A control method for intelligent anti-collision of a truss robot

Abstract

The present application belongs to the field of truss robot, and particularly relates to a control method for intelligent anti-collision of a truss robot, which comprises the following steps: 1) automatically dividing the running interval of the truss robot; 2) obtaining the actual position data of each running interval and the torque value data corresponding to each actual position in Q complete cycle periods from the X and Z axis servo drivers of the truss robot, and inputting the data into a self-learning database to complete the establishment of the self-learning database; 3) automatically dividing the work load interval of the truss robot according to the actual position data of each running interval in the self-learning data cycle, the corresponding torque value data and the coefficient k; and 4) executing the automatic operation of the truss robot, determining that the truss robot has an abnormal external load intervention according to the work load interval, and controlling the braking of each servo shaft. The present application does not need to add or externally hang a monitoring device, and can be directly applied to the existing truss robot control to independently open and close the protection function.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of truss robots, in particular to a control method for intelligent anti-collision of a truss robot. BACKGROUND

[0002] Truss robots are mostly applied in the field of automatic processing and assembly, and can replace human work to quickly complete the pre-set work. In the existing control technology of truss robots, the robot action control is pre-written according to the process flow and special working conditions, and the working coordinate points of each action of the robot are completely realized through teaching. If the workstations, toolings and fixtures are not accurately prepared according to the conditions, or there is an external load intervention in the automatic process, and the truss robot is started to work automatically and quickly, serious collision will occur.

[0003] When an abnormal phenomenon occurs in the automatic work, and the abnormal phenomenon is not within the monitoring range of the sensor, serious collision will occur in the high-speed motion process of the robot, and the robot will be damaged in severe cases. Even if there is sensor monitoring, serious collision will also occur due to the imprecise PLC program. Serious collision will cause damage to the corresponding equipment, which needs a long time for repair or replacement of the corresponding parts, and will also affect the production phenomenon, which most user units cannot accept. SUMMARY

[0004] In view of the above technical problems, the present application adds a self-learning database and a self-monitoring function to the control program of the truss robot. When the truss robot collides, the abnormality can be monitored by the system in time in the monitoring parameters, and each shaft can immediately realize emergency braking. The process time of feedback and braking execution is in the order of milliseconds, which can effectively prevent serious collision of the robot during automatic operation.

[0005] The technical solution adopted by the present application to achieve the above-mentioned purpose is: a control method for intelligent anti-collision of a truss robot, comprising the following steps:

[0006] 1) Debug the truss robot, complete the setting of Q times of motion cycle motion as a complete cycle, and complete the automatic division of the running interval of the truss robot;

[0007] 2) Real-time acquisition of each actual position data and each actual position corresponding torque value data of each running interval of Q times of complete cycle from the X-axis servo driver and Z-axis servo driver of the truss robot, and input into the self-learning database to complete the establishment of the self-learning database;

[0008] 3) Automatically dividing the working load interval of the truss robot according to the data in the self-learning database and the set torque adjustment coefficient k;

[0009] 4) The truss robot performs an automatic operation, and determines whether an abnormal external load is intervened according to a work load interval; if yes, the PLC controls each servo shaft to brake, otherwise the operation is continued.

[0010] The step 1) is specifically:

[0011] 1-1) According to the working condition, the motion parameters, interval size and running route of the truss robot are set; the truss robot moves according to the specified motion parameters and the set running route, and completes the motion cycle movement of the set Q times as a complete cycle, wherein 3<Q<5;

[0012] 1-2) According to the actual motion total stroke of the X axis and Z axis of the truss robot in the complete cycle and the set interval size, the number xn and zn of each axis running interval are obtained, and each axis running interval of the truss robot is automatically divided.

[0013] The automatic division of the running interval of the truss robot includes automatic division of the interval and manual setting of the intensive collection interval.

[0014] The automatic division of the interval is that the upper computer automatically divides the running interval of the truss robot according to the actual motion stroke of the X axis and Z axis of the truss robot.

[0015] The manual setting of the intensive collection interval is that the running interval corresponding to the motion section with an interface space less than 5mm in the process of picking and placing parts by the manipulator.

[0016] The motion parameters include the speed parameter, acceleration parameter, interval size parameter and torque adjustment coefficient k of the X axis and Z axis of the truss robot.

[0017] The step 3) is specifically:

[0018] 3-1) The actual position of each running interval of each complete cycle and the torque value corresponding to each actual position are filtered to eliminate the peak value parameter.

[0019] 3-2) For each running interval in each complete cycle, the maximum torque value M max and the minimum torque value M min are found. max min ;

[0020] 3-3) According to the maximum torque value M max and the minimum torque value M min of each running interval, the average value thereof is obtained as the torque average value parameter, and the position corresponding to the torque average value parameter is taken as the load position to form a load position-torque average value parameter group as a reference position-torque array.

[0021] 3-4) Obtain the position-moment upper limit array and the position-moment lower limit array of the truss robot according to the reference position-moment array and the set moment adjustment coefficient k; and take the obtained position-moment upper limit and lower limit array as the working load interval.

[0022] The step 3-4) is specifically:

[0023] According to the set moment adjustment coefficient k; in combination with the load position-moment mean value parameters of each operation interval

[0024] The position-moment upper limit array is obtained through the reference position-moment array amplification coefficient k, that is, the upper limit maximum moment limit value of each operation interval is:

[0025] The position-moment lower limit array is obtained through the reference position-moment array reduction coefficient k, that is, the lower limit minimum moment limit value of each operation interval is

[0026] The step 4) is specifically:

[0027] The host computer obtains the actual moment value M of each operation interval in the working process through the X-axis servo and the Z-axis servo of the truss robot;

[0028] The actual moment value M is compared with the working load interval;

[0029] When , that is, the moment exceeds the threshold value, it is determined that the collision phenomenon occurs, the PLC controls the braking of each servo shaft, and an alarm is output;

[0030] When , that is, the moment is less than the threshold value, it is determined that the falling phenomenon occurs, the PLC controls the braking of each servo shaft, and an alarm is output.

[0031] The present application has the following beneficial effects and advantages:

[0032] 1. The present application adopts a self-learning and self-monitoring control mode, and the position-moment upper limit and lower limit data limit parameters are derived from actual monitoring and are automatically obtained, and are for multiple motion load types. The position-moment parameter group automatically set by this control mode is dynamically obtained, is formed in intervals and in load types, and is more suitable for the actual working conditions.

[0033] 2. The present application can only design one fixed value in the existing conventional program writing, and the fixed value is a theoretical value and does not combine the actual situation, and the relative error is extremely large. If no program control limit is made, the motor maximum moment load limit value is taken by default, and there is no protection effect of reducing collision loss.

[0034] 3. The automatic division interval of the application can manually set the dense collection interval, the monitoring data is denser, and the data operation amount is relatively reduced.

[0035] 4. The control program module of the application can be independently run and closed, and can be directly added to the existing truss control program, and after the addition, the original program does not need to be greatly modified.

[0036] 5. The application does not need to add or externally hang a monitoring device, and can be directly applied to increase in the existing truss robot control, and independently open and close the protection function. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a schematic diagram of the self-learning database of the application;

[0038] Figure 2 is a schematic diagram of the monitoring protection principle of the application;

[0039] Figure 3 is a schematic diagram of the actual monitoring position-moment array curve of the application. DETAILED DESCRIPTION

[0040] The application will be further described in detail below in combination with the drawings and examples.

[0041] The application proposes a self-learning and self-monitoring program method in the control program of the truss robot. Specifically, the position and moment parameters in each servo shaft motor driver are monitored to indirectly monitor whether an abnormal load appears outside. When an abnormal load appears, each shaft of the truss robot immediately executes emergency braking to avoid serious collision phenomenon.

[0042] As shown in Figure 1 is a schematic diagram of the self-learning database of the application,

[0043] 1) Start the self-learning program module, and the truss robot executes automatic operation. After the truss robot completes Q complete cycle work periods, 3

[0044] 2) In the self-learning stage, each actual position data of each running interval and each actual position corresponding moment value data of Q complete cycle periods are obtained from the X-axis servo driver and the Z-axis servo driver of the truss robot in real time, and are input into the self-learning database to complete the establishment of the self-learning database basic data;

[0045] 3) According to the data in the self-learning database and the set coefficient k value, the work load interval of the truss robot is automatically divided;

[0046] 4) start monitoring program module, truss robot performs automated operation, when the actual position-moment data exceeds the working load interval, it is determined that the truss robot has abnormal load intervention, the PLC controls each servo shaft to brake, otherwise the operation continues. The present application does not need to add or externally hang a monitoring device, and can be directly applied to increase in the existing truss robot control, and independently open and close the protection function.

[0047] Specifically, in the present embodiment, it is first necessary to automatically divide the monitoring program module to monitor the actual position-moment data of the movement interval, i.e., 1-1) according to the working condition, set the movement parameters, interval size and running route of the truss robot; the truss robot moves according to the specified movement parameters and the set running route, completes the set Q times of movement cycle as a complete cycle, wherein 3

[0048] The movement parameters include: the speed parameters, acceleration parameters, interval size parameters and moment adjustment coefficient k of the X axis and Z axis of the truss robot.

[0049] 1-2) according to the actual movement total stroke of the X axis and Z axis of the truss robot in the complete cycle and the set interval size, obtain the number xn and zn of the running interval of each axis of the truss robot, and automatically divide the running interval of the truss robot.

[0050] The automatic division of the running interval of the truss robot includes automatic division interval and manual setting of dense collection interval.

[0051] The automatic division interval is that the upper computer automatically divides the running interval of the truss robot according to the actual movement stroke of the X axis and Z axis of the truss robot.

[0052] The manual setting of the dense collection interval is that in the process of the mechanical hand picking and placing parts, the running interval corresponding to the movement section with a docking space of less than 5mm.

[0053] In the present embodiment, during the debugging of the truss robot, the control program and movement parameters can be written according to the process, first set the movement parameters such as acceleration and speed of the truss robot, and then enter the automatic running mode. Since the actual moment parameter cannot be set in advance, and the actual moment parameter is also a variable parameter, the upper computer starts self-learning;

[0054] In the present embodiment, the actual position-moment parameters of multiple complete cycle periods are monitored, the monitoring peak parameters are filtered and eliminated, and various types of movement load position-moment mean parameter groups are formed, which are used as the reference position-moment array after self-learning.

[0055] Among them, for example, Figure 1As shown, a complete working condition of the embodiment is shown, in which the gantry robot automatically completes a cycle of Q motion cycles, automatically obtains the maximum torque M max and minimum torque M min of each working condition and each interval, and calculates the average torque M, which is automatically filled into the database collected in the self-learning stage.

[0056] Taking the Z1 drive for controlling the Z-axis motion as an example, the working condition of the Z-axis empty negative motion and the downward picking are shown, in which the motion of the Z-axis along Z1 includes Q same motion intervals: z1, z2…zn corresponding to Q motion cycles; for each running interval in each complete cycle, the maximum torque M max and the minimum torque M min are found; the average of the maximum torque M max and the minimum torque M min of each running interval is taken as the torque average parameter, and the position corresponding to the torque average parameter is taken as the load position, thereby forming the load position-torque average parameter of the corresponding interval of Z1 as one of the reference position-torque arrays, and the load position-torque average parameters of the driving sources driving the X-axis or Z-axis are obtained in the same way, thereby forming the load position-torque average parameter group.

[0057] As shown in Figure 2 , it is a schematic diagram of the monitoring and protection principle of the application.

[0058] The reference position-torque array obtained in the above process is enlarged by a factor k to obtain the position-torque upper limit array, and is reduced by a factor k to obtain the position-torque lower limit array.

[0059] That is, according to the set torque adjustment factor k; combined with the load position-torque average parameter

[0060] The reference position-torque array is enlarged by a factor k to obtain the position-torque upper limit array, that is, the upper limit maximum torque limit value of each running interval is:

[0061] The reference position-torque array is reduced by a factor k to obtain the position-torque lower limit array, that is, the lower limit minimum torque limit value of each running interval is

[0062] The position-torque upper limit and lower limit arrays obtained in the self-learning stage are taken as the working load interval to enter the monitoring stage.

[0063] In the subsequent automatic work process of the truss robot, when the actual monitored position-torque data exceeds the work load interval, the truss robot judges that there is an abnormal external load intervention, and the PLC controls each servo shaft to immediately brake, realizes millisecond-level automatic feedback and execution braking, thereby avoiding serious collision and automatically protecting the truss robot body, and greatly reducing the collision damage of the truss robot to the docking equipment.

[0064] The control module of the present application uses the address during the movement of the X axis and the Z axis, and the control module will automatically read the movement data, and in the easy collision movement section, the dense collection can be set separately, the collection interval of this movement section is smaller, up to millimeter level, and when abnormal collision deformation occurs at the end, the rigidity deformation of the general mechanical mechanism can absorb 1mm deformation, so that the mechanical hand can be more safely protected.

[0065] As shown in Figure 3 , it is the actual monitoring position-torque array curve diagram of the present application. Figure 3 The servo driver is shown in the figure, and the motor torque of the X axis and the Z axis is collected; the process of realizing the collection result is as follows:

[0066] The present application automatically collects the position-torque parameters of the servo motor driver in the full cycle process of various types of loads through a certain period of complete cycle, and automatically forms the position-torque work load interval, when the actual monitored position-torque data exceeds the work load interval, the truss robot automatically judges that it is subjected to external load intervention, that is:

[0067] The host computer obtains the actual torque value M of each running interval in the work process through the X-axis servo and the Z-axis servo of the truss robot;

[0068] The actual torque value M is compared with the work load interval;

[0069] When , that is, the torque exceeds the threshold value, collision occurs, the PLC controls each servo shaft to brake, and outputs an alarm;

[0070] When , that is, the torque is less than the threshold value, falling occurs, the PLC controls each servo shaft to brake, and outputs an alarm.

[0071] When the self-learning stage is executed, the control program automatically monitors and stores the position and torque parameters in the driver, automatically divides the position interval section according to the cycle stroke, automatically calculates the position and torque fluctuation range of the interval section, automatically amplifies and reduces the coefficient, forms the set upper and lower limit position-torque load interval, and automatically stores it as the work load interval.

[0072] In the normal work of the truss robot, the actually monitored position-moment array should be within the position-moment upper limit and lower limit array work load interval, when the truss robot encounters an abnormal external load, the actually monitored position-moment array will be outside the work load interval, at this time, the PLC program automatically links each axis brake device to realize immediate braking, which can greatly reduce the damage caused by abnormal collision to the robot, and effectively automatically and intelligently protect the robot body. In summary, according to the actually monitored position-moment data, the work range interval automatically obtained in the self-learning stage is compared, when there is an external load abnormal intervention, the actual load moment will exceed the work load interval, and soft control protection is realized.

[0073] The above only describes the embodiments of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, extension, etc. made within the spirit and principle of the present application is included in the protection scope of the present application.

Claims

1. A control method of a truss robot intelligent anti-collision, characterized in that, The method comprises the following steps: 1) debugging the gantry robot, completing a set of Q motion cycle movements as a complete cycle period, and completing automatic division of the running interval of the gantry robot; 2) acquiring, from the X-axis servo driver and the Z-axis servo driver of the gantry robot, each actual position data of each running interval of Q complete cycle periods and the torque value data corresponding to each actual position in real time, and inputting the data into a self-learning database to complete establishment of the self-learning database; 3) automatically dividing the work load interval of the gantry robot according to the data in the self-learning database and a set torque adjustment coefficient k; The step 3) is specifically: 3-1) filtering each actual position of each running interval of each complete cycle period and the torque value corresponding to each actual position to eliminate peak parameters; 3-2) For each operating interval in each complete cycle, find the maximum torque value M max and the minimum torque value M min ; 3-3) Obtain the maximum torque M of each operation interval max and the minimum torque M min Obtain the average value of both as the torque average parameter, and the position corresponding to the torque average parameter as the load position, form the load position-torque average parameter group as the reference position-torque array; 3-4) acquiring the position-torque upper limit array and the position-torque lower limit array of the gantry robot according to the reference position-torque array and the set torque adjustment coefficient k; and taking the obtained position-torque upper limit and lower limit array as the work load interval; The step 3-4) is specifically: According to the set torque adjustment coefficient k; in combination with the load position-torque mean value parameters of each operating interval ; The position-moment upper limit array is obtained by a benchmark position-moment array amplification coefficient k, that is, the maximum moment limit value of each operation interval upper limit is (1+k)· ; The position-moment lower limit array is obtained by reducing the base position-moment array by a coefficient k; that is, the minimum moment limit value of each operation interval lower limit is (1-k)· ; 4) the gantry robot performs automatic work, and determines whether there is an abnormal external load intervention according to the work load interval; if there is, the PLC controls the braking of each servo shaft, otherwise the work continues. 2.The control method of the truss robot intelligent anti-collision according to claim 1, wherein, The step 1) is specifically: 1-1) setting the motion parameters, interval size and running route of the gantry robot according to the working conditions; the gantry robot moves according to the specified motion parameters and the set running route, and completes a set of Q motion cycle movements as a complete cycle period, wherein 3<Q<5; 1-2) obtaining the number xn and zn of the running intervals of each axis of the gantry robot according to the actual total travel of the X-axis and the Z-axis of the gantry robot in the complete cycle period and the set interval size, and automatically dividing the running intervals of each axis of the gantry robot. 3.The control method of the truss robot intelligent anti-collision according to claim 1, wherein, The automatic division of the running interval of the gantry robot comprises automatic division of the interval and manual setting of the dense collection interval; The automatic division of the interval is that the upper computer automatically divides the running interval of the gantry robot according to the actual motion travel of the X-axis and the Z-axis of the gantry robot; The manual setting of the dense collection interval is that the running interval corresponding to the motion segment with a docking space of less than 5mm in the process of picking and placing the workpiece by the robot hand.

4. The control method of the truss robot intelligent anti-collision according to claim 2, characterized in that, The motion parameters comprise the speed parameter, the acceleration parameter, the interval size parameter and the torque adjustment coefficient k of the X-axis and the Z-axis of the gantry robot.

5. The control method of the truss robot intelligent anti-collision according to claim 1, characterized in that, The step 4) is specifically: The upper computer acquires the actual torque value M of each running interval in the work process through the X-axis servo and the Z-axis servo of the gantry robot; The actual torque value M is compared with the work load interval. When M ≥ (1 + K) · When the moment exceeds the threshold, it is determined that the collision phenomenon occurs, the PLC controls the braking of each servo axis, and an alarm is output. When M ≤ (1 - K) · If the moment is smaller than the threshold value, it is determined that the falling phenomenon occurs, the PLC controls the braking of each servo axis, and an alarm is output.

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