Results showed that the minimum number of broken branches (0.67) and maximum number of non-fracture damage occurrences (7.67) were achieved with a bump diameter of 2.85 mm, a non-interference distance of 1.61 mm, and a helix angle of 23.85 degrees. Aiming to maximise the conditioning while minimising the conditioning loss rate and energy consumption, the optimal parameters were determined to be a roller rotational speed of 683 r min_ 1, a roller gap of 3.13 mm and a feed rate of 779 g s_ 1. The moisture content of alfalfa conditioned using the roller with bumps dropped to around 40 % within the first 60 min. Compared with the other two conditioning rollers, this design demonstrated superior performance.

Improving the uniformity of seed particle distribution is the key to the research of air blown collection and discharge seed metering devices. Analyzing the movement process of particles can help improve seed metering performance. In this study, the DEM-CFD (discrete element method and computational fluid dynamics) coupled simulation model was used to simulate the motion characteristics of oat seeds, vetch seeds, and mixed seeds in an air blown manifold distributor. From the perspectives of airflow field and seed motion, the effects of distributor cap shape and mixed seed supply ratio on the uniformity performance of oat seeds, vetch seeds, and their mixed seeds were analyzed. The coefficient of variation of seeding quantity in each row and the precision of discharging mixed seeds ratio were selected to evaluate the seed motion characteristics. The results showed that as the inlet velocity of the airflow increased, the seeds discharged from the distribution pipe decreased. When the inlet velocity of the airflow was 25 m/s, the coefficient of variation of seeding quantity in each row of seeding in the distribution pipe was the least and less than 5 %. The use of a convex distributor cap resulted in the best uniformity of the arrangement of vetch seeds, while the use of a conical distributor cap resulted in the best uniformity of oat seed arrangement. For the seeding of mixed seeds, the convex distributor better promoted the stable movement of the seeds, exhibited better seeding uniformity performance, and could effectively reduce the frequency of contact between the seeds and the distribution pipe wall, avoiding sudden changes in the velocity vector of the seeds. The convex distributor cap also exhibited superior seeding uniformity performance for different mixed seed supply ratios. This result will help to improve understanding of the distribution characteristics of mixed seeds and optimize the distributor structure of the air blown collection and discharge seed metering device.

ObjectiveFarmland consolidation for agricultural mechanization in hilly and mountainous areas can alter the landscape pattern, elevation, slope and microgeomorphology of cultivated land. It is of great significance to assess the ecological risk of cultivated land to provide data reference for the subsequent farmland consolidation for agricultural mechanization. This study aims to assess the ecological risk of cultivated land before and after farmland consolidation for agricultural mechanization in hilly and mountainous areas, and to explore the relationship between cultivated land ecological risk and cultivated land slope.MethodsTwenty counties in Tongnan district of Chongqing city was selected as the assessment units. Based on the land use data in 2010 and 2020 as two periods, ArcGIS 10.8 and Excel software were used to calculate landscape pattern indices. The weights for each index were determined by entropy weight method, and an ecological risk assessment model was constructed, which was used to reveal the temporal and spatial change characteristics of ecological risk. Based on the principle of mathematical statistics, the correlation analysis between cultivated land ecological risk and cultivated land slope was carried out, which aimed to explore the relationship between cultivated land ecological risk and cultivated land slope.Results and DiscussionsComparing to 2010, patch density (PD), division (D), fractal dimension (FD), and edge density (ED) of cultivated land all decreased in 2020, while meant Patch Size (MPS) increased, indicating an increase in the contiguity of cultivated land. The mean shape index (MSI) of cultivated land increased, indicating that the shape of cultivated land tended to be complicated. The landscape disturbance index (U) decreased from 0.97 to 0.94, indicating that the overall resistance to disturbances in cultivated land has increased. The landscape vulnerability index (V) increased from 2.96 to 3.20, indicating that the structure of cultivated land become more fragile. The ecological risk value of cultivated land decreased from 3.10 to 3.01, indicating the farmland consolidation for agricultural mechanization effectively improved the landscape pattern of cultivated land and enhanced the safety of the agricultural ecosystem. During the two periods, the ecological risk areas were primarily composed of low-risk and relatively low-risk zones. The area of low-risk zones increased by 6.44%, mainly expanding towards the northern part, while the area of relatively low-risk zones increased by 6.17%, primarily spreading towards the central-eastern and southeastern part. The area of moderate-risk zones increased by 24.4%, mainly extending towards the western and northwestern part, while the area of relatively high-risk zones decreased by 60.70%, with some new additions spreading towards the northeastern part. The area of high-risk zones increased by 16.30%, with some new additions extending towards the northwest part. Overall, the ecological safety zones of cultivated relatively increased. The cultivated land slope was primarily concentrated in the range of 2° to 25°. On the one hand, when the cultivated land slope was less than 15°, the proportion of the slope area was negatively correlated with the ecological risk value. On the other hand, when the slope was above 15°, the proportion of the slope area was positively correlated with the ecological risk value. In 2010, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.592, 0.609, and 0.849, respectively. In 2020, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 2° to 5°, 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.534, 0.667, 0.729, and 0.839, respectively.ConclusionsThe assessment of cultivated land ecological risk in Tongnan district of Chongqing city before and after the farmland consolidation for agricultural mechanization, as well as the analysis of the correlation between ecological risk and cultivated land slope, demonstrate that the farmland consolidation for agricultural mechanization can reduce cultivated land ecological risk, and the proportion of cultivated land slope can be an important basis for precision guidance in the farmland consolidation for agricultural mechanization. Considering the occurrence of moderate sheet erosion from a slope of 5° and intense erosion from a slope of 10° to 15°, and taking into account the reduction of ecological risk value and the actual topographic conditions, the subsequent farmland consolidation for agricultural mechanization in Tongnan district should focus on areas with cultivated land slope ranging from 5° to 8° and 15° to 25°.

The growth of Achnatherum splendens affects the growth of dominant forage grasses in grasslands, which leads to a decrease in grassland biomass and an increase in grassland ecological environment degradation. It is a time and labor-consuming work to measure the height of Achnatherum splendens in wild grassland, so developing an intelligent grass height estimation method is indispensable. This study aims to propose a novel method for estimating the height of Achnatherum splendens based on image processing. The mobile ground robot with the binocular depth camera captures image information from different angles. This method acquires the edge features of the image from different angles and obtains the height pixel points by feature matching and clustering. The pixel points filtered by deep learning models' Bounding Box are converted to the world coordinate system using spatial geometry. This study took YOLOv7-X as an example, as its average precision (AP) detection rate was 96.6 %, which was superior to other deep learning algorithms in terms of overall performance. In the mean height estimation experiment of 10 test sites, the mean relative error (MRE) was 6.4 % and coefficient of determination (R2) was 0.74. In the mean height estimation experiment of 10 test sites, the MRE was 3.1 % and the R2 was 0.85. It is proven that this proposed method is effective and strongly agrees with actual Achnatherum splendens heights measured manually. Experiments also showed that this method performed better in the small sample test sites (The basal coverage was no more than 1 m2 in this study). This study encapsulated the above methods and proposed a model called ASHS, which could estimate the height of grassland vegetation represented by Achnatherum splendens. Different algorithm modules in the model can be replaced according to the vegetation situation. This study may contribute to estimating the quadrat height of grasses and developing intelligent robots in grassland resource surveys.

To analyze the interaction between the surface soil and the soil-contacting component (65 Mn) in the camellia oleifera forest planting area in Changsha City, Hunan, China, in this study, we conducted discrete element calibration using physical and simulation tests. The chosen contact model was Hertz–Mindlin with JKR cohesion, with the soil repose angle as the response variable. The repose angle of the soil was determined to be 36.03° based on the physical tests. The significant influencing factors of the repose angle determined based on the Plackett–Burman test were the soil–soil recovery coefficient, soil–soil rolling friction coefficient, soil-65 Mn static friction coefficient, and surface energy of soil for the JKR model. A regression model for the repose angle was developed using the Box–Behnken response surface optimization method to identify the best parameter combination. The optimal parameter combination for the JKR model was determined as follows: surface energy of soil: 0.400, soil–soil rolling friction coefficient: 0.040, soil-65 Mn static friction coefficient: 0.404, and soil–soil recovery coefficient: 0.522. The calibrated discrete element parameters were validated through experiments on the repose angle and steel rod insertion. The results indicated that the relative errors obtained from the two verification methods were 2.44% and 1.71%, respectively. This research offers fundamental insights for understanding the interaction between soil and soil-contacting components and optimizing their design.

In response to the weaknesses of traditional agricultural equipment chassis with poor environmental adaptability and inferior mobility, a novel unmanned agricultural machinery chassis has been developed that can operate stably and efficiently under various complex terrain conditions. Initially, a new wheel-legged structure was designed by drawing inspiration from the motion principles of locust hind legs and combining them with pneumatic-hydraulic linkage mechanisms. Kinematic analysis was conducted on this wheel-legged configuration by utilizing the D-H parameter method, which revealed that its end effector has a travel range of 0-450 mm in the X-direction, 0-840 mm in the Y-direction, and 0-770 mm in the Z-direction, thereby providing the structural foundation for features such as independent four-wheel steering, adjustable wheel track, automatic vehicle body elevation adjustment, and maintaining a level body posture on different slopes. Subsequently, theoretical analysis and structural parameter calculations were completed to design each subsystem of the unmanned chassis. Further, kinematic analysis of the wheel-legged unmanned chassis was carried out using RecurDyn, which substantiated the feasibility of achieving functions like slope leveling and autonomous obstacle negotiation. An omnidirectional leveling control system was also established, taking into account factors such as pitch angle, roll angle, virtual leg deployment, and center of gravity height. Joint simulations using Adams and Matlab were performed on the wheel-legged unmanned chassis, comparing its leveling performance with that of a PID control system. The results indicated that the maximum absolute value of leveling error was 1.08 degrees for the pitch angle and 1.19 degrees for the roll angle, while the standard deviations were 0.216 47 degrees for the pitch angle and 0.176 22 degrees for the roll angle, demonstrating that the wheel-legged unmanned chassis surpassed the PID control system in leveling performance, thus validating the correctness and feasibility of its full-directional body posture leveling control in complex environments. Finally, the wheel-legged unmanned chassis was fabricated, assembled, and subjected to in-place leveling and ground clearance adjustment tests. The experimental outcomes showed that the vehicle was capable of achieving in-place leveling with response speed and leveling accuracy meeting practical operational requirements under the action of the posture control system. Moreover, the adjustable ground clearance proved sufficient to meet the demands of actual obstacle crossing scenarios.