Robot control method and device, equipment and medium

Abstract

The invention relates to a robot control method and device, equipment and a medium. The method comprises the steps that state data of a mechanical arm of a robot are obtained; wherein the state data comprises interaction force of interaction between the robot and the external environment; constructing an instability index based on the interaction force; wherein the instability index is used for representing the instability degree of the robot influenced by the environmental rigidity in the man-machine interaction process; determining an admittance control parameter based on the instability index; and the tail end position of the robot is controlled according to the admittance control parameters. According to the invention, stable and safe interaction between the robot and the environment can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of robotics, and in particular, to a robot control method, apparatus, device, and medium. Background Art

[0002] In recent years, when performing various tasks such as precision tasks, heavy-load operations, and rehabilitation, the most direct way of communication between humans and robots is through the interaction force of contact between humans and robots. As a common human-robot interaction strategy, admittance control can achieve precise control of the position of the robot end-effector by sensing changes in external forces or torques through an external force sensor.

[0003] However, when the robot contacts the environment, the dynamic changes of the system become more complex, especially when the environmental stiffness changes suddenly. Such stiffness mutations may cause unstable oscillations at the robot end-effector, thereby affecting the motion stability of the robot and even potentially posing a danger to the operator. Therefore, how to effectively respond to changes in environmental stiffness and avoid oscillation problems caused by stiffness changes has become a key challenge for ensuring safe and stable human-robot interaction. Summary of the Invention

[0004] To solve the above technical problems, the present disclosure provides a robot control method, apparatus, device, and medium.

[0005] According to one aspect of the present disclosure, there is provided a robot control method, including:

[0006] Obtaining state data of a robot manipulator; wherein, the state data includes: the interaction force between the robot and the external environment;

[0007] Constructing an instability index based on the interaction force; wherein, the instability index is used to represent the degree of instability of the robot affected by environmental stiffness during human-robot interaction;

[0008] Determining admittance control parameters based on the instability index;

[0009] Controlling the end position of the robot according to the admittance control parameters.

[0010] According to one aspect of the present disclosure, there is provided a robot control apparatus, including:

[0011] A data acquisition module, configured to obtain state data of a robot manipulator; wherein, the state data includes: the interaction force between the robot and the external environment;

[0012] An instability index construction module for constructing an instability index based on the interaction force, where the instability index is used to represent the degree of instability of the robot affected by the environmental stiffness during human-robot interaction;

[0013] A admittance control parameter determination module for determining admittance control parameters based on the instability index;

[0014] A robot control module for controlling the end position of the robot according to the admittance control parameters.

[0015] The present disclosure also provides an electronic device, which includes:

[0016] A processor;

[0017] A memory for storing executable instructions of the processor;

[0018] The processor is configured to read the executable instructions from the memory and execute the instructions to implement the above method.

[0019] The present disclosure also provides a computer-readable storage medium storing a computer program for executing the above method.

[0020] The technical solution provided by the embodiments of the present disclosure has the following advantages compared with the prior art:

[0021] The technical solution provided by the embodiments of the present disclosure includes: obtaining state data of a robot manipulator, where the state data includes: an interaction force of the robot interacting with the external environment; constructing an instability index based on the interaction force, where the instability index is used to represent the degree of instability of the robot affected by the environmental stiffness during human-robot interaction; determining admittance control parameters based on the instability index; and controlling the end position of the robot according to the admittance control parameters.

[0022] This technical solution proposes a variable admittance control strategy for suppressing robot oscillation caused by environmental stiffness changes. This strategy can autonomously adjust the behavior of the robot according to the real-time change of environmental stiffness, thereby effectively avoiding unstable oscillation caused by stiffness mutation and improving the stable and safe interaction between the robot and the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure and used together with the specification to explain the principles of the present disclosure.

[0024] To more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0025] Figure 1 It is a flowchart of the robot control method according to the embodiment of the present disclosure;

[0026] Figure 2 It is a schematic diagram of the robot control process according to the embodiment of the present disclosure;

[0027] Figure 3 It is a schematic diagram of the relationship between the interaction force and the instability index according to the embodiment of the present disclosure;

[0028] Figure 4 It is a schematic diagram of the relationship between the interaction force, the instability index and the damping coefficient according to the embodiment of the present disclosure;

[0029] Figure 5 It is a schematic diagram of the structure of the robot control device according to the embodiment of the present disclosure;

[0030] Figure 6 It is a schematic diagram of the structure of the electronic device according to the embodiment of the present disclosure. Detailed implementation manners

[0031] In order to more clearly understand the above-mentioned objects, features and advantages of the present disclosure, the following will further describe the solutions of the present disclosure. It should be noted that, without conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other.

[0032] Many specific details are set forth in the following description in order to fully understand the present disclosure, but the present disclosure can also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only a part of the embodiments of the present disclosure, rather than all of the embodiments.

[0033] When the robot comes into contact with the environment, a sudden change in the environmental stiffness may cause unstable oscillations at the end of the robot, which may further affect the motion stability of the robot and even pose a potential danger to the operator. Therefore, how to effectively cope with the change in environmental stiffness and avoid the oscillation problem caused by the stiffness change has become a key challenge to ensure safe and stable human-robot interaction.

[0034] When humans interact with robots and face changes in environmental stiffness, a admittance control strategy is needed that can sense the environmental stiffness in real time and autonomously adjust the physical behavior of the robot according to the changes in environmental stiffness, so as to avoid the oscillation problem of the robot's end caused by stiffness changes and achieve stable and safe interaction between humans and the environment. Based on this, the embodiments of the present disclosure provide a robot control method, device, equipment and medium. For ease of understanding, the embodiments of the present disclosure are described below.

[0035] Figure 1 FIG. is a flowchart of a robot control method provided by an embodiment of the present disclosure. This method can be executed by a robot control device, and the device can be implemented by software and / or hardware.

[0036] As Figure 1 , a robot control method may include the following steps:

[0037] S102, obtaining state data of the robot manipulator; wherein, the state data includes: the interaction force of the robot interacting with the external environment; the state data may also include data such as the reference end position of the robot;

[0038] S104, constructing an instability index based on the interaction force; wherein, the instability index is used to represent the degree of instability of the robot affected by the environmental stiffness during human-robot interaction;

[0039] S106, determining admittance control parameters based on the instability index;

[0040] S108, controlling the end position of the robot according to the admittance control parameters.

[0041] The following embodiments describe the above steps separately.

[0042] Regarding step S104, an instability index is constructed based on the interaction force. The instability index can reflect the change in environmental stiffness during robot contact, and reflect the dynamic relationship between the environmental interaction force and the environmental stiffness during human-robot interaction, and can be used to represent the degree of instability of the robot affected by the environmental stiffness during human-robot interaction.

[0043] In the embodiment of constructing the instability index based on the interaction force, the interaction force in the state data can be obtained. This interaction force is, for example, the time-domain signal of the human-robot interaction force collected by the robot external force sensor.

[0044] Convert the interaction force from the time-domain signal to the frequency-domain signal to obtain the spectral information corresponding to the interaction force. Specifically, perform a discrete Fourier transform on the interaction force over a period of time to achieve the conversion of the interaction force from the time-domain signal to the frequency-domain signal and obtain the spectral information. Among them, the spectral information includes, for example: the center frequency of the frequency spectrum, the width of the frequency spectrum, the ratio of the high-frequency spectrum to the sum of the spectra, the root mean square of the interaction force within a preset time, etc.

[0045] Furthermore, construct an instability index according to the preset amplification factor and spectral information. The instability index can refer to the following expression:

[0046]

[0047] Among them, λ represents the preset first amplification factor; μ ω represents the center frequency of the frequency spectrum corresponding to the interaction force, or the distribution center of the frequency spectrum on the frequency axis, which is used to determine the overall movement trend of the analysis frequency spectrum over time; σ ω represents the width of the frequency spectrum corresponding to the interaction force, which is used to reflect the concentration degree of the frequency distribution; I ω represents the ratio of the high-frequency spectrum corresponding to the interaction force to the sum of the spectra corresponding to the interaction force; I f represents the root mean square of the interaction force within the preset time window.

[0048] In the above expression of the instability index, the determination methods of each parameter refer to the following embodiments.

[0049] The center frequency μ of the frequency spectrum corresponding to the interaction force ω is expressed as:

[0050]

[0051] Among them, P(ω k ) represents the power density of the frequency ω k , and N is the number of signal samples of the interaction force.

[0052] The width σ of the frequency spectrum corresponding to the interaction force ω is expressed as:

[0053]

[0054] The ratio I of the high-frequency spectrum corresponding to the interaction force to the sum of the spectra corresponding to the interaction force ω is expressed as:

[0055]

[0056] Among them, when k = j, ω j is the cross frequency used to distinguish the human-computer interaction environment. Specifically, for example, it can take a constant value of 3.5 Hz.

[0057] Root mean square I of the interaction force within a preset time f Expressed as:

[0058]

[0059] Where p represents the size of the time window for observing the interaction force, f(t) represents the interaction force at the current time t, and f max Is the maximum range of the force sensor used to detect the interaction force.

[0060] In this embodiment, for step S106, the implementation process of determining the admittance parameter of the control system based on the instability index may include:

[0061] Detect whether the time when the instability index remains at the peak reaches a preset time threshold; if not, determine the admittance control parameter according to the instability index; if so, use the peak value of the instability index as the maximum instability index, and determine the admittance control parameter according to the maximum instability index and the interaction force varying with time.

[0062] In this embodiment, if the time when the instability index remains at the peak does not reach the preset time threshold, it means that during the human-robot interaction process, the degree of instability of the robot affected by the environmental stiffness has not exceeded the maximum controllable degree. In this case, the admittance control parameter can be determined according to the instability index.

[0063] In this embodiment, the admittance control parameter may include: virtual damping; correspondingly, the embodiment of determining the admittance control parameter according to the instability index can be referred to as follows.

[0064] Referring to the admittance control parameter shown in formula (6) below, when the instability index is less than the preset instability index threshold (i.e., I s <ε), determine the preset initial damping coefficient as the admittance control parameter; specifically, c(t) = c0.

[0065] When the instability index is between the instability index threshold and the peak value of the instability index (i.e., ε ≤ I s ≤ I smax ), determine the admittance control parameter according to the preset second amplification coefficient, initial damping coefficient, instability index threshold, and instability index; specifically,

[0066]

[0067] Where c0 represents the initial damping coefficient, I s (t) and I srepresents the instability index at the current time t, ε represents the instability index threshold, and I smax represents the peak value of the instability index, and α is a preset second amplification factor between the instability index and the damping coefficient.

[0068] The instability index in the above embodiments can be used to determine whether the environmental stiffness exceeds the instability index threshold. If it does not exceed the instability index threshold, it is determined as non-interactive or human-machine interaction with low environmental stiffness. When the instability index exceeds the instability index threshold, according to the mapping relationship between the damping and the instability index, the damping coefficient is changed to suppress the unstable oscillation.

[0069] In this embodiment, if the time for which the instability index remains at the peak value reaches the preset time threshold, it indicates that during the human-machine interaction process, the degree of instability of the robot affected by the environmental stiffness has exceeded the maximum controllable degree, realizing force interaction in a high-stiffness environment. In the case of interaction in such a high-stiffness environment, relying solely on the instability index to determine the admittance control parameters can no longer control the motion stability of the robot. It is necessary to further combine the current interaction force to determine the admittance control parameters, thereby switching to a control mode based on the change of the external interaction force, that is, determining the admittance control parameters according to the maximum instability index and the interaction force varying with time; the maximum instability index refers to the instability index maintained at the peak.

[0070] In this embodiment, determining the admittance control parameters according to the maximum instability index and the interaction force varying with time includes:

[0071] Determining the comparison result of the magnitude between the absolute value of the interaction force at the current time and the preset interaction force threshold; determining the positive or negative result of the product between the interaction force at the current time and the interaction force at the previous time; as shown in formula (7), according to the comparison result and the positive or negative result, different control algorithms are selected, and the admittance control parameters are determined according to the selected control algorithm, the maximum instability index, and the interaction force.

[0072]

[0073] where f(t) represents the interaction force at the current time t, f(t - 1) represents the interaction force at the previous time t - 1, and ε f represents the interaction force threshold.

[0074] Combined with several control algorithms for determining the admittance control parameters shown in formula (7) below, when the comparison result is that the absolute value of the interaction force is greater than the interaction force threshold (i.e., |f(t)| > ε f ), then according to the control algorithm in formula (7) that matches this condition, based on the initial damping coefficient c0, the second amplification factor α, and the maximum instability index I smaxGiven the instability index threshold ε, the admittance control parameters are determined, and the admittance control parameters include the virtual damping c(t).

[0075] When the comparison result shows that the absolute value of the interaction force is less than the interaction force threshold (i.e., |f(t)| < ε f ), consider the positive or negative result of the product between the interaction force f(t) at the current time and the interaction force f(t - 1) at the previous time, and this positive or negative result indicates whether the direction of the interaction force has changed.

[0076] If |f(t)| < ε f , f(t - 1)f(t) > 0 (this positive or negative result indicates that the direction of the interaction force has not changed), then according to the control algorithm matching this condition in formula (7), based on the initial damping coefficient c0, the second amplification coefficient α, the maximum instability index I smax , the instability index threshold ε, the interaction force threshold ε f and the interaction force f(t), determine the admittance control parameters, and the admittance control parameters include the virtual damping c(t).

[0077] If |f(t)| < ε f , f(t - 1)f(t) < 0 (this positive or negative result indicates that the direction of the interaction force has changed), then according to the control algorithm matching this condition in formula (7), determine the initial damping coefficient c0 as the admittance control parameters, and the admittance control parameters include the virtual damping c(t).

[0078] Based on the above embodiments, the present disclosure can determine the admittance control parameters according to the instability index and the interaction force varying with the external environment stiffness, with reference to the following expression:

[0079]

[0080] In the above embodiments, by comprehensively considering the magnitude relationship between the instability index and the instability index threshold, the magnitude relationship between the absolute value of the interaction force and the preset interaction force threshold, and whether the direction of the interaction force at the current time and the previous time has changed, different control algorithms are selected to determine the admittance control parameters. Thereby, it can sense the change of the environmental stiffness in real time, and autonomously adjust the admittance control parameters adapted to the environmental stiffness according to the change of the environmental stiffness. Furthermore, by using the admittance control parameters, the behavior of the robot can be autonomously adjusted, thus effectively avoiding the unstable oscillation caused by the stiffness mutation and ensuring the stable and safe interaction between the robot and the environment.

[0081] In this embodiment, the state data further includes: the reference end position of the robot; correspondingly, as Figure 2 shown, the embodiment of controlling the end position of the robot according to the admittance control parameters may include the following content.

[0082] Obtain the deviation force between the interaction force and the preset desired force; calculate the deviation force based on the admittance control parameter to obtain the motion deviation of the robot; accumulate the motion deviation and the reference end position to obtain the target end position; solve the joint angle corresponding to the target end position through the inverse kinematics model; control the end position of the robot according to the joint angle.

[0083] Specifically, determine the interaction force F generated by human-robot interaction e (the same as the interaction force f(t) in the foregoing embodiment) and the preset desired force F of the robot d The deviation force F between r , and use the deviation force F r As the input parameter of the admittance controller, the admittance controller is based on the admittance control parameter c(t) determined in the above embodiment, and uses the mass-spring-damping model to calculate the deviation force F r The corresponding motion deviation e of the robot r . Add the motion deviation e r To the current reference end position X r To generate the target end position X d . Solve the joint angle q corresponding to the target end position through the inverse kinematics model d , and then generate the control signal τ corresponding to the joint angle q through the robot driver d ; According to the control signal τ r ; Control the end position of the robot to move to the target end position X r At the place. d

[0084] Based on the above embodiments, the following will be further elaborated through Figure 3 And Figure 4 The relationship between the signal change of the interaction force and the instability index and the damping coefficient shown in the figure further elaborates the effectiveness of the admittance hybrid control strategy based on the instability index and the interaction force proposed in the present disclosure.

[0085] Among them, Figure 3 The left figure shows the change of the interaction force over time in the cases of no interaction, human-robot interaction, and increasing environmental stiffness when changing the admittance parameter. The corresponding Figure 3 The right figure shows the change of the instability index over time. By comparison, it can be seen that the instability index is less than a certain instability index threshold in the cases of no interaction and low environmental stiffness during human-robot interaction. When the environmental stiffness suddenly increases, the instability index rises significantly and exceeds the instability index threshold, indicating the effectiveness of the instability index in judging the change of environmental stiffness.

[0086] Figure 4The left figure shows the variation of the interaction force with time in three cases of human - machine interaction and increased environmental stiffness when the admittance parameter is changed, corresponding to Figure 4 The right figure shows the variation of the instability index (indicated by the dashed line) and the damping parameter (indicated by the solid line) with time. By comparison, it can be seen that when the instability index is less than a certain threshold in the case of low environmental stiffness in the human - machine interaction environment, the damping coefficient remains unchanged. When the environmental stiffness suddenly increases, the instability index rises significantly and exceeds the threshold, and the damping coefficient increases. In a high - stiffness environment, switch to a control mode based on the change of the external interaction force, and the interaction damping coefficient remains unchanged. When the interaction force is less than the force threshold, the damping parameter is changed. When the direction of the interaction force changes, switch to a control model based on the instability index. Specifically, refer to the aforementioned formulas (6) - (8).

[0087] In summary, the robot control method provided by the embodiments of the present disclosure includes: obtaining the state data of the robot manipulator; wherein, the state data includes: the interaction force between the robot and the external environment; constructing an instability index based on the interaction force; wherein, the instability index is used to represent the unstable degree of the robot affected by the environmental stiffness during the human - machine interaction process; determining the admittance control parameter based on the instability index; and controlling the end - effector position of the robot according to the admittance control parameter.

[0088] This technical solution proposes a variable - admittance control strategy for suppressing the oscillation of the robot caused by the change of environmental stiffness. This strategy can autonomously adjust the behavior of the robot according to the real - time change of the environmental stiffness, thereby effectively avoiding the unstable oscillation caused by the sudden change of stiffness and ensuring the stable and safe interaction between the robot and the environment. Among them:

[0089] It can sense in real - time and autonomously adjust the admittance parameter according to the change of environmental stiffness to achieve stable and safe interaction between humans and the environment;

[0090] It can achieve stable human - machine interaction in a high - stiffness environment and avoid unstable oscillation caused by the failure of the instability index in a continuous high - stiffness environment;

[0091] The proposed instability index has a smaller delay and higher detection accuracy compared with general methods.

[0092] Figure 5 This is a schematic structural diagram of a robot control device provided by the embodiments of the present disclosure. This device can be used to implement the robot control method, and this device can be implemented by software and / or hardware. As Figure 5 For example, a robot control device may include the following modules:

[0093] A data acquisition module 210 is configured to acquire the state data of the robotic arm of the robot; wherein, the state data includes: the interaction force between the robot and the external environment;

[0094] An instability index construction module 220 is configured to construct an instability index based on the interaction force; wherein, the instability index is used to represent the degree of instability of the robot affected by the environmental stiffness during the human-robot interaction process;

[0095] An admittance control parameter determination module 230 is configured to determine admittance control parameters based on the instability index;

[0096] A robot control module 240 is configured to control the end position of the robot according to the admittance control parameters.

[0097] For the device provided in this embodiment, its implementation principle and the technical effects produced are the same as those of the foregoing method embodiment. For the sake of brief description, for the parts not mentioned in the device embodiment, reference may be made to the corresponding content in the foregoing method embodiment.

[0098] Figure 6 The figure is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. As Figure 6 shown, the electronic device 400 includes one or more processors 401 and a memory 402.

[0099] The processor 401 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 400 to perform desired functions.

[0100] The memory 402 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 401 may run the program instructions to implement the robot control method of the embodiment of the present disclosure described above and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage media.

[0101] In one example, the electronic device 400 may further include: an input device 403 and an output device 404, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0102] In addition, the input device 403 may further include, for example, a keyboard, a mouse, and the like.

[0103] The output device 404 can output various information to the outside, including the determined distance information, direction information, etc. The output device 404 may include, for example, a display, a speaker, a printer, a communication network, and remote output devices connected thereto, and the like.

[0104] Of course, for the sake of simplicity, Figure 6 only some of the components related to the present disclosure in the electronic device 400 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application scenarios, the electronic device 400 may further include any other appropriate components.

[0105] Furthermore, the present embodiment also provides a computer-readable storage medium storing a computer program for executing the above-mentioned robot control method.

[0106] A computer program product of a robot control method, device, electronic device, and medium provided by an embodiment of the present disclosure includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the method described in the foregoing method embodiments. For specific implementation, reference can be made to the method embodiments, which will not be elaborated herein.

[0107] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of additional identical elements in the process, method, article or device including the said element.

[0108] The above are only specific embodiments of the present disclosure, enabling those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A robot control method, characterized in that: include: Acquire state data of the robot arm; wherein the state data includes: the interaction force between the robot and the external environment; Constructing an instability index based on the interaction force; wherein the instability index is used to indicate the instability degree of the robot affected by the environmental stiffness during the human-machine interaction process; determining an admittance control parameter based on the instability index; The end position of the robot is controlled according to the admittance control parameter.

2. The method according to claim 1, characterized in that The constructing of an instability index based on the interaction force comprises: Convert the interaction force from a time domain signal to a frequency domain signal to obtain spectrum information corresponding to the interaction force; wherein the spectrum information includes: the center frequency of the frequency spectrum, the width of the frequency spectrum, the ratio between the high frequency spectrum and the spectrum sum, and the root mean square of the interaction force within a preset time; An instability index is constructed according to a preset amplification factor and the frequency spectrum information.

3. The method according to claim 1 or 2, characterized in that: The instability index includes: Wherein, λ represents the preset first magnification factor, μ ω represents the center frequency of the frequency spectrum corresponding to the interaction force, σ ω represents the width of the frequency spectrum corresponding to the interaction force, I ω represents the ratio between the high frequency spectrum corresponding to the interaction force and the sum of the spectrum corresponding to the interaction force, I f Represents the RMS value of the interaction force within a preset time window.

4. The method according to claim 1, characterized in that: The determining of the admittance control parameter based on the instability index comprises: Detecting whether the time for which the instability index remains at a peak value reaches a preset time threshold; If not, determining an admittance control parameter according to the instability index; If yes, the peak value of the instability index is taken as the maximum instability index, and the admittance control parameter is determined according to the maximum instability index and the interaction force varying with time.

5. The method according to claim 4, characterized in that Determining the admittance control parameter according to the instability index includes: When the instability index is less than a preset instability index threshold, determining a preset initial damping coefficient as an admittance control parameter; When the instability index is between the instability index threshold and the peak value of the instability index, the admittance control parameter is determined according to a preset second amplification factor, the initial damping factor, the instability index threshold and the instability index.

6. The method according to claim 5, characterized in that The admittance control parameters include: Wherein, c0 represents the initial damping coefficient, I s (t) and I s represents the instability index at the current time t, ε represents the instability index threshold, I smax represents the peak value of the instability index, and α is a second magnification coefficient preset between the instability index and the damping coefficient.

7. The method according to claim 4, characterized in that The determining of the admittance control parameter according to the maximum instability index and the interaction force varying with time comprises: Determine a comparison result between the absolute value of the interaction force at the current time and a preset interaction force threshold; Determining the positive or negative result of the product of the interaction force at the current time and the interaction force at the previous time; Different control algorithms are selected according to the size comparison result and the positivity result, and the admittance control parameter is determined according to the selected control algorithm, the maximum instability index, and the interaction force.

8. The method according to claim 7, characterized in that The determining of the admittance control parameter according to the selected control algorithm, the maximum instability index, and the interaction force comprises: Wherein, f(t) represents the interaction force at the current time t, f(t-1) represents the interaction force at the previous time t-1, and ε f Represents the interaction force threshold.

9. The method according to claim 1, characterized in that: The state data also includes: a reference end position of the robot; and controlling the end position of the robot according to the admittance control parameter includes: Obtaining a deviation force between the interaction force and a preset expected force; Calculating the deviation force based on the admittance control parameter to obtain the motion deviation of the robot; Accumulating the motion deviation and the reference end position to obtain a target end position; Solve the joint angle corresponding to the target end position through an inverse kinematics model; The end position of the robot is controlled according to the joint angle.

10. A robot control device, characterized in that: include: A data acquisition module is used to acquire the state data of the robot arm; wherein the state data includes: the interaction force between the robot and the external environment; An index construction module, used to construct an instability index based on the interaction force; wherein the instability index is used to indicate the instability degree of the robot affected by the environmental stiffness during the human-machine interaction process; an admittance control parameter determination module, configured to determine an admittance control parameter based on the instability index; A robot control module is used to control the end position of the robot according to the admittance control parameter.

11. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the method according to any one of claims 1 to 9.

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