Teaching assistance robot impedance control method

Abstract

This invention discloses an impedance control method for a teaching aid robot, relating to the field of impedance safety control technology, comprising the following steps: obtaining the real-time screening speed based on the teaching aid robot; obtaining the historical normal force corresponding to the real-time screening speed; constructing a historical force distribution function based on the historical normal force; obtaining real-time moving line segment and area anomaly thresholds based on the historical force distribution function; obtaining a real-time force threshold based on the real-time moving line segment, the historical force distribution function, and the area anomaly threshold; constructing a threshold force comparison function based on the real-time screening speed and the real-time force threshold; obtaining a real-time detection anomaly threshold based on the real-time detection speed and the threshold force comparison function; and determining whether an abnormal collision has occurred based on the real-time detection force and the real-time detection anomaly threshold. This invention addresses the problem that existing impedance safety control technologies set collision thresholds to fixed values, leading to safety hazards such as human-machine collisions and equipment damage.

Description

Technical Field

[0001] This invention relates to the field of impedance safety control technology, specifically to an impedance control method for a teaching aid robot. Background Technology

[0002] With the popularization of intelligent training and robot hands-on teaching models, teaching auxiliary robots need to interact with people at close range for a long time. They must not only meet the control precision requirements of accurate reproduction of teaching trajectories and standardized action demonstration, but also have good human-machine compliant interaction capabilities and reliable safety protection performance.

[0003] Currently, most educational auxiliary robots still employ traditional fixed-parameter impedance control and constant collision force threshold protection strategies. The control parameters cannot adapt to dynamically changing teaching conditions and motion states. During low-speed, hands-on teaching, the fixed collision threshold is prone to accidental triggering and shutdown, severely impacting the smoothness and efficiency of drag-and-drop teaching. Furthermore, in high-speed autonomous demonstration operation, the fixed threshold protection lacks sufficient sensitivity, making it difficult to quickly identify sudden collisions and impacts, posing safety hazards such as human-robot collisions and equipment damage. Simultaneously, traditional control methods do not correlate with the robot's real-time movement speed, failing to achieve dynamic adaptive adjustment of impedance parameters and safety thresholds. In other words, existing impedance safety control technologies set the collision threshold to a fixed value, resulting in safety hazards such as human-robot collisions and equipment damage. Summary of the Invention

[0004] This invention aims to at least partially address one of the technical problems in existing technologies by: acquiring real-time screening speed based on a teaching aid robot; acquiring the historical normal force corresponding to the real-time screening speed; constructing a historical force distribution function based on the historical normal force; acquiring real-time moving line segment and area anomaly thresholds based on the historical force distribution function; acquiring a real-time force threshold based on the real-time moving line segment, historical force distribution function, and area anomaly threshold; constructing a threshold force comparison function based on the real-time screening speed and real-time force threshold; acquiring real-time detection speed and real-time detection force based on the teaching aid robot; acquiring a real-time detection anomaly threshold based on the real-time detection speed and threshold force comparison function; and determining whether an abnormal collision occurs based on the real-time detection force and real-time detection anomaly threshold. This addresses the safety hazard of human-machine collisions and equipment damage caused by setting a fixed collision threshold in existing impedance safety control technologies.

[0005] To achieve the above objectives, this application provides an impedance control method for a teaching aid robot, comprising the following steps:

[0006] Real-time screening speed is obtained based on teaching assistance robots;

[0007] Obtain the historical normal force corresponding to the real-time filtering speed;

[0008] Construct a historical force distribution function based on historical normal forces;

[0009] Real-time moving line segment and area anomaly thresholds are obtained based on historical force distribution functions;

[0010] Real-time force thresholds are obtained based on real-time moving line segments, historical force distribution functions, and area anomaly thresholds.

[0011] A threshold force comparison function is constructed based on real-time screening speed and real-time force threshold.

[0012] Real-time detection speed and real-time detection force are obtained based on teaching assistance robots;

[0013] The real-time detection anomaly threshold is obtained based on the real-time detection speed and threshold force comparison function.

[0014] The system determines whether a collision is abnormal based on real-time detection force and real-time abnormal detection threshold.

[0015] Furthermore, obtaining real-time screening speed based on the teaching assistance robot includes the following sub-steps:

[0016] Obtain the movable speed of the robotic arm in the teaching aid robot and mark it as the real-time running speed;

[0017] Obtain the runnable range at real-time running speed and mark it as the real-time speed range;

[0018] Divide the real-time speed range into equal intervals, with the interval being the first interval. Obtain each division point within the real-time speed range and mark it as a real-time division point.

[0019] The real-time running speed of each dividing point is obtained in ascending order of real-time running speed and marked as the real-time filtering speed.

[0020] Furthermore, obtaining the historical normal force corresponding to the real-time filtering speed includes the following sub-steps:

[0021] At each real-time screening speed, the forces required for normal human dragging, safe operation of the teaching aid robot, and personnel safety are collected and marked as historical normal forces.

[0022] At each real-time filtering speed, obtain the first number of historical normal forces.

[0023] Furthermore, constructing the historical force distribution function based on historical normal forces includes the following sub-steps:

[0024] The first number of historical normal forces at any real-time filtering speed are marked as historical target forces;

[0025] A Cartesian coordinate system is established with historical target forces as the horizontal axis data and the quantity of historical target forces as the vertical axis data, and it is marked as the historical force distribution coordinate system.

[0026] The coordinates of the historical target force and the number of historical target forces are obtained as the x-axis and y-axis points, respectively, and marked as the historical force distribution coordinate points;

[0027] Plot all historical force distribution coordinate points on the historical force distribution coordinate system to obtain a scatter plot, and label it as a historical force distribution scatter plot;

[0028] The function is obtained by fitting all the coordinate points of the historical force distribution in the scatter plot of historical force distribution, and is marked as the historical force distribution function.

[0029] Furthermore, obtaining the real-time moving line segment and area anomaly thresholds based on the historical force distribution function includes the following sub-steps:

[0030] In the historical force distribution coordinate system, the range of the horizontal axis is the distribution range of the historical target force. The area enclosed by the vertical lower part of the historical force distribution function to the horizontal axis of the historical force distribution coordinate system is marked as the overall historical force region.

[0031] Obtain the area of ​​the entire historical force region and mark it as the total area of ​​the historical force.

[0032] In the historical force distribution coordinate system, establish a line segment on the horizontal axis that can move left and right and has a length of the first length, and mark it as the real-time moving line segment;

[0033] Obtain the length of the historical target force distribution along the horizontal axis in the historical force distribution coordinate system, and mark it as the overall length of the historical force;

[0034] Set a ratio value and mark it as the first set ratio value;

[0035] The area anomaly threshold is obtained as follows: K = f × [S1 × (D1 ÷ D2)]; where K is the area anomaly threshold, c is the first set ratio value, S1 is the total area of ​​the historical force, D1 is the first length, and D2 is the total length of the historical force.

[0036] Furthermore, obtaining the real-time force threshold based on the real-time moving line segment, historical force distribution function, and area anomaly threshold includes the following sub-steps:

[0037] The real-time moving line segment is shifted from the rightmost side of the historical force distribution coordinate system to the left. During the shift, the area of ​​the entire historical force region vertically above the real-time moving line segment is obtained and marked as the real-time judgment area. When the real-time judgment area is greater than or equal to the area anomaly threshold, the real-time moving line segment is stopped. The historical target force corresponding to the largest horizontal coordinate of the real-time moving line segment at this time is obtained and marked as the real-time force threshold.

[0038] Obtain the real-time force threshold for all real-time filtering speeds.

[0039] Furthermore, constructing a threshold force comparison function based on real-time screening speed and real-time force threshold includes the following sub-steps:

[0040] A Cartesian coordinate system is established with real-time screening speed as the horizontal axis and real-time force threshold as the vertical axis, and it is marked as the threshold force comparison coordinate system.

[0041] Obtain the coordinate points where the real-time filtering speed and the real-time force threshold are the x and y coordinates, respectively, and mark them as threshold force comparison coordinate points;

[0042] Plot the threshold force reference coordinate points on the threshold force reference coordinate system to obtain a scatter plot, and mark it as the threshold force reference scatter plot;

[0043] The function is obtained by fitting a function to all the threshold force reference coordinate points in the threshold force reference scatter plot, and is marked as the threshold force reference function.

[0044] Furthermore, obtaining real-time detection speed and real-time detection force based on the teaching assistance robot includes the following sub-steps:

[0045] The real-time moving speed of the robotic arm in the teaching aid robot is obtained and marked as the real-time detection speed;

[0046] The real-time sensing force of the robotic arm in the teaching aid robot is obtained and marked as the real-time detected force.

[0047] Furthermore, obtaining the real-time detection anomaly threshold based on the real-time detection speed versus threshold force comparison function includes the following sub-steps:

[0048] The real-time detection speed is used as the horizontal axis data and substituted into the threshold force comparison function to obtain the vertical axis data, which is then marked as the real-time detection abnormal threshold.

[0049] Furthermore, determining whether a collision is abnormal based on real-time detection force and real-time anomaly threshold includes the following sub-steps:

[0050] If the real-time detected force is greater than the real-time detected abnormal threshold, it is considered that an abnormal collision has occurred and corresponding safety controls are implemented; if the real-time detected force is less than or equal to the real-time detected abnormal threshold, it is considered that a normal dragging force has occurred and corresponding resistance force is generated.

[0051] The beneficial effects of this invention are as follows: This invention obtains real-time screening speed based on a teaching aid robot; obtains historical normal force corresponding to the real-time screening speed; constructs a historical force distribution function based on the historical normal force; obtains real-time moving line segment and area anomaly thresholds based on the historical force distribution function; obtains real-time force thresholds based on real-time moving line segments, historical force distribution function, and area anomaly thresholds; constructs a threshold force comparison function based on real-time screening speed and real-time force thresholds; obtains real-time detection speed and real-time detection force based on the teaching aid robot; obtains real-time detection anomaly thresholds based on the real-time detection speed and threshold force comparison function; and determines whether an abnormal collision occurs based on the real-time detection force and real-time detection anomaly thresholds. The advantage lies in dynamically adjusting the collision judgment threshold according to the robot's real-time motion state, achieving robot protection adaptation control at different speeds, and effectively improving the human-computer interaction experience and operational safety level of the teaching robot.

[0052] This invention obtains the real-time detection anomaly threshold based on a real-time detection speed and threshold force comparison function. Its advantage lies in dynamically adjusting the collision judgment threshold according to the robot's real-time motion state, realizing adaptive control of robot protection at different speeds, and effectively improving the human-computer interaction experience and operational safety level of the teaching robot. Attached Figure Description

[0053] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0054] Figure 2 This is a schematic diagram of the real-time force threshold of the present invention;

[0055] Figure 3 This is a schematic diagram of the threshold force comparison function of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Example 1, please refer to Figure 1 As shown, this application provides an impedance control method for a teaching aid robot, comprising the following steps:

[0058] Step S1: Obtain the real-time screening speed based on the teaching assistance robot; Step S1 includes the following sub-steps:

[0059] Step S101: Obtain the movable speed of the robotic arm in the teaching assistance robot and mark it as the real-time running speed; the robotic arm of the teaching assistance robot will move when it is working, and the real-time running speed is the movement speed at the position where dragging or collision occurs;

[0060] Step S102: Obtain the runnable range of real-time running speed and mark it as the real-time speed range;

[0061] Step S103: Divide the real-time speed range into equal intervals, with the interval being the first interval; obtain each division point within the real-time speed range and mark it as a real-time division point.

[0062] In practical applications, in order to obtain all real-time operating speeds within a near-real-time speed range, the first interval should not be set too large. For example, if the real-time speed range is 0 m / s to 6 m / s, the first interval should be 0.01 m / s.

[0063] Step S104: Obtain the real-time running speed of the real-time division points in ascending order of real-time running speed, and mark them as real-time filtering speeds; in order to prevent safety hazards such as human-machine collisions and equipment damage, collision thresholds are set for different speeds; in order to obtain the collision threshold corresponding to each real-time running speed within the real-time speed range.

[0064] Step S2: Obtain the historical normal force corresponding to the real-time screening speed; Step S2 includes the following sub-steps:

[0065] Step S201: Collect the forces required for normal human dragging, safe operation of the teaching assistance robot, and personnel safety at each real-time screening speed, and mark them as historical normal forces; collision forces are generally greater than the forces required for safe operation of the teaching assistance robot and personnel safety, so obtain the range of historical normal forces and determine whether it is a collision force;

[0066] Step S202: Obtain a first number of historical normal forces at each real-time filtering speed. To facilitate obtaining the historical normal forces corresponding to each real-time filtering speed, the first number should not be set too small, for example, the first number is 1000.

[0067] Step S3: Construct the historical force distribution function based on historical normal forces; Step S3 includes the following sub-steps:

[0068] Step S301: Mark the first number of historical normal forces at any real-time filtering speed as historical target forces;

[0069] Step S302: Establish a Cartesian coordinate system with historical target force as the horizontal axis data and the number of historical target forces as the vertical axis data, and mark it as the historical force distribution coordinate system;

[0070] Step S303: Obtain the coordinates of the historical target force and the number of historical target forces as the x-axis and y-axis, respectively, and mark them as historical force distribution coordinate points;

[0071] Step S304: Plot all historical force distribution coordinate points on the historical force distribution coordinate system to obtain a scatter plot, and mark it as a historical force distribution scatter plot;

[0072] Step S305: Fit all the historical force distribution coordinate points in the historical force distribution scatter plot to obtain a function, and mark it as the historical force distribution function;

[0073] In practical applications, for example, the first number of historical normal forces corresponding to a real-time screening speed of 9 m / s are marked as historical target forces; the historical force distribution function is obtained by fitting all the coordinate points of the historical force distribution scatter plot. Please refer to [link to relevant documentation]. Figure 2 As shown, the historical force distribution function is obtained by fitting.

[0074] Step S4: Obtain real-time moving line segment and area anomaly thresholds based on the historical force distribution function; Step S4 includes the following sub-steps:

[0075] Step S401: In the historical force distribution coordinate system, the range of the horizontal axis is the distribution range of the historical target force. Obtain the area enclosed by the vertical lower part of the historical force distribution function to the horizontal axis of the historical force distribution coordinate system, and mark it as the overall historical force region. The overall historical force region represents the quantity of historical target force distribution.

[0076] Step S402: Obtain the area of ​​the entire historical force region and mark it as the area of ​​the entire historical force; the area of ​​the entire historical force represents the number of the entire historical target force, i.e., the first number;

[0077] Step S403: Establish a line segment on the horizontal axis of the historical force distribution coordinate system that can move left and right and has a length of the first length, and mark it as the real-time moving line segment; in order to observe the distribution of historical target forces, the real-time moving line segment filters out the edge areas with smaller historical target force quantities.

[0078] Step S404: Obtain the distribution length of the historical target force on the horizontal axis in the historical force distribution coordinate system, and mark it as the overall length of the historical force;

[0079] Step S405: Set a ratio value and mark it as the first set ratio value;

[0080] Step S406, obtain the area anomaly threshold as: K=f×[S1×(D1÷D2)]; where K is the area anomaly threshold, c is the first set ratio value, S1 is the overall area of ​​the historical force, D1 is the first length, and D2 is the overall length of the historical force.

[0081] In practical applications, historical target forces may be excessively large or about to exceed safe limits during historical target force data collection. Therefore, it is necessary to exclude excessively large historical target forces to ensure safer and more accurate setting of the safety threshold for the teaching aid robot. This is achieved through screening using an area anomaly threshold. Therefore, the area anomaly threshold should not be set too high. Furthermore, since S1×(D1÷D2) represents the real-time judgment area (mean area) obtained when the historical target force is uniformly distributed within the range, f is less than 1, for example, f is 0.2. Please refer to [link / reference]. Figure 2 As shown, S1 is 430cm 2 If D1 is 1cm and D2 is 41cm, then the area anomaly threshold is: K = 0.2 × [410 × (1 ÷ 41)] = 2cm 2 .

[0082] Step S5: Obtain the real-time force threshold based on the real-time moving line segment, historical force distribution function, and area anomaly threshold; Step S5 includes the following sub-steps:

[0083] Step S501: Move the real-time moving line segment from the rightmost side of the historical force distribution coordinate system to the left. During the movement, obtain the area of ​​the entire historical force region vertically above the real-time moving line segment and mark it as the real-time judgment area. When the real-time judgment area is greater than or equal to the area anomaly threshold, stop moving the real-time moving line segment. Obtain the historical target force corresponding to the largest horizontal coordinate of the real-time moving line segment at this time and mark it as the real-time force threshold. In order to filter out historical target forces that are too large and too few in number, that is, historical target forces that may be abnormal during the historical target force data collection, or historical target forces that are about to exceed the safety limit, the real-time force threshold is used as the maximum value of the historical target force, so that the safety threshold setting of the teaching auxiliary robot is safer and more accurate.

[0084] Step S502: Obtain the real-time force threshold of all real-time filtering speeds;

[0085] In practical applications, by moving the real-time moving line segment and judging the area and area anomaly threshold in real time, excessively large historical target forces can be excluded. When filtering historical target forces with a real-time screening speed of 0 m / s, the real-time moving line segment is moved from the rightmost side of the historical force distribution coordinate system to the left. During the movement, the area of ​​the entire historical force region vertically above the real-time moving line segment is obtained and marked as the real-time judged area; please refer to [link to relevant documentation]. Figure 2 As shown, when the real-time measured area is 4.9 cm² 2 Area anomaly threshold greater than 2cm 2 When the real-time moving line segment stops moving, the historical target force corresponding to the largest horizontal coordinate of the real-time moving line segment at this time is obtained. If the force is 40N, then the real-time force threshold is 40N. When the real-time filtering speed is 0m / s, the corresponding real-time force threshold is 40N. Similarly, the real-time force threshold for all real-time filtering speeds is obtained.

[0086] Step S6 involves constructing a threshold force comparison function based on the real-time screening speed and the real-time force threshold. Step S6 includes the following sub-steps:

[0087] Step S601: Establish a Cartesian coordinate system with real-time screening speed as the horizontal axis and real-time force threshold as the vertical axis, and mark it as the threshold force comparison coordinate system;

[0088] Step S602: Obtain the coordinate points where the real-time screening speed and the real-time force threshold are the abscissa and ordinate respectively, and mark them as threshold force comparison coordinate points;

[0089] Step S603: Plot the threshold force reference coordinate points on the threshold force reference coordinate system to obtain a scatter plot, and mark it as the threshold force reference scatter plot;

[0090] Step S604: Perform function fitting on all the threshold force reference coordinate points in the threshold force reference scatter plot to obtain a function, and mark it as the threshold force reference function;

[0091] In practical applications, by understanding the relationship between real-time force thresholds corresponding to different real-time screening speeds, the real-time force thresholds corresponding to all real-time operating speeds within the real-time speed range can be obtained. This allows for the acquisition of a threshold force comparison function. This facilitates setting different safety force thresholds based on the real-time movement speed of the robotic arm in different teaching aid robots. Please refer to [link / reference]. Figure 3 The diagram shows the obtained threshold force comparison function.

[0092] Step S7: Obtain real-time detection speed and real-time detection force based on the teaching assistance robot; Step S7 includes the following sub-steps:

[0093] Step S701: Obtain the real-time moving speed of the robotic arm in the teaching assistance robot and mark it as the real-time detection speed;

[0094] Step S702: Obtain the real-time sensing force of the robotic arm in the teaching assistance robot and mark it as the real-time detected force;

[0095] In practical applications, the real-time detection speed is 0.2 m / s and the real-time detection force is 20 N.

[0096] Step S8: Obtain the real-time detection anomaly threshold based on the real-time detection speed and threshold force comparison function; Step S8 includes the following sub-steps:

[0097] Step S801: Substitute the real-time detection speed as the horizontal axis data into the threshold force comparison function to obtain the vertical axis data, and mark it as the real-time detection abnormal threshold.

[0098] For practical applications, please refer to Figure 3As shown, the real-time detection speed of 0.2 m / s is used as the horizontal axis data and substituted into the threshold force comparison function to obtain the vertical axis data of 34 N. Therefore, the real-time detection anomaly threshold is 34 N.

[0099] Step S9: Determine whether it is an abnormal collision based on the real-time detection force and the real-time detection anomaly threshold; Step S9 includes the following sub-steps:

[0100] Step S901: If the real-time detected force is greater than the real-time detected abnormal threshold, it is considered that an abnormal collision has occurred and corresponding safety control is implemented; if the real-time detected force is less than or equal to the real-time detected abnormal threshold, it is considered that the force is generated by normal human dragging and corresponding resistance force is generated; the human active dragging force is relatively small, while the collision force and the force that endangers safety are relatively large, so the real-time detected force cannot be greater than the real-time detected abnormal threshold; the corresponding safety control can be to stop the operation.

[0101] In practical applications, if the real-time detection force is 20N, which is less than the real-time detection abnormal threshold of 34N, it is considered to be the force generated by normal human dragging, which produces the corresponding resistance force.

[0102] Example 2: This application also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps of an impedance control method for a teaching aid robot are performed to achieve the following functions: obtaining the real-time screening speed based on the teaching aid robot; obtaining the historical normal force corresponding to the real-time screening speed; constructing a historical force distribution function based on the historical normal force; obtaining real-time moving line segment and area anomaly thresholds based on the historical force distribution function; obtaining a real-time force threshold based on the real-time moving line segment, the historical force distribution function, and the area anomaly threshold; constructing a threshold force comparison function based on the real-time screening speed and the real-time force threshold; obtaining the real-time detection speed and real-time detection force based on the teaching aid robot; obtaining a real-time detection anomaly threshold based on the real-time detection speed and threshold force comparison function; and determining whether it is an abnormal collision based on the real-time detection force and the real-time detection anomaly threshold.

[0103] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0104] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a teaching aid robot impedance control method provided by the above methods. The method includes: obtaining a real-time screening speed based on the teaching aid robot; obtaining a historical normal force corresponding to the real-time screening speed; constructing a historical force distribution function based on the historical normal force; obtaining a real-time moving line segment and area anomaly threshold based on the historical force distribution function; obtaining a real-time force threshold based on the real-time moving line segment, the historical force distribution function, and the area anomaly threshold; constructing a threshold force comparison function based on the real-time screening speed and the real-time force threshold; obtaining a real-time detection speed and real-time detection force based on the teaching aid robot; obtaining a real-time detection anomaly threshold based on the real-time detection speed and threshold force comparison function; and determining whether it is an abnormal collision based on the real-time detection force and the real-time detection anomaly threshold.

[0105] Example 4: This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of the above-described impedance control method for a teaching aid robot to achieve the following functions: obtaining real-time screening speed based on the teaching aid robot; obtaining historical normal force corresponding to the real-time screening speed; constructing a historical force distribution function based on the historical normal force; obtaining real-time moving line segment and area anomaly thresholds based on the historical force distribution function; obtaining a real-time force threshold based on the real-time moving line segment, historical force distribution function, and area anomaly threshold; constructing a threshold force comparison function based on the real-time screening speed and real-time force threshold; obtaining real-time detection speed and real-time detection force based on the teaching aid robot; obtaining a real-time detection anomaly threshold based on the real-time detection speed and threshold force comparison function; and determining whether it is an abnormal collision based on the real-time detection force and real-time detection anomaly threshold.

[0106] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0107] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An impedance control method for a teaching aid robot, characterized in that, Includes the following steps: Real-time screening speed is obtained based on teaching assistance robots; Obtain the historical normal force corresponding to the real-time filtering speed; Construct a historical force distribution function based on historical normal forces; Real-time moving line segment and area anomaly thresholds are obtained based on historical force distribution functions; Real-time force thresholds are obtained based on real-time moving line segments, historical force distribution functions, and area anomaly thresholds. A threshold force comparison function is constructed based on real-time screening speed and real-time force threshold. Real-time detection speed and real-time detection force are obtained based on teaching assistance robots; The real-time detection anomaly threshold is obtained based on the real-time detection speed and threshold force comparison function. The system determines whether a collision is abnormal based on real-time detection force and real-time abnormal detection threshold.

2. The impedance control method for a teaching aid robot according to claim 1, characterized in that, Obtaining real-time screening speed based on a teaching assistance robot includes the following sub-steps: Obtain the movable speed of the robotic arm in the teaching aid robot and mark it as the real-time running speed; Obtain the runnable range at real-time running speed and mark it as the real-time speed range; Divide the real-time speed range into equal intervals, with the interval being the first interval. Obtain each division point within the real-time speed range and mark it as a real-time division point. The real-time running speed of each dividing point is obtained in ascending order of real-time running speed and marked as the real-time filtering speed.

3. The impedance control method for a teaching aid robot according to claim 2, characterized in that, Obtaining the historical normal force corresponding to the real-time filtering speed includes the following sub-steps: At each real-time screening speed, the forces required for normal human dragging, safe operation of the teaching aid robot, and personnel safety are collected and marked as historical normal forces. At each real-time filtering speed, obtain the first number of historical normal forces.

4. The impedance control method for a teaching aid robot according to claim 3, characterized in that, Constructing the historical force distribution function based on historical normal forces includes the following sub-steps: The first number of historical normal forces at any real-time filtering speed are marked as historical target forces; A Cartesian coordinate system is established with historical target forces as the horizontal axis data and the quantity of historical target forces as the vertical axis data, and it is marked as the historical force distribution coordinate system. The coordinates of the historical target force and the number of historical target forces are obtained as the x-axis and y-axis points, respectively, and marked as the historical force distribution coordinate points; Plot all historical force distribution coordinate points on the historical force distribution coordinate system to obtain a scatter plot, and label it as a historical force distribution scatter plot; The function is obtained by fitting all the coordinate points of the historical force distribution in the scatter plot of historical force distribution, and is marked as the historical force distribution function.

5. The impedance control method for a teaching aid robot according to claim 4, characterized in that, Obtaining real-time moving line segment and area anomaly thresholds based on historical force distribution functions includes the following sub-steps: In the historical force distribution coordinate system, the range of the horizontal axis is the distribution range of the historical target force. The area enclosed by the vertical lower part of the historical force distribution function to the horizontal axis of the historical force distribution coordinate system is marked as the overall historical force region. Obtain the area of ​​the entire historical force region and mark it as the total area of ​​the historical force. In the historical force distribution coordinate system, establish a line segment on the horizontal axis that can move left and right and has a length of the first length, and mark it as the real-time moving line segment; Obtain the length of the historical target force distribution along the horizontal axis in the historical force distribution coordinate system, and mark it as the overall length of the historical force; Set a ratio value and mark it as the first set ratio value; The area anomaly threshold is obtained as follows: K = f × [S1 × (D1 ÷ D2)]; where K is the area anomaly threshold, c is the first set ratio value, S1 is the total area of ​​the historical force, D1 is the first length, and D2 is the total length of the historical force.

6. The impedance control method for a teaching aid robot according to claim 5, characterized in that, Obtaining the real-time force threshold based on real-time moving line segments, historical force distribution functions, and area anomaly thresholds includes the following sub-steps: The real-time moving line segment is shifted from the rightmost side of the historical force distribution coordinate system to the left. During the shift, the area of ​​the entire historical force region directly above the real-time moving line segment is obtained and marked as the real-time judgment area. When the real-time judgment area is greater than or equal to the area anomaly threshold, the real-time moving line segment is stopped. Obtain the historical target force corresponding to the maximum x-coordinate of the real-time moving line segment at this moment, and mark it as the real-time force threshold; Obtain the real-time force threshold for all real-time filtering speeds.

7. The impedance control method for a teaching aid robot according to claim 6, characterized in that, Constructing a threshold force comparison function based on real-time screening speed and real-time force threshold includes the following sub-steps: A Cartesian coordinate system is established with real-time screening speed as the horizontal axis and real-time force threshold as the vertical axis, and it is marked as the threshold force comparison coordinate system. Obtain the coordinate points where the real-time filtering speed and the real-time force threshold are the x and y coordinates, respectively, and mark them as threshold force comparison coordinate points; Plot the threshold force reference coordinate points on the threshold force reference coordinate system to obtain a scatter plot, and mark it as the threshold force reference scatter plot; The function is obtained by fitting a function to all the threshold force reference coordinate points in the threshold force reference scatter plot, and is marked as the threshold force reference function.

8. The impedance control method for a teaching aid robot according to claim 7, characterized in that, The acquisition of real-time detection speed and real-time detection force based on teaching assistance robots includes the following sub-steps: The real-time moving speed of the robotic arm in the teaching aid robot is obtained and marked as the real-time detection speed; The real-time sensing force of the robotic arm in the teaching aid robot is obtained and marked as the real-time detected force.

9. The impedance control method for a teaching aid robot according to claim 8, characterized in that, Obtaining the real-time detection anomaly threshold based on the real-time detection speed versus threshold force comparison function includes the following sub-steps: The real-time detection speed is used as the horizontal axis data and substituted into the threshold force comparison function to obtain the vertical axis data, which is then marked as the real-time detection abnormal threshold.

10. The impedance control method for a teaching aid robot according to claim 9, characterized in that, Determining whether a collision is abnormal based on real-time detected force and real-time detected anomaly threshold includes the following sub-steps: If the real-time detected force is greater than the real-time detected abnormal threshold, it is considered that an abnormal collision has occurred and corresponding safety controls are implemented; if the real-time detected force is less than or equal to the real-time detected abnormal threshold, it is considered that a normal dragging force has occurred and corresponding resistance force is generated.

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