CN115026820A - Control system and control method for man-machine cooperation assembly robot - Google Patents
Control system and control method for man-machine cooperation assembly robot Download PDFInfo
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- B25J9/00—Programme-controlled manipulators
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Abstract
The invention discloses a control system and a control method of a man-machine cooperation assembly robot, wherein the control system comprises a network main control layer, the network main control layer is in communication connection with a master drive control layer and a slave drive control layer, the master drive control layer and the slave drive control layer receive a control instruction of a PC (personal computer) upper computer and acquire data information of a feedback execution component layer, the master drive control layer and the slave drive control layer are in communication connection with the execution component layer, the execution component layer finishes the whole motion control of the assembly robot, and simultaneously, the execution component layer feeds back the data information; the control method comprises the following steps: the human-computer interaction software interface module and the control cabinet operation panel module receive control instruction information; the force/torque sensor module receives a cooperative control instruction; solving target motion information; calculating the encoder code disc value of the corresponding servo motor; sending a control signal to the motor; the pose of the tail end moving platform is accurately adjusted until the assembly operation is completed, the development difficulty is low, the cost is low, and the portability requirement is met; the real-time performance is high, and the reliability is good; and realizing the self-adaptive control of human-computer cooperative assembly.
Description
Technical Field
The invention belongs to the technical field of assembly robot control, and particularly relates to a man-machine cooperation assembly robot control system and a control method.
Background
The adoption of a man-machine cooperation semi-automatic assembly technology and equipment has important significance for ensuring the assembly quality and improving the assembly efficiency. The root cause of the cooperative robot is closely related to the fact that the traditional industrial robot cannot meet the complicated production and manufacturing requirements. Through man-machine cooperation, the operation quality can be further guaranteed, the comfort of worker operation is improved, the man-machine cooperation safe, flexible and efficient assembly operation is finally realized, and the application requirements of low cost, high efficiency, flexibility and complex operation automation, which are difficult to deal with by a traditional industrial robot, are met.
The software type open structure in the control system type of the present robot is based on a PC, and runs software platform servo control under a computer operating system, thereby realizing the software of the control scheme, having strong openness, meeting diversified requirements of users and having very wide development and application prospects.
However, due to high requirements of the human-machine cooperation assembly operation field on portability, reliability, advanced control technology and the like of the robot system, the control system and the control method of the existing cooperation assembly robot still have the following defects:
first, the development cost is high, and the portability requirement is difficult to meet. According to the robot control system disclosed in patent CN109202722A, a purchased motion control card is selected as a main controller to realize corresponding functions, the control system has a high cost, and meanwhile, the system has a large volume and low convenience.
Secondly, the real-time performance of the system is difficult to ensure, and the reliability is poor. As for the serial communication protocol-based robot control system disclosed in patent CN110757460A, the communication mode is usually performed by polling of the master station, and the real-time performance of the system is seriously affected by the delay characteristic of the system, and the reliability is poor.
Thirdly, an integrated control technology and method of man-machine cooperative assembly are lacked, for example, an admittance control algorithm described in patent CN109249394B realizes cooperative control of the robot based on guiding force and speed only, and an admittance coefficient is selected according to a manner of simply dividing regions, which lacks adaptivity and flexibility.
Disclosure of Invention
The invention is provided for solving the problems in the prior art, and aims to provide a human-computer cooperation assembly robot control system and a control method.
The technical scheme of the invention is as follows: a man-machine cooperation assembly robot control system comprises a network main control layer, wherein the network main control layer is in communication connection with a master drive control layer and a slave drive control layer, the master drive control layer receives and executes a control command of a PC upper computer in the network main control layer and collects data information of a feedback execution component layer, the master drive control layer is in communication connection with an execution component layer, the execution component layer completes assembly robot integral motion control, and meanwhile, the execution component layer feeds back data information.
Furthermore, the network master control layer comprises a human-computer interaction software interface module for realizing human-computer interface interaction, the human-computer interaction software interface module is connected with the PLC master control system module, the PLC master control system module realizes communication connection configuration and data interaction of system hardware and controls the hardware in real time, and the PLC master control system module is connected with the cooperative motion control algorithm module.
Furthermore, the master-slave driving and controlling layer comprises a communication coupling module, the communication coupling module is connected with an input/output module, the input/output module connects external input/output variables to an EtherCAT field bus network, the input/output module is connected with a force/torque sensor module, a driver module and a control cabinet operation panel module, and the driver module realizes high-precision positioning movement of the servo motor, receives and analyzes related instructions of an external control motor and sends control signals to the corresponding motor.
Furthermore, the PC upper computer in the network main control layer is an EtherCAT master station, and the master-slave drive control layer is an EtherCAT slave station.
Furthermore, the driver module is used for high-precision positioning movement of the servo motor, an input port of the driver module receives and analyzes a related instruction of an external control motor, and an output of the driver module sends a control signal to a corresponding driver.
Furthermore, the force/torque sensor module is used for acquiring force/torque information applied by an operator in man-machine cooperation, and the output end of the force/torque sensor module transmits the force/torque information to the input and output module.
Furthermore, the execution component layer comprises a motor, the motor receives control information of the driver and executes the control information, and the motor is connected with the servo motor module.
A control method of a human-computer cooperation assembly robot control system comprises the following steps:
a human-computer interaction software interface module and a control cabinet operation panel module receive control instruction information of an operator;
the force/torque sensor module receives a cooperative control instruction of an operator;
solving target motion information of the robot tail end moving platform according to a corresponding algorithm by the received control instruction information and the received cooperative control instruction;
obtaining the rod length of each branched chain of the robot by a robot mechanism kinematics inverse solution method, and converting to the encoder code wheel value of the corresponding servo motor according to the lead pitch relation of the ball screw;
v, the driver module receives the target value of the encoder according to the currently selected control mode, and sends a control signal to the corresponding motor;
the tail end moving platform of the robot is directly touched and dragged to be close to a target position by an operator, and the pose of the tail end moving platform is further accurately adjusted through a human-computer interaction software interface module and a control cabinet operation panel module according to actual operation conditions until assembly operation is completed;
and in the cooperative assembly period, an operator presses down an emergency stop protection button contained in the human-computer interaction software interface module and the control cabinet operation panel module at any time according to specific working conditions or stops contacting with the force/torque sensor module, so that the robot stops moving.
Furthermore, the PLC master control system module is an ADS server, the cooperative motion control algorithm module is an ADS client, the ADS client sends an ADS request to the ADS server, and the client program stops executing in the communication process until a response returned by the ADS server is obtained.
Furthermore, the cooperative motion control algorithm module comprises a joint space trajectory planning control algorithm and a man-machine cooperative adaptive admittance control algorithm;
the joint space trajectory planning control algorithm is realized based on a trajectory planning control algorithm of cubic polynomial interpolation;
the man-machine cooperation self-adaptive admittance control algorithm is realized based on a machine reinforcement learning variable admittance control algorithm.
The invention has the following beneficial effects:
the invention has small development difficulty, low cost and meets the requirement of portability, the open structure of the invention is clear and reasonable, the operation is simple and convenient, the operation is safe, the space of a motion control card is saved, the cost is reduced, the real-time operation capability is endowed to an upper computer, the integral encapsulation of the system is enhanced by adopting modular thinking, the development difficulty is reduced, data is transmitted through a network cable, and the system is portable.
Compared with the traditional field bus, the invention has high real-time performance and good time certainty, most of the transmitted information is short-frame information, the information exchange is frequent, the fault-tolerant capability is strong, and the reliability is good.
The self-adaptive admittance control algorithm is used for adjusting admittance parameters in real time according to interaction force information acquired by a force/torque sensor arranged at the tail end and information such as robot tail end movement and the like when the system is used for human-computer cooperative assembly operation so as to enhance the flexibility and comfort of cooperation, thereby improving the cooperative assembly efficiency and reducing the labor intensity of workers.
Drawings
FIG. 1 is a block diagram of a system configuration of a control system in the present invention;
FIG. 2 is a block diagram of a human-computer interaction software interface module according to the present invention;
FIG. 3 is a diagram of a robot reinforcement learning algorithm architecture in accordance with the present invention;
FIG. 4 is a block diagram of the variable admittance control algorithm based on machine reinforcement learning according to the present invention;
wherein:
1 network master control layer 2 master-slave driving control layer
3 executive component layer
11 PLC Master control System Module 12 Man-machine interaction software interface Module
13 cooperative motion control algorithm module
21 communication coupling module 22 input/output module
23 force/torque sensor module 24 driver module
25 control cabinet operation panel module 26 driver
27 electric component module
31 motor 32 servo motor module
33 Assembly robot
121 data interaction communication function and 122 robot motion control function
123 information acquisition feedback function
1211 servo driver communication interface
1212 force/moment sensor communication interface
1231 servo motor action information acquisition
1232 force/moment sensor information acquisition and processing
1233 and feeding back the motion information of the end-moving platform of the robot.
Detailed Description
The invention is described in detail below with reference to the figures and examples:
as shown in fig. 1 to 4, a human-computer cooperation assembly robot control system includes a network main control layer 1, the network main control layer 1 is in communication connection with a master-slave drive control layer 2, the master-slave drive control layer 2 receives and executes a control instruction of a PC upper computer in the network main control layer 1 and collects data information fed back to an execution component layer, the master-slave drive control layer 2 is in communication connection with an execution component layer 3, the execution component layer 3 completes the overall motion control of an assembly robot, and the execution component layer 3 feeds back data information.
The network main control layer 1 comprises a human-computer interaction software interface module 12 for realizing human-computer interface interaction, the human-computer interaction software interface module 12 is connected with a PLC main control system module 11, the PLC main control system module 11 realizes communication connection configuration and data interaction of system hardware and controls the hardware in real time, and the PLC main control system module 11 is connected with a cooperative motion control algorithm module 13.
The master-slave driving and controlling layer 2 comprises a communication coupling module 21, the communication coupling module 21 is connected with an input-output module 22, the input-output module 22 connects external input-output variables to an EtherCAT field bus network, the input-output module 22 is connected with a force/torque sensor module 23, a driver module 24 and a control cabinet operation panel module 25, and the driver module 24 realizes high-precision positioning movement of a servo motor, receives and analyzes related instructions of an external control motor and sends control signals to the corresponding motor.
The PC upper computer in the network master control layer 1 is an EtherCAT master station, and the master-slave drive control layer 2 is an EtherCAT slave station.
The driver module 24 is used for high-precision positioning movement of the servo motor, an input port of the driver module 24 receives and analyzes a relevant instruction of an external control motor, and an output of the driver module 24 sends a control signal to a corresponding driver 26.
The force/moment sensor module 23 is used for acquiring force/moment information applied by an operator in man-machine cooperation, and an output end of the force/moment sensor module 23 transmits the force/moment information to the input and output module 22.
The execution component layer 3 comprises a motor 31, the motor 31 receives the control information of the driver 26 and executes the control information, and the motor 31 is connected with a servo motor module 32.
Specifically, the network main control layer 1 is designed and developed based on a control software platform of an upper computer, and specifically comprises four parts, namely a PC upper computer, a PLC main control system module 11, a cooperative motion control algorithm module 13 and a human-computer interaction software interface module 12.
The PC upper computer is an EtherCAT main station and is provided with a Beckhoff TwinCAT3 automatic industrial control software platform.
And a mechanism kinematics forward and backward solution algorithm of the robot is embedded in the PLC master control system module 11.
The cooperative motion control algorithm module 13 is developed and designed based on a Visual Studio software environment, and is used for solving the motion information of the tail end of the robot in real time by the system according to feedback data, and embedding a motion trajectory planning control algorithm and a man-machine cooperative adaptive admittance control algorithm.
The human-computer interaction software interface module 12 is implemented based on an HMI module in a Beckhoff TwinCAT3 platform and is used for human-computer information interaction.
Meanwhile, the PLC master control system module 11, the human-computer interaction software interface module 12 and the cooperative motion control algorithm module 13 are all located in the host station of the PC upper computer, and belong to local communication, and an ADS (automatic Device specification) communication protocol based on TCP/IP is adopted between the TwinCAT3 platform and the Visual Studio software environment for data exchange.
Specifically, the master-slave driving and controlling layer 2 is used for receiving and executing a control instruction of a PC upper computer and collecting data information of a feedback executing component layer, and specifically comprises six parts, namely a communication coupling module 21, an input/output module 22, a driver module 24, a force/torque sensor module 23, a control cabinet operation panel module 25 and an electrical component module 27.
The input/output module 22 connects the external input/output variables to the EtherCAT fieldbus network, and the input/output module 22 specifically includes an analog quantity type module and a digital quantity type module.
The driver module 24 is used for high-precision positioning movement of the servo motor, receiving and analyzing relevant instructions of an external control motor, and sending control signals to the corresponding driver 26.
More specifically, the driver module 24 includes six sets of servo motor drivers.
The force/torque sensor module 23 is used for acquiring force/torque information applied by an operator in human-computer cooperation, and specifically comprises a set of six-dimensional force/torque sensors.
The control cabinet operation panel module 25 is configured to receive an operation command from an operator, and specifically includes control hardware such as a self-locking/self-resetting button, a second-gear/third-gear knob, and the like.
The electrical component module 27 is used for implementing a logic control circuit for perfecting a control hardware system, and includes control hardware such as a contactor, a dc power supply, a dc circuit breaker, an intermediate relay, a wiring terminal, and a cable.
Specifically, the execution component layer 3 is used for the robot to integrally complete motion control and feed back data information, and specifically comprises an assembly robot 33 and a servo motor module 32:
the assembly robot 33 is a six-degree-of-freedom parallel robot, and specifically comprises a movable platform, a static platform and six moving branched chains, wherein each moving branched chain is composed of two spherical hinge moving pairs and a ball screw linear moving pair.
The servo motor module 32 specifically includes six sets of servo motors, and a corresponding motor brake and an absolute encoder.
The human-computer interaction software interface module 12 includes a data interaction communication function 121, a robot motion control function 122, and an information acquisition feedback function 123.
The data interaction communication function 121 includes a servo driver communication interface 1211 and a force/torque sensor communication interface 1212. The servo driver communication interface 1211 and the force/torque sensor communication interface 1212 are communicated with each other.
The information acquisition feedback function 123 comprises servo motor action information acquisition 1231, force/torque sensor information acquisition processing 1232 and robot end moving platform motion information feedback 1233. The method comprises the steps of servo motor action information acquisition 1231, force/torque sensor information acquisition and processing 1232 and robot tail end moving platform motion information feedback 1233, and accordingly data acquisition is achieved.
A control method of a human-computer cooperation assembly robot control system comprises the following steps:
a human-computer interaction software interface module and a control cabinet operation panel module receive control instruction information of an operator;
the force/torque sensor module receives a cooperative control instruction of an operator;
III, solving the target motion information of the robot tail end moving platform according to the received control instruction information and the cooperative control instruction and a corresponding algorithm;
obtaining the rod length of each branched chain of the robot by a robot mechanism kinematics inverse solution method, and converting to the encoder code wheel value of the corresponding servo motor according to the lead pitch relation of the ball screw;
v, the driver module receives the target value of the encoder according to the currently selected control mode, and sends a control signal to the corresponding motor;
the tail end moving platform of the robot is directly touched and dragged to be close to a target position by an operator, and the pose of the tail end moving platform is further accurately adjusted through a human-computer interaction software interface module and a control cabinet operation panel module according to actual operation conditions until assembly operation is completed;
and in the cooperative assembly period, an operator presses down an emergency stop protection button contained in the human-computer interaction software interface module and the control cabinet operation panel module at any time according to specific working conditions or stops contacting with the force/torque sensor module, so that the robot stops moving.
The PLC master control system module is an ADS server, the cooperative motion control algorithm module is an ADS client, the ADS client sends an ADS request to the ADS server, and the client program stops executing in the communication process until a response returned by the ADS server is obtained.
In order to facilitate ADS communication of computer high-level language Visual C + + and environment thereof, Beckhoff TwinCAT3 provides a TcAdsDll.dll component, and files required for carrying out linking and program development in the Visual C + + specifically comprise a dynamic link library TcAdsDll.dll, a function library TcAdsDll.lib, a head file TcAdADS pi.h for declaring a structure and a head file TcAdsDef.h for declaring a constant.
Specifically, the control system adopts an ADS communication synchronous read-write mode, and can immediately return a data interaction result. The PLC main control system module 11 is used as an ADS server, the cooperative motion control algorithm module 13 is used as an ADS client, the ADS client sends an ADS request to the ADS server, and the client program stops executing in the communication process until a response returned by the ADS server is obtained.
Meanwhile, the ADS client and the ADS server are both designed in the same PC upper computer and belong to local communication.
The PLC master control system module 11 and the cooperative motion control algorithm module 13 perform data information interaction, and the specific process is as follows:
a. the port variable, port address variable, and AMS address variable are defined in a Visual Studio environment.
b. And opening an ADS communication port by calling an AdsPortOpen () instruction, and calling an AdsGetLocalAddress () instruction to automatically acquire a local address, thereby establishing communication between the PLC main control system module 11 and the cooperative motion control algorithm module 13.
c. The port address pointer is pointed to the 851 port of TwinCAT 3.
d. Creating a handle variable in a Visual Studio environment, and defining a control system variable to be read/written and a character string variable corresponding to the control system variable.
e. The method comprises the steps of synchronously writing data to an ADS server and receiving data from ADS equipment by calling an AdsSyncReadWriteReq () instruction, and automatically generating a handle size corresponding to a variable according to the ADS server address and a control system variable needing to be read/written.
f. Data may be read synchronously from the ADS server by calling the AdsSyncReadReq () instruction.
g. Data can be synchronously written to the ADS server by calling the adssyncwrite req () instruction.
Specifically, the cooperative motion control algorithm module 13 specifically includes a joint space trajectory planning control algorithm and a human-machine cooperative adaptive admittance control algorithm.
The joint space trajectory planning control algorithm is realized based on a trajectory planning control algorithm of cubic polynomial interpolation, and the man-machine cooperation self-adaptive admittance control algorithm is realized based on a variable admittance control algorithm of machine reinforcement learning.
Specifically, the joint space trajectory planning control algorithm comprises the following steps:
a. the control system receives an operator control instruction according to the selected current working mode to obtain the pose information of the key point process of the assembly robot terminal moving platform central point expected to reach the target point;
b. through a mechanism kinematics inverse solution algorithm embedded in the PLC master control system module 11, the key point pose information of the tail end operation space is sequentially resolved into joint space path point information corresponding to the six motors, so that the motors are ensured to run smoothly without impact.
c. And each motor performs track interpolation based on a cubic polynomial interpolation track planning algorithm according to the path point information of the corresponding joint space key to obtain the motion position, speed and acceleration curve of the motor in the motion process.
d. The servo motors work in a position control mode, and the positions, which need to be reached by the motors at each period moment, are sent in real time according to the clock period of the operation of the PLC master control system module 11 until the tail end movable platform moves to an expected target point.
Specifically, the man-machine cooperation self-adaptive admittance control algorithm comprises the following steps:
a. inputting the information of the speed change rate and the information of the human-computer interaction force and the interaction force change rate of the terminal six-dimensional force/torque sensor as observable states into a reinforcement learning controller according to the speed information and the speed change rate information of the central point of the terminal movable platform of the robot;
b. adjusting the damping value of the output admittance parameter in real time based on the selected machine reinforcement learning algorithm according to the Markov decision process regulated by the variable admittance parameter, and transmitting the parameter value to a system admittance controller;
c. calculating to obtain cooperative displacement, speed and acceleration information of a central point of the tail end moving platform under the action of human-computer interaction force according to the admittance controller;
d. and the cooperative displacement, speed and acceleration information are used as the input of a robot control system to control the robot to move, so that the cooperative assembly operation is completed.
Yet another embodiment
As shown in fig. 1, a control system of a human-computer cooperation assembly robot includes a network main control layer 1, a master-slave drive control layer 2, and an execution component layer 3.
The network main control layer 1 is designed and developed based on an upper computer industrial control software platform and specifically comprises a PC upper computer main station, a PLC main control system module 11, a cooperative motion control algorithm module 13 and a human-computer interaction software interface module 12:
the PC host computer station is provided with a Beckhoff TwinCAT3 automatic industrial control software platform, and the PC kernel is a Windows10 operating system and needs to be inserted with a network card supported by TwinCAT 3.
The PLC master control system module 11 is realized based on a TwinCAT3 industrial control platform, is used for realizing communication connection configuration and data interaction of system hardware resources, simultaneously realizes real-time control on the hardware resources, adopts a distributed clock technology to realize motion control and IO control functions, is a master control core of a robot system, and is internally embedded with a mechanism kinematics forward and inverse solution algorithm of a robot.
The cooperative motion control algorithm module 13 is realized based on a Visual Studio software environment, is used for solving the motion information behind the robot in real time according to feedback data by the system, is embedded with a motion track planning control algorithm and a man-machine cooperative adaptive admittance control algorithm, and automatically runs/stops along with the start/close of the whole control system.
The human-computer interaction software interface module 12 is realized based on an HMI module in a Beckhoff TwinCAT3 platform and is used for human-computer information interaction, an operator clicks and touches the software interface to enable the whole system of the robot to be powered on, and different working modes of the robot are selected according to a logic algorithm controlled by a motion trail, so that the robot is controlled to perform assembly operation better. Meanwhile, the motion information of the robot can be collected in real time and recorded and fed back, so that an operator can conveniently evaluate and judge the progress condition of the assembly process.
Meanwhile, the PLC master control system module 11, the cooperative motion control algorithm module 13 and the human-computer interaction software interface module 12 are all located in a PC host station and belong to local communication, and an ADS (automatic Device specification) communication protocol based on TCP/IP is adopted between the TwinCAT3 platform and the Visual Studio software environment for data exchange.
The master-slave driving and controlling layer 2 is used for receiving and executing a control instruction of a PC upper computer and collecting data information of a feedback executing component layer, and specifically comprises a communication coupling module 21, an input-output module 22, a driver module 24, a force/torque sensor module 23, a control cabinet operation panel module 25 and an electrical component module 27.
The communication coupling module 21 is used for coupling a plurality of input and output modules together and jointly accessing an EtherCAT field bus network, and the communication coupling module 21, the input and output module 22 and other connected control system hardware can be regarded as an EtherCAT slave station, so that the electric wiring is simplified, and the space of a control cabinet is saved.
The input/output module 22 is configured to connect an external input/output variable to the EtherCAT fieldbus network, so as to perform input data processing and output instruction issuing in the PLC main control system module 11, and specifically includes an analog quantity type module and a digital quantity type module.
The driver module 24 is used for positioning movement of the servo motor with high precision, receiving and analyzing related instructions of an external control motor, sending motor control signals to the corresponding motor, adopting an absolute encoder as a speed measuring sensor, and controlling the servo motor through three control modes of position, speed and moment, and specifically comprising six sets of servo motor drivers.
Meanwhile, based on an EtherCAT bus communication protocol, a host station of a PC upper computer in a network master control layer is sequentially connected with a communication coupling module 21, an input/output module 22 and a driver module 24 in a master/slave drive control layer through a network cable, and a bus type topological structure is adopted.
The force/torque sensor module 23 is used for acquiring force/torque information applied by an operator during man-machine cooperation, and converting an analog quantity signal into a digital quantity signal through an embedded data acquisition system, so that corresponding processing is performed in a network main control layer, man-machine cooperation control is realized, and the force/torque sensor module specifically comprises a set of six-dimensional force/torque sensors.
Meanwhile, the input/output module 22 is connected with the force/torque sensor module 23 for performing input data acquisition on a force/torque signal applied by an operator.
The control cabinet operation panel module 25 is used for receiving an operation instruction of an operator, can realize the same function as the human-computer interaction software interface module 12, is used synchronously with a software interface or independently used to complete the motion control of the robot, and specifically comprises control hardware such as a self-locking/self-resetting button, a second-gear/third-gear knob and the like.
Meanwhile, the input/output module 22 is connected to the devices included in the control cabinet operation panel module 25, and performs input acquisition and output control on the devices.
The electrical component module 27 is used for implementing a logic control circuit for perfecting a control hardware system, and includes control hardware such as a contactor, a dc power supply, a dc circuit breaker, an intermediate relay, a wiring terminal, and a cable.
The execution component layer 3 is used for the robot to integrally complete the motion operation and feed back information to other two layers, and specifically comprises an assembly robot 33 and a servo motor module 32:
the assembly robot 33 is a six-degree-of-freedom parallel robot, and specifically comprises a movable platform, a static platform and six moving branched chains, wherein each moving branched chain is composed of two spherical hinge moving pairs and a ball screw linear moving pair.
The servo motor module 32 specifically includes six sets of servo motors, and a corresponding motor brake and an absolute encoder.
Meanwhile, the servo motor module 32 is installed at the bottom end of the six moving branch chain linear motion pairs of the assembly robot and is connected with the spherical hinge motion pair fixedly connected with the static platform through the external frame of the motor, and the other end of the linear motion pair is connected with the spherical hinge motion pair fixedly connected with the movable platform.
As shown in fig. 2, the functional structure of the human-computer interaction software interface module 12 includes a data interaction communication function 121, an information acquisition feedback function 123 and a robot motion control function 122.
The data interaction communication function 121 includes: servo driver communication interface 1211, force/torque sensor communication interface 1212.
The information collection feedback function 123 includes: and acquiring action information of the servo motor 1231. Force/moment sensor information acquisition and processing 1232, and robot end moving platform motion information feedback 1233.
The robot motion control function 122 includes: the method comprises the following steps of robot initial pose zeroing, system enabling/disabling, robot space axis single-degree-of-freedom stepping control, robot space axis single-degree-of-freedom inching control, system scram and space trajectory planning control.
As shown in fig. 3, the variable admittance control method based on machine reinforcement Learning of the present invention, specifically based on Deep Q-Learning Network (hereinafter abbreviated as DQN) algorithm, includes the following steps:
a. acquiring the interaction force F acquired by the force/torque sensor module 23 h Information, and interaction force change rate dF obtained through processing of an upper computer h And information, the moving speed V of the central point of the movable platform at the tail end of the robot and the dV information of the change rate of the moving speed are established for the human-computer cooperation control environment.
b. And constructing a Markov Decision Process (MDP) of the variable admittance parameters in the man-machine cooperation assembly process, wherein the MDP specifically comprises a state space, an action space and a reward function.
First, a state space of the assembly robot is determined, wherein the current state s is defined by the interaction force F h Rate of change of interaction dF h The speed V of the center point of the movable platform and the speed change rate dV.
Secondly, determining an action space of man-machine cooperation, and selecting a discrete action a according to a trained decision network, wherein the action space is discrete into four actions of increasing a damping value in a small amplitude, decreasing the damping value in the small amplitude, increasing the damping value in a large amplitude and decreasing the damping value in the large amplitude.
And finally, determining a reward function, and defining an instantaneous reward function r as the inverse number of the square of the change rate of the motion acceleration of the central point of the robot tail end movable platform obtained by real-time calculation.
c. Given the starting reference damping value, the spatial pose information of the starting point and the target point, the Batch size (Batch _ size), the Learning rate (Learning _ rate), the number of training times (Episode), the attenuation factor (Gamma), the value of the Memory playback unit size (Memory _ size) and the number of layers of the neural network of the DQN algorithm are set.
d. According to the current state s, an approximation function Q (s, a; theta) is obtained by using a neural network of the current value, then an action a is selected according to an Epsilon-Greedy strategy, the robot feeds back an instantaneous reward r based on the action during the movement, and the system enters the next state s', wherein the process is one step;
e. storing experience sample data (s, a, r, s') of each time step into an experience pool memory playback unit, randomly extracting batch sample data from the experience pool memory playback unit for updating network parameters of a current value during network training, breaking the relevance among data, and solving the problem of non-static distribution, wherein a DQN error function is updated by adopting a gradient descent method, which is specifically represented as:
L(θ)＝E[(r+γmax a Q(s′,a′；θ)-Q(s,a；θ)) 2 ]
copying the parameters of the current value network to a target value network every N time steps;
f. and finally, iterating the target value network until convergence according to the MDP process of the variable admittance parameters and a termination condition, and finishing training.
As shown in fig. 4, the variable admittance control process based on machine reinforcement learning specifically includes the following steps:
a. in the admittance control outer ring, the interaction force F acquired according to the force/torque sensor module h Interaction force change rate dF obtained by information and data processing h Information, resolving the obtained movement speed V and movement speed change rate dV information of the central point of the robot tail end movable platform as environment input items for reinforcement learning;
b. adjusting an output admittance parameter damping value B in real time based on a DQN algorithm according to the MDP process of variable admittance parameter adjustment, and transmitting the parameter value to an admittance controller designed by the system;
c. calculating cooperative displacement, speed and acceleration information generated by the central point of the tail end moving platform under the action of human-computer interaction according to the admittance controller;
d. optionally, the admittance model expression is:
wherein the content of the first and second substances,
respectively a Cartesian space target reference track position, a speed and an acceleration preset for the robot,
respectively receiving the actual track position, speed and acceleration of the Cartesian space target after the interaction force is applied by the operator for the robot,
for the interaction force information collected by the force/torque sensor module,
and respectively assembling the inertia, damping and rigidity diagonal matrixes of the robot admittance model in a cooperative manner.
Under the man-machine cooperation assembly working condition, the actual motion track of the robot is the target track, and the robot does not return to the initial pose after an operator removes the man-machine interaction force, namely the rigidity diagonal matrix can be eliminated, so that the admittance model expression is transformed into:
e. and the cooperative displacement, speed and acceleration information is used as the input of a position control inner ring of the robot control system, and is transmitted to the TwinCAT3 controller to calculate the control instruction of the servo motor, so as to control the assembly robot to finish the movement.
The invention has small development difficulty, low cost and meets the requirement of portability, the open structure of the invention is clear and reasonable, the operation is simple and convenient, the operation is safe, the space of a motion control card is saved, the cost is reduced, the real-time operation capability is endowed to an upper computer, the integral encapsulation of the system is enhanced by adopting modular thinking, the development difficulty is reduced, data is transmitted through a network cable, and the system is portable.
Compared with the traditional field bus, the invention has high real-time performance and good time certainty, most of the transmitted information is short-frame information, the information exchange is frequent, the fault-tolerant capability is strong, and the reliability is good.
The self-adaptive admittance control algorithm is used for adjusting admittance parameters in real time according to interaction force information acquired by a force/torque sensor arranged at the tail end and information such as robot tail end movement and the like when the system is used for human-computer cooperative assembly operation so as to enhance the flexibility and comfort of cooperation, thereby improving the cooperative assembly efficiency and reducing the labor intensity of workers.
Claims (10)
1. A man-machine cooperation assembly robot control system comprises a network main control layer (1), and is characterized in that: the network main control layer (1) is in communication connection with the master-slave drive control layer (2), the master-slave drive control layer (2) receives and executes a control instruction of a PC upper computer in the network main control layer (1) and collects data information of the feedback execution component layer, the master-slave drive control layer (2) is in communication connection with the execution component layer (3), the execution component layer (3) completes the whole motion control of the assembly robot, and the execution component layer (3) feeds back the data information.
2. A human-machine cooperative assembling robot control system according to claim 1, wherein: the network main control layer (1) comprises a human-computer interaction software interface module (12) for realizing human-computer interface interaction, the human-computer interaction software interface module (12) is connected with a PLC main control system module (11), the PLC main control system module (11) realizes communication connection configuration and data interaction of system hardware and controls the hardware in real time, and the PLC main control system module (11) is connected with a cooperative motion control algorithm module (13).
3. A human-machine cooperation assembly robot control system as claimed in claim 1, wherein: the master-slave driving and controlling layer (2) comprises a communication coupling module (21), the communication coupling module (21) is connected with an input-output module (22), the input-output module (22) connects external input-output variables to an EtherCAT field bus network, the input-output module (22) is connected with a force/torque sensor module (23), a driver module (24) and a control cabinet operation panel module (25), and the driver module (24) realizes high-precision positioning movement of a servo motor, receives and analyzes related instructions of an external control motor and sends control signals to the corresponding motor.
4. A human-machine cooperation assembly robot control system as claimed in claim 1, wherein: the PC upper computer in the network main control layer (1) is an EtherCAT master station, and the master and slave drive control layers (2) are EtherCAT slave stations.
5. A human-machine cooperation assembly robot control system as claimed in claim 3, wherein: the driver module (24) is used for high-precision positioning movement of the servo motor, an input port of the driver module (24) receives and analyzes a related instruction of an external control motor, and an output of the driver module (24) sends a control signal to a corresponding driver (26).
6. A human-machine cooperation assembly robot control system as claimed in claim 3, wherein: the force/torque sensor module (23) is used for acquiring force/torque information applied by an operator in man-machine cooperation, and the output end of the force/torque sensor module (23) transmits the force/torque information to the input and output module (22).
7. A human-machine cooperative assembling robot control system according to claim 1, wherein: the execution component layer (3) comprises a motor (31), the motor (31) receives control information of the driver (26) and executes the control information, and the motor (31) is connected with the servo motor module (32).
8. A control method of a human-computer cooperation assembly robot control system is characterized in that: the method comprises the following steps:
the method comprises the following steps that (i) a man-machine interaction software interface module and a control cabinet operation panel module receive control instruction information of an operator;
(ii) the force/torque sensor module receives a coordinated control command from an operator;
(iii) the received control instruction information and the cooperative control instruction are used for calculating the target motion information of the robot tail end moving platform according to the corresponding algorithm;
(vi) obtaining the rod length of each branched chain of the robot by a robot mechanism kinematics inverse solution method, and converting to the encoder code wheel value of the corresponding servo motor according to the lead pitch relation of the ball screw;
(v) the driver module receives the target value of the encoder according to the currently selected control mode, and sends a control signal to the corresponding motor;
(vi) dragging the tail end moving platform of the robot to be close to a target position through direct contact of an operator, and further accurately adjusting the pose of the tail end moving platform through a human-computer interaction software interface module and a control cabinet operation panel module according to actual operation conditions until assembly operation is completed;
(vii) during cooperative assembly, the operator presses down the scram protection button included in the human-computer interaction software interface module and the control cabinet operation panel module at any time according to specific working conditions, or stops contacting with the force/torque sensor module, so that the robot stops moving.
9. The control method of a human-machine cooperation assembling robot control system according to claim 8, characterized in that: the PLC master control system module is an ADS server, the cooperative motion control algorithm module is an ADS client, the ADS client sends an ADS request to the ADS server, and the client program stops executing in the communication process until a response returned by the ADS server is obtained.
10. The control method of a human-machine cooperation assembling robot control system according to claim 8, characterized in that:
the cooperative motion control algorithm module comprises a joint space trajectory planning control algorithm and a man-machine cooperative adaptive admittance control algorithm;
the joint space trajectory planning control algorithm is realized based on a trajectory planning control algorithm of cubic polynomial interpolation;
the man-machine cooperation self-adaptive admittance control algorithm is realized based on a machine reinforcement learning variable admittance control algorithm.
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