Robot attitude matching method, electronic equipment, storage medium and program product

Abstract

The invention provides a posture matching method of a robot, electronic equipment, a storage medium and a program product, and relates to the field of robot control and human-computer interaction. The method comprises the following steps: acquiring master hand posture data and slave hand posture data of the robot; determining an attitude error vector between the master hand attitude data and the slave hand attitude data; determining an adjustment direction based on the attitude error vector; and a damping moment is applied to the main hand of the robot in the adjusting direction. According to the invention, the precision and efficiency of master-slave hand matching are improved.

Description

Technical Field

[0001] This application relates to the fields of robot control and human-computer interaction, and in particular to a robot posture matching method, electronic device, storage medium and program product. Background Technology

[0002] Master-slave collaborative systems have wide applications in remote operation, rehabilitation training, and surgical robotics. These systems typically consist of a master hand and a slave hand. The user controls the slave hand's posture, such as joint angles or Euler angles, through the operation of the master hand. In practice, when the slave hand reaches its mechanical or spatial limits, the master hand needs to backtrack or adjust along the direction of the posture error to achieve posture matching between the master and slave hands.

[0003] Currently, master-slave hand posture matching is typically achieved by applying torque or angle feedback. Specifically, the slave and master hand postures are acquired, and the posture error between them is calculated. Based on the calculated posture error, a corresponding torque is determined and applied to the master hand drive mechanism, thereby adjusting the master hand posture to achieve matching with the slave hand. However, this method results in a low accuracy rate in posture matching. Summary of the Invention

[0004] This application provides a robot posture matching method, electronic device, storage medium, and program product to improve the accuracy of posture matching.

[0005] In a first aspect, this application provides a robot posture matching method, comprising:

[0006] Acquire the robot's master hand posture data and slave hand posture data;

[0007] Determine the attitude error vector between the master hand attitude data and the slave hand attitude data;

[0008] Determine the adjustment direction based on the attitude error vector;

[0009] Apply a damping torque to the robot's main hand in the adjustment direction.

[0010] In one possible implementation, applying a damping torque to the robot's master hand in the adjustment direction includes:

[0011] The damping torque is dynamically adjusted based on the angular velocity component of the master hand in the adjustment direction. The magnitude of the damping torque is negatively correlated with the angular velocity component.

[0012] Apply a damping torque to the robot's main hand in the adjustment direction.

[0013] In one possible implementation, the damping torque is dynamically adjusted based on the angular velocity component of the master hand in the adjustment direction, including:

[0014] The damping coefficient is dynamically adjusted based on the attitude error vector, where the damping coefficient is positively correlated with the attitude error vector.

[0015] The negative of the product of the angular velocity component and the damping coefficient is determined as the damping torque.

[0016] In one possible implementation, determining the adjustment direction based on the attitude error vector includes:

[0017] The direction of the attitude error vector is determined as the adjustment direction.

[0018] In one possible implementation, before determining the adjustment direction based on the attitude error vector, the method further includes:

[0019] Determine whether the magnitude of the attitude error vector is less than or equal to the error threshold;

[0020] When the magnitude of the attitude error vector is greater than the error threshold, the adjustment direction is determined based on the attitude error vector.

[0021] In one possible implementation, the error threshold is determined in the following manner:

[0022] Determine the main operator's operational phase;

[0023] The error threshold is dynamically adjusted based on the operation stage.

[0024] In one possible implementation, acquiring the robot's master hand pose data and slave hand pose data includes:

[0025] The master hand posture data and slave hand posture data are acquired through joint angle sensors;

[0026] And / or, acquire master hand attitude data and slave hand attitude data through an inertial measurement unit.

[0027] Secondly, this application provides a robot posture matching device, comprising:

[0028] The acquisition module is used to acquire the robot's master hand posture data and slave hand posture data;

[0029] The determination module is used to determine the attitude error vector between the master hand attitude data and the slave hand attitude data;

[0030] The determination module is also used to determine the adjustment direction based on the attitude error vector;

[0031] The processing module is used to apply damping torque to the robot's main hand in the adjustment direction.

[0032] In one possible implementation, the processing module is specifically used for:

[0033] The damping torque is dynamically adjusted based on the angular velocity component of the master hand in the adjustment direction. The magnitude of the damping torque is negatively correlated with the angular velocity component.

[0034] Apply a damping torque to the robot's main hand in the adjustment direction.

[0035] In one possible implementation, the processing module is specifically used for:

[0036] The damping coefficient is dynamically adjusted based on the attitude error vector, where the damping coefficient is positively correlated with the attitude error vector.

[0037] The negative of the product of the angular velocity component and the damping coefficient is determined as the damping torque.

[0038] In one possible implementation, the determining module is specifically used for:

[0039] The direction of the attitude error vector is determined as the adjustment direction.

[0040] In one possible implementation, the determining module is specifically used for:

[0041] Determine whether the magnitude of the attitude error vector is less than or equal to the error threshold;

[0042] When the magnitude of the attitude error vector is greater than the error threshold, the adjustment direction is determined based on the attitude error vector.

[0043] In one possible implementation, the processing module is specifically used for:

[0044] Determine the main operator's operational phase;

[0045] The error threshold is dynamically adjusted based on the operation stage.

[0046] In one possible implementation, the acquisition module is specifically used for:

[0047] The master hand posture data and slave hand posture data are acquired through joint angle sensors;

[0048] And / or, acquire master hand attitude data and slave hand attitude data through an inertial measurement unit.

[0049] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0050] The memory stores instructions that the computer executes;

[0051] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0052] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the first aspect and / or various possible embodiments of the first aspect.

[0053] Fifthly, this application provides a computer program product, including a computer program that, when executed, implements the first aspect and / or various possible implementations of the first aspect.

[0054] This application provides a robot posture matching method, electronic device, storage medium, and program product, relating to the fields of robot control and human-computer interaction. The method includes: acquiring robot master hand posture data and slave hand posture data; determining the posture error vector between the master hand posture data and the slave hand posture data; determining an adjustment direction based on the posture error vector; and applying a damping torque to the robot's master hand in the adjustment direction. This application first calculates the posture error vector using real-time master hand posture data and slave hand posture data; secondly, based on the posture error vector, it determines the adjustment direction and applies a damping torque to the robot's master hand in the determined adjustment direction, thereby dynamically restricting user operation along that adjustment direction. The above process reduces user misoperation through directional guidance, significantly reducing the probability of matching failure. Furthermore, the application of the damping torque is correlated with the posture error vector in real time, ensuring the naturalness and smoothness of damping assistance, thereby improving the accuracy and efficiency of master-slave hand matching. Attached Figure Description

[0055] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0056] Figure 1 A flowchart illustrating the robot posture matching method provided in this application embodiment. Figure 1 ;

[0057] Figure 2 A flowchart illustrating the robot pose matching method provided for the implementation of this application. Figure 2 ;

[0058] Figure 3 A schematic diagram of the robot posture matching device provided in an embodiment of this application;

[0059] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0060] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0062] Master-slave hand posture matching technology is crucial in fields such as minimally invasive laparoscopic surgical robots and industrial remote operation, but existing methods have significant shortcomings. Currently, master-slave hand posture matching mainly relies on torque control matching methods. This method calculates the posture errors between the master and slave hands in real time, generates a restoring torque pointing towards the matching posture, and guides the master hand to adjust in the direction of the error. For example, when the slave hand cannot continue to adjust due to mechanical limits, the system applies a torque to the master hand in the opposite direction of the posture error, prompting the user to return to the matching posture. However, this method only provides guidance through torque feedback and lacks impedance control for incorrect adjustment directions. Users may misoperate, causing the adjustment direction to deviate from the correct path, thus leading to matching failure.

[0063] In minimally invasive laparoscopic surgical robots, the operator precisely controls the slave hand (such as a robotic arm) to complete the surgery. When the slave hand cannot reach the target posture due to mechanical structure or surgical space limitations, the master hand needs to adjust its posture to achieve a match. Current technology relies primarily on the operator's perception of force feedback or visual cues to determine the adjustment direction. However, the lack of intelligent guidance for adjustment direction makes it easy for the operator to repeatedly adjust due to incorrect operation direction. This not only prolongs the operation time and reduces surgical efficiency but may also increase surgical risks.

[0064] Similar problems exist in industrial remote operation scenarios. Operators control slave hands via a master hand to perform assembly or maintenance in confined spaces. Once the slave hand becomes unable to move due to spatial obstacles, the master hand's posture adjustment must strictly adhere to a specific direction. Current technology is insufficient in this regard, requiring operators to rely heavily on experience for repeated attempts, resulting in low operational efficiency, fatigue, and potentially damage to equipment or safety issues.

[0065] In summary, the shortcomings of existing technologies in directional cues and damping control force users to rely on extensive trial and error based on experience when matching master-slave hand postures, resulting in low operational efficiency and fatigue. Therefore, developing a control method that can provide clear directional guidance to assist users in making precise adjustments is an urgent need to improve the matching accuracy, operational efficiency, and user experience of master-slave collaborative systems.

[0066] To address the aforementioned issues, this application provides a robot posture matching method, which involves acquiring the robot's master hand posture data and slave hand posture data; determining the posture error vector between the master hand posture data and the slave hand posture data; determining the adjustment direction based on the posture error vector; and applying a damping torque to the robot's master hand in the adjustment direction.

[0067] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0068] The robot posture matching method provided in this application can be executed by a computing device such as a server or server cluster. The server can be a mobile phone, computer, tablet, or other similar device. This application does not impose any particular restrictions on the implementation method of the execution entity.

[0069] Figure 1 A flowchart illustrating the robot posture matching method provided in this application embodiment. Figure 1 ,like Figure 1 As shown, the method includes:

[0070] S101. Obtain the robot's master hand posture data and slave hand posture data.

[0071] The master hand posture data represents the real-time parameters of the master hand's spatial state; the slave hand posture data represents the real-time parameters of the slave hand's spatial state. For example, real-time parameters include joint angles, Euler angles, or position coordinates. It should be noted that this is merely an example.

[0072] The master hand serves as the user's operating terminal, while the slave hand acts as the execution terminal; the two operate in tandem through a master-slave collaborative system. Optionally, the master hand can be a robotic arm or a glove-type controller, while the slave hand can be an abdominal surgical instrument or a remotely operated robotic arm.

[0073] S102. Determine the attitude error vector between the master hand attitude data and the slave hand attitude data.

[0074] The posture error vector is the difference vector between the master hand posture data and the slave hand posture data, used to measure the degree of matching.

[0075] As an example, if the joint angle of the master hand is θm and the joint angle of the slave hand is θs, then the posture error vector is Δθ = θm - θs.

[0076] S103. Determine the adjustment direction based on the attitude error vector.

[0077] For example, determining the adjustment direction based on the attitude error vector includes: determining the direction of the attitude error vector as the adjustment direction. This can be understood as splitting the attitude error vector into two directions to determine the adjustment direction, where the adjustment direction is the direction of the attitude error vector. Furthermore, this adjustment direction can be considered an incorrect adjustment direction. This direction splitting logic allows users to intuitively perceive whether the adjustment direction is correct, reducing reliance on experience.

[0078] For example, if the attitude error vector is [5°, 0°, -3°], then the adjustment direction is [5°, 0°, -3°], and the opposite direction is [-5°, 0°, 3°].

[0079] This example ensures that the user's action path always matches the matching requirements by clearly distinguishing the direction of error adjustment.

[0080] S104. Apply a damping torque to the robot's main hand in the adjustment direction.

[0081] After determining the adjustment direction, a damping torque is applied to the robot's master arm in that direction. This effectively reduces user error through directional guidance, significantly lowering the probability of matching failure.

[0082] This embodiment first calculates the posture error vector using real-time master hand posture data and slave hand posture data. Second, based on the posture error vector, an adjustment direction is determined, and a damping torque is applied to the robot's master hand in that direction, dynamically restricting user operation along that direction. This process reduces user error through directional guidance, significantly lowering the probability of matching failure. Furthermore, the application of the damping torque is correlated with the posture error vector in real time, ensuring the naturalness and smoothness of the damping assistance, thereby improving the accuracy and efficiency of master-slave hand matching.

[0083] Based on the above embodiments, applying a damping torque to the robot's main hand in the adjustment direction includes: dynamically adjusting the damping torque according to the angular velocity component of the main hand in the adjustment direction, wherein the magnitude of the damping torque is negatively correlated with the angular velocity component; and applying a damping torque to the robot's main hand in the adjustment direction.

[0084] After determining the adjustment direction, this embodiment further calculates the angular velocity component of the main hand based on that adjustment direction. For example, if the main hand rotates at a speed of 5° / s in that adjustment direction, then the angular velocity component is 5° / s. Specifically, the damping torque is generated by dynamically adjusting the damping torque through the angular velocity component. The magnitude of the damping torque is negatively correlated with the angular velocity component. This negative correlation means that the magnitude of the damping torque decreases as the angular velocity component increases, or increases as the angular velocity component decreases.

[0085] For example, the angular velocity component in the adjustment direction is output in real time by the angular velocity sensor of the main hand. Based on the angular velocity component and the preset negative correlation, the magnitude of the damping torque is dynamically adjusted, and the calculated damping torque is output to the drive mechanism of the main hand to suppress the user from adjusting in the adjustment direction.

[0086] This application embodiment achieves a balance between guidance and restraint by dynamically adjusting the magnitude of the damping torque, so that the resistance changes with the operating speed when the user operates in the adjustment direction. Specifically, the magnitude of the damping torque is negatively correlated with the angular velocity component; the faster the user operates in the adjustment direction, the less resistance they experience, avoiding abrupt operation caused by fixed resistance. Dynamically adjusting the damping torque makes the user's operation smoother when approaching the matching point, reducing repeated adjustments caused by fixed resistance. The negative correlation design allows the system to adapt to the operating habits of different users, improving the naturalness of master-slave matching.

[0087] Furthermore, master-slave hand posture matching also relies on impedance control. Specifically, by pre-setting the impedance model of the master hand (such as the joint damping coefficient), resistance is applied when the master hand deviates from the matching direction. For example, when a user attempts to adjust the master hand in the wrong direction, the movement is restricted by increasing the damping torque. However, existing impedance control typically uses a fixed damping coefficient, which cannot be dynamically adjusted according to posture errors, resulting in unnatural damping effects and potentially affecting the smoothness of operation due to excessive damping when approaching the matching state.

[0088] To address this issue, this application introduces a dynamic damping coefficient and further determines the damping torque based on the dynamic damping coefficient. Specifically, the damping torque is dynamically adjusted based on the angular velocity component of the master arm in the adjustment direction, including: dynamically adjusting the damping coefficient based on the attitude error vector, wherein the damping coefficient is positively correlated with the attitude error vector; and determining the damping torque by taking the negative of the product of the angular velocity component and the damping coefficient. The positive correlation means that the damping coefficient increases as the magnitude of the attitude error vector increases and decreases as the magnitude of the attitude error vector decreases. For example, if the magnitude of the attitude error vector is 10°, the damping coefficient is k. base ×1.5, the damping coefficient is k when the magnitude of the attitude error vector is 5°. base×0.8. This positive correlation design enables the method provided in this application embodiment to adapt to matching requirements with different error ranges, improving the overall stability of the method.

[0089] Furthermore, the adjusted damping coefficient is substituted into the formula for calculating the damping moment. The formula for calculating the damping moment is as follows: τ d =-k d ×ω e , where τ d k represents the magnitude of the damping torque. d ω represents the negative correlation coefficient. e This represents the angular velocity component.

[0090] This application embodiment improves operational comfort by dynamically adjusting the damping coefficient, allowing the damping torque to vary with the attitude error. Specifically, the larger the magnitude of the attitude error vector, the larger the damping coefficient, and the stronger the guiding force experienced by the user, resulting in higher matching efficiency. Furthermore, the dynamic variation of the damping coefficient with the magnitude of the error vector avoids the abrupt operation caused by fixed damping, making the operation smoother, especially when approaching the matching point.

[0091] Based on the above embodiments, before determining the adjustment direction based on the attitude error vector, the method further includes: determining whether the magnitude of the attitude error vector is less than or equal to an error threshold; when the magnitude of the attitude error vector is greater than the error threshold, determining the adjustment direction based on the attitude error vector.

[0092] In this embodiment, it can be understood that before determining the adjustment direction, it is necessary to first determine whether the magnitude of the attitude error vector is less than or equal to the error threshold, and determine the subsequent operation based on the determination result. That is, the matching status flag is determined based on the determination result, and the subsequent operation process is determined based on the matching status flag. If the magnitude of the attitude error vector is less than or equal to the error threshold, the damping setting is canceled, allowing the master hand to operate freely. Optionally, if the magnitude of the attitude error vector is less than or equal to the error threshold, it is necessary to generate a corresponding torque or impedance based on the attitude error vector and apply the torque or impedance to the master hand.

[0093] Furthermore, if the magnitude of the attitude error vector is greater than the error threshold, an adjustment direction determination operation needs to be performed. The detailed principle has been explained in the previous embodiments, and will not be repeated here.

[0094] This application embodiment improves the accuracy and efficiency of posture matching by determining subsequent operation procedures based on the matching status flag.

[0095] Furthermore, the error threshold is determined by: determining the operation stage of the master operator; and dynamically adjusting the error threshold based on the operation stage. In this embodiment, the error threshold is dynamically adjusted according to the operation stage of the master operator (e.g., coarse adjustment, fine adjustment). For example, a larger error threshold is set in the coarse adjustment stage to speed up the matching process, while a smaller error threshold is set in the fine adjustment stage to improve accuracy.

[0096] In summary, it can be understood that the embodiments of this application further optimize the adaptability of matching judgment by dynamically adjusting the error threshold, and significantly improve the flexibility and efficiency of the operation process, avoiding the matching misjudgment or low efficiency caused by a fixed threshold.

[0097] Based on the above embodiments, acquiring the robot's master hand posture data and slave hand posture data includes: acquiring master hand posture data and slave hand posture data through joint angle sensors; and / or, acquiring master hand posture data and slave hand posture data through an inertial measurement unit (IMU). Here, a joint angle sensor refers to a sensor that measures the rotation angle of a mechanical joint, such as an encoder; an inertial measurement unit (IMU) refers to a sensor that measures acceleration and angular velocity, such as a three-axis gyroscope.

[0098] This embodiment acquires real-time posture data of the master and slave hands using joint angle sensors or inertial measurement units (IMUs). For example, in surgical robots, joint angle sensors are used to measure the rotation angles of the robotic arm joints, and IMUs are used to measure the three-dimensional spatial posture of the master hand controller. This step provides diverse data sources for subsequent processing.

[0099] Furthermore, embodiments of this application further enhance the accuracy and robustness of attitude data acquisition through multi-sensor fusion. For example, in complex operational scenarios, the combined use of joint angle sensors and IMUs ensures the real-time performance and reliability of attitude data, thereby providing higher-quality input for subsequent processing. Multi-sensor fusion significantly enhances the adaptability and stability of attitude matching, especially in high-precision or dynamic operational requirements.

[0100] Next, examples will be given to illustrate how to use the robot posture matching method provided in the embodiments of this application. Figure 2 A flowchart illustrating the robot pose matching method provided for the implementation of this application. Figure 2 .like Figure 2 As shown, the method includes:

[0101] Data acquisition phase: The sensors of the master and slave hands acquire posture data in real time and transmit it to the controller through the communication module.

[0102] Error calculation and judgment stage: The controller calculates the attitude error vector and compares it with the dynamic error threshold to determine the matching state.

[0103] Directional guidance phase: Based on the attitude error vector, the correct and incorrect adjustment directions are defined, and a dynamic damping torque is applied in the incorrect direction. The dynamic damping coefficient is adaptively adjusted according to the magnitude of the attitude error vector to ensure that the damping strength matches the operational requirements.

[0104] Damping control and matching release phase: When the matching status is matched, the damping torque is canceled and the master can operate freely; when the matching status is mismatched, the damping torque is maintained until the user adjusts in the correct direction.

[0105] The entire process is achieved through closed-loop feedback, ensuring that the main hand operation is always performed in the correct direction, while dynamically adapting to different error states, thereby improving operating efficiency and comfort.

[0106] It should be noted that when the matching state is mismatched, the magnitude of the attitude error vector is greater than the error threshold; when the matching state is matched, the magnitude of the attitude error vector is less than or equal to the error threshold.

[0107] Furthermore, the embodiments of this application are applicable to master-slave collaborative systems, such as minimally invasive laparoscopic surgical robots, industrial remote-controlled devices, and rehabilitation training devices. In surgical scenarios, surgeons control slave hands to perform delicate operations using a master hand. When the slave hand cannot be further adjusted due to mechanical structure or spatial limitations, the master hand needs to perform posture matching based on the slave hand's extreme state. This application requires real-time acquisition of posture data from both the master and slave hands, and the generation of damping torque based on directional guidance to prevent the user from adjusting in the wrong direction. This method can be integrated into the controller of the master-slave collaborative system, working collaboratively with the actuator through an algorithm module to form closed-loop control.

[0108] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0109] Figure 3 This is a schematic diagram of the robot posture matching device provided in the embodiments of this application, as shown below. Figure 3 As shown, the robot posture matching device provided in this embodiment includes:

[0110] The acquisition module 301 is used to acquire the robot's master hand posture data and slave hand posture data;

[0111] The determination module 302 is used to determine the attitude error vector between the master hand attitude data and the slave hand attitude data;

[0112] The determination module 302 is also used to determine the adjustment direction based on the attitude error vector;

[0113] Processing module 303 is used to apply damping torque to the robot's main hand in the adjustment direction.

[0114] In one possible implementation, the processing module 303 is specifically used for:

[0115] The damping torque is dynamically adjusted based on the angular velocity component of the master hand in the adjustment direction. The magnitude of the damping torque is negatively correlated with the angular velocity component.

[0116] Apply a damping torque to the robot's main hand in the adjustment direction.

[0117] In one possible implementation, the processing module 303 is specifically used for:

[0118] The damping coefficient is dynamically adjusted based on the attitude error vector, where the damping coefficient is positively correlated with the attitude error vector.

[0119] The negative of the product of the angular velocity component and the damping coefficient is determined as the damping torque.

[0120] In one possible implementation, the determining module 302 is specifically used for:

[0121] The direction of the attitude error vector is determined as the adjustment direction.

[0122] In one possible implementation, the determining module 302 is specifically used for:

[0123] Determine whether the magnitude of the attitude error vector is less than or equal to the error threshold;

[0124] When the magnitude of the attitude error vector is greater than the error threshold, the adjustment direction is determined based on the attitude error vector.

[0125] In one possible implementation, the processing module 303 is specifically used for:

[0126] Determine the main operator's operational phase;

[0127] The error threshold is dynamically adjusted based on the operation stage.

[0128] In one possible implementation, the acquisition module 301 is specifically used for:

[0129] The master hand posture data and slave hand posture data are acquired through joint angle sensors;

[0130] And / or, acquire master hand attitude data and slave hand attitude data through an inertial measurement unit.

[0131] The robot posture matching device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0132] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. For example, a processing module can be a separate processing element, or it can be integrated into an integrated circuit within the above device. Alternatively, it can be stored as program code in the device's memory, and its functions can be called and executed by a processing element. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0133] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs). As another example, when a module is implemented by calling program code through a processing element, that processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together to implement a System-On-a-Chip (SOC).

[0134] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 400 provided in this application embodiment may include: a processor 401, and a memory 402 communicatively connected to the processor, wherein:

[0135] The memory stores instructions that the computer executes;

[0136] The processor executes computer execution instructions stored in memory to implement the method described in the foregoing method embodiments.

[0137] It should be understood that processor 401 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor. Memory 402 may include high-speed random access memory (RAM), and may also include non-volatile memory (NVM), such as at least one disk storage device, or a USB flash drive, external hard drive, read-only memory, disk, or optical disc, etc.

[0138] Optionally, the electronic device 400 may also include a communication interface 403. In specific implementations, if the communication interface 403, memory 402, and processor 401 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0139] Optionally, in a specific implementation, if the communication interface 403, memory 402 and processor 401 are integrated on a single integrated circuit, then the communication interface 403, memory 402 and processor 401 can communicate through an internal interface.

[0140] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the methods described in any of the foregoing embodiments.

[0141] It is understood that the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0142] An exemplary computer-readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the computer-readable storage medium. Of course, the computer-readable storage medium can also be a component of the processor. The processor and the computer-readable storage medium can reside in an ASIC. Alternatively, the processor and the computer-readable storage medium can exist as discrete components in an electronic device.

[0143] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a computer-readable storage medium, include several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application.

[0144] This application also provides a computer program product, including a computer program that, when executed, implements the method described in any of the foregoing embodiments.

[0145] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0146] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0147] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as these combinations of technical features do not contradict each other, they should be considered within the scope of this specification.

[0148] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0149] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A robot posture matching method, characterized in that, include: Acquire the robot's master hand posture data and slave hand posture data; Determine the posture error vector between the master hand posture data and the slave hand posture data; Based on the attitude error vector, the adjustment direction is determined; A damping torque is applied to the robot's main hand in the adjustment direction.

2. The method according to claim 1, characterized in that, Applying a damping torque to the robot's main hand in the adjustment direction includes: The damping torque is dynamically adjusted based on the angular velocity component of the main hand in the adjustment direction, wherein the magnitude of the damping torque is negatively correlated with the angular velocity component; The damping torque is applied to the robot's main hand in the adjustment direction.

3. The method according to claim 2, characterized in that, The step of dynamically adjusting the damping torque based on the angular velocity component of the main hand in the adjustment direction includes: The damping coefficient is dynamically adjusted based on the attitude error vector, wherein the damping coefficient is positively correlated with the attitude error vector. The negative of the product of the angular velocity component and the damping coefficient is determined as the damping torque.

4. The method according to any one of claims 1 to 3, characterized in that, Determining the adjustment direction based on the attitude error vector includes: The direction of the attitude error vector is determined as the adjustment direction.

5. The method according to any one of claims 1 to 3, characterized in that, Before determining the adjustment direction based on the attitude error vector, the method further includes: Determine whether the magnitude of the attitude error vector is less than or equal to the error threshold; When the magnitude of the attitude error vector is greater than the error threshold, the adjustment direction is determined based on the attitude error vector.

6. The method according to claim 5, characterized in that, The error threshold is determined in the following way: Determine the operation phase of the main hand; The error threshold is dynamically adjusted based on the operation stage.

7. The method according to any one of claims 1 to 3, characterized in that, The acquisition of the robot's master hand posture data and slave hand posture data includes: The master hand posture data and the slave hand posture data are acquired using a joint angle sensor; And / or, the master hand posture data and the slave hand posture data are acquired through an inertial measurement unit.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, are used to implement the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, Includes a computer program that, when executed, implements the method described in any one of claims 1-7.

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