A Biomechanics-Constrained Human-Machine Interaction Safety Testing System and Method

Abstract

The present invention relates to a biomechanics-constrained human-machine interaction safety testing system and method, belonging to the fields of biomechanics and manipulator detection. The system uses a matrix distribution sensor to establish a first-layer epidermal tissue mechanics model, and uses a motor control drive to drive a second-layer musculoskeletal mass model connected thereto, achieving multi-freedom of its own movement and multi-freedom of testing, providing a platform for the biomechanical performance testing of the manipulator; the method realizes the test analysis of the accuracy, consistency, robustness and stability of the force and position of the manipulator by calculating the number of contact points, the magnitude and planar coordinate positions of the force and deformation of each contact point, and the three-dimensional coordinate positions of the contact points. The method of the present invention can accurately test the safety characteristics such as the accuracy, consistency, robustness and stability of the manipulator.

Description

Technical Field

[0001] The present invention relates to a biomechanics-constrained human-machine interaction safety testing system and method, belonging to the fields of biomechanics and manipulator detection, and particularly applicable to a testing system and method for human-machine interaction safety under biomechanics constraints. Background Art

[0002] With the progress of technology, robots have been widely used in production automation and people's daily lives. When redundant robotic arms are engaged in operations that involve contact with the environment, such as assembly, medical technology, polishing, and scrubbing, it is necessary to control both the position and force of the robotic arm simultaneously to achieve the best operation effect. Biomechanical testing of human tissues is used to study the mechanical and kinematic properties of the contact between robotic arms or agents and human tissues, which helps to improve human-machine interaction technology, develop more intelligent rehabilitation devices, assist rehabilitation patients in restoring motor function, and improve the rehabilitation effect.

[0003] Currently, there are various testing platforms for robotic arms that use various sensing technologies, such as inertial measurement units (IMUs), optical tracking systems, force sensors, etc., to collect motion data of robotic arms, and use mathematical and computational methods for data analysis and modeling to detect the force or position of robotic arms. However, these testing platforms are limited to specific industrial scenarios, using robotic arms for auxiliary testing, and the tested performance is single, such as the "Online flatness detection platform and detection method based on a multi-joint robot" disclosed in the invention patent CN116175283A. There are relatively few systematic platforms for testing the robotic arm itself, let alone research on testing platforms for the interaction between robotic arms and the human biological tissue system. Currently, the application prospect of robotic arms in medical auxiliary equipment is quite broad, but there is still a lack of corresponding testing systems for the biomechanical detection of the contact between robotic arms and human tissues to ensure the performance and safety of robotic arms during operation. The accuracy, consistency, robustness, and stability testing of the force and position of the manipulator are important reference indicators for safety testing. The trajectories of multi-degree-of-freedom manipulators and testing platforms are relatively complex during movement. Generally, only considering the data at the measurement moment cannot accurately describe the situation during the entire movement process, and this problem will inevitably lead to inaccurate test results, which is also one of the important problems to be solved by the present invention. Summary of the Invention

[0004] In view of this, the present invention provides a biomechanics-constrained human-machine interaction safety testing system and method, aiming to build a biomechanical testing system for the manipulator and human tissues by building a multi-degree-of-freedom multi-layer anisotropic biological tissue model and combining it with a multi-degree-of-freedom motion device; using the built testing system and combining error-controllable methods to accurately test the accuracy, consistency, robustness, and stability of the force and position of the manipulator.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A biomechanics-constrained human-computer interaction safety testing system is composed of a first-layer epidermal tissue mechanics model, a second-layer musculoskeletal mass model, a rotation system, a lifting system, an electric control system, and a data acquisition server; characterized in that, the first-layer epidermal tissue mechanics model is composed of a skin layer and a plurality of subcutaneous tissue modules; the skin layer can cover all the subcutaneous tissue modules, is an elastic plastic cushion, is tightened with a certain pre-tightening force, and is closely attached to the epidermal mass module; the plurality of subcutaneous tissue modules are distributed in a matrix; one of the subcutaneous tissue modules is composed of an epidermal mass module, a spring, a damper, a displacement sensor, and a pressure sensor; the epidermal mass module is a cap button in the shape of a keyboard epidermis, and the other end is connected to the spring and the damper; the other ends of the spring and the damper are connected to the pressure sensor; the displacement sensor is a laser ranging sensor, installed on the upper surface of the bone mass module, and is used to detect the deformation of the first-layer epidermal tissue mechanics model; the second-layer musculoskeletal mass model is composed of a bone mass module, a second-layer spring and a second-layer damper connected in parallel, a second-layer displacement sensor, and a second-layer pressure sensor connected in series therewith; the bone mass module is a plane made of metal, and pressure sensors and second-layer pressure sensors are respectively pasted on the upper and lower surfaces; the second-layer displacement sensor is a laser ranging sensor, installed on the lower surface of the bone mass module, and is used to detect the deformation of the second-layer musculoskeletal mass model; the second-layer spring and the second-layer damper connected in parallel are respectively connected to the second-layer pressure sensor and the rotation system; the rotation system is composed of a rotation motor and a rotation device, wherein, the rotation motor is a stepping motor, and the rotation device is a gear transmission device; the lifting system is composed of a lifting motor and a lifting device, wherein, the lifting motor is a stepping motor, and the lifting device is a lead screw nut device; the rotation system and the lifting system are connected in series, and the control of the stepping motor is realized by using the electric control system respectively connected to them; the electric control system is a microcomputer with a motor drive and a control circuit; the data acquisition server is a server, and is connected to the displacement sensor, the pressure sensor, the second-layer displacement sensor, the second-layer pressure sensor, and the electric control system respectively through a network or a serial connection to realize data collection.

[0007] For the first-layer epidermal tissue mechanics model distributed in a matrix, a matrix-type sequence controller is used to realize the reading of the signals of the displacement sensor and the pressure sensor. It should be particularly noted that the system needs to establish a reference coordinate system at the initial moment. Preferably, the vertical direction is taken as the z-axis, the horizontal plane is taken as xoy, and the ground support fixed point is selected as the origin to establish the coordinate system.

[0008] Furthermore, the elastic coefficient and damping coefficient of the subcutaneous tissue module are monotonically and uniformly distributed along the rows and columns of the matrix distribution of the first-layer epidermal tissue mechanical model.

[0009] Preferably, the springs and dampers of the subcutaneous tissue module are equivalent springs and equivalent dampers. In a specific implementation, multiple springs and multiple dampers can be connected in parallel.

[0010] Specifically, the damper is an adjustable damper. For the test of smooth skin tissue scenarios, the elastic coefficients of each equivalent spring are equal, and the damping coefficients of each equivalent damper are equal. For the test of non-smooth skin tissue scenarios, the size of the damper can be adjusted so that the size of the equivalent damper is monotonically and uniformly distributed.

[0011] Furthermore, the number of rotation systems is two, enabling rotation with two degrees of freedom in the horizontal plane.

[0012] Furthermore, due to the existence of the skin layer, there are lateral interaction forces between two adjacent epidermal mass modules. A camera can be installed on the upper surface of the bone mass module to identify the lateral displacement between the epidermal mass modules.

[0013] Applied to a human-computer interaction safety test system under biomechanical constraints, the present invention provides a human-computer interaction safety test method under biomechanical constraints, which includes the following steps:

[0014] S1: At the initial moment, a drive signal is input to the manipulator to be tested for motion control, and the manipulator to be tested is controlled to contact the skin layer, causing the skin layer to deform accordingly, further resulting in the displacement of the first-layer epidermal tissue mechanical model and the second-layer musculoskeletal mass model.

[0015] S2: Signals from displacement sensors and pressure sensors are obtained through a data acquisition server, and the deformation and force at the corresponding element positions in the matrix distribution corresponding to the first-layer epidermal tissue mechanical model are calculated.

[0016] S3: The data acquisition server determines the number of contact points of the manipulator based on the displacement at the corresponding element positions calculated in step S2.

[0017] S4: The data acquisition server uses the decomposition of forces and the principle of force and moment balance to establish the first-layer epidermal tissue mechanical model, and calculates the magnitude and planar coordinate positions of the forces and deformations at each contact point of the manipulator using the displacement and force at the corresponding element positions.

[0018] S5: Signals from the second-layer displacement sensors and second-layer pressure sensors are obtained through the data acquisition server, the deformation and force of the second-layer musculoskeletal mass model are calculated, and the three-dimensional coordinate positions of the contact points of the manipulator are calculated.

[0019] S6: Use the electric control system to control the lifting displacement and inclination angle of the rotating system and the lifting system, so as to test and analyze the accuracy, consistency, robustness and stability of the force and position of the manipulator;

[0020] Among them, the test of the accuracy described in step S6 is: when controlling the electric control system to make the rotating system and the lifting system stationary at a certain specified position, judge the number of contact points of the manipulator, and whether the magnitude and position of the contact point force are accurate;

[0021] The test of the consistency described in step S6 is: control the electric control system to make the rotating system and the lifting system move according to the set path, and judge whether the number of contact points of the manipulator, and the magnitude and position of the contact point force are accurate throughout the path;

[0022] The test of the robustness described in step S6 is: continuously input random small disturbance signals to the electric control system, so that the rotating system or the lifting system continuously performs small disturbances near a certain specific position, and judge the change of the number of contact points of the manipulator, and the magnitude and position of the contact point force during the process;

[0023] The test of the stability described in step S6 is: input a random small disturbance signal to the electric control system at the initial moment, so that the position of the rotating system or the lifting system is disturbed, and judge whether the number of contact points of the manipulator, and the magnitude and position of the contact point force can return to the previous state.

[0024] Further, the method for judging the number of contact points of the manipulator described in step S3 is to judge by convexity, that is, use the displacement z of the subcutaneous tissue module at the corresponding element position (i, j) in the i-th row and j-th column i,j and the displacements z of the 4 adjacent subcutaneous tissue modules i-1,j 、z i+1,j 、z i,j-1 、z i,j+1 for comparison. If z i,j is greater than all 4 displacements, then there is 1 contact point near the corresponding element position (i, j).

[0025] Further, the specific step S4 is as follows:

[0026] S401: Take the vertical direction as the z-axis, the horizontal plane as xoy, select an origin, and establish a coordinate system; preferably, the coordinate system here is consistent with the reference coordinate system;

[0027] S402: For any k-th contact point, according to the principle of moment balance and equal resultant force, there is:

[0028]

[0029] Among them, the force f of the k-th contact pointk and the component force generated at each corresponding element position (i, j) by the position (x k , y k ) is f k i,j , and the corresponding position (x k i,j , y k i,j ) is known;

[0030] S403: For the resultant force of all contact points, there is: where f i,j is the force at the corresponding element position (i, j), which can be directly measured by a pressure sensor;

[0031] The mechanical model of the first-layer epidermal tissue is the equation obtained in steps S402 to S403;

[0032] S404: Use the least squares method to calculate the mechanical model of the first-layer epidermal tissue to obtain the force f k of the contact point and the position (x k , y k );

[0033] S405: Through the deformations z k , y k ) of the two closest corresponding element positions (i1, j1) and (i2, j2) to the contact point, calculate the deformation k i1,j1 and z k i2,j2 generated by the contact point force

[0034] Furthermore, the three-dimensional coordinates of the force of the contact point need to be calculated through geometric coordinates by using the rotation system angle, the lifting system displacement, the deformation of the first-layer epidermal tissue mechanical model, the deformation of the second-layer musculoskeletal mass model, and the mechanical structure data.

[0035] Preferably, in order to ensure the accuracy of the test and reduce the influence of system errors and measurement errors on the test results, in the consistency, robustness, and stability test analysis, the residual control method can be adopted in steps S403 and S405 to correct the force f i,j and the deformation z k i,j at the corresponding element position (i, j), specifically:

[0036] (1) Using the values of the force f i,j and the deformation z k i,j at the corresponding element position (i, j) obtained by multiple measurements, combined with the mechanical model

[0037] Fit to obtain E i,j and η i,j ;

[0038] (2) For the force f at the corresponding element positions (i, j) obtained from multiple measurements i,j and the deformation z k i,j Use orthogonal least squares fitting to obtain the approximate solutions of force and deformation and Substitute the approximate solutions into the mechanical model to obtain where δ i,j is the residual function at the corresponding element positions (i, j);

[0039] (3) Establish an unconstrained optimization model min∫||δ i,j ||dt, and use an NLP solver to solve for the optimization parameters in the orthogonal least squares fitting;

[0040] where ||·|| is the two-norm.

[0041] If it is optimized, in step (3), constraint equations such as acceleration and boundary can be introduced to form a constrained optimization model and solve it.

[0042] If it is preferred, the force f at the corresponding element positions (i, j) is i,j It is also possible to judge the lateral displacement between the epidermal quality modules through a camera, and then calculate the magnitude of the component force in its horizontal plane in combination with the elastic modulus of the skin layer; for example, the lateral displacement Δx i,j , and the corresponding component force f in the horizontal plane i,j = E·Δx i,j ; It should be noted that the lateral displacement is the displacement in two perpendicular directions of the x-axis and y-axis of the horizontal plane xoy, and the component forces also need to be calculated separately. Similarly, establish an equation according to the moment balance to calculate the component force of the force f k in the horizontal plane, and correct the magnitude and direction of f k ; for example where, Δy i,j is the lateral displacement in the y direction; Δy k is the lateral displacement in the y direction of the contact point, which can be obtained through image recognition.

[0043] The beneficial effects of the present invention are as follows: The present invention provides a biomechanically constrained human-machine interaction safety testing system. Under the framework of biological tissue structure, a first-layer epidermal tissue mechanical model is established using a matrix distribution sensor, and a second-layer musculoskeletal mass model connected thereto is driven by a motor control, achieving multi-freedom of its own movement and multi-freedom of testing, providing a platform for the biomechanical performance testing of a manipulator. At the same time, based on this system, the present invention provides a method for biomechanically constrained human-machine interaction safety testing. Based on mechanical analysis and by introducing controllable errors, accurate testing of the accuracy, consistency, robustness, and stability of the force and position of the manipulator is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to illustrate the objectives and technical solutions of the present invention, the following drawings are provided for description:

[0045] Figure 1 Schematic diagram of a 3-degree-of-freedom manipulator in Embodiment 1 of the present invention; wherein, 1-8 are rods;

[0046] Figure 2 Structure diagram of a biomechanically constrained human-machine interaction safety testing system in Embodiment 1 of the present invention; wherein, 11 is the skin layer, 12 is the subcutaneous tissue module, 21 is the bone mass module, 22 is the second-layer spring and the second-layer damper connected in parallel, 3 is the rotation system, and 4 is the lifting system;

[0047] Figure 3 Control flowchart of a biomechanically constrained human-machine interaction safety testing system in Embodiment 1 of the present invention; wherein, 3 is the rotation system and 4 is the lifting system;

[0048] Figure 4 Schematic diagram of the first-layer epidermal tissue mechanical model in Embodiment 1 of the present invention; wherein, 1201 is the epidermal mass module, 1202 is the spring, 1203 is the damper, 13 is the displacement sensor, 14 is the pressure sensor, 21 is the bone mass module, and 6 is the data acquisition server;

[0049] Figure 5 Schematic diagram of the second-layer musculoskeletal mass model in Embodiment 1 of the present invention; wherein, 21 is the bone mass module, 2201 is the second-layer spring, 2202 is the second-layer damper, 23 is the second-layer displacement sensor; 24 is the second-layer pressure sensor, 3 is the rotation system, and 6 is the data acquisition server;

[0050] Figure 6 Flowchart of a method for biomechanically constrained human-machine interaction safety testing in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] To make the objectives and technical solutions of the present invention clearer and more understandable, the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0052] Embodiment 1: Existing Figure 1 For the shown 3-degree-of-freedom manipulator, its parameters are shown in Table 1. Taking node 0 as the origin, a coordinate system is constructed.

[0053] Table 1 Parameters of 3-degree-of-freedom manipulator

[0054]

[0055]

[0056] By separately controlling the rotation angles θ1, θ4, and θ7 corresponding to joint 1, joint 4, and joint 7, respectively, the control of the motion trajectory of the manipulator can be achieved. From the inverse kinematics calculation, the relationship between the end position (x, y, z) of the manipulator and the rotation angles θ1, θ4, and θ7 is as follows:

[0057]

[0058] Currently, it is necessary to test this manipulator to determine whether the motion trajectory of its end (x, y, z) meets the requirements.

[0059] For this requirement, a test platform is designed, and the present invention provides "a human-machine interaction safety test system under biomechanical constraints". Combining Figure 2 and Figure 3, which is composed of a first-layer epidermal tissue mechanical model (1), a second-layer musculoskeletal mass model (2), a rotation system (3), a lifting system (4), an electric control system (5), and a data acquisition server (6); characterized in that the first-layer epidermal tissue mechanical model (1) is composed of a skin layer (11) and a plurality of subcutaneous tissue modules (12); the skin layer (11) can cover all the subcutaneous tissue modules (12), is an elastic plastic cushion, is tightened with a certain pre-tightening force, and is closely attached to the epidermal mass module (1201); the plurality of subcutaneous tissue modules (12) are distributed in a matrix; one of the subcutaneous tissue modules (12) is composed of an epidermal mass module (1201), a spring (1202), a damper (1203), a displacement sensor (13), and a pressure sensor (14); the epidermal mass module (1201) is a cap button in the shape of a keyboard epidermis, and the other end is connected to the spring (1202) and the damper (1203); the other ends of the spring (1202) and the damper (1203) are connected to the pressure sensor (14); the displacement sensor (13) is a laser ranging sensor, which is installed on the upper surface of the bone mass module (21) and is used to detect the deformation of the first-layer epidermal tissue mechanical model (1); the second-layer musculoskeletal mass model (2) is composed of a bone mass module (21), a second-layer spring (2201) and a second-layer damper (2202) connected in parallel, a second-layer displacement sensor (23), and a second-layer pressure sensor (24) connected in series therewith; the bone mass module (21) is a plane made of metal, and a pressure sensor (14) and a second-layer pressure sensor (24) are respectively pasted on the upper and lower surfaces; the second-layer displacement sensor (23) is a laser ranging sensor, which is installed on the lower surface of the bone mass module (21) and is used to detect the deformation of the second-layer musculoskeletal mass model (2); the second-layer spring (2201) and the second-layer damper (2202) connected in parallel are respectively connected to the second-layer pressure sensor (24) and the rotation system (3); the rotation system (3) is composed of a rotation motor (31) and a rotation device (32), wherein the rotation motor (31) is a stepping motor and the rotation device (32) is a gear transmission device; the lifting system (4) is composed of a lifting motor (41) and a lifting device (42), wherein the lifting motor (41) is a stepping motor and the lifting device (42) is a lead screw nut device; the rotation system (3) and the lifting system (4) are connected in series, and the control of the stepping motor is realized by using the electric control system (5) connected to them respectively; the electric control system (5) is a microcomputer with a motor drive and control circuit; the data acquisition server (6) is a server, which is connected to the displacement sensor (13), the pressure sensor (14), the second-layer displacement sensor (23), the second-layer pressure sensor (24), and the electric control system (5) through a network or a serial connection to realize data collection.

[0060] The elastic coefficient and damping coefficient of the subcutaneous tissue module (12) are monotonically and uniformly distributed along the rows and columns of the matrix distribution of the first-layer epidermal tissue mechanical model (1).

[0061] The number of the rotation systems (3) is two, which can realize the rotation of two degrees of freedom in the horizontal plane.

[0062] Due to the existence of the skin layer (11), there are lateral acting forces connecting the epidermal mass modules (1201) on two adjacent first-layer epidermal tissue mechanical models (1). A camera (8) is installed on the bone mass module (21) to identify the lateral displacement between the epidermal mass modules (1201).

[0063] Embodiment 2: For the test platform of Embodiment 1, in order to better achieve the accurate test of the accuracy, consistency, robustness and stability of the force and position of the manipulator, the present invention provides "a method for safe human-machine interaction test under biomechanical constraints", as Figure 6 shown, which includes the following steps:

[0064] S1: At the initial moment, an input driving signal is given to the manipulator (7) to be tested for motion control, and the manipulator (7) to be tested is controlled to contact the skin layer (11); this causes the skin layer (11) to deform accordingly, further resulting in the displacement of the first-layer epidermal tissue mechanical model (1) and the second-layer musculoskeletal mass model (2).

[0065] S2: The signals of the displacement sensor (13) and the pressure sensor (14) are obtained through the data acquisition server (6), and the deformation and force at the corresponding element positions in the matrix distribution corresponding to the first-layer epidermal tissue mechanical model (1) are calculated.

[0066] S3: The data acquisition server (6) determines the number of contact points of the manipulator (7) by using the displacement at the corresponding element positions calculated in step S2.

[0067] Among them, the method for determining the number of contact points of the manipulator (7) in step S3 is to make a judgment using convexity, that is, using the displacement z of the subcutaneous tissue module (12) at the corresponding element position (i, j) in the i-th row and j-th column i,j and the displacements z of the 4 adjacent subcutaneous tissue modules (12) i-1,j 、z i+1,j 、z i,j-1 、z i,j+1 for comparison. If z i,j is greater than or equal to all 4 displacements, then there is 1 contact point near the corresponding element position (i, j).

[0068] S4: The data acquisition server (6) uses the decomposition of forces and the principle of the balance of forces and torques to establish the mechanical model of the first-layer epidermal tissue (1), and calculates the magnitudes and planar coordinate positions of the forces and deformations at each contact point of the manipulator (7) using the displacements and forces at the corresponding element positions.

[0069] The specific steps of step S4 are as follows:

[0070] S401: For any k-th contact point, according to the principle of torque balance and equal resultant force, we have:

[0071]

[0072] where the force f at the k-th contact point k and the position (x k , y k ) generate component forces f k i,j at each corresponding element position (i, j), and the corresponding positions (x k i,j , y k i,j ) are known;

[0073] S402: For the resultant force of all contact points, we have: where f i,j is the force at the corresponding element position (i, j), which can be directly measured by the pressure sensor (14);

[0074] S403: Use the least squares method to calculate the mechanical model of the first-layer epidermal tissue to obtain the force f at the contact point k and the position (x k , y k );

[0075] S404: Through the deformations z k , y k ) of the two closest corresponding element positions (i1, j1) and (i2, j2) to (x k i1,j1 and z k i2,j2 , calculate the deformation

[0076] where the three-dimensional coordinates of the force at the contact point need to be calculated through geometric coordinates using the rotation angle of the rotation system (3), the displacement of the lifting system (4), the deformation of the first-layer epidermal tissue mechanical model (1), the deformation of the second-layer musculoskeletal mass model (2), and the mechanical structure data.

[0077] To ensure the accuracy of the test and reduce the influence of systematic errors and measurement errors on the test results, in the consistency, robustness, and stability test analysis, the residual control method can be adopted in steps S402 and S404 to correct the force f i,j and deformation z k i,j at the corresponding element position (i, j), specifically as follows:

[0078] (1) After the test platform is built, use the values of the force f i,j and deformation z k i,j at the corresponding element position (i, j) obtained from 20 measurements, and combine with the mechanical model to fit and obtain E i,j and η i,j ;

[0079] (2) During the actual test, obtain the values of the force f i,j and deformation z k i,j at the corresponding element position (i, j) measured at all sampling times, use orthogonal least squares fitting to construct an interpolation function in time, and obtain the approximate solutions of the force and deformation and

[0080] Substitute the approximate solutions into the mechanical model to obtain where δ i,j is the residual function at the corresponding element position (i, j);

[0081] (3) Establish an unconstrained optimization model min∫||δ i,j ||dt, and use an NLP solver to solve for the optimization parameters in the orthogonal least squares fitting;

[0082] where ||·|| is the second norm.

[0083] The force f i,j at the corresponding element position (i, j) can also be used to determine the lateral displacement between the epidermal mass modules (1201) through the camera (8), and then calculate the magnitude of the component force in the horizontal plane in combination with the elastic modulus of the skin layer (11); similarly, establish an equation based on torque balance to calculate the force f k of the component force in the horizontal plane, and correct the magnitude and direction of f k .

[0084] S5: Obtain the signals of the second-layer displacement sensor (23) and the second-layer pressure sensor (24) through the data acquisition server (6), calculate the deformation and force of the second-layer musculoskeletal mass model (2), and calculate the three-dimensional coordinate position of the contact point of the manipulator (7);

[0085] S6: Use the electronic control system (5) to control the lifting displacement and inclination angle of the rotating system (3) and the lifting system (4), so as to test and analyze the accuracy, consistency, robustness and stability of the force and position of the manipulator (7);

[0086] Among them, the accuracy test described in step S6 is: when the electronic control system (5) is controlled to make the rotating system (3) and the lifting system (4) stationary at a certain specified position, judge the number of contact points of the manipulator (7), and whether the magnitude and position of the contact point force are accurate;

[0087] The consistency test described in step S6 is: control the electronic control system (5) to make the rotating system (3) and the lifting system (4) move along the set path, and judge whether the number of contact points of the manipulator (7), the magnitude and position of the contact point force are accurate throughout the path;

[0088] The robustness test described in step S6 is: continuously input random small disturbance signals to the electronic control system (5) to make the rotating system (3) or the lifting system (4) continuously perform small disturbances near a certain specific position, and judge the number of contact points of the manipulator (7) during the process, and the changes in the magnitude and position of the contact point force;

[0089] The stability test described in step S6 is: input a random small disturbance signal to the electronic control system (5) at the initial moment to make the position of the rotating system (3) or the lifting system (4) disturbed, and judge whether the number of contact points of the manipulator (7), the magnitude and position of the contact point force can return to the previous state.

[0090] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A biomechanically constrained human-machine interaction safety testing system is composed of a first-layer epidermal tissue mechanics model (1), a second-layer musculoskeletal mass model (2), a rotation system (3), a lifting system (4), an electric control system (5), and a data acquisition server (6); characterized in that, The described first-layer epidermal tissue mechanical model (1) consists of a skin layer (11) and several subcutaneous tissue modules (12); the skin layer (11) can cover all the subcutaneous tissue modules (12), is an elastic plastic cushion, is tightened with a certain pre-tightening force, and is closely attached to the epidermal mass module (1201); the several subcutaneous tissue modules (12) are distributed in a matrix; one subcutaneous tissue module (12) consists of an epidermal mass module (1201), a spring (1202), a damper (1203), a displacement sensor (13), and a pressure sensor (14); the epidermal mass module (1201) is a cap button in the shape of a keyboard epidermis, and the other end is connected to the spring (1202) and the damper (1203); the other ends of the spring (1202) and the damper (1203) are connected to the pressure sensor (14); the displacement sensor (13) is a laser ranging sensor, installed on the upper surface of the bone mass module (21), and is used to detect the deformation of the first-layer epidermal tissue mechanical model (1); the second-layer muscle-skeleton mass model (2) consists of a bone mass module (21), a second-layer spring (2201) and a second-layer damper (2202) connected in parallel, a second-layer displacement sensor (23), and a second-layer pressure sensor (24) connected in series therewith; the bone mass module (21) is a plane made of metal, and pressure sensors (14) and the second-layer pressure sensor (24) are respectively pasted on the upper and lower surfaces; the second-layer displacement sensor (23) is a laser ranging sensor, installed on the lower surface of the bone mass module (21), and is used to detect the deformation of the second-layer muscle-skeleton mass model (2); the second-layer spring (2201) and the second-layer damper (2202) connected in parallel are respectively connected to the second-layer pressure sensor (24) and the rotation system (3); the rotation system (3) consists of a rotation motor (31) and a rotation device (32), wherein the rotation motor (31) is a stepping motor and the rotation device (32) is a gear transmission device; the lifting system (4) consists of a lifting motor (41) and a lifting device (42), wherein the lifting motor (41) is a stepping motor and the lifting device (42) is a lead screw nut device; the rotation system (3) and the lifting system (4) are connected in series, and the control of the stepping motor is realized by using an electric control system (5) respectively connected to them; the electric control system (5) is a microcomputer with a motor drive and control circuit; the data acquisition server (6) is a server, and is connected to the displacement sensor (13), the pressure sensor (14), the second-layer displacement sensor (23), the second-layer pressure sensor (24), and the electric control system (5) respectively through a network connection to realize data collection.

2. The biomechanics-constrained human-computer interaction safety test system according to claim 1, characterized in that, The elastic coefficient and damping coefficient of the described subcutaneous tissue module (12) are monotonically and uniformly distributed along the rows and columns of the matrix distribution of the first-layer epidermal tissue mechanical model (1).

3. The biomechanics-constrained human-computer interaction safety test system according to claim 1, wherein, The number of the described rotation systems (3) is two, and two degrees of freedom of rotation in the horizontal plane can be realized.

4. A biomechanically constrained human-computer interaction safety testing system according to claim 1, characterized in that, Due to the existence of the skin layer (11), there are lateral acting forces connecting the epidermal mass modules (1201) on two adjacent first-layer epidermal tissue mechanical models (1). A camera (8) is installed on the bone mass module (21) to identify the lateral displacement between the epidermal mass modules (1201).

5. A biomechanics-constrained human-computer interaction safety testing method applied to the biomechanics-constrained human-computer interaction safety testing system according to any one of claims 1 to 4, characterized in that, The method includes the following steps: S1: At the initial moment, a drive signal is input to the manipulator (7) to be tested for motion control, and the manipulator (7) to be tested is controlled to contact the skin layer (11); this causes the skin layer (11) to deform accordingly, further resulting in displacements of the first-layer epidermal tissue mechanical model (1) and the second-layer musculoskeletal mass model (2). S2: Signals from the displacement sensor (13) and the pressure sensor (14) are acquired through the data acquisition server (6), and the deformations and forces at the corresponding element positions in the matrix distribution corresponding to the first-layer epidermal tissue mechanical model (1) are calculated. S3: The data acquisition server (6) determines the number of contact points of the manipulator (7) using the displacements at the corresponding element positions calculated in step S2. S4: The data acquisition server (6) uses the decomposition of forces and the principle of force and moment balance to establish the first-layer epidermal tissue mechanical model (1), and calculates the magnitudes and planar coordinate positions of the forces and deformations at each contact point of the manipulator (7) using the displacements and forces at the corresponding element positions. S6: The electronic control system (5) is used to control the lifting displacement and inclination of the rotation system (3) and the lifting system (4) to test and analyze the accuracy, consistency, robustness, and stability of the forces and positions of the manipulator (7). Among them, the test for accuracy in step S6 is: when the electronic control system (5) is controlled to make the rotation system (3) and the lifting system (4) stationary at a specified position, determine whether the number of contact points of the manipulator (7), the magnitude and position of the contact force are accurate. The test for consistency in step S6 is: when the electronic control system (5) is controlled to make the rotation system (3) and the lifting system (4) move along a set path, determine whether the number of contact points of the manipulator (7), the magnitude and position of the contact force are accurate throughout the path. The test for robustness in step S6 is: continuously input random small disturbance signals to the electronic control system (5) to make the rotation system (3) or the lifting system (4) continuously undergo small disturbances near a specific position, and determine the changes in the number of contact points of the manipulator (7), the magnitude and position of the contact force during the process. The test for stability in step S6 is: at the initial moment, input a random small disturbance signal to the electronic control system (5) to cause a disturbance in the position of the rotation system (3) or the lifting system (4), and determine whether the number of contact points of the manipulator (7), the magnitude and position of the contact force can return to the previous state. The specific content of step S4 is as follows:

6. The biomechanics-constrained human-computer interaction safety test method according to claim 5, characterized in that, The method for judging the number of contact points of the manipulator (7) described in step S3 is to judge by using convexity, that is, to use the displacement z of the subcutaneous tissue module (12) at the corresponding element position (i, j) in the i-th row and j-th column i,j and the displacements z of its adjacent 4 subcutaneous tissue modules (12) i-1,j 、z i+1,j 、z i,j-1 、z i,j+1 for comparison. If z i,j is greater than or equal to all 4 displacements, then there is 1 contact point near the corresponding element position (i, j).

7. A biomechanically constrained human-computer interaction safety testing method according to claim 5, characterized in that, ​ S401: Take the vertical direction as the z-axis, the horizontal plane as the xoy, select an origin, and establish a coordinate system; S402: For any k-th contact point, according to the principles of moment balance and equal resultant force, we have: Among them, the force f of the k-th contact point k and the position (x k , y k ) generate a component force of f k i,j at each corresponding element position (i, j), and the corresponding position (x k i,j , y k i,j ) is known; S403: For the resultant force of all contact points, there is: where f i,j is the force at the corresponding element position (i, j), which is directly measured by the pressure sensor (14); S404: Calculate the mechanical model of the first layer of subcutaneous tissue using the least squares method to obtain the force f at the contact point k and the position (x k , y k ); S405: Through (x k , y k ) the deformations z k i1,j1 and z k i2,j2 of the two corresponding element positions (i1, j1) and (i2, j2) closest to the contact point, calculate the deformation generated by the contact point force 8. A biomechanics-constrained human-computer interaction safety testing method according to claim 5, characterized in that The three-dimensional coordinates of the force at the contact point need to be calculated through geometric coordinates using the rotation angle of the rotation system (3), the displacement of the lifting system (4), the deformation of the first-layer epidermal tissue mechanical model (1), the deformation of the second-layer musculoskeletal mass model (2), and the mechanical structure data.

9. A method for testing the safety of human-computer interaction under biomechanical constraints according to claim 7, characterized in that, To ensure the accuracy of the test and reduce the influence of systematic errors and measurement errors on the test results, in the consistency, robustness, and stability test analysis, the forces f at the corresponding element positions (i, j) and the deformations z are corrected by means of residual control in steps S403 and S405, specifically as follows: i,j and the deformation z k i,j , specifically as follows: (1) Using the forces f at the corresponding element positions (i, j) obtained from multiple measurements i,j and the deformations z k i,j values, combined with the mechanical model to fit and obtain E i,j and η i,j ; (2) The forces f at the corresponding element positions (i, j) obtained from multiple measurements i,j and the deformations z k i,j The numerical values of are used to obtain the approximate solutions of force and deformation by orthogonal least squares fitting and Substitute the approximate solution into the mechanical model to obtain where δ i,j is the residual function at the corresponding element position (i, j); (3) Establish an unconstrained optimization model min∫||δ i,j ||dt, and use the NLP solver to solve for the optimization parameters in the orthogonal least squares fitting; Among them, ||·|| is the two-norm.

10. A biomechanically constrained human-computer interaction safety testing method according to claim 7, characterized in that The horizontal displacement between the epidermal quality modules (1201) is judged by the camera (8), and then the magnitude of the component force in the horizontal plane is calculated by combining the elastic modulus of the skin layer (11); similarly, an equation is established according to the moment balance to calculate the force f at the contact point. k The component force in the horizontal plane, and for f k Perform corrections on the magnitude and direction.

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