In the context of modern agriculture transitioning towards automation and intelligence, the mechanization of tea harvesting has become an inevitable trend. As a major tea-producing country, China faces significant challenges in selectively picking tender tea shoots, which is a labor-intensive and time-consuming process. Traditional harvesting machines often employ a non-selective cutting method, which is unsuitable for high-quality tea production. Therefore, developing an intelligent harvesting system capable of selective picking is crucial. This study focuses on designing an end effector for tea shoot picking, leveraging the physical and mechanical properties of tea shoots to achieve efficient and selective harvesting. The end effector is a critical component of the harvesting manipulator, and its design directly impacts picking performance. Through mathematical modeling, parameter optimization, kinematic simulation, and field experiments, this research aims to provide a theoretical foundation and technical support for the development of tea shoot harvesting machinery.
The primary objective is to solve the selective picking problem for tea shoots, specifically targeting tender shoots like “one bud one leaf” and “one bud two leaves” while avoiding older leaves. The end effector must apply an appropriate clamping force to detach tender shoots without damaging them or picking older leaves. Based on prior experimental data, the clamping force required to break the petiole of tender shoots ranges from 2.76 N to 7.80 N, while older leaves require forces above 10 N. Thus, the end effector must be designed to exert a controlled force within this range. The design incorporates a clip-type mechanism that mimics human picking motions, ensuring minimal damage to the shoots and surrounding tea plants.
The overall harvesting system consists of a crawler base, machine vision module, microprocessor, drive module, assembly frame, multiple manipulators, and a collection device. Each manipulator includes a mechanical arm (with large and small arms) and the end effector attached at its tip. The end effector is responsible for the actual picking action through a clamping and lifting motion. This design allows for selective picking based on visual recognition of shoot positions, enhancing efficiency and reducing missed-picking rates. The end effector itself is a key innovation, as it enables precise force application tailored to tea shoot characteristics.
To design the end effector, I first analyzed the physical properties of tea shoots. Experiments were conducted to measure the breaking force of petioles for different shoot types. The average breaking force for “one bud one leaf” was found to be 3.08 N, with an upper limit of 3.51 N, while for “one bud two leaves,” it was 5.51 N, with an upper limit of 7.40 N. Older leaves had breaking forces exceeding 10 N. These values informed the target clamping force for the end effector. Additionally, the contact surface width of the clamping components was determined using regression analysis. The relationship between the clamping force \( y \) and the contact width \( x \) is given by:
$$ y = 0.64 \times (1.555x + 2.5238) $$
Solving for \( x \) with an average clamping force of 5.51 N yields \( x = 4 \) mm. Thus, the clamping components were designed with a contact area of 176 mm × 4 mm, and overall dimensions of 176 mm × 56 mm × 90 mm, using waterproof and oxidation-resistant aluminum alloy material.
The structural design of the end effector employs a trapezoidal four-bar mechanism, which ensures smooth and stable clamping motion. This mechanism includes symmetrically arranged rocker arms, gears, clamping components, a transmission shaft, a servo motor, and a housing. The servo motor drives the mechanism through a gear system, causing the clamping components to open and close. The four-bar mechanism parameters—lengths of the active rocker \( l_2 \), connecting rod \( l_3 \), follower rocker \( l_4 \), and fixed link \( l_1 \)—are critical for achieving the desired clamping force and motion trajectory. The mechanism is designed to operate with a maximum rotation angle of 30° to avoid over-picking or under-picking.
To optimize the end effector’s performance, I developed a mathematical model of the four-bar mechanism. Setting point B as the origin of the coordinate system, the displacement equations for point C (which corresponds to the clamping point E) are:
$$ x_C = l_4 \times \cos(\gamma – \beta) $$
$$ y_C = -l_4 \times \sin(\gamma – \beta) $$
where \( \gamma \) is the angle between BD and BC, and \( \beta \) is the angle between BD and the positive X-axis. The velocity and acceleration equations were derived to analyze motion stability and efficiency. The transmission angle \( \alpha_1 \), defined as the angle between the active rocker and the connecting rod, influences the mechanism’s efficiency. A larger transmission angle improves force transmission. The clamping force \( F’ \) at point C is related to the servo torque \( M \) and the force arm \( d_3 \):
$$ M = F’ \times d_3 $$
$$ d_3 = l_2 \times \sin(\alpha_1) $$
The target clamping force at point E is set to \( F_1 = 8 \) N, accounting for safety factors and multiple shoot pickings. Using MATLAB’s GUI module, I optimized the four-bar parameters to maximize the transmission angle, ensure a horizontal clamping trajectory, and achieve the desired force. The optimal parameters were found to be \( l_1 = 35 \) mm, \( l_2 = 60 \) mm, \( l_3 = 35 \) mm, and \( l_4 = 50 \) mm. The gear radius was set to 20 mm, and the housing dimensions to 150 mm × 70 mm.
The following table summarizes the key parameters of the end effector design:
| Parameter | Value | Description |
|---|---|---|
| Clamping component contact width | 4 mm | Width of the contact surface with tea shoots |
| Clamping component dimensions | 176 mm × 56 mm × 90 mm | Overall size of the clamping parts |
| Servo motor angular velocity | 8.055 rad/s | Speed of the servo driving the mechanism |
| Four-bar rotation angle | 30° | Maximum angle of rotation for clamping |
| Gear radius | 20 mm | Radius of the driving and driven gears |
| Optimal four-bar lengths | \( l_1 = 35 \) mm, \( l_2 = 60 \) mm, \( l_3 = 35 \) mm, \( l_4 = 50 \) mm | Lengths of the four-bar mechanism links |
| Target clamping force \( F_1 \) | 8 N | Maximum force applied at the clamping point |
Kinematic simulation was performed using SolidWorks software to validate the design. The virtual prototype of the end effector was assembled and analyzed in the Motion module. A servo angular velocity of 8.055 rad/s was applied, and a reverse pressure of 8 N was exerted at the clamping point to simulate picking resistance. The simulation results showed that the servo torque reached a maximum of 845 N·mm during clamping, closely matching the theoretical calculation of 840 N·mm. The acceleration at point C minimized at the clamping moment, indicating stable operation. The motion trajectory of the clamping components was arcuate and nearly horizontal, as intended. These results confirm the feasibility of the end effector design and its parameters.
Field experiments were conducted in a tea plantation to evaluate the practical performance of the end effector. A prototype was built using a DS32250 metal servo motor, and tests were performed on “one bud one leaf” and “one bud two leaves” shoots, as well as older leaves. Each test involved 72 picking attempts, and metrics such as missed-picking rate and shoot integrity rate were recorded. The missed-picking rate \( R \) and integrity rate \( R_1 \) are calculated as:
$$ R = \frac{m_2}{m + m_2} \times 100\% $$
$$ R_1 = \frac{m_1}{m} \times 100\% $$
where \( m \) is the total number of shoots picked, \( m_1 \) is the number of undamaged shoots, and \( m_2 \) is the number of missed shoots. The actual clamping force \( F \) was varied to assess its impact on picking quality. The results are summarized in the table below:
| Shoot Type | Clamping Force Range (N) | Average Missed-Picking Rate (%) | Average Integrity Rate (%) |
|---|---|---|---|
| One bud one leaf | 2.76 – 3.51 | 2.8 | 91 |
| One bud two leaves | 4.51 – 7.80 | 3.0 | 94 |
| Older leaves | 13.70 – 27.20 | 11.0 | 83 |
The experiments demonstrated that the end effector effectively selects tender shoots while avoiding older leaves when the clamping force is within the specified ranges. For “one bud one leaf,” the missed-picking rate was below 2.8% with an integrity rate of 91%, and for “one bud two leaves,” it was below 3% with an integrity rate of 94%. These outcomes meet the requirements for selective harvesting. Comparative tests between March and August showed that picking performance was better in March due to uniform shoot growth, highlighting the influence of seasonal factors on end effector efficiency.
In conclusion, this study successfully designed and optimized an end effector for tea shoot picking. The clip-type mechanism, based on a four-bar linkage, allows for controlled clamping forces that match the mechanical properties of tea shoots. Parameter optimization using MATLAB and kinematic simulation in SolidWorks ensured that the end effector operates smoothly and efficiently. Field tests validated the design, showing low missed-picking rates and high shoot integrity rates. This end effector provides a practical solution for selective tea harvesting and serves as a foundation for developing advanced tea picking robots. Future work could consider additional factors such as material friction, environmental resistance, and integration with machine vision systems for enhanced accuracy.
The development of this end effector represents a significant step towards automating tea harvesting. By addressing the selective picking challenge, it can reduce labor costs and improve yield quality. The methodologies employed—mathematical modeling, simulation, and experimental validation—can be extended to other agricultural applications. As robotics and AI continue to advance, end effectors like this will play a crucial role in transforming traditional farming into smart agriculture.
Further research could explore adaptive control algorithms for the end effector to adjust clamping force in real-time based on shoot size and maturity. Additionally, miniaturizing the design and improving energy efficiency would make it more suitable for large-scale deployment. Collaboration with tea growers for long-term testing could provide insights for refinements. Ultimately, the goal is to create a fully autonomous harvesting system that integrates multiple end effectors for high-throughput picking.
In summary, the end effector designed in this study demonstrates the potential of mechanical engineering and robotics in agriculture. It highlights the importance of understanding crop-specific characteristics and tailoring technology accordingly. As the demand for precision agriculture grows, innovations in end effector design will continue to drive progress in crop harvesting automation.