CN111438692A - Robot control method, device, medium, equipment and robot - Google Patents
Robot control method, device, medium, equipment and robot Download PDFInfo
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- CN111438692A CN111438692A CN202010306640.0A CN202010306640A CN111438692A CN 111438692 A CN111438692 A CN 111438692A CN 202010306640 A CN202010306640 A CN 202010306640A CN 111438692 A CN111438692 A CN 111438692A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/1605—Simulation of manipulator lay-out, design, modelling of manipulator
Abstract
The disclosure relates to a robot control method, a device, a medium, equipment and a robot, which belong to the field of robots and can accurately control the robot and avoid the robot from colliding with other objects or human beings in the service process. A robot control method comprising: acquiring initial kinetic parameters of a robot kinetic model; acquiring a position, a speed, an acceleration and a current data set of a joint of the robot participating in dynamics calculation in the motion process of the robot; calibrating the initial kinetic parameters by using the position, speed, acceleration and current data set of the joint to obtain calibrated kinetic parameters; and controlling the robot by using the calibrated kinetic parameters, and taking the calibrated kinetic parameters as new initial kinetic parameters.
Description
Technical Field
The present disclosure relates to the field of robots, and in particular, to a robot control method, apparatus, medium, device, and robot.
Background
The service robot needs to help human beings in daily life, however, there is no good method for accurately controlling the robot to avoid collision with other objects or human beings in the service process.
Disclosure of Invention
The purpose of the disclosure is to provide a robot control method, a robot control device, a robot control medium, a robot control device and a robot, which can accurately control the robot and avoid the robot from colliding with other objects or human beings in the service process.
According to a first embodiment of the present disclosure, there is provided a robot control method including: acquiring initial kinetic parameters of a robot kinetic model; acquiring a position, a speed, an acceleration and a current data set of a joint of the robot participating in dynamics calculation in the motion process of the robot; calibrating the initial kinetic parameters by using the position, speed, acceleration and current data set of the joint to obtain calibrated kinetic parameters; and controlling the robot by using the calibrated kinetic parameters, and taking the calibrated kinetic parameters as new initial kinetic parameters.
According to a second embodiment of the present disclosure, there is provided a robot control device including: the first acquisition module is used for acquiring initial kinetic parameters of the robot kinetic model; the second acquisition module is used for acquiring a position, a speed, an acceleration and a current data set of a joint of the robot, which participates in dynamics calculation, in the motion process of the robot; the calibration module is used for calibrating the initial kinetic parameters by utilizing the position, speed, acceleration and current data set of the joint to obtain calibrated kinetic parameters; and the control module is used for controlling the robot by utilizing the calibrated kinetic parameters and taking the calibrated kinetic parameters as new initial kinetic parameters.
According to a third embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to the first embodiment of the present disclosure.
According to a fourth embodiment of the present disclosure, there is provided an electronic apparatus including: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to carry out the steps of the method according to the first embodiment of the disclosure.
By adopting the technical scheme, because the initial kinetic parameters of the robot kinetic model are firstly obtained, then acquiring position, speed, acceleration and current data sets of joints of the robot participating in dynamic calculation in the motion process of the robot, then utilizing the position, speed, acceleration and current data sets of the joints, calibrating the initial kinetic parameters to obtain calibrated kinetic parameters, then controlling the robot by using the calibrated kinetic parameters, the calibrated kinetic parameters are used as new initial kinetic parameters, so that the newly calibrated kinetic parameters can be used as initial values for next calibration for calibration again each time, a cycle is formed, the kinetic parameters are more and more accurate, and further, the current value calculated when the robot calls dynamics calculation is more and more accurate, and the control of the robot is more and more accurate.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is a flowchart of a robot control method according to an embodiment of the present disclosure.
Fig. 2 is a schematic block diagram of a robot control device according to an embodiment of the present disclosure.
FIG. 3 is a block diagram illustrating an electronic device in accordance with an example embodiment.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flowchart of a robot control method according to an embodiment of the present disclosure. As shown in fig. 1, the method includes the following steps S11 to S14.
In step S11, initial kinetic parameters of the robot kinetic model are acquired.
The method for acquiring the initial kinetic parameters can comprise the following steps: physical experiment method, CAD parameter obtaining method and identification technique method.
The physical experiment method is to disassemble each connecting rod of the mechanical arm of the robot and obtain some inertia parameters through experiments. For example, the mass may be measured directly, the coordinates of the center of mass may be obtained by determining the balance point of the connecting rod, and the diagonal elements of the inertia tensor may be obtained by the rocking motion, and so on.
The CAD acquisition parameter method is to find the kinetic parameters of the connecting rod by using its geometric and material characteristics.
The identification technique is based on "input/output" behavior and analysis of the robot in certain planned movements and estimation of parameter values by minimizing the difference between the function of the actual variables and its mathematical model.
In step S12, position, velocity, acceleration and current data sets of joints of the robot that participate in kinetic calculations are acquired during the robot motion.
In this step, the robot controller may be caused to run a process alone during the movement of the robot to record the current data values of the robot, including the position, velocity, acceleration, current, etc. of each joint of the robot, and store the data values in a file. If one mechanical arm has seven joints, recording the positions, the speeds, the accelerations and the current values of the seven joints according to a certain frequency, such as 1000Hz or 500Hz and the like according to the communication frequency of the controller; in the case of a humanoid robot, it is generally possible to record only the values of the joints used for calibration, such as the joints of the two arms, and generally the trunk may not record the current data values of the trunk if it does not participate in the kinetic calculation.
In step S13, the initial kinetic parameters are calibrated using the position, velocity, acceleration and current data sets of the joint to obtain calibrated kinetic parameters.
After data acquisition is performed for a number of times, calibration may be performed using the acquired data set. Moreover, before calibration is performed, the acquired data may be processed, for example, a repeated data set in the data set is deleted, so that a large number of repeated parts in the data can be deleted, and an abnormal data set in the data set may also be deleted, where the abnormal data set is a data set whose current value is greater than a first preset value or less than a second preset value compared with current values of other data sets in the case of a similar joint position, velocity, and acceleration. By the data processing, the data processing amount can be reduced.
The nature of the calibration process performed in step S13 is a process of data fitting, namely:
Cur＝Dyn(Pos,Vel,Acc) (1)
the robot comprises a base, a control group, a robot body, a control group, a robot arm, a robot body, a control group, a robot body, a robot arm and a robot body, wherein Cur represents current, Pos represents position, Vel represents speed, Acc represents acceleration, Cur, Pos, Vel and Acc are vectors of N × 1 respectively, N is the number of joints of the control group to be calibrated of the robot, if the robot arm body is calibrated only, N is the degree of freedom of each arm, if the body and the two arms are calibrated, N is the degree of freedom of the whole calibration tree structure, Dyn:
M(Pos)Acc+H(Pos,Vel)+G(Pos)＝τ＝k*Cur (2)
wherein τ is the joint output torque, and k is the proportionality coefficient of the motor current and the motor torque of the robot, which can be generally found in motor parameters. M is an inertia matrix, H contains Korea and centrifugal forces, and G represents gravity.
In addition, equation (2) can be written in a linear separation form as follows:
k*Cur＝τ＝φ(Pos,Vel,Acc)*Parm (3)
equation (3) can also be expressed as:
Parm＝k*Cur/φ(Pos,Vel,Acc) (4)
where φ is a linear system of equations that includes the position, velocity, and acceleration of each joint, and Parm is a parameter vector that includes the mass, center of mass, moment of inertia, coefficient of friction, etc. of each joint.
One of the calibration methods is as follows: and (3) substituting the m groups of position, speed, acceleration and current data sets obtained after data processing into the equation (4) to obtain m groups of parameter vectors Parm, and then processing the m groups of parameter vectors Parm by a least square method to obtain a group of more accurate parameter vectors Parm.
The other calibration method comprises the steps of continuously and randomly generating m groups of random initial kinetic parameters within a preset upper limit range and a preset lower limit range of the initial kinetic parameters, calculating currents of the joints by using the m groups of random initial kinetic parameters to obtain m groups of calculated currents, subtracting the m groups of calculated currents from the corresponding m groups of acquired currents respectively, taking the average value as an optimization target, and optimizing the optimization target by using an optimization algorithm such as a genetic algorithm to minimize the optimization target to obtain the calibrated kinetic parameters.
In step S14, the robot is controlled using the calibrated kinetic parameters, and the calibrated kinetic parameters are used as new initial kinetic parameters.
After the calibrated kinetic parameters are obtained, the calibrated kinetic parameters can be written into the robot system, and when the robot system calls kinetic calculation, the calibrated kinetic parameters can be used for performing kinetic calculation, so that a more accurate current value can be obtained, and the robot can be controlled more accurately. And the calibrated kinetic parameters can be used as new initial kinetic parameters for next calibration, namely, the newly calibrated kinetic parameters are used as initial values of the next calibration for calibration again each time, so that a cycle is formed, and the kinetic parameters are more and more accurate.
By adopting the technical scheme, because the initial kinetic parameters of the robot kinetic model are firstly obtained, then acquiring position, speed, acceleration and current data sets of joints of the robot participating in dynamic calculation in the motion process of the robot, then utilizing the position, speed, acceleration and current data sets of the joints, calibrating the initial kinetic parameters to obtain calibrated kinetic parameters, then controlling the robot by using the calibrated kinetic parameters, the calibrated kinetic parameters are used as new initial kinetic parameters, so that the newly calibrated kinetic parameters can be used as initial values for next calibration for calibration again each time, a cycle is formed, the kinetic parameters are more and more accurate, and further, the current value calculated when the robot calls dynamics calculation is more and more accurate, and the control of the robot is more and more accurate.
Fig. 2 is a schematic block diagram of a robot control device according to an embodiment of the present disclosure. As shown in fig. 2, the apparatus includes: the first acquisition module 21 is used for acquiring initial kinetic parameters of a robot kinetic model; the second acquisition module 22 is used for acquiring a position, a speed, an acceleration and a current data set of a joint of the robot participating in dynamics calculation in the motion process of the robot; the calibration module 23 is configured to calibrate the initial kinetic parameters by using the position, speed, acceleration, and current data set of the joint to obtain calibrated kinetic parameters; and the control module 24 is used for controlling the robot by using the calibrated kinetic parameters and taking the calibrated kinetic parameters as new initial kinetic parameters.
By adopting the technical scheme, because the initial kinetic parameters of the robot kinetic model are firstly obtained, then acquiring position, speed, acceleration and current data sets of joints of the robot participating in dynamic calculation in the motion process of the robot, then utilizing the position, speed, acceleration and current data sets of the joints, calibrating the initial kinetic parameters to obtain calibrated kinetic parameters, then controlling the robot by using the calibrated kinetic parameters, the calibrated kinetic parameters are used as new initial kinetic parameters, so that the newly calibrated kinetic parameters can be used as initial values for next calibration for calibration again each time, a cycle is formed, the kinetic parameters are more and more accurate, and further, the current value calculated when the robot calls dynamics calculation is more and more accurate, and the control of the robot is more and more accurate.
Optionally, the calibration module 23 calibrates the initial dynamic parameters by using the position, velocity, acceleration and current data sets of the joint, and is implemented by the following formula:
Parm＝k*Cur/φ(Pos,Vel,Acc)
phi is a linear equation system containing the position, the speed and the acceleration of each joint, Cur represents current, Pos represents position, Vel represents speed, Acc represents acceleration, k is a proportional coefficient of motor current and motor torque of the robot, and Parm is a parameter vector containing the mass, the mass center, the inertia moment and the friction coefficient of each joint.
Optionally, the number of the position, velocity, acceleration and current data sets is m, the number of the calibrated parameter vectors Parm is m, and the calibration module 23 is further configured to: the m sets of parameter vectors Parm are processed by a least squares method.
Optionally, the calibration module 23 is configured to: randomly generating m groups of random initial kinetic parameters within the preset upper and lower limits of the initial kinetic parameters; calculating the current of the joint by using m groups of random initial kinetic parameters to obtain m groups of calculated currents; subtracting the m groups of calculated currents from the corresponding m groups of acquired currents respectively, and then taking the average value as an optimization target; and optimizing the optimization target by using an optimization algorithm to obtain a calibration kinetic parameter.
Optionally, the calibration module 23 is further configured to: the repeated data group and the abnormal data group in the data group acquired by the second acquisition module 22 are deleted, and the abnormal data group is a data group whose current value is larger than the first preset value or smaller than the second preset value compared with the current values of other data groups under the condition of the similar joint position, velocity and acceleration.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Fig. 3 is a block diagram illustrating an electronic device 700 according to an example embodiment. As shown in fig. 3, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input/output (I/O) interface 704, and a communication component 705.
The processor 701 is configured to control the overall operation of the electronic device 700, so as to complete all or part of the steps in the robot control method. The memory 702 is used to store various types of data to support operation at the electronic device 700, such as instructions for any application or method operating on the electronic device 700 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 702 may be implemented by any type of volatile or non-volatile Memory device or 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 Memory, flash Memory, magnetic disk, or optical disk. The multimedia components 703 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 702 or transmitted through the communication component 705. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 704 provides an interface between the processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding communication component 705 may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the electronic Device 700 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable logic devices (Programmable L ic devices, P L D), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for performing the robot control method described above.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the robot control method described above is also provided. For example, the computer readable storage medium may be the above-mentioned memory 702 comprising program instructions executable by the processor 701 of the electronic device 700 to perform the above-mentioned robot control method.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, various possible combinations will not be separately described in this disclosure.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (10)
1. A robot control method, comprising:
acquiring initial kinetic parameters of a robot kinetic model;
acquiring a position, a speed, an acceleration and a current data set of a joint of the robot participating in dynamics calculation in the motion process of the robot;
calibrating the initial kinetic parameters by using the position, speed, acceleration and current data set of the joint to obtain calibrated kinetic parameters;
and controlling the robot by using the calibrated kinetic parameters, and taking the calibrated kinetic parameters as new initial kinetic parameters.
2. The method of claim 1, wherein said calibrating said initial kinetic parameters using said joint position, velocity, acceleration and current data sets is performed by the following equation:
Parm＝k*Cur/φ(Pos,Vel,Acc)
phi is a linear equation system containing the position, the speed and the acceleration of each joint, Cur represents the current, Pos represents the position, Vel represents the speed, Acc represents the acceleration, k is a proportional coefficient of motor current and motor torque of the robot, and Parm is a parameter vector containing the mass, the mass center, the inertia moment and the friction coefficient of each joint.
3. The method of claim 2, wherein the number of position, velocity, acceleration and current data sets is m sets, and the number of calibrated parameter vectors Parm is m sets, the method further comprising:
the m sets of parameter vectors Parm are processed by a least squares method.
4. The method of claim 1, wherein said calibrating said initial kinetic parameters using said joint position, velocity, acceleration and current data sets comprises:
randomly generating m groups of random initial kinetic parameters within the preset upper and lower limit ranges of the initial kinetic parameters;
calculating the current of the joint by using the m groups of random initial kinetic parameters to obtain m groups of calculated currents;
subtracting the m groups of calculated currents from the corresponding m groups of acquired currents respectively, and then taking the average value as an optimization target;
and optimizing the optimization target by using an optimization algorithm to obtain the calibration kinetic parameters.
5. The method according to any one of claims 1 to 4, further comprising: and after acquiring the position, speed, acceleration and current data sets of the joints of the robot participating in the dynamics calculation, deleting repeated data sets and abnormal data sets in the data sets, wherein the abnormal data sets are data sets of which the current values are larger than a first preset value or smaller than a second preset value compared with the current values of other data sets under the conditions of the similar joint position, speed and acceleration.
6. A robot control apparatus, comprising:
the first acquisition module is used for acquiring initial kinetic parameters of the robot kinetic model;
the second acquisition module is used for acquiring a position, a speed, an acceleration and a current data set of a joint of the robot, which participates in dynamics calculation, in the motion process of the robot;
the calibration module is used for calibrating the initial kinetic parameters by utilizing the position, speed, acceleration and current data set of the joint to obtain calibrated kinetic parameters;
and the control module is used for controlling the robot by utilizing the calibrated kinetic parameters and taking the calibrated kinetic parameters as new initial kinetic parameters.
7. The apparatus of claim 6, wherein the calibration module calibrates the initial kinetic parameter using a position, velocity, acceleration, and current data set of the joint by:
Parm＝k*Cur/φ(Pos,Vel,Acc)
phi is a linear equation system containing the position, the speed and the acceleration of each joint, Cur represents the current, Pos represents the position, Vel represents the speed, Acc represents the acceleration, k is a proportional coefficient of motor current and motor torque of the robot, and Parm is a parameter vector containing the mass, the mass center, the inertia moment and the friction coefficient of each joint.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
9. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 5.
10. A robot, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 5.
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