Flexible economic forest fruit picking end effector and force-position cooperative control method

Abstract

The invention belongs to the technical field of agricultural picking robots, particularly relates to a flexible economic forest fruit picking end effector and a force-position cooperative control method, and aims to enable the end effector to realize high-quality picking. Comprising a base, a grasping structure and a driving mechanism. The grasping structure comprises a driving finger, a first driven finger, a second driven finger and correspondingly connected bases. The grabbing structure further comprises a first gear adjusting plate, a second gear adjusting plate and a supporting plate. The grabbing structure is fixed to the base, the first passive finger base is connected with the first gear adjusting plate through a mortise and tenon joint structure, the second passive finger base is connected with the second gear adjusting plate through a mortise and tenon joint structure, and the supporting plate is connected with the first gear adjusting plate and the second gear adjusting plate and further connected with the active finger base. The driving mechanism is arranged in the base and comprises a micro servo electric cylinder and a push rod, the servo electric cylinder is connected with one end of the push rod, and the other end of the push rod is connected with the driving finger.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural picking robots, and in particular to a flexible economic fruit picking end effector and a force-position coordinated control method. Background Art

[0002] Against the backdrop of the development of smart agricultural automation, large-scale harvesting of economic fruits (such as citrus, apples, tomatoes, etc.) places higher demands on the adaptability and control accuracy of the end effector.

[0003] Existing end-effectors lack structural adaptability, leading to frequent fruit damage during the harvesting process. Furthermore, existing control strategies for end-effectors struggle to balance positioning speed with flexible contact force control, failing to meet the demands of high-precision harvesting. Summary of the Invention

[0004] The purpose of the present invention is to provide a flexible economic fruit picking end effector and a force-position coordinated control method, aiming to enable the end effector to achieve high-quality picking.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a flexible economic fruit picking end effector including: a base, a gripping structure and a driving mechanism; the gripping structure includes an active finger, a first passive finger and a second passive finger and correspondingly connected active finger bases, a first passive finger base and a second passive finger base; the gripping structure also includes a first gear adjustment plate, a second gear adjustment plate and a support plate; the gripping structure is fixed on the base, the first passive finger base is connected to the first gear adjustment plate through a mortise and tenon structure, the second passive finger base is connected to the second gear adjustment plate through a mortise and tenon structure, the support plate is connected to the first gear adjustment plate, the second gear adjustment plate, and also to the active finger base; the driving mechanism is arranged inside the base, including a micro servo electric cylinder and a push rod, the servo electric cylinder is connected to one end of the push rod, and the other end of the push rod is connected to the active finger.

[0006] The first and second passive finger bases of the flexible economic fruit picking end effector provided in the embodiment of the present application are connected to the gear adjustment plate through a mortise and tenon structure, which allows for rapid switching of multiple gears without the need for additional tools, greatly enhancing flexibility and efficiency, and solving the problem of poor adaptability of existing fixed claw structures. The active finger and the dual passive fingers form a triangular gripping structure, which, in conjunction with the rigid connection of the support plate, allows the three-claw opening angle to be adjusted via the gear adjustment plate during gripping, so that the contact force is evenly distributed on the surface of the fruit, helping to prevent damage to the fruit during the picking process.

[0007] In some embodiments, the flexible economic fruit picking end effector also includes a thin film pressure sensor, which is arranged on the side of the active finger. The thin film pressure sensor is configured to: connect to the controller, collect the gripping force data of the gripping structure and output it to the controller.

[0008] In some embodiments, the first gear adjustment plate and the second gear adjustment plate include multiple adjustment gears, and the distances between different adjustment gears and the support plate are different; the first passive finger base and the second passive finger base are configured to be able to be fixed on any level of adjustment gear through a mortise and tenon structure.

[0009] In some embodiments, the materials of the active finger, the first passive finger, and the second passive finger include soft materials with fin ray effects; and the base material includes carbon fiber 3D printing material.

[0010] In the second aspect, an embodiment of the present application provides a force-position coordinated control method for a flexible economic fruit picking end effector. Based on the flexible economic fruit picking end effector mentioned in the first aspect, the force-position coordinated control method for the flexible economic fruit picking end effector includes: S1: performing active finger kinematic analysis based on a simplified mechanical structure, deriving forward and inverse kinematic equations and establishing a force calculation model; S2: constructing a hybrid control architecture that coordinates self-disturbance rejection control and model predictive control, introducing a custom dynamics feedforward module and a custom linear dynamic compensator; S3: building an experimental platform to verify the effectiveness of the actuator and control method through a multi-index evaluation system.

[0011] In some embodiments, active finger kinematic analysis is performed based on a simplified mechanical structure, forward and inverse kinematic equations are derived, and a force calculation model is established, including: kinematic analysis constructs an equation system through a closed vector loop and the cosine theorem to determine the kinematic relationship between the push rod and the grasping position.

[0012] In some embodiments, in a hybrid control architecture, a custom dynamics feedforward module provides input to a model predictive control based on the relationship between force and displacement, and a custom linear dynamic compensator corrects the prediction deviation using velocity error.

[0013] In some embodiments, the hybrid control architecture estimates and compensates for system disturbances in real time through an extended state observer.

[0014] In some embodiments, the evaluation indicators of the experimental platform include steady-state arrival time, force tracking response time, and steady-state force tracking mean square error.

[0015] In some embodiments, the multi-index evaluation system performs dynamic performance quantitative analysis based on the deviation between force sensor data and control instructions.

[0016] Among them, the beneficial effects of the second aspect can refer to the first aspect and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a structural diagram of a flexible economic fruit picking end effector at an angle provided by an embodiment of the present application; Figure 2 This is a schematic diagram of a flexible economic fruit picking end effector from another angle provided in an embodiment of the present application; Figure 3 This is a flow chart of a force-position coordinated control method for a flexible economic fruit picking end effector provided in an embodiment of the present application; Figure 4 This is a schematic diagram of experimental data of a hybrid architecture provided by an embodiment of the present application under different gripping forces; Figure 5 This is an ablation experiment data result diagram provided in an embodiment of the present application; Figure 6 This is another ablation experiment data result diagram provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] In the description of the invention, it should be understood that the terms "upper," "lower," "left," "right," "front," "back," "inner," "outer," and the like, indicating directions or positional relationships, are based on the directions or relative positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of the invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific direction, be constructed, or operate in a specific direction. Therefore, they should not be construed as limitations on the invention. Unless otherwise specified, the above-mentioned directions may be flexibly set in actual application, provided that the relative positional relationships shown in the accompanying drawings are met.

[0020] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0021] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," and "communicated" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections. They may be directly connected, indirectly connected through an intermediary, or internally connected between two components. Those skilled in the art will understand the specific meanings of these terms in the present invention based on specific circumstances.

[0022] In embodiments of the present invention, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, article, or apparatus comprising the element.

[0023] In the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0024] Against the backdrop of the development of smart agricultural automation, large-scale harvesting of economic fruits (such as citrus, apples, tomatoes, etc.) places higher demands on the adaptability and control accuracy of the end effector.

[0025] The end effector is the part of the robot that directly contacts the work object and performs the task. In agricultural harvesting robots, the end effector is the core component that completes the harvesting task, responsible for grasping, cutting, and transferring the fruit. It needs to directly face the complex natural environment and fruits of different shapes and sizes. Therefore, its design directly determines the efficiency, accuracy, and degree of protection of the fruit. Existing end effectors suffer from structural incompatibilities, resulting in poor protection of the fruit during operation and often causing damage. Furthermore, current control methods struggle to achieve both rapid and precise positioning of the end effector and flexible control of contact force, failing to meet the stringent requirements of high-precision harvesting.

[0026] In view of this, the embodiment of the present application provides a flexible economic fruit picking end effector, for example, Figure 1 and Figure 2As shown, the end effector 100 includes a base 1, a gripping structure 2, and a drive mechanism 3. The gripping structure 2 includes an active finger 21, a first passive finger 22, and a second passive finger 23, as well as correspondingly connected active finger bases 24, first passive finger bases 25, and second passive finger bases 26.

[0027] The gripping structure 2 also includes a first gear adjustment plate 27, a second gear adjustment plate 28, and a support plate 29. The gripping structure 2 is fixed to the base 1. The first passive finger base 25 is connected to the first gear adjustment plate 27 via a mortise and tenon structure. The second passive finger base 25 is connected to the second gear adjustment plate 28 via a mortise and tenon structure. The support plate 29 is connected to the first and second gear adjustment plates 27 and 28, as well as to the active finger base 24. The drive mechanism 3 is disposed within the base 1 and includes a micro servo cylinder 31 and a push rod 32. The servo cylinder 31 is connected to one end of the push rod 32, and the other end of the push rod 32 is connected to the active finger 21.

[0028] The active finger 21, connected to the drive mechanism 3 through a micro-servo cylinder 31, drives a push rod 32 to control its opening and closing, collaborating with the first and second passive fingers 22, 23 to pick and discard the fruit. The first and second passive fingers 22, 23 are connected to the gear adjustment plate via a mortise and tenon structure, enabling quick, plug-in gear switching along the plate's slots.

[0029] In some embodiments, the first gear adjustment plate 27 and the second gear adjustment plate 28 include multiple adjustment gears, and the distances between different adjustment gears and the support plate 29 are different; the first passive finger base 25 and the second passive finger base 26 are configured to be able to be fixed on any level of adjustment gear through a mortise and tenon structure.

[0030] Illustratively, the first gear adjustment plate 27 and the second gear adjustment plate 28 include four adjustment gears, and the distances between the first gear adjustment plate 27 and the second gear adjustment plate 28 and the active finger 21 decrease gradually, which can flexibly adapt to fruits of different sizes.

[0031] The different distances between the different adjustment levels and the support plate 29 mean that the distances between the first and second passive fingers 22, 23 and the active finger 21 also vary. This can be adjusted based on actual conditions, such as the size of the fruit. The first and second gear adjustment plates 27, 28 are secured to the first and second passive finger bases 25, 26 via fixing elements 20, forming a "convex-concave" mortise-and-tenon structure. The tenons of the first and second passive fingers 22, 23 fit into the mortises of the gear adjustment plates, enabling switching between different gears.

[0032] As a possible implementation method, the flexible economic fruit picking end effector also includes a thin film pressure sensor, which is arranged on the side of the active finger. The thin film pressure sensor is configured to: connect to the controller, collect the gripping force data of the gripping structure and output it to the controller.

[0033] For example, the micro servo cylinder 31 (hereinafter referred to as the cylinder) is a LASF16-024D model with a stroke of 16 mm, a peak thrust of 105 N, a repeatability of ±0.03 mm, and supports a 50 Hz control signal. The thin film pressure sensor has a range of 20 g to 6 kg.

[0034] Thin-film pressure sensors, positioned close to the gripping point, collect real-time contact force data between the gripping structure and the fruit and feed it back to the controller, forming a closed-loop "force sensing, control, and regulation" system. This design enables the controller to dynamically adjust the drive mechanism output based on the actual gripping force, avoiding fruit damage or unstable gripping caused by improper gripping force in traditional open-loop control. This achieves the coordinated optimization of flexible contact and stable gripping.

[0035] In some embodiments, the material of the active finger, the first passive finger, and the second passive finger includes a soft material with a fin-ray effect, which can provide a stable gripping force for the fruit within a diameter range of 10-100 mm. The base material includes a carbon fiber 3D printing material, such as Raise3D Industrial PA12 CF+, a nylon 6,12 (PA6,12; Nylon6,12)-based carbon fiber reinforced composite material. The soft material forms a bionic contact surface through the fin-ray effect, which can adaptively conform to the curvature of the fruit surface during grasping, evenly distributing the contact force to the fruit skin, avoiding the concentrated stress damage of traditional rigid materials, ensuring grip stability, and buffering contact impact through material deformation. Carbon fiber 3D printing material combines the high strength characteristics of carbon fiber with the complex structure forming capabilities of 3D printing, allowing the base to maintain rigid support while significantly reducing weight.

[0036] The present application also provides a method for coordinated force and position control of a flexible economic fruit picking end effector. For example, referring to Figure 3 , the method comprising: S1: Perform active finger kinematic analysis based on a simplified mechanical structure, derive forward and inverse kinematic equations, and establish a force calculation model.

[0037] In some embodiments, active finger kinematic analysis is performed based on a simplified mechanical structure, forward and inverse kinematic equations are derived, and a force calculation model is established, including: kinematic analysis constructs an equation system through a closed vector loop and the cosine theorem to determine the kinematic relationship between the push rod and the grasping position.

[0038] For example, based on a simplified mechanical structure, the forward and inverse kinematic equations are established using closed vector loop properties and the law of cosines to clarify the relationship between the push rod and the end effector's grasping position, velocity, and acceleration. The forces acting on the active finger are analyzed, and a force calculation formula is derived based on the principle of torque balance. A geometric model of the end effector is constructed in Matlab to simulate the push rod and finger end motion. Under specific initial conditions, the position, velocity, and acceleration of the relevant points are recorded and compared with the results calculated using the kinematic formulas to verify the accuracy of the forward and inverse kinematic calculations.

[0039] S2: Build a hybrid control architecture that combines active disturbance rejection control with model predictive control, and introduce a custom dynamic feedforward module and a custom linear dynamic compensator.

[0040] A staged force-position coordinated control strategy is employed. Based on the target fruit geometry, an inverse kinematics model is used to calculate the optimal gripping stroke of the end-effector's active finger. This allows the expected motion trajectory and required dynamic load of the actuator rod to be deduced. A hybrid control architecture, based on the collaboration of active disturbance rejection control (ADRC) and model predictive control (MPC), is constructed, incorporating a custom dynamic feedforward module (CPV), an extended state observer (ESO), and a custom linear dynamic compensator (LSEF). The specific mathematical models and parameter settings for the ESO, CPV, LSEF, and MPC modules are determined to achieve precise staged force-position coordinated control.

[0041] In the hybrid control architecture, a custom dynamics feedforward module provides input to the model predictive control based on the relationship between force and displacement, while a custom linear dynamic compensator corrects the prediction deviation using velocity error. The hybrid control architecture uses an extended state observer to estimate and compensate for system disturbances in real time.

[0042] Specifically, ESO, as the core unit for disturbance observation and dynamic decoupling, expands the system's unmodeled dynamics (friction nonlinearity, inertial coupling) into additional state variables to achieve real-time estimation and compensation of the total disturbance. For the end effector transmission system, a third-order ESO is constructed, and its dynamic equation is as follows: in, are the actual position and actual velocity of the observation system, is the state expansion, which represents the total disturbance of the system, including friction, external interference and model error. is the output instruction of MPC, are the nonlinear observation gains respectively.

[0043] In traditional active disturbance rejection control (ADRC) architectures, a tracking differentiator module is typically used to generate a smooth reference trajectory and extract a differential signal. However, in precision transmission scenarios, this module is susceptible to degraded dynamic performance due to phase delay and noise sensitivity. To address this, this application utilizes a custom dynamic feedforward module (CPV) to calculate the displacement x and velocity v under the action of force F using corresponding formulas, which serve as inputs for model predictive control (MPC). This module effectively improves MPC's optimization efficiency and dynamic responsiveness while retaining the interference rejection advantages of ADRC.

[0044] in, , are the initial position and initial velocity, t is the time, and a is the acceleration.

[0045] As a possible implementation method, a custom linear dynamic compensator, as a collaborative hub between MPC and ESO, assumes the dual functions of dynamic error compensation and disturbance feedforward suppression. Its mathematical model can be described as: in, is the reference speed predicted by MPC, is the speed observed by ESO, k is the speed error gain, F is the force measured by the sensor, and m is the equivalent mass of the electric cylinder.

[0046] As the core optimization unit of the ADRC-MPC hybrid architecture, the MPC module achieves the coordinated optimization of high-precision trajectory tracking and strong disturbance rejection through rolling-horizon optimization and disturbance feedforward mechanisms. This module uses the theoretical undisturbed position x and velocity v generated by the CPV module as dual reference inputs. MPC builds a prediction model based on Newton-Euler dynamics, and its state equation is expressed as: in, and are the position and velocity states of the kth step respectively, is the control period, m is the equivalent mass of the electric cylinder, is the control quantity to be optimized. Then construct the quadratic cost function in the prediction time domain N: Among them, Q and R are the weights of state tracking and input change rate respectively. is the total disturbance estimate of the ESO output, which is obtained by Realize disturbance feedforward compensation.

[0047] S3: Build an experimental platform and verify the effectiveness of the actuator and control method through a multi-index evaluation system.

[0048] In some embodiments, the evaluation indicators of the experimental platform include steady-state arrival time, force tracking response time, and steady-state force tracking mean square error.

[0049] The steady-state arrival time is defined as the time interval from the moment force control is initiated to the point where the absolute difference between the control force and the steady-state force for three consecutive steps is less than 0.1 N. The force tracking response time is determined by the time interval from the moment force control is initiated to the point where the absolute difference between the force sensor reading and the control command force for three consecutive steps is less than 0.1 N. The mean square error of steady-state force tracking is based on data within a 10-20 second time window and is calculated as follows: In some embodiments, a multi-metric evaluation system quantifies dynamic performance based on the deviation between force sensor data and control instructions. By analyzing the deviation between the real-time measured data collected by the force sensor and the control instructions, the end-effector's grasping performance is converted into quantifiable dynamic indicators (such as steady-state arrival time and force tracking response time). This data-driven approach intuitively presents the response characteristics of the control strategy under different operating conditions. For example, the deviation curve clearly identifies the entire process of the system's transition from dynamic to steady state after force control is activated, providing precise targeting for performance optimization.

[0050] As an example, an experimental platform was constructed. With the electric cylinder unloaded, incremental thrust forces ranging from 1N to 30N were applied. Push rod position data was collected, and the cylinder's equivalent mass m was calculated using quadratic polynomial fitting, differentiation, and Newton's second law. A standard apple with a diameter of 55.59mm was used as the test object. A target gripping force was set, and the end effector was subjected to a two-stage control strategy for grasping. Metrics such as steady-state reach time, force tracking response time, and steady-state force tracking mean square error (MSE) were quantitatively analyzed to evaluate the effectiveness of the control strategy.

[0051] Reference Figure 4 , Figure 4 The experimental data of the hybrid structure under different grip forces are given in the following table. Figure 4 As can be seen, the hybrid architecture has an average steady-state arrival time of 3.08s, an average force tracking response time of 0.85s, and an average steady-state force tracking mean square error of 0.00397N². This series of quantitative indicators fully verifies the three core characteristics of the control system: First, the CPV module's model feedforward compensation mechanism gives the system rapid response capabilities, with response times controlled within 1 second under 90% of operating conditions; second, the collaborative working mode of the ESO disturbance observer and the LSEF linear compensator ensures high-precision force tracking control, with the steady-state error stably maintained within the range of ±0.1N; third, the MPC's multi-step predictive optimization mechanism significantly improves force tracking efficiency and effectively shortens force tracking time.

[0052] This application also verifies the role of MPC and LSEF in the hybrid control architecture through ablation experiments. For example, refer to Figure 5 and Figure 6 ,This experiment compares the performance of the hybrid control architecture with the ,CMP, ESO and LSEF modules intact, the hybrid control architecture ,with the MPC removed, and the hybrid control architecture with the LSEF removed.

[0053] Reference Figure 5 Compared with the complete hybrid control architecture, ten sets of experimental data under different gripping forces after removing the MPC module show that the system steady-state establishment time is extended by an average of 60.06%, and the force tracking response time deteriorates by 323.5%, showing the important role of the multi-step predictive optimization mechanism of the MPC module in improving the dynamic performance of the system, especially in accelerating the convergence process and improving the force tracking response time.

[0054] It should be noted that the steady-state force tracking mean square error does not change significantly compared to the complete architecture. This phenomenon reveals that the linear compensation mechanism of the LSEF module can effectively maintain the steady-state control accuracy of the system in the absence of MPC predictive optimization, verifying the effectiveness of the LSEF module design.

[0055] Reference Figure 6 Compared with the complete hybrid control architecture, the LSEF module is removed and replaced with a traditional nonlinear state error feedback (NLSEF) controller. Ten sets of experimental data under different grip forces show that: the system steady-state establishment time is shortened by 0.088%, the force tracking response time is extended by 0.024%, and the average error is also improved to a certain extent.

[0056] This result demonstrates both the potential advantages of nonlinear control in specific scenarios and its inherent shortcomings. While the NLSEF module leverages a nonlinear feedback mechanism to achieve more precise steady-state control, the number of parameters required for adjustment (three or more) is far greater than that of the LSEF module (only one). This leads to a series of problems in practical engineering applications: First, the parameter tuning process is cumbersome and time-consuming. Second, the parameters are poorly adaptable under different operating conditions. Third, system stability is more sensitive to parameter fluctuations. In contrast, the LSEF module, with its simple linear architecture and single adjustment parameter, significantly improves the system's engineering applicability and parameter robustness while ensuring control performance.

[0057] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0058] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A flexible economic fruit picking end effector, characterized in that: include: base, gripping structure and drive mechanism; The gripping structure includes an active finger, a first passive finger and a second passive finger, and a correspondingly connected active finger base, a first passive finger base and a second passive finger base; The gripping structure further includes a first gear adjustment plate, a second gear adjustment plate, and a support plate; the gripping structure is fixed to the base, the first passive finger base is connected to the first gear adjustment plate via a mortise and tenon structure, the second passive finger base is connected to the second gear adjustment plate via a mortise and tenon structure, the support plate is connected to the first gear adjustment plate, the second gear adjustment plate, and also to the active finger base; The driving mechanism is arranged inside the base, and includes a micro servo electric cylinder and a push rod. The servo electric cylinder is connected to one end of the push rod, and the other end of the push rod is connected to the active finger.

2. The flexible economic fruit picking end effector according to claim 1 is characterized in that: It also includes a thin film pressure sensor, which is arranged on the side of the active finger. The thin film pressure sensor is configured to: connect with a controller, collect gripping force data of the gripping structure and output it to the controller.

3. The flexible economic fruit picking end effector according to claim 1 is characterized in that: The first gear adjustment plate and the second gear adjustment plate include multiple adjustment gears, and the distances between different adjustment gears and the support plate are different; the first passive finger base and the second passive finger base are configured to be able to be fixed on any level of adjustment gear through a mortise and tenon structure.

4. The flexible economic fruit picking end effector according to claim 1 is characterized in that: The active finger, the first passive finger and the second passive finger are made of a soft material having a fin effect; The base material includes carbon fiber 3D printing material.

5. A force-position coordinated control method, based on the flexible economic fruit picking end effector according to any one of claims 1 to 4, characterized in that: include: S1: Perform active finger kinematic analysis based on a simplified mechanical structure, derive forward and inverse kinematic equations, and establish a force calculation model; S2: Build a hybrid control architecture that combines active disturbance rejection control with model predictive control, introducing a custom dynamics feedforward module and a custom linear dynamic compensator. S3: Build an experimental platform and verify the effectiveness of the actuator and control method through a multi-index evaluation system.

6. The force-position coordinated control method according to claim 5, characterized in that: The active finger kinematics analysis based on the simplified mechanical structure, the derivation of forward and inverse kinematics equations and the establishment of a force calculation model include: The kinematic analysis constructs an equation system by using a closed vector loop and the law of cosines to determine the kinematic relationship between the push rod and the grasping position.

7. The force-position coordinated control method according to claim 5, characterized in that: In the hybrid control architecture, a custom dynamics feedforward module provides input for model predictive control based on the relationship between force and displacement, and a custom linear dynamic compensator corrects the prediction deviation through velocity error.

8. The force-position coordinated control method according to claim 7, characterized in that: The hybrid control architecture estimates and compensates for system disturbances in real time through an extended state observer.

9. The force-position coordinated control method according to claim 5, characterized in that: The evaluation indicators of the experimental platform include steady-state arrival time, force tracking response time and steady-state force tracking mean square error.

10. The force-position coordinated control method according to claim 5, characterized in that: The multi-index evaluation system performs dynamic performance quantitative analysis based on the deviation between force sensor data and control instructions.

Images