Spherical fruit and vegetable mechanical picking clamping force sensing method

Abstract

The invention discloses a spherical fruit and vegetable mechanical picking clamping force sensing method, and relates to the technical field of agricultural fruit and vegetable mechanical picking, real fruits and vegetables are selected for three-dimensional modeling, and a modeled model is subjected to 3D printing; a pressure sensor is arranged in the 3D printed fruit and vegetable model, so that the contact position of the spherical fruit and vegetable mechanical picking flexible hand and the grabbed object block is located at the center of the pressure sensor; a stepping motor for driving the flexible hand is controlled to gradually step by a preset stroke, and data of the pressure sensor are obtained after stepping by the preset distance each time; and determining the clamping force of the spherical fruit and vegetable mechanical picking flexible hand in different states according to the change trend of the data of the pressure sensor for many times. Real fruit and vegetable modeling is carried out, sensors are arranged in the fruit and vegetable model, the change conditions of force under different grabbing degrees when the fruit and vegetable model is grabbed by the flexible hand are collected in real time, and then proper grabbing force can be determined according to different fruits and vegetables when the spherical fruit and vegetable picking robot carries out real picking.

Description

Technical Field

[0001] The present application relates to the technical field of mechanical picking of agricultural fruits and vegetables, and in particular to a method for sensing the clamping force of mechanical picking of spherical fruits and vegetables. Background Art

[0002] As the field of fruit and vegetable picking robots continues to expand, robots need more complex and dexterous force perception and control capabilities to ensure efficient operation in unstructured agricultural environments. The harvesting end effector is one of the key components of fruit and vegetable picking robots. The flexible picking hand is the most widely used spherical fruit and vegetable picking end effector. The interaction force of the picking manipulator holding the spherical fruits and vegetables during the harvesting process determines the stability and reliability of fruit and vegetable picking. Excessive clamping force will damage the fruits and vegetables.

[0003] Real-time and accurate acquisition of the interaction force when the robot picks the fruit is a key link in the force perception and intelligent control of fruit and vegetable mechanical picking, and is also the core issue of efficient and low-loss mechanical picking of fruits and vegetables. Since the flexible robot has a large deformation during the picking process, traditional rigid pressure sensors are difficult to attach. At the same time, due to size limitations, the sensors cannot be simply arranged on the robot fingers or embedded in the robot fingers. Flexible film pressure sensors have been tried in many fruit and vegetable picking robot force perception solutions.

[0004] However, flexible film pressure sensors can measure surface pressure and interface contact force on flat surfaces or surfaces with small curvature changes, but are not suitable for spherical fruits and vegetables with large curvature changes. When the robot wraps around spherical fruits and vegetables for picking, the robot deforms significantly, and the flexible film pressure sensor cannot accurately measure the clamping force of each finger of the robot when picking fruits and vegetables. Summary of the invention

[0005] In order to solve the above technical problems, this application proposes the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a method for sensing the clamping force of mechanically picking spherical fruits and vegetables, comprising:

[0007] By selecting real fruits and vegetables for 3D modeling and then 3D printing the modeled models;

[0008] A pressure sensor is arranged in the 3D printed fruit and vegetable model so that the contact position between the spherical fruit and vegetable mechanical picking flexible hand and the grasped object is at the center of the pressure sensor;

[0009] Controlling the stepping motor driving the flexible hand to step a preset stroke successively, and acquiring data from the pressure sensor after each stepping of the preset distance;

[0010] The clamping force of the spherical fruit and vegetable mechanical picking flexible hand in different states is determined according to the changing trend of the pressure sensor data for multiple times.

[0011] In a possible implementation, the method of selecting real fruits and vegetables for three-dimensional modeling and performing 3D printing on the modeled models includes:

[0012] Select spherical fruit and vegetable samples with uniform quality, use 3D scanning to scan the fruits and vegetables to be tested and build models. The fruit and vegetable models have the shape and texture of real fruits and vegetables.

[0013] The model is segmented according to the number of fingers of the flexible hand through three-dimensional mapping software and divided into modules for 3D printing.

[0014] In a possible implementation, the pressure sensor is arranged in the 3D printed fruit and vegetable model so that the contact position between the spherical fruit and vegetable mechanical picking flexible hand and the grasped object is at the center of the pressure sensor, including:

[0015] Determining the force point of each finger when the flexible hand grasps the 3D fruit and vegetable model using different grasping postures;

[0016] Reserving a pressure sensor installation position at the divided module position corresponding to the force point;

[0017] The pressure sensors are arranged at the pressure sensor installation positions so that a line connecting a center point of each pressure sensor and a corresponding finger force point is perpendicular to a detection end surface of the pressure sensor.

[0018] In a possible implementation, determining the force point of each finger when the flexible hand grasps the 3D fruit and vegetable model using different grasping postures includes:

[0019] Determine the number of joints of the fingers and different grasping postures of the flexible hand in actual picking;

[0020] The position of the force point is determined according to the contact point between each joint and the 3D fruit and vegetable model in different grasping postures.

[0021] In a possible implementation, each joint determines one or more fulcrum points, and the number of the fulcrum points is dynamically adjusted according to the volume of the 3D fruit and vegetable model and the size of the flexible hand.

[0022] In a possible implementation, each module on which the pressure sensor is mounted has the same width, and an anti-collision gap is set between adjacent modules.

[0023] In a possible implementation, the stepping motor that controls and drives the flexible hand to step a preset stroke successively, and acquires data from the pressure sensor after each stepping of the preset distance, includes:

[0024] Determine the forward distance of the stepping motor outputting a positive step of 1 mm as the preset stroke;

[0025] Dividing the preset step into a plurality of sub-strokes, and controlling the stepping motor to stop after each sub-stroke;

[0026] The data of the pressure sensor is collected at each stopping point and after each stepping of a preset distance.

[0027] In a possible implementation, collecting data from the pressure sensor at each stop point and after each stepping of a preset distance includes:

[0028] Collect voltage signals of each channel of the pressure sensor in real time;

[0029] The collected voltage signal is transmitted to the host computer via the data acquisition card;

[0030] The data processing system of the host computer receives the voltage signal of the signal acquisition card, performs linear transformation and feature extraction on the voltage signal received corresponding to the acquisition channel, and obtains the feature vector of the voltage of each acquisition channel. The feature extraction includes extracting the average value, maximum value and minimum value of the voltage.

[0031] In the embodiment of the present application, real fruits and vegetables are modeled, and sensors are arranged in the fruit and vegetable model to collect in real time the changes in force at different grasping degrees when the flexible hand grasps the fruit and vegetable model. Therefore, the appropriate grasping force can be determined according to the different fruits and vegetables when the spherical fruit and vegetable picking robot is actually picking. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a flow chart of a method for sensing the clamping force of mechanically picking spherical fruits and vegetables provided in an embodiment of the present application;

[0033] Figure 2 A schematic diagram of a 3D printed model of fruits and vegetables provided in an embodiment of the present application;

[0034] Figure 3 A schematic diagram of placing pressure sensors in a 3D printed model of fruits and vegetables provided in an embodiment of the present application;

[0035] Figure 4 A schematic diagram of a pressure sensor provided in an embodiment of the present application;

[0036] Figure 5 A schematic diagram of a three-finger flexible hand picking gripping force sensing device provided in an embodiment of the present application;

[0037] Figure 6 The diagram of the change of different motor strokes and pressures at a height of 30 mm, 40 mm, and 50 mm from the flexible palm provided in the embodiment of the present application;

[0038] Figure 7 A diagram showing the variation of the clamping force of a single finger under different motor strokes of the three-finger flexible hand provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The present solution is described below in conjunction with the accompanying drawings and specific implementation methods.

[0040] See also Figure 1 The present embodiment provides a method for sensing the gripping force of mechanically picking spherical fruits and vegetables, including:

[0041] S101, selecting real fruits and vegetables to perform three-dimensional modeling and then performing 3D printing on the modeled models.

[0042] Spherical fruit and vegetable samples with uniform quality are selected, and the fruits and vegetables to be tested are scanned and modeled by three-dimensional scanning, and the fruit and vegetable models have real fruit and vegetable shapes and textures; the model is segmented according to the number of fingers of the flexible hand by three-dimensional mapping software and divided into modules for 3D printing, such as Figure 2 In this embodiment, the 3D printing material is white resin with a precision of 0.1 mm.

[0043] S102, placing a pressure sensor in the 3D printed fruit and vegetable model so that the contact position between the spherical fruit and vegetable mechanical picking flexible hand and the grasped object is at the center of the pressure sensor.

[0044] Since the spherical fruit and vegetable robot has different grasping postures according to the different growth postures of fruits and vegetables in actual operation, in this embodiment, the force point of each finger when the flexible hand grasps the 3D fruit and vegetable model in different grasping postures is first determined; then, according to the force point, a pressure sensor installation position is reserved at the divided module position; the pressure sensor is arranged at the pressure sensor installation position, see Figure 3 , so that the line connecting the center point of each pressure sensor and the corresponding finger force point is perpendicular to the detection end surface of the pressure sensor. Figure 4 The pressure sensor in this embodiment is a cylindrical resistive sensor, which can detect the tensile pressure in the direction of the sensing normal line, one end of which is a fixed end and the other end is a pressure detection end surface. The range of the pressure sensor is 0-20N and the accuracy is 0.1%.

[0045] Because the flexible hand includes multiple fingers, and each finger includes multiple joints, the force points of different joints are different under different grasping postures, so it is necessary to consider the different force points of different joints under a variety of different grasping postures. In this embodiment, in order to determine the force point of each finger when the flexible hand adopts different grasping postures to grasp the 3D fruit and vegetable model, the number of joints of the finger and the different grasping postures of the flexible hand in actual picking are first determined, and then the position of the force point is determined according to the contact point between each joint and the 3D fruit and vegetable model under different grasping postures. In this embodiment, the force point determined for each joint includes one or more, and the number of the force points is dynamically adjusted according to the volume of the 3D fruit and vegetable model and the size of the flexible hand.

[0046] In this embodiment, each module for installing the pressure sensor has the same width, which is set to 20-22 mm, to prevent mutual interference during the clamping process, and an anti-collision gap is set between adjacent modules, which is set to 4-5 mm. In this embodiment, the modules and the pressure sensor are combined and fixed by gluing.

[0047] S103, controlling the stepping motor driving the flexible hand to step a preset stroke successively, and acquiring data from the pressure sensor after each stepping of the preset distance.

[0048] The grasping action of the flexible hand is not only controlled by the motor, but also by the controller sending instructions to the stepper motor driver, which drives the motor to rotate. In this embodiment, the forward distance of the stepper motor rotation output in the positive step of 1mm is determined as the preset stroke; in order to prevent the deformation delay of the flexible picking manipulator from affecting the experimental accuracy, the preset stroke is divided into multiple sub-strokes, and the stepper motor is controlled to stop after each sub-stroke; the data of the pressure sensor is collected at each stop point and after each step preset stroke.

[0049] The pressure data acquisition system in this embodiment includes: a host computer, a data processing system and a data acquisition card. The data acquisition card is connected to the signal line of the pressure sensor through a wire, and is used to collect the voltage signals of each channel of the pressure sensor in real time, and transmit the collected voltage signals to the host computer through the data acquisition card. The data processing system receives the voltage signal of the signal acquisition card, performs linear transformation and feature extraction on the received voltage signal corresponding to the acquisition channel, and obtains the feature vector of the voltage of each acquisition channel. The feature extraction includes extracting the average value, maximum value, minimum value and other features of the voltage, which provides a basis for the fusion analysis of the pressure signal in the later stage.

[0050] S104, determining the clamping force of the spherical fruit and vegetable mechanical picking flexible hand in different states according to the changing trends of the pressure sensor data for multiple times.

[0051] The embodiment of the present application takes apple as an example but is not limited to apple, takes three-finger flexible hand as an example but is not limited to three-finger manipulator, and the present embodiment takes three-finger flexible hand as an example for modular design, and the method is universal for flexible hands with different structures (different flexible hands and fruits and vegetables have different modular designs). In the present embodiment, the midline of the adjacent longitudinal front modules and the sensor is 120°, which coincides with the midline of the three-finger flexible hand.

[0052] See also Figure 5 The pressure sensors include: a first pressure sensor 1, a second pressure sensor 2, a third pressure sensor 3, a fourth pressure sensor 4, a fifth pressure sensor 5, a sixth pressure sensor 6, a seventh pressure sensor 7, an eighth pressure sensor 8 and a ninth pressure sensor 9. The pressure sensors are all resistive sensors that can detect the pulling force in the direction of the sensor normal. The combined force of the first pressure sensor 1, the fourth pressure sensor 4 and the seventh pressure sensor 7 is used as the clamping force of the first mobile phone, the combined force of the second pressure sensor 2, the fifth pressure sensor 5 and the eighth pressure sensor 8 is used as the clamping force of the second finger, and the combined force of the third pressure sensor 3, the sixth pressure sensor 6 and the ninth pressure sensor 9 is used as the clamping force of the third finger.

[0053] In this embodiment, three groups of tests were conducted at 30mm, 40mm and 50mm from the bottom of the fruit and vegetable model to the palm. To ensure data accuracy, each group of tests was conducted three times to obtain the average value, simulating the clamping force at different gripping positions during the actual picking process. The test was conducted in the following steps:

[0054] First, calibrate the pressure sensor using a standard mass weight according to the instructions for use. Adjust the device to a suitable height, and send a command to the stepper motor driver through the controller. The driver drives the motor to rotate, so that the stepper motor moves forward 1mm. When the motor stops rotating, the pressure sensor data of the data acquisition card is recorded through the host computer. Continue to repeat the above steps, and each time the motor steps forward 1mm until the maximum stroke is reached. During the experiment, the data acquisition card is connected to the signal line of the pressure sensor through a wire, and these signals are transmitted to the host computer for analysis. In order to prevent the deformation delay of the flexible picking manipulator from affecting the accuracy of the experiment, the motor is stepped forward 1mm each time to complete it in multiple sections, and the pressure sensor data is collected through the host computer at each pause point to record the clamping force changes under different strokes.

[0055] After one set of tests was completed, the flexible hand was reset and the height of the apple model was adjusted, and another set of tests was performed at different heights. Figure 6As shown in the figure, the force-motor stroke relationship detected by different pressure sensors is shown at heights of 30mm, 40mm, and 50mm respectively. At a height of 30mm from the palm, the force recorded by the sensor gradually increases with the increase of displacement. The responses of different sensors in the figure are significantly different, and the highest force value detected is close to 20N, indicating that the clamping force is relatively large at this height. At a height of 40mm, the force increase trend is more stable than that of 30mm, but the response distribution of different sensors is still wide, and the maximum detection force is about 10N. This shows that the clamping force generally shows a downward trend with increasing height. At a height of 50mm, the force response further decreases, and the force values ​​of all sensors are less than 10N, showing a trend that the clamping force decreases with increasing height. The overall force-displacement curve is closer to smooth, indicating that the force response of the system at a higher position is more consistent. The experiment shows that the clamping force detection device can clearly show the clamping force changes of the pressure sensor in different positions, and can help analyze the distribution of clamping force in different positions.

[0056] In this embodiment, the combined force of the three sensors in the longitudinal direction of the sensor is used as the clamping force of the flexible hand. Although the direction of the clamping force changes with the movement of the finger, for the fin-shaped clamp, when the clamp angle reaches the maximum, the maximum angle between the normal direction and the sensor axis direction is about 12.5°. Therefore, assuming that the grasping force direction is consistent with the sensor axis direction, the maximum error caused by is only about 1-cos(12.5°)=2.4%, which can be ignored. The finger clamping force at different distances from the palm is as follows: Figure 7 As shown, the finger clamping force at different heights presents different growth trends, while the finger clamping force at the same height has almost the same growth trend, which proves that the clamping force detection device of the present invention can quickly and accurately reflect the clamping force of the flexible hand.

[0057] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0058] The above is only a specific implementation of the present application. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. The protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for sensing the gripping force of mechanically picking spherical fruits and vegetables, characterized in that: include: By selecting real fruits and vegetables for 3D modeling and then 3D printing the modeled models; A pressure sensor is arranged in the 3D printed fruit and vegetable model so that the contact position between the spherical fruit and vegetable mechanical picking flexible hand and the grasped object is at the center of the pressure sensor; Controlling the stepping motor driving the flexible hand to step a preset stroke successively, and acquiring data from the pressure sensor after each stepping of the preset distance; The clamping force of the spherical fruit and vegetable mechanical picking flexible hand in different states is determined according to the changing trend of the pressure sensor data for multiple times.

2. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 1, characterized in that: The method of selecting real fruits and vegetables for three-dimensional modeling and performing 3D printing on the modeled models includes: Select spherical fruit and vegetable samples with uniform quality, use 3D scanning to scan the fruits and vegetables to be tested and build models. The fruit and vegetable models have the shape and texture of real fruits and vegetables. The model is segmented according to the number of fingers of the flexible hand through three-dimensional mapping software and divided into modules for 3D printing.

3. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 1, characterized in that: The pressure sensor is arranged in the 3D printed fruit and vegetable model so that the contact position between the spherical fruit and vegetable mechanical picking flexible hand and the grasped object is at the center of the pressure sensor, including: Determining the force point of each finger when the flexible hand grasps the 3D fruit and vegetable model using different grasping postures; Reserving a pressure sensor installation position at the divided module position corresponding to the force point; The pressure sensors are arranged at the pressure sensor installation positions so that a line connecting a center point of each pressure sensor and a corresponding finger force point is perpendicular to a detection end surface of the pressure sensor.

4. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 3, characterized in that: The determining of the force point of each finger when the flexible hand grasps the 3D fruit and vegetable model using different grasping postures includes: Determine the number of joints of the fingers and different grasping postures of the flexible hand in actual picking; The position of the force point is determined according to the contact point between each joint and the 3D fruit and vegetable model in different grasping postures.

5. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 4, characterized in that: Each joint determines one or more fulcrum points, and the number of the fulcrum points is dynamically adjusted according to the volume of the 3D fruit and vegetable model and the size of the flexible hand.

6. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 3, characterized in that: The width of each module on which the pressure sensor is installed is the same, and anti-collision gaps are set between adjacent modules.

7. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 1, characterized in that: The stepping motor of the control driving the flexible hand to step through a preset stroke one by one, and obtaining data of the pressure sensor after each stepping through a preset distance, comprises: Determine the forward distance of the stepping motor outputting a positive step of 1 mm as the preset stroke; Dividing the preset stroke into a plurality of sub-strokes, and controlling the stepping motor to stop after each sub-stroke; The data of the pressure sensor is collected at each stopping point and after each stepping of a preset distance.

8. The method for sensing the gripping force of mechanical picking of spherical fruits and vegetables according to claim 7, characterized in that: The step of collecting the data of the pressure sensor at each stop point and each time the preset distance is stepped includes: Collect voltage signals of each channel of the pressure sensor in real time; The collected voltage signal is transmitted to the host computer via the data acquisition card; The data processing system of the host computer receives the voltage signal of the signal acquisition card, performs linear transformation and feature extraction on the voltage signal received corresponding to the acquisition channel, and obtains the feature vector of the voltage of each acquisition channel. The feature extraction includes extracting the average value, maximum value and minimum value of the voltage.

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