Transplanting machines have been widely used for the Chrysanthemum seedlings in smart agriculture. Challenges have remained on the unstable seedling gripping damage to seedlings. Fortunately, a three-needle concentrating seedling picker can be expected for the seedling extraction. However, current models often focus primarily on the growing medium rather than the root fixation. This study aims to construct the three-dimensional complex root system of Chrysanthemum seedlings using L-system theory. A numerical model was established to more accurately simulate the root architecture and its interaction with the surrounding medium during extraction. A EDEM-RecurDyn model was coupled with discrete element method and multi-body dynamics. The mechanical behavior of the seedlings was predicted to experimentally validate interaction between the complex root system, the growing medium, and the seeding needles during seedling extraction. A systematic investigation was made to explore the impact of various operational factors, such as the structure of seeding needles, seeding depth, seeding speed, and push plate stroke on the mechanical properties and damage levels of the seedlings. The seeding needle and operational parameters were finally optimized to minimize the seedling damage with the high success rates during seedling extraction. The results indicate that the seedling damage depended on the seeding depth, speed, and push plate stroke. Notably, the seeding depth increased the seedling displacement, which in turn increased the risk of damage, while the higher seeding speed caused more severe breakage of root system. The push plate stroke also dominated the movement of the seedling within the claw, the overall stability and force distribution during extraction. Multivariable regression was developed to predict the relationship between operational variables—seeding depth, seeding speed, and push plate stroke—and the seedling’s damage rate and integrity using Response Surface method. The optimal extraction parameters were determined to be an seeding depth of 20 mm, an seeding speed of 200 mm/s, and a push plate stroke of 5 mm. The extraction success rate reached 84.3%, with the seedling integrity rate of 93.10%. The optimal parameters were significantly reduced the seedling damage during extraction. Field trials were conducted to further validate the optimization for the high seedling quality. The operational settings were verified for the transplanting success rates after simulation. The optimal seeding needle was reduced seedling damage for the overall performance of the transplanting machine. In conclusion, the seedling extraction mechanisms were developed to consider the mechanical interactions among seeding needles, seedling root system, and the growing medium during extraction. Three-pronged seeding needle was coupled with the optimal parameters to highlight the seedling fixation, including root characteristics. The finding can offer the strong reference for the high transplanting success rates and seedling quality in transplanter.

Flexible operation and high handling stability are often required in the distributed electric drive mobile platform in special scenarios of facility horticulture. This study aims to design a mobile platform with distributed electric driven independently by four-wheel hub motors. An adaptive anti-slip control strategy was also proposed to improve the steering flexibility and stability. The dynamic model and Ackermann differential steering model were constructed for the distributed electric drive mobile platform. The target steering speed of each wheel was determined to combine the instantaneous center of speed and tire side deflection angle. Then, the time-varying adhesion coefficient was selected to improve the adaptability of the distributed electric drive mobile platform. A complex road identifier was designed using strong tracking adaptive untracked Kalman filter, in order to accurately estimate the road adhesion coefficient. Finally, an anti-slip controller was obtained with adaptive sliding mode. The optimal wheel slip rate was determined, according to the estimated road adhesion coefficient and control the wheel slip rate in real time, Finally, the self-adaptive anti-slip control was realized for the drive wheel of the distributed electric drive mobile platform in the facility horticulture scene. Both Carsim-MATLAB/Simulink co-simulation and vehicle tests of the distributed horticultural electric drive mobile platform were carried out to verify the effectiveness of the control strategy. The simulation results show that the estimated errors of the wheel to road adhesion coefficient were 0.009 and 0.033 on the unchanged and docked road surfaces, respectively, while 0.01 and 0.007 on the opposite road surfaces for left and right wheel, respectively; When using anti-slip control, the slip rate errors of the left wheel were 0.031, 0.015, and 0.038, respectively, and the slip rate errors of the right wheel were 0.026, 0.005, and 0.028, respectively. The test results show that the maximum slip rates of the left front, right front, left rear, and right rear wheels without anti-slip control were 0.80, 0.85, 0.90, and 0.93, respectively, indicating severe wheel slip. Under the same road conditions, there was a significant deviation in the wheel slip rate between adjacent moments, resulting in the slipping at all times unsuitable for the stable driving of the mobile platform. The adaptive anti-skid control with road recognition can be expected to accurately estimate the wheel road adhesion coefficient on complex roads, thus reducing the error of wheel slip rate. The overall estimated values were around 0.44 and 0.47 for the four-wheel road adhesion coefficient after the stable starting of the mobile platform. The maximum slip rates of the controlled wheel under two tested road conditions were approximately 0.69 and 0.68, respectively. The tire slip was greatly reduced during turning, in order to effectively improve the driving stability of the mobile platform.

The hub motor-driven mobile platform has gradually replaced the traditional centralized electric drive system. There is ever-increasing demand for flowers, fruits, vegetables, and tea horticulture for the new energy-powered operating equipment, particularly with high efficiency, energy saving, compact structure, independent and controllable advantages. Compared with direct-drive hub motors, the geared hub motors have been the mainstream of the drive unit for facility horticulture, due to the higher overload and torque output. The operational requirements of large load and torque can be fully met in the operation scenarios of facility horticulture. However, the geared hub motors are limited to the size of the space inside the hub. The high heat generation has seriously restricted the operational performance of electric drive mobile platforms. In this study, a decelerated inner-rotor axial flux hub motor was designed to meet the requirements of the low-speed and high-torque traction for electric-driven mobile platforms in facility horticulture operation scenarios. The electromagnetic finite element (FE) model was established to analyze the electromagnetic and loss features of the hub motor. Moreover, an improved magnetic-thermal coupling FE model of the hub motor was also constructed using the thermal network. The effect of temperature on the winding resistivity was considered to reduce the prediction accuracy of the simulation model, compared with the conventional magnetic-thermal bidirectional model. The prediction accuracy of the torque was improved by 5.33% using the improved model, compared with the bench tests. The correctness of the model was verified using the magnetic-thermal coupling FE model. A systematic investigation was made on the influence of the temperature and phase current on the torque of the motor. The experiments were also conducted on the external efficiency of the hub motor under peak operating conditions. The simulation results reveal that the average output torque of the motor decreased, as the steady-state temperature increased. The prediction value of torque was deviated by less than 1.56% from the measured at the motor speed of 800 r/min. The output torque of the motor also decreased with increasing motor temperature. The output torque of 15.23 N·m was reduced by 7.66% at the current of 32 A, compared with the conventional. The experimental results demonstrate that the power of the hub motor increased with the increase of the rotational speed in the middle and low-speed ranges. The peak power was up to 4.59 kW, while the torque almost remained constant. The output torque also decreased with the increase of motor temperature. The average output torque of the motor was linearly related to the phase current in the range of 0 to 20 A. The efficiency of the motor was up to 93.2% in the middle speed range with the torques in the range of 300 to 600 N·m. This finding can provide a direct guideline for the structural design of hub motors and the magnetic-thermal multi-physical field coupling performance analysis.

Protected horticulture is required for the high positioning accuracy and stability of mobile platforms. However, the electric drive mobile platforms can be often confined to object obstruction under the natural scenes. In this study, a high-precision positioning system was designed using an ultra-wide band (UWB) and inertial measurement unit (IMU). Additionally, an adaptive robust combination positioning algorithm (ARCPA) with Kalman filtering was developed to effectively improve positioning accuracy and stability. Firstly, a multi-sensor integrated positioning was constructed to combine UWB and IMU. Secondly, a differential distance-based sliding window was introduced to precisely detect nonline of sight (NLOS) errors in the positioning data of UWB. Thirdly, a cosine restart function was used to dynamically adjust the fading factor in real time, in order to reduce the interference of noise fluctuations in Kalman filtering. The accuracy and robustness of the filter were enhanced after optimization. Finally, a position dilution of precision (PDOP) weighted robust factor was incorporated to improve the resilience of the positioning system against noise and model disturbances under-protected horticulture scenes. An electric drive mobile platform and real-time positioning were constructed to verify the effectiveness of the integrated system. Then the simulation and real experiments of vehicle positioning were conducted in the typical protected horticulture. The experimental results demonstrate that the root-mean-square errors before and after UWB ranging correction under line-of-sight condition were 119.0 and 49.0 cm, respectively, and the ranging accuracy was improved by 58.8% after correction. The root mean squared error of the integrated positioning was only 6.63 cm, which was 81.92% lower than that of the single sensor (36.68 cm). The maximum error of positioning accuracy was also reduced by 88.89%. Therefore, this integrated positioning significantly reduced the impact of NLOS and geometric error on the positioning accuracy of the electric drive mobile platform for protected horticulture. Moreover, the root-mean-square error and the maximum positioning error of ARCPA were 17.70 and 44.44 cm, respectively. Furthermore, the root mean squared error of the improved system decreased by 50.15%, 74.63%, 60.01%, 60.88%, and 28.34%, respectively, compared with the Kalman filtering, unscented Kalman filtering, extended Kalman filtering, particle filtering, and adaptive robust Kalman filtering. Correspondingly, the maximum positioning error was then reduced by 66.83%, 73.67%, 69.07%, 71.2%, and 50.50%, respectively. The integrated positioning significantly improved the robustness of the electric drive mobile platform for protected horticulture. The finding can also provide a specific theoretical basis and plan for the positioning and navigation in a protected horticulture environment.