A rigid-flexible manipulator posture measuring device based on a six-dimensional force sensor of flexible piezoresistive material

Abstract

The present application relates to the technical field of mechanical arm posture measurement, and discloses a rigid and flexible mechanical arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor, which comprises a flexible six-dimensional force sensor and a Bluetooth module, the flexible six-dimensional force sensor is installed at the joint of the mechanical arm through bolts, and the Bluetooth module is installed in the flexible six-dimensional force sensor; the flexible six-dimensional force sensor comprises, from top to bottom, a flexible top cover, a sponge pad, an encapsulating film, a flexible piezoresistive unit, a flexible printed circuit board and a flexible base, and the flexible piezoresistive unit is connected with the Bluetooth module. When the posture of the mechanical arm changes, the mechanical arm transmits external force to the flexible six-dimensional force sensor, the flexible piezoresistive unit generates a response under stress, and an electric resistance signal is output through the Bluetooth module. The present application can complete dynamic real-time measurement of space six-dimensional force and can be applied to both rigid and flexible mechanical arms. Six-dimensional force monitoring of the mechanical arm is completed through the flexible sensor, and then posture measurement of the mechanical arm is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of robot arm posture measurement, and in particular to a rigid and flexible robot arm posture measurement device based on a six-dimensional force sensor made of flexible piezoresistive material. Background Art

[0002] When various mechanical devices perform operational tasks, tactile sensing is required to provide feedback on force and torque information in the x, y, and z directions. For example, when measuring the posture of a robotic arm during movement.

[0003] Generally speaking, piezoresistive, piezoelectric, and capacitive sensors can all sense pressure stimuli. Traditional six-dimensional force sensors are usually based on rigid materials. Although they are highly integrated and miniaturized and can detect six-dimensional forces, they are difficult to adapt to various deformations of flexible interfaces. Flexible sensors are usually made of soft materials or stretchable elastic materials to provide proprioception and external perception capabilities for soft structures. Flexible sensors have good flexibility, extensibility, ductility, and stability, and their structural forms are flexible and diverse. At the same time, flexible sensors exhibit good conductivity and sensitivity under compression and extension. At present, flexible sensors based on various mechanisms such as resistance and capacitance have been used to measure external contact information such as pressure and touch of soft robots, but there is relatively little research on force sensors that can be used to measure the bending posture of flexible robotic arms.

[0004] Therefore, the present invention provides a rigid and flexible robotic arm posture measurement device based on a six-dimensional force sensor made of flexible piezoresistive material. Summary of the Invention

[0005] The purpose of the present invention is to provide a rigid and flexible robotic arm posture measurement device based on a six-dimensional force sensor made of flexible piezoresistive material, aiming to solve the above problems.

[0006] The present invention provides a rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor, comprising: a flexible six-dimensional force sensor and a Bluetooth module, wherein the flexible six-dimensional force sensor is mounted on the joint of the robotic arm through bolts, and the Bluetooth module is mounted inside the flexible six-dimensional force sensor;

[0007] The flexible six-dimensional force sensor includes a flexible top cover, a sponge pad, a force response layer and a flexible base;

[0008] The flexible top cover is a circular structure with four protrusions on the bottom. The flexible base is a circular structure with four grooves on the top. The grooves match the protrusions to form an interlocking structure. The sponge pad and the force response layer are arranged between the flexible top cover and the flexible base.

[0009] The force response layer includes an encapsulating film, a flexible piezoresistive unit and a flexible printed circuit board; the flexible printed circuit board is a layered structure with four U-shaped grooves, and the flexible printed circuit board matches the flexible base; the flexible piezoresistive unit is adhered to the top and side of the U-shaped groove of the flexible printed circuit board; the encapsulating film is used to encapsulate the flexible piezoresistive unit on the flexible printed circuit board; the sponge pad is arranged on the encapsulating film, and the sponge pad is arranged in the gap between the flexible top cover bumps; the flexible piezoresistive unit is connected to the Bluetooth module.

[0010] Preferably, the thickness of the sponge pad is the same as that of the flexible piezoresistive unit, and the sponge pad is used to prevent a gap from being generated between the flexible top cover and the flexible base.

[0011] Preferably, twelve flexible piezoresistive units are provided on the flexible printed circuit board, each of the flexible piezoresistive units is provided with an electrode, one lead of each electrode is integrated into the inner interface of the flexible piezoresistive unit, and the other lead of each electrode is integrated into the outer interface of the flexible piezoresistive unit.

[0012] Preferably, the six-dimensional force of the flexible six-dimensional force sensor includes:

[0013] A three-dimensional coordinate system is established with the center of the upper surface of the flexible top cover as the origin, and the six-dimensional forces are: positive pressure Fx in the X-axis direction, positive pressure Fy in the Y-axis direction, positive pressure Fz in the Z-axis direction, torque Mx in the X-axis direction, torque My in the Y-axis direction, and torque Mz in the Z-axis direction.

[0014] Preferably, the specific steps of the device measurement method are:

[0015] S1, use the six-dimensional force mechanical testing system to apply six-dimensional forces Fx, Fy, Fz, Mx, My, and Mz to the flexible six-dimensional force sensor for calibration, and use an impedance analyzer to connect the interface of the flexible piezoresistive unit to collect the output resistance signal;

[0016] S2, installing the flexible six-dimensional force sensor on the joint of the robotic arm through bolts, so that the flexible top cover and the flexible base of the flexible six-dimensional force sensor are connected to the robotic arm;

[0017] S3, the posture of the robotic arm changes, the force is transmitted to the flexible piezoresistive unit through the robotic arm, and the flexible piezoresistive unit outputs a resistance signal through the Bluetooth module;

[0018] S4: Calculate the actual six-dimensional force at the joint when the robotic arm moves based on the output resistance signal.

[0019] Preferably, the step S4 calculates the actual six-dimensional force at the joint when the robotic arm moves according to the output resistance signal, including:

[0020] Repeat step S1 multiple times to obtain calibration data, which includes six-dimensional force and calibration resistance signals. The calibration data is divided into a training set and a test set. The training set and the test set are used to train and test the deep neural network model to obtain a trained deep neural network model. The output resistance signal is input into the trained deep neural network model to obtain the output result as the actual six-dimensional force at the joint when the robotic arm moves;

[0021] Among them, the construction process of the deep neural network model is:

[0022] A41, normalizes the calibration data, scales the calibration data to the range of [-1, 1], and performs normalization according to the following formula;

[0023]

[0024] Where x' i is the value after normalization of the input i-th calibration data, x i is the value of the input i-th calibration data before normalization, x min is the minimum value of the calibration data range, x max is the maximum value of the calibration data range;

[0025] A42, in MATLAB, use the layers function to define the architecture of a deep neural network model;

[0026] Construct a network with 12 input nodes and six output nodes, and use the ReLU function as the hidden layer activation function:

[0027] ReLU=max(0,x i );

[0028] A43: Use the trainingOptions function to configure training options, including learning rate, number of iterations, and validation set, and use the trainNetwork function to train a deep neural network model.

[0029] A44: The mean square error is used as the error of the deep neural network model to evaluate the calculation formula:

[0030]

[0031] Where: e is the mean square error, y i is the output of the i-th dimension in the training set, y' i is the output of the i-th dimension of the output layer.

[0032] Preferably, the step S4 calculates the actual six-dimensional force at the joint when the robotic arm moves according to the output resistance signal, including:

[0033] B41, convert the resistance signal into a voltage signal matrix V, and determine the calibration force matrix F through a static calibration algorithm c and the calibration voltage signal matrix V, and determine the calibration force matrix F c The mapping relationship matrix C with the calibration voltage signal matrix V;

[0034] Wherein, the calibration force matrix F c , the relationship between the calibration voltage signal matrix V and the mapping relationship matrix C is as follows:

[0035] F c =CV;

[0036] B42: Calculate the mapping relationship matrix C using the least squares method;

[0037] C=(V T ×V)\(V T ×F c T );

[0038] In the above formula, F c is an N×6 matrix, V is an N×12 matrix, N is the number of sample points, V T and V and F respectively c The transpose of

[0039] B43: According to the mapping relationship matrix C and the electrical signal V actually measured by the sensor u Calculate the actual six-dimensional force F u , calculate the actual six-dimensional force F u The formula is as follows:

[0040] F u =CV u .

[0041] Preferably, the step S4 calculates the actual six-dimensional force at the joint when the manipulator moves according to the output resistance signal, and further includes: determining the actual six-dimensional force F u With the calibration force matrix F c The difference between them is used to determine the comprehensive nonlinear deviation of the flexible six-dimensional force sensor;

[0042] ΔL=|F c -F u |;

[0043] Where ΔL is the comprehensive nonlinear deviation.

[0044] Compared with the existing technology, the beneficial effects of the present invention are that the size of the present invention can be customized according to the size of the robotic arm, and the device can be applied to robotic arms of different sizes; the overall structure and piezoresistive unit of the present invention are both made of flexible materials, which can meet the application requirements of rigid robotic arms and flexible robotic arms at the same time; the present invention can complete the dynamic six-dimensional force acquisition at the joints when the posture of the robotic arm changes, so as to complete the posture measurement of the robotic arm. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0046] Figure 1 This is a structural schematic diagram of a rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to the present invention;

[0047] Figure 2 Schematic diagram of the structure of the flexible six-dimensional force sensor in an embodiment of the present invention.

[0048] In the figure, 1. Flexible top cover; 2. Sponge pad; 3. Encapsulation film; 4. Flexible piezoresistive unit; 5. Flexible printed circuit board; 6. Flexible base; 7. Robotic arm; 8. Flexible six-dimensional force sensor; 9. Bluetooth module. DETAILED DESCRIPTION

[0049] 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 this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0050] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0051] 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 number 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. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0052] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0053] like Figure 1-Figure 2 As shown, the present invention provides a rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor, comprising: a flexible six-dimensional force sensor 8 and a Bluetooth module 9, wherein the flexible six-dimensional force sensor 8 is mounted at the joint of the robotic arm 7 by bolts, and the Bluetooth module 9 is mounted inside the flexible six-dimensional force sensor 8;

[0054] The flexible six-dimensional force sensor 8 includes a flexible top cover 1, a sponge pad 2, a force response layer and a flexible base 6;

[0055] The flexible top cover 1 is a circular structure with four protrusions on the bottom. The flexible base 6 is a circular structure with four grooves on the top. The grooves match the protrusions to form an interlocking structure. The sponge pad 2 and the force response layer are arranged between the flexible top cover 1 and the flexible base 6.

[0056] The force response layer includes an encapsulating film 3, a flexible piezoresistive unit 4 and a flexible printed circuit board 5; the flexible printed circuit board 5 is a layered structure with four U-shaped grooves, and the flexible printed circuit board 5 matches the flexible base 6; the flexible piezoresistive unit 4 is pasted on the top and side of the U-shaped groove of the flexible printed circuit board 5; the encapsulating film 3 is used to encapsulate the flexible piezoresistive unit 4 on the flexible printed circuit board 5; the sponge pad 2 is arranged on the encapsulating film 3, and the sponge pad 2 is arranged in the gap between the bumps of the flexible top cover 1; the flexible piezoresistive unit 4 is connected to the Bluetooth module 9.

[0057] In this embodiment, the force response layer is designed to match the size of the flexible top cover 1 and the flexible base 6, and is composed of an encapsulating film 3, a flexible piezoresistive unit 4, and a flexible printed circuit board 5. It is mounted on top of the flexible base 6 by adhesive tape.

[0058] It is understandable that the flexible top cover 1 and the flexible base 6 are made of polydimethylsiloxane (PDMS) material, and the encapsulating film 3 is made of polytetrafluoroethylene (PTFE) material.

[0059] In some embodiments of the present application, the thickness of the sponge pad 2 is the same as that of the flexible piezoresistive unit 4 , and the sponge pad 2 is used to prevent a gap from being generated between the flexible top cover 1 and the flexible base 6 .

[0060] In this embodiment, a sponge pad 2 is arranged between the encapsulating film 3 and the flexible top cover 1. The sponge pad 2 is placed in the gap between the bumps of the flexible top cover 1. Its size is slightly smaller than the gap and its thickness is the same as that of the flexible piezoresistive unit 4. The purpose is to prevent a gap from being generated when the flexible top cover 1 and the flexible base 6 are installed, thereby affecting the function.

[0061] When the flexible sensor is stimulated by external force, the flexible top cover 1 and the flexible base 6 squeeze each other, the pressure resistance of the piezoresistive unit changes, and the response signal is transmitted to the host computer through the circuit board.

[0062] In some embodiments of the present application, twelve flexible piezoresistive units 4 are provided on the flexible printed circuit board 5, each flexible piezoresistive unit 4 is provided with an electrode, one lead of each electrode is integrated into the inner interface of the flexible piezoresistive unit 4, and the other lead of each electrode is integrated into the outer interface of the flexible piezoresistive unit 4.

[0063] The flexible piezoresistive units 4 are key components of the circuit board. They can change their resistance values ​​according to the applied pressure, thereby realizing the detection and measurement of pressure. Each flexible piezoresistive unit 4 is equipped with electrodes, which are contact points for measuring resistance changes. In order to ensure efficient connection and signal transmission of the circuit, each electrode has a lead, which is integrated into the inner interface of the flexible piezoresistive unit 4. The inner interface is the area where the electrode is connected to other electronic components or circuits inside the circuit board, ensuring that the signal can be transmitted from the piezoresistive unit to other parts of the circuit board. In addition, each electrode also has a lead integrated into the outer interface of the flexible piezoresistive unit 4, and these outer interfaces are used to lead the signal from the piezoresistive unit to the device or system outside the circuit board.

[0064] In this way, each flexible piezoresistive unit 4 can independently input and output signals, allowing the entire flexible printed circuit board 5 to flexibly respond to changes in external pressure and convert these changes into electrical signals for pressure sensing and control in various electronic devices. This design not only improves the performance of the circuit board, but also enhances its reliability and adaptability in various applications.

[0065] It is understood that the signal acquisition of the twelve flexible piezoresistive units 4 is independent of each other. The Bluetooth module 9 aggregates the information data of all units to the host computer, which then packages and transmits all the data to the terminal device. The flexible six-dimensional force sensor 8 is installed at the joint of the robot arm 7. When the circuit is connected, it generates a signal. The piezoresistive signal changes are transmitted to the terminal device in real time via the Bluetooth device to complete the real-time measurement.

[0066] In some embodiments of the present application, the six-dimensional force of the flexible six-dimensional force sensor 8 includes:

[0067] A three-dimensional coordinate system is established with the center of the upper surface of the flexible top cover 1 as the origin, and the six-dimensional forces are: positive pressure Fx in the X-axis direction, positive pressure Fy in the Y-axis direction, positive pressure Fz in the Z-axis direction, torque Mx in the X-axis direction, torque My in the Y-axis direction, and torque Mz in the Z-axis direction.

[0068] In some embodiments of the present application, the specific steps of the device measurement method are:

[0069] S1, use the six-dimensional force mechanical testing system to apply six-dimensional forces Fx, Fy, Fz, Mx, My, and Mz to the flexible six-dimensional force sensor for calibration, and use an impedance analyzer to connect the interface of the flexible piezoresistive unit to collect the output resistance signal;

[0070] S2, installing the flexible six-dimensional force sensor on the joint of the robotic arm through bolts, so that the flexible top cover and the flexible base of the flexible six-dimensional force sensor are connected to the robotic arm;

[0071] S3, the posture of the robotic arm changes, the force is transmitted to the flexible piezoresistive unit through the robotic arm, and the flexible piezoresistive unit outputs a resistance signal through the Bluetooth module;

[0072] S4: Calculate the actual six-dimensional force at the joint when the robotic arm moves based on the output resistance signal.

[0073] In some embodiments of the present application, step S4 of calculating the actual six-dimensional force at the joint when the robotic arm moves according to the output resistance signal includes:

[0074] Repeat step S1 multiple times to obtain calibration data, which includes six-dimensional force and calibration resistance signals. The calibration data is divided into a training set and a test set. The training set and the test set are used to train and test the deep neural network model to obtain a trained deep neural network model. The output resistance signal is input into the trained deep neural network model to obtain the output result as the actual six-dimensional force at the joint when the robotic arm moves;

[0075] Among them, the construction process of the deep neural network model is:

[0076] A41, normalizes the calibration data, scales the calibration data to the range of [-1, 1], and performs normalization according to the following formula;

[0077]

[0078] Where x' i is the value after normalization of the input i-th calibration data, x i is the value of the input i-th calibration data before normalization, x min is the minimum value of the calibration data range, x max is the maximum value of the calibration data range;

[0079] A42, in MATLAB, use the layers function to define the architecture of a deep neural network model;

[0080] Construct a network with 12 input nodes and six output nodes, and use the ReLU function as the hidden layer activation function:

[0081] ReLU=max(0,x i );

[0082] A43: Use the trainingOptions function to configure training options, including learning rate, number of iterations, and validation set, and use the trainNetwork function to train a deep neural network model.

[0083] A44: The mean square error is used as the error of the deep neural network model to evaluate the calculation formula:

[0084]

[0085] Where: e is the mean square error, y i is the output of the i-th dimension in the training set, y' i is the output of the i-th dimension of the output layer.

[0086] In some embodiments of the present application, step S4 of calculating the actual six-dimensional force at the joint when the robotic arm moves according to the output resistance signal includes:

[0087] B41, convert the resistance signal into a voltage signal matrix V, and determine the calibration force matrix F through a static calibration algorithm c and the calibration voltage signal matrix V, and determine the calibration force matrix F c The mapping relationship matrix C with the calibration voltage signal matrix V;

[0088] Wherein, the calibration force matrix F c , the relationship between the calibration voltage signal matrix V and the mapping relationship matrix C is as follows:

[0089] F c =CV;

[0090] B42: Calculate the mapping relationship matrix C using the least squares method;

[0091]

[0092] In the above formula, F c is an N×6 matrix, V is an N×12 matrix, N is the number of sample points, V T and V and F respectively c The transpose of

[0093] B43: According to the mapping relationship matrix C and the electrical signal V actually measured by the sensor u Calculate the actual six-dimensional force F u , calculate the actual six-dimensional force F u The formula is as follows:

[0094] F u =CV u .

[0095] In some embodiments of the present application, the step S4 calculates the actual six-dimensional force at the joint when the manipulator moves according to the output resistance signal, and further includes: determining the actual six-dimensional force F u With the calibration force matrix F c The difference between them is used to determine the comprehensive nonlinear deviation of the flexible six-dimensional force sensor;

[0096] ΔL=|F c -F u |;

[0097] Where ΔL is the comprehensive nonlinear deviation.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A rigid and flexible robotic arm posture measurement device based on a six-dimensional force sensor made of flexible piezoresistive material, characterized in that: include: A flexible six-dimensional force sensor and a Bluetooth module, wherein the flexible six-dimensional force sensor is mounted on the joint of the robotic arm through bolts, and the Bluetooth module is mounted inside the flexible six-dimensional force sensor; The flexible six-dimensional force sensor includes a flexible top cover, a sponge pad, a force response layer and a flexible base; The flexible top cover is a circular structure with four protrusions on the bottom. The flexible base is a circular structure with four grooves on the top. The grooves match the protrusions to form an interlocking structure. The sponge pad and the force response layer are arranged between the flexible top cover and the flexible base. The force response layer includes an encapsulating film, a flexible piezoresistive unit, and a flexible printed circuit board; the flexible printed circuit board is a layered structure with four U-shaped grooves, and the flexible printed circuit board matches the flexible base; the flexible piezoresistive unit is adhered to the top and side of the U-shaped groove of the flexible printed circuit board; the encapsulating film is used to encapsulate the flexible piezoresistive unit on the flexible printed circuit board; the sponge pad is arranged on the encapsulating film and is arranged in the gap between the protrusions of the flexible top cover; the flexible piezoresistive unit is connected to the Bluetooth module; The specific steps of the device measurement method are: S1, use the six-dimensional force mechanical testing system to apply six-dimensional forces Fx, Fy, Fz, Mx, My, and Mz to the flexible six-dimensional force sensor for calibration, and use an impedance analyzer to connect the interface of the flexible piezoresistive unit to collect the output resistance signal; S2, installing the flexible six-dimensional force sensor on the joint of the robotic arm through bolts, so that the flexible top cover and the flexible base of the flexible six-dimensional force sensor are connected to the robotic arm; S3, the posture of the robotic arm changes, the force is transmitted to the flexible piezoresistive unit through the robotic arm, and the flexible piezoresistive unit outputs a resistance signal through the Bluetooth module; S4: Calculate the actual six-dimensional force at the joint when the robotic arm moves based on the output resistance signal; The step S4 calculates the actual six-dimensional force at the joint when the robot arm moves according to the output resistance signal, including: Repeat step S1 multiple times to obtain calibration data, which includes six-dimensional force and calibration resistance signals. The calibration data is divided into a training set and a test set. The training set and the test set are used to train and test the deep neural network model to obtain a trained deep neural network model. The output resistance signal is input into the trained deep neural network model to obtain the output result as the actual six-dimensional force at the joint when the robotic arm moves; Among them, the construction process of the deep neural network model is: A41, normalizes the calibration data, scales the calibration data to the range of [-1, 1], and performs normalization according to the following formula; Where x ′ i is the value after normalization of the input i-th calibration data, x i is the value of the input i-th calibration data before normalization, x min is the minimum value of the calibration data range, x max is the maximum value of the calibration data range; A42, in MATLAB, use the layers function to define the architecture of a deep neural network model; Construct a network with 12 input nodes and six output nodes, and use the ReLU function as the hidden layer activation function: ReLU=max(0,x i ); A43: Use the trainingOptions function to configure training options, including learning rate, number of iterations, and validation set, and use the trainNetwork function to train a deep neural network model. A44: The mean square error is used as the error of the deep neural network model to evaluate the calculation formula: Where: e is the mean square error, y i is the output of the i-th dimension in the training set, y ′ i is the output of the i-th dimension of the output layer.

2. The rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to claim 1 is characterized in that: The thickness of the sponge pad is the same as that of the flexible piezoresistive unit, and the sponge pad is used to prevent a gap from being generated between the flexible top cover and the flexible base.

3. The rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to claim 1 is characterized in that: Twelve flexible piezoresistive units are arranged on the flexible printed circuit board, each of which is provided with an electrode, one lead of each electrode is integrated into the inner interface of the flexible piezoresistive unit, and the other lead of each electrode is integrated into the outer interface of the flexible piezoresistive unit.

4. The rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to claim 1 is characterized in that: The six-dimensional force of the flexible six-dimensional force sensor includes: A three-dimensional coordinate system is established with the center of the upper surface of the flexible top cover as the origin, and the six-dimensional forces are: positive pressure Fx in the X-axis direction, positive pressure Fy in the Y-axis direction, positive pressure Fz in the Z-axis direction, torque Mx in the X-axis direction, torque My in the Y-axis direction, and torque Mz in the Z-axis direction.

5. The rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to claim 1 is characterized in that: The step S4 calculates the actual six-dimensional force at the joint when the robot arm moves according to the output resistance signal, including: B41, convert the resistance signal into a voltage signal matrix V, and determine the calibration force matrix F through a static calibration algorithm c and the calibration voltage signal matrix V, and determine the calibration force matrix F c The mapping relationship matrix C with the calibration voltage signal matrix V; Wherein, the calibration force matrix F c , the relationship between the calibration voltage signal matrix V and the mapping relationship matrix C is as follows: F c =CV; B42: Calculate the mapping relationship matrix C using the least squares method; In the above formula, F c is an N×6 matrix, V is an N×12 matrix, N is the number of sample points, V T and V and F respectively c The transpose of B43: According to the mapping relationship matrix C and the electrical signal V actually measured by the sensor u Calculate the actual six-dimensional force F u , calculate the actual six-dimensional force F u The formula is as follows: F u =CV u 。 6. The rigid and flexible robotic arm posture measurement device based on a flexible piezoresistive material six-dimensional force sensor according to claim 5 is characterized in that: The step S4 calculates the actual six-dimensional force at the joint when the manipulator moves according to the output resistance signal, and also includes: determining the actual six-dimensional force F u With the calibration force matrix F c The difference between them is used to determine the comprehensive nonlinear deviation of the flexible six-dimensional force sensor; ΔL=|F c -F u |; Where ΔL is the comprehensive nonlinear deviation.

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