CN117124327A - A robot contact force constraint control method based on control obstacle function - Google Patents
A robot contact force constraint control method based on control obstacle function Download PDFInfo
- Publication number
- CN117124327A CN117124327A CN202311233616.9A CN202311233616A CN117124327A CN 117124327 A CN117124327 A CN 117124327A CN 202311233616 A CN202311233616 A CN 202311233616A CN 117124327 A CN117124327 A CN 117124327A
- Authority
- CN
- China
- Prior art keywords
- robot
- control
- contact force
- model
- controlled robot
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/1605—Simulation of manipulator lay-out, design, modelling of manipulator
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1633—Programme controls characterised by the control loop compliant, force, torque control, e.g. combined with position control
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Manipulator (AREA)
Abstract
The invention discloses a robot contact force constraint control method based on a control barrier function, which is characterized in that an affine nonlinear system model containing contact force is constructed based on a established kinematic model, a dynamic model and a contact force model of a robot, compared with a single contact force model, the affine nonlinear system model has better dynamic performance, the control barrier function is applied to robot contact force safety constraint control, compared with the existing position safety constraint control method, the application of the control barrier function in the field of robots is widened, meanwhile, the control barrier function can be combined with a plurality of existing force position control methods, the method has good contact force constraint effect, high flexibility, good instantaneity and strong robustness, is simple and convenient to apply, and the problem that the conventional force position control is difficult to constraint the contact force is effectively solved.
Description
Technical Field
The invention belongs to the technical field of robot control, and particularly relates to a robot contact force constraint control method based on a control obstacle function.
Background
Robots are widely used in various fields as an important industrial automation device. The flexibility and versatility of robots make them an integral part of automated production. However, as robots are increasingly used in work scenarios, so too are the demands on their control and accuracy, single position control often has not been able to meet the various demands in production. Taking an assembly task as an example, the position control robot cannot sense the stress state of the part, so that the precision part is easily assembled in place, and even the part is damaged.
At present, classical methods such as impedance control and force position mixed control are effective ways for realizing force control, the impedance control is better in treating the force control problem in a hard environment, the mixed force position control is better in a soft environment, but both the impedance control and the force position mixed control are easy to generate obvious overshoot and oscillation, and the requirement of accurate control is difficult to meet. The traditional method can obtain a more gentle control process by adjusting an environment model, but constraint control is difficult to realize, and safe operation of a system cannot be ensured by simply relying on impedance control or force-position hybrid control.
Disclosure of Invention
In view of the above, the invention provides a robot contact force constraint control method based on a control obstacle function, which is combined with the existing control method by modifying the expected speed to realize safe constraint control of the robot contact force, and solve the problem of difficult realization of the contact force constraint in the existing robot control method.
The invention provides a robot contact force constraint control method based on a control obstacle function, which comprises the following steps:
step 1, establishing a robot dynamics model of a controlled robot; determining a force position control mode based on the angular speed of a robot joint, and designing a corresponding controlled robot controller;
step 2, establishing a contact force model of the controlled robot interaction process, and establishing an affine nonlinear system model of the controlled robot by combining a robot dynamics model of the controlled robot;
step 3, designing a control barrier function related to contact force according to an affine nonlinear system model and task requirements of a controlled robot, designing a safety controller according to the control barrier function, wherein the input of the safety controller is the output of the controlled robot controller, the current joint angle and the current contact force of the controlled robot, solving the safety joint angular velocity of the controlled robot when the contact force constraint is met, and integrating according to the safety joint angular velocity to obtain the safety joint angle;
and 4, replacing the expected angular speed and the expected angle of the controlled robot controller by using the safety joint angular speed and the safety joint angle obtained in the step 3 as the final control quantity of the controlled robot, and realizing the contact force safety constraint control of the robot and the environment interaction system.
Further, the method for establishing the robot dynamics model of the controlled robot in the step 1 is as follows:
the PD controller with gravity compensation is introduced:
wherein τ J ∈R n Representing the control moment of n joints, K p ,K D As a parameter of the PD controller,joint angles respectively representing n joints of a controlled robotSpeed and joint angular acceleration ++>The expected joint angular velocity and the expected joint angular acceleration of n joints of the robot are represented;
thereby establishing a robot dynamics model as follows:
wherein F is ext And J (q) is a Jacobian matrix of the controlled robot.
Further, the force level tracking control mode of the controlled robot controller is impedance control, admittance control or model prediction control.
Further, the contact force model in the step 2 is:
wherein,representing stiffness characteristics of a controlled robot, p d Representing the position and desired position of the controlled robotic end effector, respectively.
Further, the affine nonlinear system model in the step 2 is:
wherein x= [ q ] T q d T F ext T ] T Is of a systematic shapeThe state quantity of the catalyst is calculated,to control the amount.
Further, the method for solving the safe joint angular velocity of the controlled robot when the contact force constraint is satisfied by the safe controller in the step 3 is as follows: converting the control obstacle function into a quadratic programming problem for solving, wherein the quadratic programming problem is as follows:
wherein,indicating the angular velocity of the safety joint>Represents the derivative of h (x), α (h (x)) represents a monotonically increasing function of lipschitz succession, and α (0) =0, +.>Indicating the range of joint angular velocities allowed by the controlled robot.
The beneficial effects are that:
the affine nonlinear system model containing the contact force is constructed based on the established kinematic model, dynamic model and contact force model of the robot, compared with the single contact force model, the affine nonlinear system model containing the contact force has better dynamic performance, the control barrier function is applied to the safety constraint control of the contact force of the robot, compared with the existing position safety constraint control method, the application of the control barrier function in the field of robots is widened, meanwhile, the affine nonlinear system model containing the contact force can be combined with various existing force position control methods, the affine nonlinear system model containing the contact force has good contact force constraint effect, is high in flexibility, good in instantaneity and strong in robustness, is simple and convenient to apply, and the problem that the contact force is difficult to constraint by the traditional force position control is effectively solved.
Drawings
Fig. 1 is a UR3 robot used in an embodiment of a robot contact force constraint control method based on a control obstacle function according to the present invention.
Fig. 2 is a diagram of simulation results of an end effector at rest in an embodiment of a robot contact force constraint control method based on a control obstacle function according to the present invention.
Fig. 3 is a diagram of simulation results when an end effector moves in an embodiment of a robot contact force constraint control method based on a control obstacle function provided by the invention.
Detailed Description
The invention will now be described in detail by way of example with reference to the accompanying drawings.
The control obstacle function is attracting attention as a safety control method, and is generally better in real-time performance than a constraint control method such as model predictive control or reference speed governor. The control barrier function is an application of the barrier function in safety control design, and the safety control problem is converted into a convex optimization problem which is easier to process through the concepts of a safety state set, an unsafe state set and the like. The invention provides a robot contact force safety constraint control method based on a control barrier function, which has the core ideas that an affine nonlinear system model of the contact force is established when a robot interacts with the environment, and the control barrier function related to the contact force is designed by means of the control barrier function theory, so that the robot joint safety speed meeting constraint control requirements is obtained, and the safety constraint control of the robot contact force is realized.
The invention provides a robot contact force constraint control method based on a robot model and a control obstacle function, which mainly comprises the following steps:
and step 1, establishing a robot dynamics model of the controlled robot.
The invention introduces a PD controller with gravity compensation:
wherein τ J ∈R n Representing the control moment of n joints, K p ,K D As a parameter of the PD controller,respectively representing the joint speeds and the joint accelerations of n joints of the robot, < >>The desired joint velocity and the desired joint acceleration of the n joints of the robot are represented.
A robot dynamics model is built for the controlled robot, as shown in the following formula:
wherein F is ext J (q) is the Jacobian matrix of the robot for the external force applied to the end effector of the robot.
And 2, determining a force position control mode based on the angular velocity of the robot joint, designing a corresponding controlled robot controller, and realizing tracking control of the position and force of the controlled robot by adopting the expected angular velocity and the expected angle of the joint output by the controlled robot controller.
The method can adopt impedance control, admittance control, model prediction control and the like to determine the force position tracking control mode, and can solve the expected joint angular velocity and the expected joint angle meeting the force position tracking control constraint through the force position tracking control.
And 3, establishing a contact force model of the controlled robot in the interaction process, and establishing an affine nonlinear system model of the controlled robot by combining a robot dynamics model of the controlled robot on the basis.
The contact force model of the controlled robot established by the invention is as follows:
wherein,representing the stiffness characteristics of the robot, p d The position and desired position of the robotic end effector are represented, respectively.
The established affine nonlinear system model of the controlled robot is as follows:
wherein x= [ q ] T q d T F ext T ] T As a state quantity of the system,for control volume, the present model describes the dynamics and contact force characteristics of a robot with a PD controller when interacting with the environment.
Step 4, designing a control obstacle function related to the contact force according to the affine nonlinear system model and the task requirement of the controlled robot, and designing a safety controller according to the control obstacle function, wherein the input of the safety controller is the output of the controller in step 2, the current joint angle q of the controlled robot and the current contact force F ext The safety controller is used for solving the safety joint angular velocity of the controlled robot when the contact force constraint is met, and then obtaining the safety joint angle according to the integral of the safety joint angular velocity.
The safety controller input is the current of the controlled robotJoint angle q, current contact force F ext Desired joint angle q d Desired angular velocity of jointAnd a control obstacle function h (x) designed according to the contact force constraint target; the output is safe joint speed satisfying the safety constraint>
The control process is solved through a quadratic programming problem, wherein the quadratic programming problem is as follows:
wherein,represents the derivative of h (x), α (h (x)) represents a monotonically increasing function of lipschitz succession, and α (0) =0, +.>Indicating the range of joint speeds allowed by the robot.
And 5, replacing the expected angular speed and the expected angle of the controller in the step 2 by using the safety joint angular speed and the safety joint angle obtained in the step 4 as the final control quantity of the controlled robot, and realizing the contact force safety constraint control of the robot and the environment interaction system.
Examples:
in this embodiment, the robot contact force constraint control method based on the robot model and the control barrier function provided by the invention selects the force constraint control problem in the interaction process of the six-degree-of-freedom robot UR3 and the rigid plane as a controlled object, and the following details are provided in conjunction with the accompanying drawings:
in this embodiment, the controlled robot is a UR3 robot, the structure of which is shown in fig. 1, and the end effector of the controlled robot is stationary or moves in the horizontal direction along the plane, and meanwhile, force interaction is generated with the rigid plane, so that the constraint control target of the contact force is that the absolute value of the contact force in the vertical direction is not greater than 4N.
In order to achieve this task, the specific steps are as follows:
a. and introducing a PD controller, performing kinematic and dynamic modeling on the controlled robot, and establishing a robot dynamic model.
Obtaining a kinematic model of the UR3 robot by a rotation method, designing a corresponding PD controller, and establishing a robot dynamics model:
wherein PD control parameter K is selected p ＝100I，K d ＝50I。
b. The position and force tracking controller is designed, and admittance control is adopted as a force position control mode based on the angular velocity of the robot joint in the embodiment.
In the direction of force interaction, i.e. in the vertical direction, admittance control is designed:
wherein m is an inertial parameter, b is a damping parameter, k is a stiffness parameter, f ext For the contact force in this direction,respectively the position, speed and acceleration in this direction,/->Respectively representing the reference position, the reference speed and the reference acceleration in the direction, f d Is the desired contact force in that direction. In order to obtain a better contact force control effect, the parameters are selected as follows: m=100, b=120, k=0, the length unit being in millimeters.
Correction amount x defining reference position f :＝x-x r First, the corresponding acceleration correction amount is solved:
the correction of the speed correction and the correction of the reference position are then solved by integration:
the present embodiment realizes impedance control by the correction amount of the reference speed, and converts into a form of an angular speed correction amount:
wherein,is->Expression in Cartesian space, < >>Is a correction amount of the angular velocity. Combined with reference angular velocity->Obtain the desired angular velocity +.>
c. Modeling the contact force to obtain an affine nonlinear system model of the force interaction problem.
For a rigid contact, it can be approximated that the end effector position remains unchanged in the force interaction direction, and then the control moment is used to generate the contact force, according to the PD controller:
τ ext ＝K p (q d -q)
using contact force instead of moment, we get:
J(q) T F ext ＝K p (q d -q)
since the end effector is approximately stationary, the error of position control dp: =p d -p≈J(q)(q d Q), the relationship of contact force to position error can be obtained:
F ext ＝(J(q)K p -1 J(q) T ) -1 (p d -p)
wherein,stiffness characteristics of a robot interacting with an environment are described.
The contact force is written in differential form:
the affine nonlinear system model of the force interaction problem of the robot system can be obtained by combining the dynamics model:
d. and designing and controlling the barrier function according to the constraint target and solving the corresponding quadratic programming problem.
The design control barrier function is:
h(x)＝F z +4
wherein F is z For the component of the contact force in the vertical direction under the end effector coordinate system, the force interaction is typically negative.
The safety speed is then solved by quadratic programming as follows
Wherein the method comprises the steps ofa is a parameter, and->q max ＝π。
e. Will beIntegrating to obtain q safe And use +.>Replace->q safe Instead of q d For tracking by the PD controller introduced in a.
After solving the safety speed through the steps and tracking the safety speed by using the PD controller, the safety constraint control of the contact force can be realized, two groups of simulation experiments are respectively carried out, and the tracking targets and the tracking results are as follows:
the first group, the end effector position remains unchanged and the contact force is a sinusoidal function that varies with time, selecting a different a. The simulation results are shown in fig. 2, the contact force is effectively restrained under the action of the controller, and the contact force can have different rejection effects on the safety boundary by selecting proper alpha.
The second group, the end effector, moves along an archimedes' spiral, with the contact force remaining unchanged. The simulation result is shown in fig. 3, the contact force is basically maintained in a safe area during the movement process, and the controller can still better maintain the constraint on the contact force when being disturbed.
The experiment verifies the effectiveness of the method provided by the invention, can perform good constraint control on the contact force when the robot interacts with the environment under various conditions, and can remarkably improve the problem that the contact force constraint control is difficult to realize by part of the existing robot force position control methods.
In summary, the foregoing description is only illustrative of the preferred embodiments of the present invention, and the accompanying drawings are only used to illustrate the effectiveness of the embodiments of the present invention, not to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. The robot contact force constraint control method based on the control obstacle function is characterized by comprising the following steps of:
step 1, establishing a robot dynamics model of a controlled robot; determining a force position control mode based on the angular speed of a robot joint, and designing a corresponding controlled robot controller;
step 2, establishing a contact force model of the controlled robot interaction process, and establishing an affine nonlinear system model of the controlled robot by combining a robot dynamics model of the controlled robot;
step 3, designing a control barrier function related to contact force according to an affine nonlinear system model and task requirements of a controlled robot, designing a safety controller according to the control barrier function, wherein the input of the safety controller is the output of the controlled robot controller, the current joint angle and the current contact force of the controlled robot, solving the safety joint angular velocity of the controlled robot when the contact force constraint is met, and integrating according to the safety joint angular velocity to obtain the safety joint angle;
and 4, replacing the expected angular speed and the expected angle of the controlled robot controller by using the safety joint angular speed and the safety joint angle obtained in the step 3 as the final control quantity of the controlled robot, and realizing the contact force safety constraint control of the robot and the environment interaction system.
2. The method for controlling contact force constraint of robot according to claim 1, wherein the method for establishing the robot dynamics model of the controlled robot in step 1 is as follows:
the PD controller with gravity compensation is introduced:
wherein τ J ∈R n Representing the control moment of n joints, K p ,K D As a parameter of the PD controller,respectively representing the joint angular velocity and the joint angular acceleration of n joints of the controlled robot, +.>The expected joint angular velocity and the expected joint angular acceleration of n joints of the robot are represented;
thereby establishing a robot dynamics model as follows:
wherein F is ext And J (q) is a Jacobian matrix of the controlled robot.
3. The robot contact force constraint control method of claim 1, wherein the force level tracking control mode of the controlled robot controller is impedance control, admittance control or model predictive control.
4. The robot contact force constraint control method according to claim 1, wherein the contact force model in step 2 is:
wherein,representing stiffness characteristics of a controlled robot, p d Representing the position and desired position of the controlled robotic end effector, respectively.
5. The method according to claim 1, wherein the affine nonlinear system model in step 2 is:
wherein x= [ q ] T q d T F ext T ] T As a state quantity of the system,to control the amount.
6. The method according to claim 1, wherein the method for solving the safe joint angular velocity of the controlled robot when the contact force constraint is satisfied by the safe controller in the step 3 is as follows: converting the control obstacle function into a quadratic programming problem for solving, wherein the quadratic programming problem is as follows:
wherein,
representing the angular velocity of the safety joint, h (x) representing the derivative of h (x), a (h (x)) representing a monotonically increasing function of lipschz succession, and a (0) =0,indicating the range of joint angular velocities allowed by the controlled robot.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311233616.9A CN117124327A (en) | 2023-09-22 | 2023-09-22 | A robot contact force constraint control method based on control obstacle function |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311233616.9A CN117124327A (en) | 2023-09-22 | 2023-09-22 | A robot contact force constraint control method based on control obstacle function |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117124327A true CN117124327A (en) | 2023-11-28 |
Family
ID=88852782
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311233616.9A Pending CN117124327A (en) | 2023-09-22 | 2023-09-22 | A robot contact force constraint control method based on control obstacle function |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117124327A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118809620A (en) * | 2024-08-30 | 2024-10-22 | 北京理工大学 | An assembly task optimization control method based on contact force constraint and posture constraint |
| CN119283038A (en) * | 2024-11-27 | 2025-01-10 | 中能坤域科技控股(浙江)有限公司 | Motion trajectory optimization method and storage medium for robotic arm |
| CN119717627A (en) * | 2024-12-19 | 2025-03-28 | 北京理工大学 | Robot whole body safety control method and system based on robust control obstacle function |
| CN119704204A (en) * | 2025-02-21 | 2025-03-28 | 湖南大学 | Robust visual constraint control method, system and computer device for manipulator |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104723340A (en) * | 2015-03-07 | 2015-06-24 | 哈尔滨工业大学 | Impedance control method for flexibility joint mechanical arm based on connection and damping configuration |
| CN105320138A (en) * | 2015-11-28 | 2016-02-10 | 沈阳工业大学 | Control method for tracking motion speed and motion track of rehabilitation training robot at the same time |
| CN108972560A (en) * | 2018-08-23 | 2018-12-11 | 北京邮电大学 | A kind of activation lacking mechanical arm Hierarchical sliding mode control method based on fuzzy optimization |
| CN110673544A (en) * | 2019-09-27 | 2020-01-10 | 上海大学 | Upper limb rehabilitation robot control method based on adaptive online learning |
| US20210011458A1 (en) * | 2017-03-27 | 2021-01-14 | South China University Of Technology | Method for programming repeating motion of redundant robotic arm |
| CN115256395A (en) * | 2022-08-17 | 2022-11-01 | 北京理工大学 | Model uncertain robot safety control method based on control barrier function |
| US20230064332A1 (en) * | 2021-08-31 | 2023-03-02 | Siemens Aktiengesellschaft | Controller for autonomous agents using reinforcement learning with control barrier functions to overcome inaccurate safety region |
| CN116214530A (en) * | 2023-05-10 | 2023-06-06 | 苏州大学 | Safety predefined time control method, equipment and medium for second-order nonlinear system |
-
2023
- 2023-09-22 CN CN202311233616.9A patent/CN117124327A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104723340A (en) * | 2015-03-07 | 2015-06-24 | 哈尔滨工业大学 | Impedance control method for flexibility joint mechanical arm based on connection and damping configuration |
| CN105320138A (en) * | 2015-11-28 | 2016-02-10 | 沈阳工业大学 | Control method for tracking motion speed and motion track of rehabilitation training robot at the same time |
| US20210011458A1 (en) * | 2017-03-27 | 2021-01-14 | South China University Of Technology | Method for programming repeating motion of redundant robotic arm |
| CN108972560A (en) * | 2018-08-23 | 2018-12-11 | 北京邮电大学 | A kind of activation lacking mechanical arm Hierarchical sliding mode control method based on fuzzy optimization |
| CN110673544A (en) * | 2019-09-27 | 2020-01-10 | 上海大学 | Upper limb rehabilitation robot control method based on adaptive online learning |
| US20230064332A1 (en) * | 2021-08-31 | 2023-03-02 | Siemens Aktiengesellschaft | Controller for autonomous agents using reinforcement learning with control barrier functions to overcome inaccurate safety region |
| CN115256395A (en) * | 2022-08-17 | 2022-11-01 | 北京理工大学 | Model uncertain robot safety control method based on control barrier function |
| CN116214530A (en) * | 2023-05-10 | 2023-06-06 | 苏州大学 | Safety predefined time control method, equipment and medium for second-order nonlinear system |
Non-Patent Citations (1)
| Title |
|---|
| YUHAN XIONG等: "multi-layered safety-critical control design for robotic systems via control barrier functions", PROCEEDINGS OF THE 41ST CHINESE CONTROL CONFERENCE, 11 October 2022 (2022-10-11), pages 3674 - 3679 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118809620A (en) * | 2024-08-30 | 2024-10-22 | 北京理工大学 | An assembly task optimization control method based on contact force constraint and posture constraint |
| CN119283038A (en) * | 2024-11-27 | 2025-01-10 | 中能坤域科技控股(浙江)有限公司 | Motion trajectory optimization method and storage medium for robotic arm |
| CN119717627A (en) * | 2024-12-19 | 2025-03-28 | 北京理工大学 | Robot whole body safety control method and system based on robust control obstacle function |
| CN119717627B (en) * | 2024-12-19 | 2025-09-12 | 北京理工大学 | Robot whole body safety control method and system based on robust control obstacle function |
| CN119704204A (en) * | 2025-02-21 | 2025-03-28 | 湖南大学 | Robust visual constraint control method, system and computer device for manipulator |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117124327A (en) | A robot contact force constraint control method based on control obstacle function | |
| CN115157238B (en) | A dynamic modeling and trajectory tracking method for multi-degree-of-freedom robots | |
| CN114952849B (en) | Robot track tracking controller design method based on reinforcement learning and dynamics feedforward fusion | |
| WO2022205940A1 (en) | Robot motion control method and apparatus, and robot | |
| Sarkhel et al. | Fuzzy logic-based tuning of PID controller to control flexible manipulators | |
| CN112847373B (en) | Robot track synchronous control method and computer readable storage medium | |
| CN106406098B (en) | A Human-Computer Interaction Control Method of Robot System in Unknown Environment | |
| CN115431271B (en) | A method for anti-interference pointing control at the end of a flying manipulator | |
| CN116512242A (en) | Quick terminal sliding mode-based fuzzy variable impedance control method for polishing robot | |
| CN111515928A (en) | Mechanical arm motion control system | |
| CN114055467A (en) | Space pose online simulation system based on five-degree-of-freedom robot | |
| Saied et al. | From non-model-based to model-based control of pkms: a comparative study | |
| Sun | Kinematics model identification and motion control of robot based on fast learning neural network | |
| Zhang et al. | Trajectory tracking control of a 3-CRU translational parallel robot based on PD+ robust controller | |
| Huang et al. | Research on vibration suppression for industrial robots based on dynamic feedforward control | |
| CN118219260A (en) | A motion control method for a mobile robotic arm in a dynamic scene and its application | |
| CN112034869B (en) | Design method and application of variable parameter neurodynamics controller of unmanned aerial vehicle | |
| CN110774286B (en) | Control method of five-degree-of-freedom manipulator based on rigid-flexible coupling dynamics | |
| CN118181292A (en) | Multi-target force position control method for serial mechanical arm | |
| CN116394259A (en) | Truss robot anti-interference positioning control method and system | |
| Hua et al. | A force/position hybrid controller for rehabilitation robot | |
| CN119681868B (en) | High-precision double-closed-loop robust control method for rope-driven super-redundancy mechanical arm | |
| Yang et al. | Q-Learning-Based Trajectory Tracking Control of Delta Robot | |
| Chen et al. | Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance. | |
| CN119805928B (en) | Robot self-adaptive neural optimal tracking control method and device considering dynamic constraint |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |