WO2015101088A1

WO2015101088A1 - Intelligent control method, device and system for multi-joint mechanical arm

Info

Publication number: WO2015101088A1
Application number: PCT/CN2014/089443
Authority: WO
Inventors: 代晴华; 谭凌群; 蒲东亮; 武利冲
Original assignee: 三一汽车制造有限公司
Priority date: 2013-12-31
Filing date: 2014-10-24
Publication date: 2015-07-09
Also published as: CN103955231B; CN103955231A

Abstract

An intelligent control method, device and system for a multi-joint mechanical arm. The intelligent control method for the multi-joint mechanical arm comprises: receiving a velocity vector, input by a manipulator, of a tail end of the mechanical arm (S11); performing trajectory prediction on each knuckle arm of the multi-joint mechanical arm on the basis of the velocity vector of the tail end of the mechanical arm (S12); determining an optimal planning solution on the basis of the motion restraint and trajectory prediction result of the multi-joint mechanical arm (S13); determining the oil cylinder driving quantity of each knuckle arm according to the optimal planning solution (S14); and determining, according to a proportional feature of the oil cylinder driving quantity and an execution mechanism, a driving current used for driving rotation of a multi-joint arm rest and a rotating tower (S15). The control method, device and system can improve the control precision of the multi-joint mechanical arm, ensure the stable motion of the arm rest and reduce the complexity of the manipulation.

Description

Multi-joint mechanical arm intelligent control method, device and system

The present application claims priority to Chinese Patent Application No. 201310749595.6, entitled "Multi-joint Manipulator Intelligent Control Method, Apparatus and System" on December 31, 2013, the entire contents of which are incorporated by reference. In this application.

Technical field

The invention relates to the field of engineering machinery, in particular to a multi-joint mechanical arm intelligent control method, device and system.

Background technique

The multi-joint ultra-long boom is a nonlinear coupling system. As the length of the boom increases and the number of joints increases, the difficulty of control is gradually increased, making it difficult to accurately control. How to reduce the labor intensity and handling complexity of the multi-joint ultra-long boom has become a difficult problem to be solved by those skilled in the art.

Summary of the invention

In view of this, the present invention provides a multi-joint mechanical arm intelligent control method, device and system to further improve the control precision of the multi-joint mechanical arm and reduce the complexity of the manipulation.

In a first aspect, the present invention discloses a multi-joint robot arm intelligent control method, which includes the following steps:

Step S11, receiving a velocity vector of the end of the robot arm input by the manipulator; step S12, performing trajectory prediction on each of the articulated arms of the multi-joint robot based on the velocity vector of the end of the arm and the state of the current arm; If the obtained motion trajectory of the next moment is abrupt with respect to the current time, the result of the trajectory prediction is discarded; and in step S13, the optimal planning solution is determined based on the motion constraint of the multi-joint robot arm and the result of the trajectory prediction; step S14, according to The optimal planning solution determines the cylinder driving amount of each of the pitch arms; and in step S15, determines a driving current according to the cylinder driving amount and the proportional characteristic of the actuator, and the driving current is used to drive the multi-joint boom and the turret The turn.

Further, in the above-described multi-joint robot arm intelligent control method, in the step S13, the motion constraint is a hydraulic system flow extreme value constraint, and the optimal planning solution is a planning solution with a minimum system flow cost.

Further, in the above-described multi-joint robot arm intelligent control method, after step S15, further comprising step S16, detecting a state parameter of the driven multi-joint boom, and feeding back the state parameter of the multi-joint boom to the step S12. The result of the trajectory prediction is jointly determined according to the velocity vector of the input end of the arm and the state parameter of the multi-joint boom.

Further, in the above-described multi-joint robot arm intelligent control method, the step S16 further includes the following sub-steps: performing signal filtering and deformation compensation on the acquired state parameters of the multi-joint boom, and feeding back the obtained result to the Step S12 is described.

The working principle of the multi-joint mechanical arm intelligent control method of the present invention is as follows: the trajectory prediction of the boom is performed based on the end speed of the mechanical arm outputted to the controller and the current posture of each articulated arm; and the optimal planning solution is determined based on the prediction result and the constraint, and further Determine the driving amount ΔL of each articulated arm; finally, according to the proportional relationship between the driving amount ΔL and the current i (current i is the actuator driving characteristic, that is, the magnitude of the current i determines the actuator driving capability, which determines the speed of the cylinder driving amount Size), accurately determine the drive current required to drive the boom, thereby achieving high-precision control of the multi-joint manipulator; and, as the trajectory prediction is made, if the predicted trajectory of the next moment occurs relative to the current moment If the mutation is made, the result of the trajectory prediction is discarded. Therefore, this kind of motion trend-based prediction can ensure that the movement state of the boom does not abruptly in the case of small amplitude motion, that is, the smooth motion of the boom can be well ensured. In addition, for the present invention, the controller only needs to input the speed of the end of the arm through the speed input device, which is the controller's willingness to control the end of the boom, and can realize the action of the boom by completing the above steps. Control, therefore, is simple and easy, greatly reducing the complexity of the manipulation.

In a second aspect, the present invention also discloses a multi-joint robot arm intelligent control device, comprising: a velocity vector receiving unit, a trajectory prediction unit, an optimal planning solution determining unit, a cylinder driving amount calculating unit, and a driving current calculating unit. Wherein the speed vector receiving unit is configured to receive a velocity vector of the end of the robot arm input by the manipulator; the trajectory predicting unit is configured to perform each section of the multi-joint robot arm based on the velocity vector of the end of the arm and the state of the current arm The arm performs trajectory prediction, and if the predicted trajectory of the next moment is abrupt with respect to the current moment, the result of the trajectory prediction is abandoned; the optimal planning solution determining unit is used for the motion based on the multi-joint robot Determining an optimal planning solution by the result of the beam and the trajectory prediction; the cylinder driving amount calculating unit is configured to determine a cylinder driving amount of each of the pitch arms according to the optimal planning solution; and the driving current calculating unit is configured to use the driving amount of the cylinder and The proportional characteristic of the actuator determines the drive current, which is used to drive the rotation of the multi-joint boom and the turret.

Further, in the above-described multi-joint robot arm intelligent control device, in the optimal planning solution determining unit, the motion constraint is a hydraulic system flow extreme value constraint, and the optimal planning solution is a planning solution with a minimum system flow cost.

Further, the multi-joint robot arm intelligent control device further includes a feedback unit configured to detect a state parameter of the driven multi-joint boom and feed back the state parameter of the multi-joint boom to the a trajectory prediction unit that further determines a prediction result according to the input velocity vector of the end of the robot arm and the state parameter of the multi-joint boom.

Further, the feedback unit of the multi-joint robot arm intelligent control device further includes a signal filtering and deformation compensation sub-unit for performing signal filtering and deformation compensation on the acquired state parameters of the multi-joint boom.

The multi-joint robot arm intelligent control device of the present invention works as follows: the trajectory prediction of the boom is performed based on the end speed of the arm output to the controller and the current posture of each articulated arm. Based on the prediction results and constraints, the optimal planning solution is determined, and then the driving amount ΔL of each articulated arm is determined. Finally, according to the proportional relationship between the driving amount ΔL and the current i, the driving current required to drive the boom is accurately determined, thereby implementing multiple joints. High precision control of the robot arm. Further, since the trajectory prediction is performed, if the predicted motion trajectory at the next time is abrupt with respect to the current time, the result of the trajectory prediction is discarded. Therefore, this kind of motion trend-based prediction can ensure that the movement state of the boom does not abruptly in the case of small amplitude motion, that is, the smooth motion of the boom can be well ensured. In addition, for the present invention, the controller only needs to input the speed of the end of the arm through the speed input device, which is the controller's willingness to control the end of the boom, and can realize the action of the boom by completing the above steps. Control, therefore, is simple and easy, greatly reducing the complexity of the manipulation.

In a third aspect, the present invention also discloses a multi-joint mechanical arm intelligent control system, comprising the above-mentioned multi-joint mechanical arm intelligent control device, and a manipulator matched with the multi-joint mechanical arm intelligent control device, the manipulation The device is used to input the velocity vector at the end of the arm.

Further, in the above-described multi-joint robot arm intelligent control system, the manipulator is a universal handle.

Since the multi-joint mechanical arm intelligent control system includes the above-described multi-joint mechanical arm intelligent control device, the multi-joint mechanical arm intelligent control system also has the technical effect of the multi-joint mechanical arm intelligent control device. Since the structure and effect of the multi-joint robot arm intelligent control device have been described, the present invention will not be described herein.

DRAWINGS

1 is a flow chart showing the steps of a first embodiment of a multi-joint robot arm intelligent control method according to the present invention;

2 is a flow chart showing the steps of a second embodiment of the intelligent control method for a multi-joint robot arm according to the present invention;

3 is a structural block diagram of an embodiment of a multi-joint mechanical arm intelligent control device according to the present invention;

4 is a structural block diagram of a preferred embodiment of the multi-joint robot arm intelligent control device of the present invention;

FIG. 5 is a structural block diagram of an embodiment of a multi-joint robot arm intelligent control system according to the present invention.

detailed description

It should be noted that the embodiments in the present invention and the features in the embodiments may be combined with each other without conflict. The invention will be described in detail below with reference to the drawings in conjunction with the embodiments.

Referring to FIG. 1, FIG. 1 is a flow chart of steps of a first embodiment of a multi-joint robot arm intelligent control method according to the present invention. This embodiment includes the following five steps:

Step S11, receiving a velocity vector of the end of the robot arm input by the manipulator.

For a pump truck, the end of the boom refers to the end of the last boom, the delivery hose end of the pump truck. The manipulator can be a manipulator with a universal handle whose input directly reflects the controller's willingness to control the end of the boom, ie the speed and direction at which the end of the boom is desired.

Step S12, based on the velocity vector at the end of the arm and the state of the current boom, trajectory prediction is performed on each of the joint arms of the multi-joint robot; if the predicted motion trajectory at the next moment is abrupt with respect to the current moment, the discard is discarded. The result of the trajectory prediction. Here, the meaning of "mutation" is the incoherence of the boom movement, or the boom motion "repetition", suddenly crossing from one state to another, rather than a gradual change.

The state of the current boom mainly refers to the angle parameter of each section arm. Master of trajectory prediction If the end of the boom is to reach the speed V at the next moment and the state of the current moment, or the attitude θ of the boom. Trajectory prediction based on velocity V and attitude θ, and the results of trajectory prediction are known to those skilled in the art, and there are many methods, and the cost of implementation of different methods is different. The core of the invention is not here.

In this step, it should be noted that if the predicted motion trajectory at the next moment is abrupt with respect to the current time, the result of the trajectory prediction is discarded. This is based on the following considerations: things in nature are continuous, non-continuous things do not exist, objects are mass, mass has inertia, discontinuity is the state of motion of the object to be changed, frequent Changing the motion state of an object, the entire system is unstable, and unstable systems are prohibited in control. Corresponding to the movement of the pitch arm of the pump truck, the movement tendency of the pitch arm does not allow "repetition (ie, abrupt change)" to ensure the smoothness of the movement of the arm.

Step S13, determining an optimal planning solution based on the results of the motion constraint and the trajectory prediction of the multi-joint robot. There are many ways to predict the trajectory. The cost of different methods is different. The constraint is to find the conditions for obtaining the optimal planning result. In the specific implementation, the optimal programming solution here may be the attitude Δθ of each joint arm.

In step S14, the cylinder driving amount of each pitch arm is determined according to the optimal planning solution Δθ.

The length and attitude (angle) of each pitch arm have a specific paradigm relationship L = S (θ). Now that Δθ has been obtained, the driving amount ΔL of each articulated arm can be obtained by calculation.

In addition, it should be noted that the constraint relationship of the link mechanism has a derivation relationship, and only a paradigm is provided. In the specific implementation, the specific form and value only need geometry and derivation and calculation, and those skilled in the art That is, it is known, and no further explanation will be given here.

In step S15, the driving current is determined according to the driving amount of the cylinder and the proportional characteristic of the actuator, and the driving current is used to drive the rotation of the multi-joint boom and the turret.

The working principle of the joint robot arm intelligent control method of the present embodiment is as follows: the trajectory prediction of the boom is performed based on the end speed of the arm output to the controller and the current posture of each arm. Based on the prediction result and the constraint, the optimal planning solution is determined, and then the driving amount ΔL of each arm is determined. Finally, according to the proportional relationship between the driving amount ΔL and the current i, the driving current required to drive the boom is accurately determined, thereby implementing multiple joints. High precision control of the robot arm.

Further, since the trajectory prediction is performed, if the predicted motion trajectory at the next time is abrupt with respect to the current time, the result of the trajectory prediction is discarded. Therefore, this is based on The prediction of the movement trend can ensure that the movement state of the boom does not abruptly change under the condition of small amplitude motion, that is, the smooth movement of the boom can be well ensured.

In addition, for the embodiment, the controller only needs to input the speed of the end of the arm through the speed input device, and the speed is the controller's willingness to control the end of the arm frame, and the arm frame action can be realized by completing the above steps. The control, therefore, is simple and easy, greatly reducing the complexity of the manipulation.

Referring to FIG. 2, FIG. 2 is a flow chart of steps of a second embodiment of a multi-joint robot arm intelligent control method according to the present invention, including the following steps:

Step S21, receiving the velocity vector v of the end of the robot arm input by the manipulator;

Step S22, based on the velocity vector at the end of the robot arm and the state of the current robot arm, performing trajectory prediction on each of the joint arms of the multi-joint robot; if the predicted motion trajectory at the next moment is abrupt with respect to the current moment, then discarding the The result of the trajectory prediction.

Step S23, based on the results of the hydraulic system flow Q extreme value constraint and the trajectory prediction of the multi-joint manipulator, determine the optimal planning solution, that is, the optimal planning solution is the planning solution with the lowest system flow Q cost.

The hydraulic system flow Q is the most important constraint parameter of the engineering machinery of the pump truck. This constraint is not established and the structure is difficult to implement according to the control idea. Therefore, system traffic constraints must be within the achievable range.

Using the motion planning based on the minimum cost constraint, the end point is the fastest under the same conditions. Because the size of the cylinder corresponding to each section arm is different, the cylinder corresponding to the end point is the smallest. Therefore, moving the same distance, the amount of oil required at the end of the boom is the smallest. From another angle, the end point is the fastest under the same conditions.

Step S24, determining the cylinder driving amount of each pitch arm according to the optimal planning solution;

Step S25, determining a driving current according to the driving amount of the cylinder and the proportional characteristic of the actuator, and the driving current is used for driving the rotation of the multi-joint boom and the turret;

Step S26, detecting the state parameter of the driven multi-joint boom, and feeding back the state parameter of the multi-joint boom to step S22, the result of the trajectory prediction is based on the input speed vector of the arm end and the state of the multi-joint boom The parameters are determined together.

And, step S26 further includes the following sub-steps, sub-step S261, performing signal filtering and deformation compensation on the acquired state parameters (attitudes) of the multi-joint boom, and feeding back the obtained results. Go to step S22.

Among them, the detection of the state parameter (attitude) of the multi-joint boom can be obtained by a cylinder displacement sensor or a rotary encoder.

It can be seen that, in this embodiment, the step S26 and its sub-step S261 are added, that is, the closed-loop constant current driving is adopted, and the control precision is further higher, and the signal filtering and the deformation compensation further improve the control precision.

In a second aspect, the present invention also discloses an embodiment of a multi-joint mechanical arm intelligent control device, with reference to FIG. 3.

The multi-joint robot arm intelligent control device embodiment includes a speed vector receiving unit 31, a trajectory predicting unit 32, an optimal plan solution determining unit 33, a cylinder driving amount calculating unit 34, and a driving current calculating unit 35.

The working principle of each unit will be described in more detail below.

The speed vector receiving unit 31 is for receiving a velocity vector of the end of the robot arm input by the manipulator. For a pump truck, the end of the boom refers to the end of the last boom, the delivery hose end of the pump truck. The manipulator can be a manipulator with a universal handle whose input directly reflects the controller's willingness to control the end of the boom, ie the speed and direction at which the end of the boom is desired.

The trajectory prediction unit 32 is configured to perform trajectory prediction on each of the joint arms of the multi-joint robot based on the velocity vector at the end of the arm and the state of the current arm, and if the predicted trajectory of the next moment is abrupt with respect to the current moment, Then the result of the trajectory prediction is discarded.

The state of the current boom mainly refers to the angle parameter of each articulated arm. The trajectory prediction is mainly based on the speed V to be reached at the next moment of the boom end and the state at the current time, or the attitude θ of the boom. It is well known to those skilled in the art to perform trajectory prediction based on velocity V and attitude θ, and it is known to those skilled in the art that there are many methods, and the cost of implementation of different methods is different. The core of the invention is not here.

In this step, it should be noted that if the predicted motion trajectory at the next moment is abrupt with respect to the current time, the result of the trajectory prediction is discarded. This is based on the following considerations: things in nature are continuous, non-continuous things do not exist, objects are mass, mass has inertia, discontinuity is the state of motion of the object to be changed, frequent Changing the motion state of an object, the entire system is unstable, and unstable systems are prohibited in control. Corresponding to the movement of the boom of the pump truck, the movement trend of the boom arm does not allow "repetition" (ie "mutation") One form) to ensure the smoothness of the movement of the arm.

The optimal plan solution determining unit 33 is configured to determine an optimal plan solution based on the results of the motion constraint and the trajectory prediction of the multi-joint manipulator. There are many ways to predict the trajectory. The cost of different methods is different. The constraint is to find the conditions for obtaining the optimal planning result. In the specific implementation, the optimal programming solution here may be the attitude Δθ of each joint arm.

The cylinder drive amount calculation unit 34 is configured to determine the cylinder drive amount of each of the pitch arms based on the optimal plan solution.

The length and attitude (angle) of each pitch arm have a specific paradigm relationship L = S (θ). Now that Δθ has been obtained, the driving amount ΔL of each pitch arm can be obtained by calculation.

In addition, it should be noted that the constraint relationship of the link mechanism has a derivation relationship, and only a paradigm is provided. In the specific implementation, the specific form and value only need geometry and derivation and calculation, and those skilled in the art It is customary to say that there is no more explanation here.

The drive current calculation unit 35 is configured to determine a drive current for driving the multi-joint boom and the turret according to the cylinder drive amount and the proportional characteristic of the actuator.

Further, since the trajectory prediction is performed, if the predicted motion trajectory at the next time is abrupt with respect to the current time, the result of the trajectory prediction is discarded. Therefore, this kind of motion trend-based prediction can ensure that the movement state of the boom does not abruptly in the case of small amplitude motion, that is, the smooth motion of the boom can be well ensured.

Further, in the optimal planning solution determining unit 33, the motion constraint is a hydraulic system flow Q extreme value constraint, and the optimal planning solution is a planning solution with a minimum system flow cost. The hydraulic system flow Q is the most important constraint parameter of the construction machinery of the pump truck. The hydraulic pressure is the drive mechanism. This constraint condition If it is not established, the structure is difficult to implement in accordance with the control idea. Each boom has a valve for oil supply. The flow rate of the oil supply is extremely high, not unlimited. Therefore, the system flow restriction must be within the achievable range. The source of the constraint depends only on the hydraulic system configuration of the equipment itself. , how large the valve is configured, the constraint will be fixed.

Referring to FIG. 4, FIG. 4 is a structural block diagram of a preferred embodiment of the multi-joint mechanical arm intelligent control device of the present invention.

Compared with the previous embodiment, the multi-joint robot arm intelligent control device further includes a feedback unit 36 for detecting the state parameter of the driven multi-joint boom and feeding back the state parameter of the multi-joint boom to the trajectory prediction unit 32. The trajectory prediction unit further determines the prediction result according to the input velocity vector of the end of the arm and the state parameter of the multi-joint boom.

Further preferably, the feedback unit 36 further comprises a signal filtering and deformation compensation sub-unit for performing signal filtering and deformation compensation on the acquired state parameters of the multi-joint boom.

It can be seen that, in this embodiment, since step S26 and its sub-step S261 are added, that is, closed-loop constant current driving is adopted, the control precision is further higher. Signal filtering and deformation compensation also improve the accuracy of the control.

In summary, the multi-joint mechanical arm intelligent control method and device of the present invention has the following advantages:

First, based on the prediction of sports trends, ensure that it is not repeated in the case of small vibrations;

Second, based on the motion planning under the minimum constraint of system traffic cost, the end point is the fastest under the same conditions;

Third, based on the motion planning under continuous constraint conditions, there is no sudden change in the amount of motion of each degree; the meaning of the continuity constraint here is that it can be expressed as a recognition of logical memory, the previous time, this time, the next movement The state should be as consistent as possible;

Fourth, the closed-loop constant current drive is used, and the control precision is higher.

In a third aspect, the present invention also discloses an embodiment of a multi-joint robot arm intelligent control system, comprising the above-mentioned multi-joint robot arm intelligent control device, and a manipulator matched with the multi-joint robot arm intelligent control device, The remote controller is used to input the velocity vector of the end of the arm. In the above-described multi-joint robot arm intelligent control system, preferably, the manipulator is a universal handle. The input device is controlled by a remote controller with a universal handle, and the operation direction of the handle of the remote controller is consistent with the moving direction of the end of the arm.

Referring to FIG. 5, it can be seen that the present multi-joint robot arm intelligent control system embodiment includes a universal handle controller and a control device as an execution device of the controlled object. The actuator includes a proportional valve block, a drive cylinder, and a multi-joint boom. Moreover, in order to realize the closed-loop control, the multi-joint boom is further improved and a sensor is further connected to the control unit.

The multi-joint mechanical arm intelligent control system of the present embodiment is directed to the complicated problem of multi-joint ultra-long arm frame control, adopting a one-button automatic control idea (that is, using a universal handle to input the end of the multi-joint robot arm to be reached at the next moment) Speed), in this way, the controller only needs to open the intelligent control function button, shake the universal handle to complete any desired action. That is to say, the universal handle manipulator directly reflects the controller's willingness to control the end of the boom.

At the same time, the system contains a high-speed constant current control device, which is responsible for intelligently controlled trajectory planning and optimal calculation, and precisely drives the actuator. The logic module inside the control device is shown in Figure 3. It is a boom algorithm planning software for implementing control algorithm calculation, deformation compensation, trajectory prediction, optimal control calculation, and so on.

When implemented, the controller transmits the control device to the control device according to the operation intention. The control device provides a complete set of completed control methods, so that the precise drive actuator can be realized to perform the predetermined action of the actuator.

The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., which are included in the spirit and scope of the present invention, should be included in the present invention. Within the scope of protection.

Claims

A multi-joint mechanical arm intelligent control method, comprising the following steps:

Step S11, receiving a velocity vector of the end of the robot arm input by the manipulator;

Step S12, performing trajectory prediction on each of the joint arms of the multi-joint robot based on the velocity vector of the end of the arm and the state of the current arm; if the predicted trajectory of the next moment is abrupt with respect to the current moment, then Abandon the results of the trajectory prediction;

Step S13, determining an optimal planning solution based on a result of motion constraint and trajectory prediction of the multi-joint manipulator;

Step S14, determining a cylinder driving amount of each pitch arm according to the optimal planning solution;

In step S15, a driving current is determined according to the cylinder driving amount and the proportional characteristic of the actuator, and the driving current is used to drive the rotation of the multi-joint boom and the turret.
The multi-joint robot arm intelligent control method according to claim 1, wherein

In the step S13, the motion constraint is a hydraulic system flow extreme value constraint, and the optimal planning solution is a planning solution with a minimum system flow cost.
The multi-joint robot arm intelligent control method according to claim 2, further comprising, after step S15,

Step S16, detecting a state parameter of the driven multi-joint boom, and feeding back the state parameter of the multi-joint boom to step S12, the result of the trajectory prediction is according to the speed vector and the multi-joint of the input end of the arm The state parameters of the boom are determined together.
The multi-joint robot arm intelligent control method according to claim 3, characterized in that

The step S16 further includes the following sub-steps:

Performing signal filtering and deformation compensation on the obtained state parameters of the multi-joint boom, and feeding back the obtained result to the step S12.
A multi-joint mechanical arm intelligent control device, comprising:

a speed vector receiving unit for receiving a velocity vector of a robot arm end input by the manipulator;

a trajectory prediction unit configured to perform trajectory prediction on each of the joint arms of the multi-joint robot based on the velocity vector of the end of the arm and the state of the current arm; if the predicted trajectory of the next moment occurs relative to the current moment Mutation, the result of the trajectory prediction is abandoned;

Optimal planning solution determination unit for motion constraint and trajectory prediction based on multi-joint manipulator The result of determining the optimal planning solution;

a cylinder driving amount calculation unit configured to determine a cylinder driving amount of each pitch arm according to the optimal planning solution;

The driving current calculation unit is configured to determine a driving current for driving the rotation of the multi-joint boom and the turret according to the cylinder driving amount and the proportional characteristic of the actuator.
The multi-joint robot arm intelligent control device according to claim 5, wherein

In the optimal planning solution determining unit, the motion constraint is a hydraulic system flow extreme value constraint, and the optimal planning solution is a planning solution with a minimum system flow cost.
The multi-joint robot arm intelligent control device according to claim 6, further comprising

a feedback unit, configured to detect a state parameter of the driven multi-joint boom, and feed back state parameters of the multi-joint boom to the trajectory prediction unit, the trajectory prediction unit further according to the input end of the robot arm The velocity vector and the state parameters of the multi-joint boom jointly determine a prediction result.
The multi-joint robot arm intelligent control device according to claim 7, wherein

The feedback unit further includes a signal filtering and deformation compensation sub-unit for performing signal filtering and deformation compensation on the acquired state parameters of the multi-joint boom.
A multi-joint robotic arm intelligent control system, comprising:

The multi-joint robot arm intelligent control device according to any one of claims 5 to 8, and a manipulator coupled with the multi-joint robot arm intelligent control device, the manipulator for inputting the end of the arm Speed vector.
The articulated robotic arm intelligent control system according to claim 9, wherein

The manipulator is a universal handle.