CN113370203A - Robot control method, robot control device, computer device, and storage medium - Google Patents
Robot control method, robot control device, computer device, and storage medium Download PDFInfo
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- 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
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- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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Abstract
The application discloses a robot control method, a robot control device, computer equipment and a storage medium, and relates to the technical field of robots. The robot control method comprises the steps of obtaining a measuring distance corresponding to an end effector and an arm moving distance corresponding to an arm of a robot; inputting the first control signal into the robot model to obtain a theoretical moving distance corresponding to the end effector; and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal. According to the embodiment, the second control signal is determined according to a plurality of influence factors such as the measured distance, the arm moving distance, the target distance and the theoretical moving distance, and the end effector can be controlled to align to the target position point according to the second control signal, so that the control precision of the robot is improved.
Description
Technical Field
The present application relates to the field of robotics, and in particular, to a robot control method, apparatus, computer device, and storage medium.
Background
With the upgrading of the manufacturing industry, robots are increasingly used in industrial production. A robot generally includes a controller, an arm, and an end effector mounted at the end of the arm, wherein the end effector may refer to a tool having a certain function, such as a camera, a cutter, a gripper, and the like.
In practical application, the working process of the robot may be: the controller controls the arm to drive the end effector to move, and when the arm moves to the target position point, the arm stops moving, so that the end effector executes corresponding actions at the target position point.
However, after the arm stops moving, there is still residual jitter on the end effector due to the influence of the speed, acceleration and external disturbance during the movement of the arm, and the residual jitter may cause the actual alignment position of the end effector to be different from the target position, thereby reducing the control accuracy of the robot.
Disclosure of Invention
In view of the above, it is necessary to provide a robot control method, a robot control apparatus, a computer device, and a storage medium, which address the above-mentioned problem of low robot control accuracy.
A robot control method, the method comprising:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position;
inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
In one embodiment, the end effector is provided with a monitoring sensor, and the measurement distance from a position point actually reached by the end effector mounted on an arm of the robot to a starting position is acquired, including:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring pose data of the end effector by using a monitoring sensor, wherein the pose data comprises the speed or the acceleration of the end effector;
and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
In one embodiment, the monitoring sensors are of various types, and the measurement distance from the position point actually reached by the end effector mounted on the arm of the robot to the starting position is acquired, and the measurement distance comprises the following steps:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, respectively obtaining a plurality of pose data of the end effector by using each monitoring sensor;
and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the plurality of pose data.
In one embodiment, generating the second control signal according to the measured distance, the arm movement distance, the target distance from the target position point to the start position, and the theoretical movement distance includes:
generating a feedback signal according to the measured distance, the arm moving distance, the target distance and the theoretical moving distance;
and correcting the first control signal according to the feedback signal to obtain a second control signal.
In one embodiment, generating the feedback signal based on the measured distance, the arm movement distance, the target distance, and the theoretical movement distance comprises:
estimating the real distance from the position point actually reached by the end effector to the initial position according to the measured distance and the theoretical moving distance;
determining the movement error of the end effector according to the real distance and the target distance;
and generating a feedback signal according to the movement error and the arm movement distance.
In one embodiment, estimating the true distance from the position point actually reached by the end effector to the starting position based on the measured distance and the theoretical moving distance comprises:
and performing Kalman filtering on the measured distance and the theoretical moving distance to obtain the real distance of the end effector.
In one embodiment, before inputting the first control signal into the robot model, the method further comprises:
acquiring a mass matrix, a damping matrix, a rigidity matrix and an excitation force vector corresponding to the robot;
and establishing a robot model according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
A robot control apparatus, the apparatus comprising:
the first acquisition module is used for acquiring the measurement distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and the arm movement distance from the position point actually reached by the arm of the robot to the initial position after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal;
the second acquisition module is used for inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and the control module is used for generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align at the target position point according to the second control signal.
A computer device comprising a memory and a processor, the memory storing a computer program that when executed by the processor performs the steps of:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position;
inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position;
inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
The beneficial effects brought by the technical scheme provided by the embodiment of the application at least comprise:
the robot control method, the robot control device, the computer equipment and the storage medium can improve the precision of the robot. A background controller (hereinafter, simply referred to as a controller) of the robot may send a first control signal to the servo drive system, and the servo drive system controls the arm of the robot to move from the start position to the target position point according to the first control signal. After controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, the controller obtains the measured distance from the position point actually reached by the end effector mounted on the arm of the robot to the initial position and the arm moving distance from the position point actually reached by the arm of the robot to the initial position; the controller inputs the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model; the controller generates a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controls the end effector of the robot to align to the target position point according to the second control signal. According to the embodiment, the second control signal is determined according to a plurality of influence factors such as the measured distance, the arm moving distance, the target distance and the theoretical moving distance, and the end effector can be controlled to align to the target position point according to the second control signal, so that the control precision of the robot is improved.
Drawings
Fig. 1 is a schematic view of a robot provided in an embodiment of the present application;
fig. 2 is a flowchart of a robot control method according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a second control signal generation method according to an embodiment of the present disclosure;
fig. 4 is a flowchart of a feedback signal generating method according to an embodiment of the present application;
fig. 5 is a flowchart of a robot control device according to an embodiment of the present disclosure;
fig. 6 is a block diagram of a controller according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The robot is a kind of machine device which can realize various functions by means of its own power and control capability, and is generally composed of an actuating mechanism, a driving device, a detecting device, a control system and a complex machine. With the upgrading of the manufacturing industry, robots are increasingly used in industrial production. In the prior art, the working process of the robot may be as follows: the controller controls the arm to drive the end effector to move, and when the arm moves to the target position point, the arm stops moving, so that the end effector executes corresponding actions at the target position point. In the robot control process, it is generally considered that an actual arrival position of an arm of the robot is a position at which the end effector actually arrives, and when the arm of the robot reaches the target position point, the end effector is considered to arrive at the target position point.
However, when the arm of the robot reaches the target position, there is still residual jitter on the end effector due to the influence of speed, acceleration, and external disturbance during the movement of the arm, and the residual jitter may cause the actual alignment position of the free suspended end of the end effector to be different from the target position, and the execution component, such as a tool, a camera, an optical lens, or a dispensing valve, mounted on the free suspended end of the end effector may not be aligned with the target position, thereby reducing the control accuracy of the robot.
The embodiment of the application provides a robot control method, which determines a second control signal of a robot according to a measured distance corresponding to an end effector in an actual motion process of the robot, an arm moving distance of a robot arm, a theoretical moving distance corresponding to the end effector in a theoretical motion process and a target distance corresponding to a target position point, and determines the second control signal from a plurality of influence factors, so that the end effector can be controlled to align to the target position point according to the second control signal, and the control precision of the robot is improved.
In the following, a brief description will be given of an implementation environment related to the robot control method provided in the embodiment of the present application.
Referring to fig. 1, the execution environment may include a robot and a background controller (not shown) of the robot. The robot includes a controller, a servo drive system 101, an arm 102, and an end effector 103 mounted on the end of the arm. The controller is electrically connected with a servo drive system 101, the servo drive system 101 is connected with an arm 102, one end of an end effector 103 is connected with the arm 102, and the other end is freely suspended. The end effector 103 may refer to a tool having a certain function, such as a cutter, a gripper, and the like. In general, the end effector 103 is flexibly connected to the arm 102 of the robot to facilitate flexible movement of the end effector.
Optionally, the end effector 103 may be mounted with a monitoring sensor 104, and the monitoring sensor 104 may be configured to detect an operating speed, an acceleration, a rotation angle, and the like of the end effector.
In this embodiment, the controller may send a first control signal to the servo driving system, and the servo driving system controls the arm of the robot to move from the initial position to the target position point according to the first control signal. After the controller controls the arm of the robot to move from the initial position to the target position point according to the first control signal, the controller obtains the measured distance from the position point actually reached by the end effector mounted on the arm of the robot to the initial position and the arm moving distance from the position point actually reached by the arm of the robot to the initial position; the controller inputs the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model; the controller generates a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controls the end effector of the robot to align to the target position point according to the second control signal.
Referring to fig. 2, which shows a flowchart of a robot control method provided in an embodiment of the present application, the robot control method may be applied in the implementation environment shown in fig. 1, and as shown in fig. 2, the robot control method may include the following steps:
in step 201, after controlling the arm of the robot to move from the starting position to the target position point according to the first control signal, the controller obtains a measured distance from a position point, which is actually reached by an end effector mounted on the arm of the robot, to the starting position, and an arm moving distance from the position point, which is actually reached by the arm of the robot, to the starting position.
The robot in the present embodiment may be an industrial robot which is a multi-joint manipulator or a multi-degree-of-freedom robot for industrial fields, and a special robot which is various advanced robots for non-manufacturing industries other than the industrial robot and serving humans.
In this embodiment, when not operating, the arm of the robot is set to the zero point by default, and this position is referred to as the home position in this embodiment. When the robot is in operation, for example, it needs to be controlled to move to the target position point, at this time, the controller may send a first control signal to the servo drive system, and the servo drive system drives the arm of the robot to move from the start position to the target position point according to the received first control signal.
Due to the accuracy problem of the robot, in the process that the servo driving system controls the arm of the robot to move to the target position point, the arm of the robot may not be aligned with the target position point. Therefore, in the present embodiment, the target position point cannot be set as a position point at which the arm of the robot is actually aligned. In this embodiment, a motor encoder may be installed on the robot, and the motor encoder is used to measure the actual movement distance of the arm of the robot, which is the actual movement distance of the arm between the position point where the arm of the robot actually reaches and the start position.
Further, in the actual movement process of the arm of the robot, a certain speed and acceleration exist, so that after the arm of the robot stops operating, the free-hanging end of the end effector still remains in shake, and under the influence of the remaining shake, the position point actually reached by the free-hanging end of the end effector and the target position point are deviated. In this embodiment, the controller may obtain a distance between a position point actually reached by the end effector and the start position, where the position distance is a measurement distance.
In an alternative implementation, the robot model may be a kinetic model. The process of establishing the robot model of the robot may be:
the robot is equivalent to a mass matrix, a damping matrix, a rigidity matrix and an excitation force vector, and then a dynamic model is constructed according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
Alternatively, the mathematical theoretical expression of the kinetic model may be as shown in equation (1):
wherein M represents a mass matrix, D represents a damping matrix, and K represents a stiffness matrixAnd F denotes an excitation force vector. X represents a state quantity of the state quantity,
indicating that the first derivative is made to the control signal,
indicating that the first derivative is made to the control signal.
Alternatively, in the robot model, the nature of the control signal may be a force. That is, the magnitude of the force is obtained and introduced into the kinetic model, so that the kinetic model can predict the theoretical movement distance of the arm of the robot and the theoretical movement distance of the end effector of the robot.
It should be noted that the dynamic models of robots with different specifications may have different specific expression forms.
Optionally, in this embodiment, specifications of the robot need to be obtained in advance, then a dynamic model adapted to the specifications of the robot is selected from a plurality of preset dynamic models according to the specifications of the robot as a target dynamic model, and then a theoretical moving distance of an arm of the robot and a theoretical moving distance of an end effector of the robot are predicted according to the target dynamic model.
In this embodiment, the robot models of the robots with different specifications are not exhaustive because the specific expressions of the robot models of the robots with different specifications may have some differences.
In another alternative implementation, the robot model is a machine learning model.
The machine learning model may be a neural network model, a support vector machine model, an extreme learning machine model, or the like.
In this embodiment, when the robot needs to be controlled to move from the initial position to the target position point, the coordinate value of the target position point in the robot coordinate system may be input to the controller, and the controller may send the first control signal to the servo drive system according to the coordinate value of the target position point.
In this embodiment, different target position points may be set multiple times, so that multiple first control signals may be obtained.
And acquiring actual coordinates which can be actually reached by the end effector of the robot under the control of each first control signal and real coordinates of each target position point. And establishing a training sample according to the first control signal, the actual coordinates of the end effector, corresponding to the first control signal, which actually arrive, and the real coordinates of the target position point, corresponding to the first control signal. In a similar manner, multiple training samples may be established.
In this embodiment, the machine learning model may be trained using the training samples, so as to obtain a trained robot model.
And 203, generating a second control signal by the controller according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
In an optional implementation manner, in this embodiment, a difference between the measured distance and the theoretical moving distance may be obtained to obtain a first difference value. And calculating the difference between the arm moving distance and the target distance to obtain a second difference value.
And carrying out weighted summation on the first difference and the second difference to obtain the estimated distance difference.
In this embodiment, the controller may generate a second control signal according to the estimated distance difference, and the second control signal may control the end effector to move the target position point from the actually aligned position point again.
That is, in the present embodiment, when the end effector of the robot is planned to move from point a to point B, and the controller issues the first control signal, the end effector actually reaches point C due to the influence of residual jitter. Through the disclosure of steps 201 to 203, the estimated distance difference can be obtained, and then the controller generates a second control signal according to the estimated distance difference, and the second control signal can perform new movement on the arm of the robot, so that the end effector can be aligned from point C to point B, thereby improving the control accuracy of the robot.
In this embodiment, the measurement distance corresponding to the end effector is obtained by measuring with the monitoring sensor, and in an industrial environment, the measurement result of the monitoring sensor is affected by noise, null shift, interference, nonlinear error and other factors. Therefore, the accuracy of the distance measurement by the end effector is affected and cannot reflect the actual distance moved by the end effector.
Further, in the modeling process of the robot model, the accuracy of the theoretical moving distance of the end effector output by the robot model is also affected by the influence of modeling parameters or the influence of model training samples, so that the actual moving distance of the end effector cannot be reflected.
Based on this, in this embodiment, the measured distance and the theoretical moving distance are processed again in combination with the arm moving distance and the target distance, so that the accuracy of the data is improved. Therefore, the second control signal determined by integrating the factors such as the measured distance, the theoretical moving distance, the arm moving distance and the like which can influence the actual reaching position point of the end effector can achieve the aim of aligning the end effector to the target position point, and the control precision of the robot is improved.
In an alternative implementation, the process of the controller acquiring the distance measured between the position point actually reached by the end effector and the starting position may be:
a monitoring sensor is disposed on the end effector, and optionally, the monitoring sensor may be a speed sensor, an acceleration sensor, an angle sensor (e.g., a gyroscope), a displacement sensor, or the like.
In the process that the servo driving system drives the arm of the robot to move from the initial position to the target position point, the end effector moves along with the arm of the robot, meanwhile, the monitoring sensor on the end effector also moves along with the end effector and can monitor the pose data of the end effector, the pose data can be the speed or the acceleration of the end effector, and the monitoring sensor can upload the monitored pose data to the controller in real time.
In this embodiment, since one end of the end effector is fixed to the arm of the robot and the other end is freely suspended, and the free suspended end is greatly affected by the residual vibration, the speed or acceleration of the free suspended end of the end effector (i.e., the speed or acceleration of the end effector) is different from the speed or acceleration of the arm of the robot. In this embodiment, the monitoring sensor detects the velocity or acceleration of the free-hanging end of the end effector.
And the controller calculates the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
Alternatively, when the pose data is the velocity of the end effector, the velocity may be integrated to obtain the movement distance of the end effector, and the movement distance is calculated after being measured by the sensor, that is, the measurement distance from the position point actually reached by the end effector to the start position.
In an alternative implementation, there may be a plurality of monitoring sensors. I.e., a plurality of different types of monitoring sensors are provided on the end effector. That is, at least two of the velocity sensor, the acceleration sensor, the angle sensor (e.g., gyroscope), and the displacement sensor may be provided on the end effector at the same time. In this embodiment, the process of acquiring, by the controller, the measured distance from the position point, at which the end effector mounted on the arm of the robot actually reaches, to the start position may include the following steps:
and A1, after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, the controller respectively obtains a plurality of pose data of the end effector by using each monitoring sensor.
The present embodiment is described by taking an example in which a speed sensor and an acceleration sensor are mounted at the same time. During the movement of the end-effector with the arm of the robot, the velocity sensor may detect the velocity of the end-effector, and the acceleration sensor may detect the acceleration of the end-effector.
A2, the controller calculates a measured distance from the position point actually reached by the end effector to the home position based on the plurality of pose data.
The controller may obtain the first actual movement distance of the end effector by integrating the velocity. Meanwhile, the controller can also perform secondary integral operation on the acceleration signal to obtain a second actual movement distance of the end effector.
Optionally, different weights may be set for the velocity sensor and the acceleration sensor, a weighting operation may be performed on the weight of the velocity sensor, the first actual movement distance, the weight of the acceleration sensor, and the second actual movement distance, and the calculated distance value is the measurement distance.
In one embodiment, as shown in fig. 3, step 203 may further include the steps of:
In an alternative implementation, the difference between the measured distance and the theoretical moving distance may be obtained to obtain the first difference. And calculating the difference between the arm moving distance and the target distance to obtain a second difference value. And carrying out weighted summation on the first difference and the second difference to obtain the estimated distance difference, and generating a feedback signal according to the estimated distance difference.
In another alternative implementation, as shown in fig. 4, the process of generating the feedback signal according to the measured distance, the arm movement distance, the target distance, and the theoretical movement distance may be:
Optionally, kalman filtering may be performed on the measured distance and the theoretical moving distance, and the real distance of the end effector is estimated by using a kalman filtering algorithm.
In this embodiment, a difference exists between the real distance corresponding to the end effector and the target distance of the target position point theoretically to be reached by the end effector, and in this embodiment, the movement error of the end effector may be determined by the difference between the real distance and the target distance.
And step 403, generating a feedback signal according to the movement error and the arm movement distance.
The feedback signal is used for applying driving force to the arm of the robot so as to control the arm of the robot to move, and therefore the end effector is driven to move.
The movement error is a distance by which the end effector actually shifts due to the shake, and the arm movement distance is a distance by which the robot arm moves after the servo drive system applies the driving force to the robot arm. It can be known that the movement error and the arm movement distance are important factors affecting the feedback signal. The feedback signal functions to apply a driving force to the arm of the robot so that the arm of the robot moves again, and in the process of the movement again, a movement error of the end effector can be compensated, so that the position point of the end effector can be corrected to the target position point.
In this embodiment, the first control signal controls the arm of the robot to perform a first movement, the second control signal controls the arm of the robot to perform a second movement, and the second movement is a deviation rectifying operation for the first movement based on the first movement. Therefore, the second control signal has an association relation with the first control signal and the feedback signal, and the second control signal is determined by comprehensively considering the feedback signal and the first control signal, so that the control precision of the second control signal is more accurate, and the end effector can be accurately aligned to the target position point.
Referring to fig. 5, a block diagram of a robot control device provided in an embodiment of the present application is shown, where the robot control device may be configured in a robot in the implementation environment shown in fig. 1. As shown in fig. 5, the robot controller may include a first acquisition module 501, a second acquisition module 502, and a control module 503.
A first obtaining module 501, configured to obtain a measured distance from a position point, which is actually reached by an end effector mounted on an arm of the robot, to an initial position and an arm moving distance from the position point, which is actually reached by the arm of the robot, to the initial position after controlling the arm of the robot to move from the initial position to a target position point according to a first control signal;
a second obtaining module 502, configured to input the first control signal into the robot model, so as to obtain a theoretical moving distance of the end effector output by the robot model;
and the control module 503 is configured to generate a second control signal according to the measured distance, the arm movement distance, the target distance from the target position point to the start position, and the theoretical movement distance, and control the end effector of the robot to align to the target position point according to the second control signal.
In an embodiment of the present application, a monitoring sensor is disposed on the end effector, and the first obtaining module 501 is further configured to obtain pose data of the end effector by using the monitoring sensor after controlling an arm of the robot to move from an initial position to a target position point according to the first control signal, where the pose data includes a speed or an acceleration of the end effector; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
In an embodiment of the present application, there are multiple monitoring sensors, and the first obtaining module 501 is further configured to obtain multiple pose data of the end effector by using each monitoring sensor after controlling the arm of the robot to move from the start position to the target position point according to the first control signal; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the plurality of pose data.
In an embodiment of the present application, the control module 503 is further configured to generate a feedback signal according to the measured distance, the arm movement distance, the target distance, and the theoretical movement distance; and correcting the first control signal according to the feedback signal to obtain a second control signal.
In one embodiment of the present application, the control module 503 is further configured to estimate a real distance from a position point actually reached by the end effector to the starting position according to the measured distance and the theoretical moving distance; determining the movement error of the end effector according to the real distance and the target distance; and generating a feedback signal according to the movement error and the arm movement distance.
In an embodiment of the present application, the control module 503 is further configured to perform kalman filtering on the measured distance and the theoretical moving distance to obtain the real distance of the end effector.
In an embodiment of the present application, the second obtaining module 502 is further configured to obtain a mass matrix, a damping matrix, a stiffness matrix, and an excitation force vector corresponding to the robot; and establishing a robot model according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
For specific limitations of the robot control device, reference may be made to the above limitations of the robot control method, which are not described herein again. The respective modules in the robot control device described above may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment of the present application, a controller is provided, which may be an embedded system, a server or a computer, and its internal structure diagram may be as shown in fig. 6. The controller includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the controller is configured to provide computational and control capabilities. The memory of the controller comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database may be adapted to store a robot model, and the network interface of the controller is adapted to communicate with an external terminal via a network connection. The controller is executed by the processor to implement a robot control method.
Those skilled in the art will appreciate that the configuration shown in fig. 6 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation on the controller to which the present application is applied, and that a particular controller may include more or less components than those shown, or combine certain components, or have a different arrangement of components.
In one embodiment of the present application, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position; inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model; and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
In one embodiment of the present application, the end effector is provided with a monitoring sensor, and the processor executes the computer program to further implement the following steps: after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring pose data of the end effector by using a monitoring sensor, wherein the pose data comprises the speed or the acceleration of the end effector; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
In one embodiment of the present application, the monitoring sensors are of various types, and the processor executes the computer program to further implement the following steps: after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, respectively obtaining a plurality of pose data of the end effector by using each monitoring sensor; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the plurality of pose data.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: generating a feedback signal according to the measured distance, the arm moving distance, the target distance and the theoretical moving distance; and correcting the first control signal according to the feedback signal to obtain a second control signal.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: estimating the real distance from the position point actually reached by the end effector to the initial position according to the measured distance and the theoretical moving distance; determining the movement error of the end effector according to the real distance and the target distance; and generating a feedback signal according to the movement error and the arm movement distance.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: and performing Kalman filtering on the measured distance and the theoretical moving distance to obtain the real distance of the end effector.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring a mass matrix, a damping matrix, a rigidity matrix and an excitation force vector corresponding to the robot; and establishing a robot model according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
The implementation principle and technical effect of the computer device provided by the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
In an embodiment of the application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of:
after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position; inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model; and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
In one embodiment of the present application, the end effector is provided with a monitoring sensor, and the computer program when executed by the processor further implements the steps of: after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, acquiring pose data of the end effector by using a monitoring sensor, wherein the pose data comprises the speed or the acceleration of the end effector; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
In one embodiment of the application, the monitoring sensor is of a plurality, and the computer program when executed by the processor further performs the steps of: after controlling the arm of the robot to move from the initial position to the target position point according to the first control signal, respectively obtaining a plurality of pose data of the end effector by using each monitoring sensor; and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the plurality of pose data.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: generating a feedback signal according to the measured distance, the arm moving distance, the target distance and the theoretical moving distance; and correcting the first control signal according to the feedback signal to obtain a second control signal.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: estimating the real distance from the position point actually reached by the end effector to the initial position according to the measured distance and the theoretical moving distance; determining the movement error of the end effector according to the real distance and the target distance; and generating a feedback signal according to the movement error and the arm movement distance.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: and performing Kalman filtering on the measured distance and the theoretical moving distance to obtain the real distance of the end effector.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring a mass matrix, a damping matrix, a rigidity matrix and an excitation force vector corresponding to the robot; and establishing a robot model according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
The implementation principle and technical effect of the computer-readable storage medium provided in the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A robot control method, characterized in that the method comprises:
after controlling the arm of the robot to move from an initial position to a target position point according to a first control signal, acquiring a measured distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and an arm moving distance from the position point actually reached by the arm of the robot to the initial position;
inputting the first control signal into a robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
2. The method of claim 1, wherein the end effector is provided with a monitoring sensor, and the obtaining of the measured distance from the starting position to the position point actually reached by the end effector mounted on the arm of the robot comprises:
after controlling the arm of the robot to move from the starting position to the target position point according to the first control signal, acquiring pose data of the end effector by using the monitoring sensor, wherein the pose data comprises the speed or the acceleration of the end effector;
and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the pose data.
3. The method of claim 2, wherein the plurality of monitoring sensors, the obtaining a measured distance from a location point actually reached by an end effector mounted on an arm of the robot to the starting position, comprises:
after controlling the arm of the robot to move from an initial position to a target position point according to a first control signal, respectively obtaining a plurality of pose data of the end effector by using each monitoring sensor;
and calculating the measurement distance from the position point actually reached by the end effector to the starting position according to the plurality of pose data.
4. The method of claim 1, wherein generating a second control signal based on the measured distance, the arm movement distance, the target distance from the target location point to the starting location, and the theoretical movement distance comprises:
generating a feedback signal according to the measured distance, the arm moving distance, the target distance and the theoretical moving distance;
and correcting the first control signal according to the feedback signal to obtain the second control signal.
5. The method of claim 4, wherein generating a feedback signal based on the measured distance, the arm movement distance, the target distance, and the theoretical movement distance comprises:
estimating the real distance from the position point actually reached by the end effector to the starting position according to the measured distance and the theoretical moving distance;
determining a movement error of the end effector according to the real distance and the target distance;
and generating the feedback signal according to the movement error and the arm movement distance.
6. The method of claim 5, wherein estimating the true distance from the start position to the position point actually reached by the end effector based on the measured distance and the theoretical moving distance comprises:
and performing Kalman filtering on the measured distance and the theoretical moving distance to obtain the real distance of the end effector.
7. The method of claim 1, wherein prior to inputting the first control signal into a robot model, the method further comprises:
acquiring a mass matrix, a damping matrix, a rigidity matrix and an excitation force vector corresponding to the robot;
and establishing the robot model according to the mass matrix, the damping matrix, the rigidity matrix and the excitation force vector.
8. A robot control apparatus, characterized in that the apparatus comprises:
the first acquisition module is used for acquiring the measurement distance from a position point actually reached by an end effector mounted on the arm of the robot to the initial position and the arm movement distance from the position point actually reached by the arm of the robot to the initial position after controlling the arm of the robot to move from the initial position to a target position point according to a first control signal;
the second acquisition module is used for inputting the first control signal into the robot model to obtain the theoretical moving distance of the end effector output by the robot model;
and the control module is used for generating a second control signal according to the measured distance, the arm moving distance, the target distance from the target position point to the starting position and the theoretical moving distance, and controlling an end effector of the robot to align to the target position point according to the second control signal.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. 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 of any one of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115519544A (en) * | 2022-10-10 | 2022-12-27 | 深圳进化动力数码科技有限公司 | Fresh sorting robot grabbing method, device and equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105382843A (en) * | 2015-11-30 | 2016-03-09 | 北京控制工程研究所 | Coordination control method for mechanical arm and operation platform in final stage of grabbing |
| CN107042528A (en) * | 2017-06-01 | 2017-08-15 | 中国科学院宁波材料技术与工程研究所 | A kind of Kinematic Calibration system and method for industrial robot |
| CN107107336A (en) * | 2014-11-18 | 2017-08-29 | 柿子技术公司 | The adaptive place system of robot with end effector location estimation |
| CN109202884A (en) * | 2017-06-30 | 2019-01-15 | 沈阳新松机器人自动化股份有限公司 | A kind of Flexible Multi-joint robot vibration suppressing method and control system |
| CN109352663A (en) * | 2018-09-28 | 2019-02-19 | 航天材料及工艺研究所 | A kind of robot automatic and accurate positioning punching device and method towards composite material bay section |
| CN109884985A (en) * | 2019-03-11 | 2019-06-14 | 上海理工大学 | The measurement method of numerically-controlled machine tool complete machine machining state dynamic characteristic |
| CN110842928A (en) * | 2019-12-04 | 2020-02-28 | 中科新松有限公司 | Visual guiding and positioning device and method for compound robot |
-
2020
- 2020-03-10 CN CN202010160479.0A patent/CN113370203A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107107336A (en) * | 2014-11-18 | 2017-08-29 | 柿子技术公司 | The adaptive place system of robot with end effector location estimation |
| CN105382843A (en) * | 2015-11-30 | 2016-03-09 | 北京控制工程研究所 | Coordination control method for mechanical arm and operation platform in final stage of grabbing |
| CN107042528A (en) * | 2017-06-01 | 2017-08-15 | 中国科学院宁波材料技术与工程研究所 | A kind of Kinematic Calibration system and method for industrial robot |
| CN109202884A (en) * | 2017-06-30 | 2019-01-15 | 沈阳新松机器人自动化股份有限公司 | A kind of Flexible Multi-joint robot vibration suppressing method and control system |
| CN109352663A (en) * | 2018-09-28 | 2019-02-19 | 航天材料及工艺研究所 | A kind of robot automatic and accurate positioning punching device and method towards composite material bay section |
| CN109884985A (en) * | 2019-03-11 | 2019-06-14 | 上海理工大学 | The measurement method of numerically-controlled machine tool complete machine machining state dynamic characteristic |
| CN110842928A (en) * | 2019-12-04 | 2020-02-28 | 中科新松有限公司 | Visual guiding and positioning device and method for compound robot |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115519544A (en) * | 2022-10-10 | 2022-12-27 | 深圳进化动力数码科技有限公司 | Fresh sorting robot grabbing method, device and equipment and storage medium |
| CN115519544B (en) * | 2022-10-10 | 2023-12-15 | 深圳进化动力数码科技有限公司 | Fresh sorting robot grabbing method, device, equipment and storage medium |
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