Hand-off detection method, controller, and robot

Abstract

Embodiments of the present application provide a hand-off detection method, a controller and a robot. The method comprises: a controller of the robot acquiring a sampling signal of an end effector of a master hand of the robot. The controller of the robot determines whether the robot is in a hand-off state or an operating state according to whether a signal change within a preset time length meets a hand-off condition. The method achieves the effect of improving the accuracy and real-time performance of robot hand-off determination.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of robot control, and in particular, to a hand-off detection method, a controller and a robot. BACKGROUND

[0002] An abdominal minimally invasive surgery robot system realizes remote operation through master-slave control, and its safety highly depends on real-time perception of the operation state of a doctor. If the doctor accidentally leaves the master control platform (i.e., hand-off) and the system fails to timely interrupt the master-slave mapping, the slave robot arm may continue to perform unexpected actions, increasing the risk of surgery. Therefore, hand-off detection is a core technology to ensure safe operation of the system.

[0003] Existing hand-off detection schemes mostly rely on external sensors. For example, a pressure sensor is integrated into a master end effector, and a hand-off state is determined by a grip force threshold. A capacitive touch sensor is integrated into the master end effector, and detection is realized based on changes in skin contact capacitance. Alternatively, a visual monitoring device can be used to assist in judgment by capturing the position of the hand through a camera.

[0004] However, the method of realizing hand-off detection through external sensors is susceptible to environmental interference, has poor detection stability, is prone to false detection, and thus has low detection accuracy. SUMMARY

[0005] Embodiments of the present application provide a hand-off detection method, a controller and a robot to improve detection accuracy.

[0006] In a first aspect, embodiments of the present application provide a hand-off detection method applied to a master hand of a robot, comprising:

[0007] obtaining a sampling signal of at least one end operation unit of the master hand of the robot;

[0008] if a change of the sampling signal within a preset time length meets a preset hand-off condition, determining a working state of the robot as a hand-off state; otherwise, determining the working state of the robot as an operation state.

[0009] In an example, obtaining a sampling signal of at least one end operation unit of the master hand of the robot comprises:

[0010] obtaining an encoder value of an encoder of the end operation unit according to a preset sampling frequency;

[0011] generating the sampling signal according to the encoder value.

[0012] In an example, the end operation unit is an end joint and / or an end effector.

[0013] In an example, the end operation unit is an end joint, the preset time length comprises a first time length, and the change of the sampling signals in the preset time length conforms to the preset hand-off condition, including:

[0014] In the first time length, a signal difference value of adjacent two sampling signals is obtained;

[0015] If the signal difference values are all less than a first threshold value in the first time length, it is determined that the change of the sampling signals in the preset time length conforms to the preset hand-off condition.

[0016] In an example, the end operation unit is an end effector, the preset time length comprises a second time length, and the change of the sampling signals in the preset time length conforms to the preset hand-off condition, including:

[0017] A signal number of the sampling signals less than a second threshold value in the second time length is counted;

[0018] If the signal number is less than a third threshold value, it is determined that the change of the sampling signals in the preset time length conforms to the preset hand-off condition.

[0019] In an example, the end operation unit comprises an end effector and at least one end joint, the preset time length comprises a first time length corresponding to the end joint and a second time length corresponding to the end effector, and the change of the sampling signals in the preset time length conforms to the preset hand-off condition, including:

[0020] The sampling signals of the end joint in a first time length before a current time are obtained, and a signal difference value of adjacent two sampling signals of each end joint in the first time length is calculated;

[0021] The sampling signals of the end effector in a second time length before the current time are obtained, and a signal number of the sampling signals less than a second threshold value is counted;

[0022] If the signal difference values are all less than a first threshold value and the signal number is less than a third threshold value, it is determined that the change of the sampling signals in the preset time length conforms to the preset hand-off condition.

[0023] In an example, the method further comprises:

[0024] According to the working state, a state flag bit of the robot is updated, so that the robot switches a running mode according to the state flag bit.

[0025] In an example, the method further comprises:

[0026] If the working state of the robot is a hand-off state, the master-slave synchronization mode of the robot is switched to a joint impedance mode from a current master-slave synchronization mode.

[0027] In an example, before switching the robot from the current master-slave synchronization mode to the joint impedance mode, further comprising:

[0028] suspending the redundant joint obstacle avoidance strategy, and reducing the friction compensation of the force-controlled joint.

[0029] In a second aspect, the embodiments of the present application provide a hand-off detection device, comprising: a master hand applied to a robot, comprising:

[0030] an acquisition module configured to acquire a sampling signal of at least one end operation unit of the master hand of the robot;

[0031] a judgment module configured to determine that a working state of the robot is a hand-off state if a change of the sampling signal within a preset time length meets a preset hand-off condition, and determine that the working state of the robot is an operation state if not.

[0032] In an example, the acquisition module is configured to:

[0033] acquire an encoder value of an encoder of the end operation unit according to a preset sampling frequency;

[0034] generate the sampling signal according to the encoder value.

[0035] In an example, the end operation unit is an end joint and / or an end effector.

[0036] In an example, the end operation unit is an end joint, and the preset time length comprises a first time length; the judgment module is configured to:

[0037] acquire a signal difference value of two adjacent sampling signals within the first time length;

[0038] if the signal difference value is less than a first threshold value within the first time length, determine that the change of the sampling signal within the preset time length meets the preset hand-off condition.

[0039] In an example, the end operation unit is an end effector, and the preset time length comprises a second time length; the judgment module is configured to:

[0040] count a signal number of the sampling signals less than a second threshold value within the second time length;

[0041] if the signal number is less than a third threshold value, determine that the change of the sampling signal within the preset time length meets the preset hand-off condition.

[0042] In an example, the end operation unit comprises an end effector and at least one end joint, and the preset time length comprises a first time length corresponding to the end joint and a second time length corresponding to the end effector; the judgment module is configured to:

[0043] acquire sampling signals of the end joints in a first time period before the current time; and calculate signal difference values of each of the end joints between two adjacent sampling signals in the first time period;

[0044] acquire sampling signals of the end effector in a second time period before the current time; and count a number of sampling signals less than a second threshold value;

[0045] if the signal difference values are all less than a first threshold value and the number of sampling signals is less than a third threshold value, it is determined that a change of the sampling signals in a preset time period meets a preset hand-off condition.

[0046] In an example, the apparatus further includes:

[0047] a control module configured to update a state flag of the robot according to the working state, so that the robot switches a running mode according to the state flag.

[0048] In an example, the control module is configured to:

[0049] if the working state of the robot is the hand-off state, switch the robot from a current master-slave synchronization mode to a joint impedance mode.

[0050] In an example, the control module is configured to:

[0051] suspend a redundant joint obstacle avoidance strategy and reduce friction compensation of a force control joint.

[0052] In a third aspect, an embodiment of the present application provides a controller, including: a memory, a processor;

[0053] the memory stores computer execution instructions;

[0054] the processor executes the computer execution instructions stored in the memory, so that the processor executes the first aspect and / or various possible implementation manners of the first aspect.

[0055] In a fourth aspect, an embodiment of the present application provides a robot, a master hand of the robot including at least one end operation unit and a controller as in the third aspect and / or various possible implementation manners of the third aspect.

[0056] the end operation unit is a contactor operated by a user and / or at least one end joint fixedly connected with the end effector.

[0057] In a fifth aspect, an embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the first aspect and / or various possible implementation manners of the first aspect.

[0058] In a sixth aspect, an embodiment of the present application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to implement the first aspect and / or various possible implementation manners of the first aspect.

[0059] The hand-off detection method, the controller and the robot provided by the embodiments of the present application can realize hand-off state judgment based on the mechanical arm data, thereby reducing the hardware requirement of the external sensor, reducing the hardware cost of the robot, and reducing the difficulty of the robot in assembly design. In addition, the hand-off state judgment based on the mechanical arm data can ensure the synchronization between the judgment and the mechanical arm data, thereby improving the accuracy and real-time performance of the robot hand-off judgment. Moreover, the mechanical arm data is the data that exists in the use process of the mechanical arm, and the hand-off state judgment based on the data avoids the requirement of the external sensor data, and improves the universality of the hand-off judgment method. BRIEF DESCRIPTION OF DRAWINGS

[0060] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the present application.

[0061] Figure 1 Flowchart of the hand-off detection method provided by the present application Figure 1

[0062] Figure 2 Flowchart of the hand-off detection method provided by the present application Figure 2

[0063] Figure 3 Structure diagram of the hand-off detection device provided by the present application

[0064] Figure 4 Structure diagram of the controller provided by the present application.

[0065] The above drawings have shown the specific embodiments of the present application, and the following will have more detailed description. The drawings and the text description are not intended to limit the scope of the concept of the present application by any means, but to illustrate the concept of the present application to those skilled in the art by referring to the specific embodiments. DETAILED DESCRIPTION ​​

[0066] The exemplary embodiments will be described in detail below with reference to the drawings. In the following description, unless otherwise indicated, like numbers in the different drawings represent the same or similar elements. The following exemplary embodiments described are not meant to represent all implementations consistent with the present application. Rather, they are simply examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0067] With the rapid development of minimally invasive surgical technology, laparoscopic-assisted minimally invasive surgery has gradually become an important means of modern clinical surgical treatment. In order to further improve the surgical precision, reduce the trauma and expand the operating ability of the doctors, the laparoscopic minimally invasive surgical robot system has emerged as the times require. Among them, the master-slave control type robot system represented by the da Vinci surgical robot has been widely used in urology, gynecology, general surgery and other surgical scenes, significantly improving the operability and stability of the surgery.

[0068] In such surgical robot systems, the doctor realizes fine control by operating the master hand. The master hand and the slave hand are accurately mapped through the structure. In order to ensure the safety of the doctor's operation and the accuracy of the system response, the system needs to quickly detect and interrupt the master-slave mapping relationship when the doctor "hands off" the operation platform, to prevent the slave end mechanical arm from performing unnecessary or unintended actions. This process is called "hands-off detection", and its accuracy and real-time performance directly affect the safety and robustness of the entire surgical system.

[0069] Currently, most hands-off detection schemes rely on external sensor technology. For example, by integrating pressure sensors, capacitive touch sensors, visual monitoring devices or photoelectric, infrared sensors and other devices at the end effector of the master control, it can be determined in real time whether the doctor is holding the end effector. Although these methods can effectively detect the hands-off state, their complex structure, high cost, wiring complexity and excessive dependence on external environment and sensor performance significantly restrict the integration capability, stability and industrial application potential of the system. For example, in the da Vinci surgical robot and its derivative products, once it is detected that the doctor releases the end effector (i.e. "hands off" state), the system will immediately interrupt the master-slave mapping relationship or start the safety mode to avoid misoperation, but such a scheme has high hardware complexity, high maintenance cost and poor environmental adaptability, which limits its scope of promotion and universality.

[0070] In addition, there is no public literature or product that proposes a sensorless detection method based on the motion characteristics of the end joint of the robot master control platform and the encoder change characteristics for hands-off judgment. Although the existing hands-off detection method based on sensors can realize the recognition of the doctor's control state, there are still many outstanding defects and deficiencies.

[0071] For example, strong hardware dependency leads to complex system integration, which is not conducive to product standardization and modular design; additional sensors increase manufacturing costs and maintenance difficulty, and may fail due to wear and tear, environmental interference, calibration deviation, etc., affecting system stability and safety; some sensors are easily affected by factors such as hand humidity, wearing gloves, light changes or electromagnetic interference, resulting in reduced off-hand detection accuracy, and there is a risk of misjudgment or omission; high sensitivity detection may misjudge small operations as off-hand, reducing system response stability, while too low sensitivity may delay response, causing operation safety hazards, making it difficult to balance real-time and reliability; the current sensor-dependent solution often requires significant changes to the main control platform, limiting its adaptability and portability in different types of surgical robot systems, which is not conducive to technology promotion and large-scale deployment.

[0072] Therefore, it is of great significance to develop a new off-hand detection method relying on existing motion data without additional hardware to improve the practicality, reliability and integration of surgical robot systems. Based on this, it is urgent to develop an off-hand detection method without additional sensors, simple structure, high reproducibility and superior detection accuracy.

[0073] To this end, the present application proposes an off-hand detection method based on an existing master hand end operation unit. The present application analyzes the position change information of the two joints at the end of the master hand controlled by the doctor and the operation information of the end effector to realize sensorless accurate judgment of the off-hand state. The line of sight of the present application does not change the existing operation platform structure and does not increase any additional hardware cost, and only through the kinematics and encoder information of the original system, it realizes high robustness, high real-time doctor off-hand detection, and has good adaptability, real-time and engineering implementation value.

[0074] The off-hand detection method proposed in the present application first collects the sampling signals of the end operation unit of the main control platform at a fixed frequency. The end operation unit can be two end joints and an end effector. The controller can take the encoder values of the encoders of the end joints and the end effector as the sampling signals. The sampling period can be 2ms. The two end joints can be denoted as Joint6 and Joint7, respectively. The end effector can be denoted as Gripper.

[0075] Subsequently, the controller can use the sliding time window technology to construct an incremental sequence of the values of Joint6 and Joint7 within a first time length. The controller can extract the signal difference value of the adjacent two sampling signals to obtain an incremental sequence composed of signal difference values within the sliding time window according to the first time length. If there is a signal difference value greater than or equal to the first threshold value in the incremental sequence, it can be determined that the master hand is in the user's operation state. If all signal difference values in the incremental sequence are less than the first threshold value, it can be determined that the master hand is in the off-hand state.

[0076] The first duration can be 200 ms. The first threshold can be 1.2 pulses.

[0077] Meanwhile, the controller can analyze the value of the Gripper in the second duration by using the sliding time window technology. The controller can count the number of sampling signals less than the second threshold in the second duration, so as to determine the opening and closing state of the end effector, and count the number of opening and closing times of the end effector. If the number of signals is greater than or equal to the third threshold, it can be determined that the master hand is in the user's operation state. If the number of signals is less than the third threshold, it can be determined that the master hand is in the hand-off state.

[0078] The second duration can be 100 ms. The second threshold can be 3000 pulses. The pulse value can be determined according to the pulse value when the end effector of different master hands is opened. The third threshold can be 2 times.

[0079] Subsequently, the controller can modify the flag bit of the master hand according to the working state. The flag bit can be denoted as flag. The working state can include the operation state and the hand-off state. The flag bit Flag=0 can correspond to the operation state, and Flag=1 can correspond to the hand-off state.

[0080] The controller can execute the corresponding response according to the flag bit. If Flag=1, the redundant joint obstacle avoidance strategy is suspended, and the friction compensation of the force control joint is reduced, in preparation for switching the impedance mode. If Flag=0, the master-slave synchronization is maintained.

[0081] In addition, the method also has high adjustable parameter property. The threshold and the time window can be dynamically configured according to actual needs, which is convenient for adapting to different master control mechanisms and surgical habits. At the same time, a differential filter or a standard deviation judgment mechanism can be further introduced to enhance the robustness of the hand-off detection.

[0082] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described in detail in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0083] Figure 1 Flowchart of the hand-off detection method provided by the present application Figure 1 As shown in Figure 1 The method is applied to a master hand of a robot. The controller of the robot is the execution subject of the method. The robot can also include a slave hand. When a user controls the master hand through the end effector of the master hand, the slave hand of the robot follows the motion of the master hand. The method comprises:

[0084] S101, acquiring a sampling signal of at least one end operating unit of a master hand of a robot.

[0085] Exemplarily, the user's operating end effector is usually located at the end of the master hand of the robot. Therefore, the controller can determine whether the user is currently in an operating state by acquiring the sampling signal of at least one end operating unit of the master hand of the robot.

[0086] In an example, the end operating unit is an end joint and / or an end effector.

[0087] Exemplarily, when the end operating unit is an end joint of the robot arm, the controller can correspondingly acquire the sampling signal of at least one end joint of the robot arm. For example, for a 7-joint robot arm, the controller can acquire the sixth joint and the seventh joint.

[0088] Exemplarily, when the end operating unit is an end effector at the end of the robot arm, the controller can correspondingly acquire the sampling signal of the end effector operated by the user. For example, the end effector can correspond to a gripper, a joystick, a trackball, etc.

[0089] In an example, the sampling signal can be a control signal of the end operating unit.

[0090] Exemplarily, when the user applies force to the end operating unit, the end operating unit will generate a corresponding control signal to control the corresponding end effector of the master hand to perform a corresponding operation according to the user's control. In this process, the controller can read the control signal and generate corresponding sampling information according to the control signal.

[0091] In another example, the sampling signal can be a position signal of the end operating unit.

[0092] Exemplarily, the end operating unit can be provided with a position sensor. The controller sends a reading instruction to the position sensor at a certain time interval to acquire the position coordinate data of the end operating unit.

[0093] For example, the position sensor can be an encoder or a laser displacement sensor.

[0094] For example, the encoder is installed at the joint to indirectly calculate the position of the end operating unit by measuring the rotation angle of the joint. For example, the encoder can convert the rotational displacement into a digital pulse signal.

[0095] For example, the laser displacement sensor can directly measure the distance and position information between the end operating unit and the target object. For example, the position coordinate data can be X, Y, Z coordinates in a three-dimensional space.

[0096] In another example, the sampling signal can also be a signal obtained by fusing signals collected by multiple sensors.

[0097] In S102, if the change of the sampling signal in the preset time period meets the preset hand-off condition, it is determined that the working state of the robot is the hand-off state. If not, it is determined that the working state of the robot is the operation state.

[0098] For example, the controller can collect and record the sampling signal in the preset time period, and analyze the change of the sampling signal, so as to determine the working state of the robot. The working state can include the hand-off state and the operation state.

[0099] In an example, the preset time period can be set according to the analysis condition. Alternatively, the preset time period can be set according to the type of the end operation unit.

[0100] For example, when the end operation unit is an end joint, the preset time period can be 200 ms. For another example, when the end operation unit is an end effector, the preset time period can be 100 ms.

[0101] In an example, when the master hand of the robot is in the hand-off state, the sampling signal of the end operation unit is usually stable in the inoperative state. Therefore, the controller can set a threshold value according to the stable value of the end operation unit in the inoperative state, and compare the sampling signal with the threshold value to determine the working state.

[0102] For example, if the sampling signal is consistent with the threshold value, it is determined that the master hand is in the hand-off state. If the sampling signal is inconsistent with the threshold value, it is determined that the master hand is in the operation state.

[0103] Alternatively, the threshold value can correspond to a small threshold value interval. The setting of the threshold value interval can avoid misjudgment caused by too high precision.

[0104] In another example, when the master hand of the robot is in the hand-off state, the sampling signal of the end operation unit is usually stable. Therefore, the controller can analyze the working state of the master hand of the robot according to the sampling signal curve or the sampling signal change value of the end operation unit in the preset time period.

[0105] For example, if the sampling signal curve matches the preset curve in the preset time period, it is determined that the master hand is in the hand-off state. If the sampling signal curve has an abnormal point or an abnormal curvature, it is determined that the master hand is in the operation state.

[0106] For example, if the sampling signal change value is less than the change threshold value within the preset time length, it is determined that the master hand is in the hand-off state. If the sampling signal change value is greater than the change threshold value, it is determined that the master hand is in the operating state.

[0107] In another example, the sampling signal within the preset time length can also be input into an algorithm model to predict and output the working state of the robot master hand.

[0108] Optionally, the algorithm model can be a deep learning model, a neural network model, a big data model, etc. The algorithm model is a pre-trained model.

[0109] In this example, by acquiring the sampling signal of the end operation unit of the robot master hand and determining whether the signal change within the preset time length meets the hand-off condition, the means for determining whether the robot is in the hand-off state or the operating state is realized based on the mechanical arm itself data, thereby reducing the hardware requirements of external sensors, reducing the hardware cost of the robot, and reducing the difficulty of the robot in assembly design. Moreover, the hand-off state determination based on the mechanical arm itself data can ensure the synchronization between the determination and the mechanical arm itself data, thereby improving the accuracy and real-time performance of the robot hand-off determination. In addition, the mechanical arm itself data is the data that exists during the use of the mechanical arm, and the hand-off state determination based on this data avoids the need for external sensor data, thereby improving the universality of the hand-off determination method.

[0110] In addition, the hand-off detection based on the external sensor usually needs to rely on the pressure, capacitance, photoelectricity or image data detected by the external sensor, and the collection of these data is easily affected by factors such as hand humidity, wearing gloves, light changes or electromagnetic interference. However, the hand-off state determination based on the mechanical arm itself data avoids the influence of external interference on data collection, thereby further improving the accuracy of the hand-off state determination.

[0111] In one example, S101, the sampling signal of at least one end operation unit of the master hand of the robot is acquired, including:

[0112] S1011, according to a preset sampling frequency, the encoder value of the encoder of the end operation unit is acquired.

[0113] For example, the controller first acquires the encoder value of the encoder of the end operation unit periodically according to the preset sampling frequency.

[0114] In one example, the preset sampling frequency can be determined according to the signal frequency of the encoder. For example, the sampling frequency can be once every 1ms, or once every 2ms, etc.

[0115] In one example, the controller can configure an internal hardware timer that triggers an interrupt according to the sampling frequency. When the interrupt occurs, the controller immediately sends a data read instruction to the encoder of the end-effector unit via a pre-set communication protocol. Upon receiving the instruction, the encoder sends the encoder value to the controller.

[0116] For example, the communication between the encoder and the controller can be via SPI, I2C, or SSI signals.

[0117] Optionally, the encoder value can be a pulse signal generated by the rotation of a grating disk or a magnetic grating disk inside the encoder. Alternatively, the encoder value can be a digital encoding value converted from the pulse signal.

[0118] For example, the digital encoding value can be a 16-bit binary number.

[0119] In one example, after the controller reads the encoder value, it performs a data check to confirm data integrity. If the check fails, a data retransmission mechanism is automatically triggered.

[0120] For example, the check can be a Cyclic Redundancy Check (CRC).

[0121] S1012. Generate a sampling signal according to the encoder value.

[0122] For example, after the controller obtains the encoder value, it can convert it into a sampling signal with a uniform format.

[0123] In one example, when there is only one end-effector unit, the controller can directly use the encoder value of the encoder of the end-effector unit as the sampling signal.

[0124] When there are multiple end-effector units, if the encoders of the multiple end-effector units are the same, the controller can directly use the encoder value of the encoder of the end-effector unit as the sampling signal.

[0125] In another example, the controller can scale the encoder value to the actual physical range of the joint of the robot arm, and use the physical range as the sampling signal.

[0126] For example, the encoder value in the range of 0 to 65535 is scaled to -180 degrees to 180 degrees.

[0127] In one example, the controller can also perform smoothing processing on multiple consecutive encoder values to suppress noise interference.

[0128] For example, the sliding average method can be used to take the average of the last 5 sampling values, or the Kalman filtering algorithm can be used in combination with the system model to predict the true value.

[0129] In this example, the real-time perception of the motion state of the end of the robot arm and the generation of accurate signals are achieved by triggering data collection at a preset sampling frequency and reading the encoder values of the end operation unit, and by combining the conversion processing means of the encoder values into standardized digital signals.

[0130] In one example, when the end operation unit is an end joint, the preset time length can be a first time length. For example, the first time length can be 200 ms.

[0131] In one example, when the end operation unit is an end joint, when the user contacts the master hand, due to the characteristics of the user himself, even if the user holds the handle of the master hand in a stationary state, the slight shaking of the user's arm will still cause the sampling signal of the end joint to change. Therefore, it can be considered that in the operation state, the sampling signal of the end joint is continuously changing.

[0132] When the user is away from the hand, the master hand needs to keep the position when the user is away from the hand from changing, so as to avoid accidental movement of the hand. Therefore, it can be considered that in the hand-off state, the sampling signal of the end joint will remain unchanged at the current pose of the joint.

[0133] For example, in one end joint, the step S102 of judging that the change of the sampling signal in the preset time length meets the preset hand-off condition includes:

[0134] S10211, obtaining the signal difference value of the adjacent two sampling signals.

[0135] S10212, if the signal difference value is less than the first threshold value within the first time length, it is determined that the change of the sampling signal in the preset time length meets the preset hand-off condition.

[0136] Exemplarily, the controller realizes accurate determination of whether the end operation unit of the robot arm is in the hand-off state by dynamically monitoring the continuous change characteristics of the sampling signal and combining the difference value analysis mechanism of the multi-level time window.

[0137] In one example, after the controller has collected the sampling signal sequence within the first time length, it sequentially calculates the difference value of the adjacent two sampling signals to obtain a signal difference value sequence. If the signal difference value in the signal difference value sequence is less than the first threshold value, the controller can determine that the change of the sampling signal in the preset time length meets the preset hand-off condition.

[0138] In one example, the first time length can be a sliding window. That is, the controller can obtain the sampling signal of the first time length before the current time at the current time and process the sampling signal.

[0139] In another example, the controller can calculate the difference between the sampling signal at the previous time and the sampling signal at the current time in real time during the sampling of the sampling signal, to obtain a signal difference. The controller can determine the start time of the first time length when the signal difference is less than the first threshold.

[0140] If the signal difference is less than the first threshold when the first time length is reached, the controller can determine that the change of the sampling signal within the preset time length meets the preset hand-off condition.

[0141] Otherwise, if the signal difference is greater than or equal to the first threshold within the first time length, the controller can restart the timing when the next signal difference less than the first threshold occurs.

[0142] In one example, the first threshold can be a small pulse value. For example, the first threshold can be 1.2 pulses, 1.3 pulses, 2 pulses, etc.

[0143] In this example, by monitoring whether the signal difference between adjacent sampling signals within the first time length is less than the first threshold, the analysis and verification of the sampling signal within the first time length is realized, and the effect of accurately determining whether the robot master hand is in the hand-off state is realized.

[0144] In one example, when the end operating unit is an end joint, the controller can simultaneously obtain the sampling data of at least one end joint. When at least one end joint indicates that the master hand is in the operating state, the controller can determine that the master hand is in the operating state. When all end joints indicate that the master hand is in the hand-off state, it can be determined that the master hand is in the hand-off state.

[0145] In one example, when the end operating unit is an end effector, the preset time length can be a second time length. For example, the second time length can be 100 ms.

[0146] In one example, when the end operating unit is an end effector, similar to the end joint, when the master hand is in the operating state, the sampling signal of the end effector will change with the user's operation. When the master hand is in the hand-off state, the sampling signal of the end effector will remain at a stable value.

[0147] Unlike the end joint, when the master hand is in the hand-off state, the stable value of the sampling signal of the end effector is usually the value when the end effector is not used. This value is usually a fixed value determined according to the end effector. The stable value of the end joint is the sampling signal corresponding to the pose of the end joint when the user hands off.

[0148] In the above step S102, determining that the change of the sampling signal of the end effector within the preset time length meets the preset hand-off condition includes:

[0149] S10221, counting a signal number of the sampling signals less than the second threshold in the second time length.

[0150] S10222, if the signal number is less than a third threshold, determining that a change of the sampling signals in a preset time length meets a preset hand-off condition.

[0151] Exemplarily, the controller can determine whether the user operates the controller at a time corresponding to each sampling signal by comparing each sampling signal with the second threshold. If the sampling signal is less than the second threshold, it can be determined that the sampling signal is a valid value. Further, the controller determines whether the end of the robot arm is in the hand-off state according to the valid signal number in the window.

[0152] In an example, the controller can determine whether each sampling signal is less than the second threshold after the sampling signals in the second time length have been collected, thereby accumulating the signal number of the sampling signals less than the second threshold. If the signal number is less than the third threshold, it is determined that the change of the sampling signals in the preset time length meets the preset hand-off condition.

[0153] In an example, the second time length can be a sliding window. That is, the controller can obtain the sampling signals in the second time length before the current time at the current time, and process the sampling signals.

[0154] In another example, the controller can detect a time when the sampling signal is greater than or equal to the second threshold as the start time of the second time during the collection of the sampling signals. Thereafter, the controller can accumulate the signal number of the sampling signals greater than or equal to the second threshold. If the signal number reaches the third threshold in the second time length, the controller can determine that the master hand is in the operating state.

[0155] The controller can restart accumulating the signal number of the sampling signals greater than or equal to the second threshold in the second time length when the next sampling signal greater than or equal to the second threshold is detected.

[0156] If the signal number does not reach the third threshold when the second time is reached, the controller can determine that the change of the sampling signals in the preset time length meets the preset hand-off condition.

[0157] In an example, the third threshold can be a small natural number. For example, the third threshold can be 2 times, 3 times, etc.

[0158] In an example, since the pulse values of different end effectors in the non-use state are different, the second threshold can be a threshold determined according to the pulse value of the end effector in the non-use state.

[0159] For example, when the end effector is a gripper, the gripper is in an open state when it is not in use. At this time, the encoding value of the encoder of the gripper can be 3000 pulses. Therefore, the second threshold value can be 3000 pulses.

[0160] In this example, the analysis and verification of the sampling signal in the second time length is achieved by means of counting the number of signals of the sampling signal below the second threshold value in the second time length, and the effect of accurately determining whether the master hand of the robot is in the hand-off state is achieved.

[0161] In an example, when the end effector includes an end effector and at least one end joint, the preset time length includes a first time length corresponding to the end joint and a second time length corresponding to the end effector.

[0162] In the step S102, the change of the sampling signal in the preset time length meets the preset hand-off condition, which includes:

[0163] S10231, obtaining the sampling signal of the end joint in the first time length before the current time. And calculating the signal difference value of the adjacent two sampling signals in the first time length.

[0164] For example, for the end joint, the controller can obtain the sampling signal in the first time length before the current time at the current time to obtain a sampling signal sequence. The controller can calculate the signal difference value of the adjacent two sampling signals in the sampling signal sequence to obtain a signal difference value sequence.

[0165] S10232, obtaining the sampling signal of the end effector in the second time length before the current time. And counting the number of signals less than the second threshold value.

[0166] For example, for the end effector, the controller can obtain the sampling signal in the second time length before the current time at the current time. The controller can count the number of sampling signals less than the second threshold value in the sampling signal in the second time length.

[0167] S10233, if the signal difference value is less than the first threshold value and the signal number is less than the third threshold value, it is determined that the change of the sampling signal in the preset time length meets the preset hand-off condition.

[0168] For example, the controller can compare the signal difference value obtained in step S10231. If the signal difference value of the at least one end joint is less than the first threshold value, it means that the at least one end joint remains stationary.

[0169] The controller can compare the signal number obtained in step S10232. If the signal number is less than the third threshold value, it means that the end effector is in a stationary state.

[0170] If the at least one end joint and the end effector are both in a static state, it can be determined that the change of the sampling signal within the preset time length meets the preset hand-off condition.

[0171] Otherwise, if the signal difference of the end joint is greater than the first threshold value, it can be determined that the master hand is in an operating state. At this time, if the end effector is in a static state, it means that the user is operating the handle to move the master hand, but does not control the end effector.

[0172] Or, if the number of signals is greater than or equal to the third threshold value, it means that the end effector is being operated. At this time, if the end joint is in a static state, it means that the user is operating a fixed position.

[0173] In an example, when including one end joint and one end effector, the end joint can be the 7th joint and the end effector can be a gripper based on the 7-joint robot used in the present application.

[0174] In an example, when including multiple end joints, the number of end joints can be 2, 3, 4, etc.

[0175] When including 2 end joints, the end joints can be the 7th joint and the 6th joint and the end effector can be a gripper based on the 7-joint robot used in the present application. When including 3 end joints, the end joints can be the 7th-5th joints and the end effector can be a gripper based on the 7-joint robot used in the present application. And so on.

[0176] Preferably, when including the 7th joint and the 6th joint and the gripper, the hand-off judgment accuracy of the present application can reach the best.

[0177] In the present example, by fusing the multi-point continuous monitoring of the end joint motion difference and the statistical threshold analysis of the end effector signal amplitude, combining the dynamic feature extraction of the double time window and the multi-condition joint verification means, the high-precision recognition and anti-interference safety determination effect of the robot hand-off state are realized, and the accuracy of the hand-off detection is improved.

[0178] In an example, the robot can also be provided with a state flag bit.

[0179] S103, updating the state flag bit of the robot according to the working state, so that the robot switches the running mode according to the state flag bit.

[0180] Exemplarily, the controller realizes the decoupling mapping of the working state and the control mode through the dynamic updating mechanism of the state flag bit, and provides a state decision basis for the adaptive switching of the robot running mode.

[0181] In an example, the controller can first acquire the current working state of the robot according to the above steps. Then, the controller can update the internal state flag register according to the predefined state coding rule.

[0182] In an example, the register is usually designed as a bit field, and different bit segments represent the working mode, safety level, and exception type.

[0183] For example, the state flag can be denoted as flag. When flag = 1, it indicates that the master hand of the robot is in the hand-off state. When flag = 0, it indicates that the master hand of the robot is in the operating state.

[0184] In this example, by updating the state flag in real time, the real-time and consistency of state updating are ensured, and other controllers of the robot can timely acquire the state of the robot, so as to quickly adjust the control strategy according to the real-time state.

[0185] In an example, when it is determined that the robot is in the hand-off state, the controller can perform the following operations:

[0186] S104, pause the redundant joint obstacle avoidance strategy, and reduce the friction compensation of the force control joint.

[0187] Exemplarily, the controller optimizes the allocation of computing resources and improves the control stability in a specific working state through the dynamic reconstruction mechanism of the control strategy.

[0188] In an example, when the state flag indicates that the robot enters the hand-off state, the controller first sends a pause instruction to the obstacle avoidance module. The instruction can be implemented by closing the collision detection thread of the redundant joint or disabling the related sensor data input, which can reduce the CPU occupancy.

[0189] In an example, the controller dynamically adjusts the compensation parameter according to the friction model of the force control joint, reduces the friction compensation coefficient, and reduces the joint jitter caused by excessive compensation in the hand-off state.

[0190] For example, the friction compensation coefficient can be linearly reduced from 1.0 in normal operation to 0.6-0.8.

[0191] In an example, the controller can suspend the priority of the obstacle avoidance task or set it to a dormant state based on the task scheduling of the real-time operating system to realize the suspension of the strategy.

[0192] In another example, the controller can read the corresponding value from the pre-stored compensation parameter table according to the current state flag by using the parameter table query method, and use the table lookup method to improve the parameter adjustment efficiency.

[0193] The redundant joint obstacle avoidance strategy is a multiple collision detection and avoidance mechanism configured to improve system reliability, which can avoid false triggering caused by environmental disturbance in the off-hand state.

[0194] The friction compensation is a nonlinear control term used to offset the mechanical friction of the joint in the force control system, which can reduce the force feedback noise in the non-operation state.

[0195] In this example, the collision detection calculation task of the redundant joint is dynamically disabled to reduce system resource occupation, and the friction compensation parameter of the force control joint is simultaneously optimized to suppress mechanical vibration in the non-operation state, thereby achieving a synergistic improvement effect of control accuracy and calculation efficiency of the robot in the low-priority mode.

[0196] In an example, when it is determined that the robot is in the off-hand state, the controller can perform the following operations:

[0197] S105, if the working state of the robot is in the off-hand state, the master-slave synchronization mode of the robot is switched to the joint impedance mode.

[0198] Exemplarily, the controller realizes a flexible control transition from master-slave synchronization to joint impedance in the off-hand state through a seamless switching mechanism of the control mode.

[0199] In an example, when the state flag bit detects the off-hand state, the controller first sends a stop instruction to the master-slave synchronization module to terminate the position / force tracking of the master and slave hands. At the same time, the controller can activate the joint impedance control module.

[0200] In an example, the joint impedance control module adjusts the joint stiffness (K) and damping (D) parameters to make the robot end perform passive compliance characteristics similar to a spring-damper system.

[0201] In an example, the controller can realize mode switching by switching control algorithm pointers or calling different dynamic link libraries based on the state jump of the control mode manager.

[0202] In another example, the controller can use a gradient parameter transition method to gradually attenuate the master-slave synchronization gain and improve the impedance parameter in the transition period to avoid impact caused by mode switching.

[0203] For example, the transition period can be 100-200 ms.

[0204] The master-slave synchronization mode refers to the motion / force command of the robot end strictly following the input of the master end, which is suitable for precise operation scenarios.

[0205] The joint impedance mode simulates the physical impedance characteristics to realize environment adaptation, which is suitable for safe interaction in the off-hand state.

[0206] In this example, through the switching mechanism, the preloading of the dual-mode parameters and the dynamic calibration of the switching threshold, the control continuity and environmental adaptability are ensured.

[0207] Figure 2 Flowchart of the off-hand detection method provided in the present application Figure 2 As shown in Figure 1 the embodiment, on the basis of Figure 3 the embodiment, the method comprises:

[0208] S201, system initialization.

[0209] Exemplarily, the control system of the robot is initialized.

[0210] S202, the encoder values of the two end joints and the gripper are collected in a timely manner.

[0211] Exemplarily, when the end execution unit comprises two end joints and a gripper, the controller can continuously collect the encoder values of the two end joints and the gripper during the operation of the robot.

[0212] In an example, the encoder values are the sampling information described above.

[0213] S203, the angle change in the sliding window is calculated.

[0214] Exemplarily, the controller can set a sliding window for each of the end joints and the gripper.

[0215] For example, the sliding window of the end joint can be 200 ms, and the sliding window of the gripper can be 100 ms.

[0216] In an example, the last time point of the sliding window can be the current time point.

[0217] S204, whether the change amount determined according to the encoder values of the end joint is less than a first threshold value, and whether the number of the encoder values of the gripper that are less than a second threshold value is less than a third threshold value.

[0218] Exemplarily, the controller can obtain the encoder values of the end joint in the sliding window. In the sliding window, the controller can calculate the change amount of the encoder values of the end joint. And determine whether the change amount is less than the first threshold value.

[0219] And, the controller can obtain the encoder values of the gripper in the sliding window. In the sliding window, the controller can count the number of the encoder values of the gripper that are less than the second threshold value. Further, the controller can determine whether the number is less than the third threshold value.

[0220] In one example, the variation amount can be determined according to a difference between two adjacent encoder values.

[0221] If the controller determines that both the end joint and the gripper meet the conditions, step S206 is performed. Otherwise, step S205 is performed.

[0222] S205, determining that the operation state.

[0223] S206, determining that the hand-off state.

[0224] Figure 3 A structure diagram of a hand-off detection device provided in the present application is shown in FIG. 3. The hand-off detection device 300 provided in the present embodiment includes: Figure 4

[0225] The acquisition module 301 is configured to acquire a sampling signal of at least one end operation unit of a master hand of a robot.

[0226] The determination module 302 is configured to determine that a working state of the robot is a hand-off state if a variation of the sampling signal within a preset time length meets a preset hand-off condition. Otherwise, the working state of the robot is determined to be an operation state.

[0227] In one example, the acquisition module 301 is configured to:

[0228] acquire an encoder value of an encoder of the end operation unit according to a preset sampling frequency.

[0229] generate the sampling signal according to the encoder value.

[0230] In one example, the end operation unit is an end joint and / or an end effector.

[0231] In one example, the end operation unit is an end joint, and the preset time length includes a first time length. The determination module 302 is configured to:

[0232] acquire a signal difference value of two adjacent sampling signals within the first time length.

[0233] If the signal difference value is less than a first threshold value within the first time length, it is determined that the variation of the sampling signal within the preset time length meets the preset hand-off condition.

[0234] In one example, the end operation unit is an end effector, and the preset time length includes a second time length. The determination module 302 is configured to:

[0235] count a signal number of the sampling signals less than a second threshold value within the second time length.

[0236] If the signal number is less than a third threshold value, it is determined that the variation of the sampling signal within the preset time length meets the preset hand-off condition. ​

[0237] In an example, the end operation unit includes an end effector and at least one end joint, the preset time length includes a first time length corresponding to the end joint and a second time length corresponding to the end effector. The judging module 302 is configured to:

[0238] acquire a sampling signal of the end joint within a first time length before the current time; and calculate a signal difference value of adjacent two sampling signals of each end joint within the first time length;

[0239] acquire a sampling signal of the end effector within a second time length before the current time; and count a signal number of the sampling signal less than a second threshold value;

[0240] if the signal difference value is less than a first threshold value and the signal number is less than a third threshold value, it is determined that the change of the sampling signal within the preset time length meets a preset hand-off condition.

[0241] In an example, the device further includes:

[0242] The control module 303 is configured to update a state flag bit of the robot according to the working state, so that the robot switches the operation mode according to the state flag bit.

[0243] In an example, the control module 303 is configured to:

[0244] if the working state of the robot is the hand-off state, the robot is switched from the current master-slave synchronization mode to the joint impedance mode.

[0245] In an example, the control module 303 is configured to:

[0246] suspend the redundant joint obstacle avoidance strategy and reduce the friction compensation of the force control joint.

[0247] The hand-off detection device provided in the embodiment can execute the method provided in the method embodiment, and has similar implementation principles and technical effects. Details are not described herein.

[0248] Figure 4 A structural schematic diagram of the controller provided in the present application is shown in FIG. 4. ​ As shown in FIG. 4, the controller 400 provided in the embodiment includes at least one processor 401 and a memory 402. Optionally, the controller 400 further includes a communication component 403. The processor 401, the memory 402 and the communication component 403 are connected through a bus 404.

[0249] In the specific implementation process, the at least one processor 401 executes the computer execution instructions stored in the memory 402, so that the at least one processor 401 executes the method described above.

[0250] The specific implementation process of the processor 401 can refer to the method embodiments described above, which have similar implementation principles and technical effects, and thus will not be described here.

[0251] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0252] The memory can include a random access memory (RAM), and can also include a non-volatile memory (NVM), such as at least one disk memory.

[0253] The bus can be an industry standard architecture (ISA) bus, a peripheral component (PCI) bus, an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the bus in the drawings of the present application does not limit to only one bus or one type of bus.

[0254] The present application also provides a computer program product, comprising a computer program, which is executed by a processor to implement the above method.

[0255] The present application also provides a computer readable storage medium, which stores computer execution instructions, and when a processor executes the computer execution instructions, the above method is implemented.

[0256] The above-mentioned readable storage medium can be realized by any type of volatile or nonvolatile storage devices 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 that can be accessed by a general or special purpose computer.

[0257] An exemplary readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a part of the processor. The processor and the readable storage medium can be located in an Application Specific Integrated Circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in the device.

[0258] The division of units is only a logical functional division, and in actual implementation, there can be another division manner. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0259] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0260] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.

[0261] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the method of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, and various media that can store program codes.

[0262] Those of ordinary skill in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction-related hardware. The aforementioned program can be stored in a computer readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, a magnetic disk or an optical disk, and various media that can store program codes.

[0263] Finally, it should be noted that: those skilled in the art will easily think of other embodiments of the present application after considering the specification and practicing the application disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application that follow the general principles of the present application and include common knowledge or conventional technical means in the art that are not disclosed in the present application, and is not limited to the precise structure described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present application is only limited by the appended claims.

Claims

1. A hands-off detection method, characterized by, A master hand applied to a robot, comprising: obtaining a sampling signal of at least one end operation unit of the master hand of the robot; the end operation unit is an end joint and / or an end effector; if the change of the sampling signal within the preset time length conforms to the preset hand-off condition, determining that the working state of the robot is a hand-off state; otherwise, determining that the working state of the robot is an operation state; wherein the end operation unit comprises an end effector and at least one end joint, and the preset time length comprises a first time length corresponding to the end joint and a second time length corresponding to the end effector; the change of the sampling signal within the preset time length conforms to the preset hand-off condition, comprising: obtaining the sampling signal of the end joint within a first time length before the current time; calculating the signal difference value of each end joint between two adjacent sampling signals within the first time length; obtaining the sampling signal of the end effector within a second time length before the current time; counting the number of signals less than a second threshold value in the sampling signal; if the signal difference value is less than a first threshold value, and the number of signals is less than a third threshold value, it is determined that the change of the sampling signal within the preset time length conforms to the preset hand-off condition.

2. The method of claim 1, wherein, obtaining a sampling signal of at least one end operation unit of the master hand of the robot, comprising: obtaining the encoder value of the encoder of the end operation unit according to the preset sampling frequency; generating the sampling signal according to the encoder value.

3. The method of claim 1, wherein, The end operation unit is an end joint, and the preset time length comprises a first time length; the change of the sampling signal within the preset time length conforms to the preset hand-off condition, comprising: obtaining the signal difference value of two adjacent sampling signals; if the signal difference value is less than a first threshold value within the first time length, it is determined that the change of the sampling signal within the preset time length conforms to the preset hand-off condition.

4. The method of claim 1, wherein, The end operation unit is an end effector, and the preset time length comprises a second time length; the change of the sampling signal within the preset time length conforms to the preset hand-off condition, comprising: counting the number of signals less than a second threshold value in the sampling signal within the second time length; if the number of signals is less than a third threshold value, it is determined that the change of the sampling signal within the preset time length conforms to the preset hand-off condition.

5. The method according to any one of claims 1-4, characterized in that, The method further comprises: updating the state flag bit of the robot according to the working state, so that the robot switches the running mode according to the state flag bit.

6. The method according to any one of claims 1-4, characterized in that, The method further comprises: if the working state of the robot is a hand-off state, switching the master-slave synchronization mode of the robot from the current to a joint impedance mode.

7. The method of claim 6, wherein, Before switching the master-slave synchronization mode of the robot from the current to the joint impedance mode, further comprising: pausing the redundant joint obstacle avoidance strategy and reducing the friction compensation of the force control joint.

8. A hands-off detection device characterized by, A master hand applied to a robot, comprising: an obtaining module, configured to obtain a sampling signal of at least one end operation unit of the master hand of the robot; the end operation unit is an end joint and / or an end effector; The judgment module is configured to determine that the working state of the robot is a hand-off state if the change of the sampling signals in the preset time length meets a preset hand-off condition, and determine that the working state of the robot is an operation state if not. The end operation unit comprises an end effector and at least one end joint, and the preset time length comprises a first time length corresponding to the end joint and a second time length corresponding to the end effector. The judgment module is specifically configured to acquire the sampling signals of the end joint in a first time length before the current time; calculate signal difference values of adjacent two sampling signals of each end joint in the first time length; acquire the sampling signals of the end effector in a second time length before the current time; count a signal number of the sampling signals less than a second threshold value; and determine that the change of the sampling signals in the preset time length meets the preset hand-off condition if the signal difference values are all less than a first threshold value and the signal number is less than a third threshold value.

9. A controller characterized by comprising: The device comprises: a memory and a processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory, so that the processor executes the method according to any one of claims 1-7.

10. A robot, characterized in that The master hand of the robot comprises at least one end operation unit and the controller according to claim 9. The end operation unit is a contactor operated by a user and / or at least one end joint fixedly connected with the end effector.

11. A computer readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the method according to any one of claims 1-7.

12. A computer program product, characterised in that, The computer program is executed by the processor to implement the method according to any one of claims 1-7.

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