CN114932557B - Self-adaptive admittance control method based on energy consumption under kinematic constraint - Google Patents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/0005—Manipulators having means for high-level communication with users, e.g. speech generator, face recognition means
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Abstract
The invention discloses a self-adaptive admittance control method based on energy consumption under kinematic constraint, and belongs to the field of man-machine loop interaction. The minimum energy consumption criterion of the man-machine loop interaction process is provided, an admittance control law is designed on the basis of comprehensively considering interaction force and robot movement speed, damping parameters are updated, and the flexibility and safety of man-machine loop interaction are improved. And giving a mass parameter range of the admittance controller according to the kinematic constraint of the robot, considering the speed, the acceleration and the variable acceleration limit of the robot, and improving the safety of the robot system. The admittance controller converts acting force into position correction quantity of the tail end of the mechanical arm, the position correction quantity is overlapped to the input of the robot system, and the movement control of the robot is realized through the position controller. The method can enable the robot to well conform to the intention of an operator, reduce man-machine interaction force, improve the precision of contact force with the environment, prevent unstable interaction process caused by too small admittance parameters, and improve the flexibility and safety of man-machine ring interaction.
Description
Technical Field
The invention relates to the technical field of man-machine loop interaction, in particular to a self-adaptive admittance control method based on energy consumption under kinematic constraint.
Background
Human-computer interaction is that an operator pulls a mechanical arm to complete specific movement, and the most common is human-computer teaching. The cooperative mechanical arm can autonomously realize track reproduction from teaching, and a plurality of interaction modes of the man-machine ring exist in the whole process. In order to make the interaction process more compliant and safe, the robot needs to have the ability to adapt to the intention of the operator and the hazards that may arise in the interaction.
The traditional admittance control method has the problems of poor flexibility and poor safety. In the prior art, a man-machine cooperation system control method based on intention recognition in China patent CN112276944A utilizes a neural network recognition system to estimate the intention of a person, and the method reduces the interaction force of man-machine cooperation, but does not consider the constraint condition of a mechanical arm, and cannot guarantee the safety of the mechanical arm system. According to the mechanical arm flexibility control method based on fuzzy reinforcement learning in China patent CN107053179B, a fuzzy reinforcement learning algorithm is adopted, and the active following task of the mechanical arm is completed through a real-time adjustment strategy of on-line learning training admittance parameters, but the method is slow in convergence speed, and the flexibility of man-machine cooperation is reduced. An adaptive man-machine cooperation control method based on optimal admittance parameters of Chinese patent CN113352322A is characterized in that the optimal admittance parameters are searched by an integral reinforcement learning mode and auxiliary force is introduced into an admittance control equation, but the method requires a large amount of data training and is only suitable for specific tasks.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a self-adaptive admittance control method considering energy consumption under kinematic constraint, and the flexibility and the safety of a man-machine loop interaction process are improved.
In order to achieve the above purpose, the present invention adopts the following technical scheme, including:
an adaptive admittance control method based on energy consumption under kinematic constraint considers man-machine loop interaction process, establishes capacity consumption minimum criterion according to interaction force and robot motion speed, designs admittance control law, and updates damping parameters.
Preferably, the damping update formula of the admittance controller of the man-machine interaction is as follows:
wherein b is the updated damping value, b 0 Is the initial damping value, e is a natural constant, alpha is a parameter, f h Is the force exerted on the robotic arm and v is the velocity of the robotic arm in cartesian space.
Preferably, the damping coefficient of the admittance controller of man-machine interaction is updated based on the energy consumption minimum criterion of the man-machine interaction process, and the specific method is as follows:
s11, energy consumption in the human-computer interaction process can be represented by the following formula;
wherein f h Is the force exerted on the mechanical arm, v is the velocity of the mechanical arm in Cartesian space;
s12, considering the relation between energy consumption and damping, minimizing the energy consumption in the interaction process, and solving the partial guide of energy to the damping;
wherein f h Is the force exerted on the mechanical arm, v is the velocity of the mechanical arm in Cartesian space;
s13, obtaining the damping coefficient b of the admittance controller along with the operation force f applied on the mechanical arm h And the relation expression of the mechanical arm in the Cartesian space motion velocity v, wherein the damping update formula is as follows:
wherein b is the updated damping value, b 0 Is an initial damping value, e is a natural constant, and alpha is a parameter;
s14, knowing the speed of the mechanical armAcceleration->And become acceleration->According to the operating force f h And a damping coefficient b, and the damping coefficient,
setting the value range of the quality parameter m
The subscript min represents the minimum value, i.e., the lower limit, and the subscript max represents the maximum value, i.e., the upper limit.
Preferably, the damping update formula of the admittance controller of the airplane-ring interaction is as follows:
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed, b is the updated damping value, b 0 Is the initial damping value, e is a natural constant, and α is a parameter.
Preferably, the damping coefficient of the admittance controller in the loop interaction is updated based on the energy consumption minimum criterion, and the specific method is as follows:
s21, energy consumption in the interaction process of the mechanical arm and the environment can be represented by the following formula;
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed;
s22, in order to minimize energy consumption in the interaction process, solving the partial guide of energy to damping;
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed;
s23, deviation of damping coefficient b to admittance controller along with contact forceAnd speed deviation->The admittance controller damping update expression of the machine-loop interaction is as follows:
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed, b is the updated damping value, b 0 Is an initial damping value, e is a natural constant, and alpha is a parameter;
s24, knowing the speed of the mechanical armAcceleration->And become acceleration->Is dependent on the force deviation->Damping coefficient b and ambient speed +.>Ambient acceleration->And environmental change acceleration->
Setting the value range of the quality parameter m
Wherein,,
the subscript min represents the minimum value, i.e., the lower limit, and the subscript max represents the maximum value, i.e., the upper limit.
The invention has the advantages that:
(1) The invention provides an energy consumption minimum criterion in the man-machine loop interaction process, an admittance control law is designed on the basis of comprehensively considering interaction force and robot movement speed, damping parameters are updated, damping coefficients at the beginning stage of man-machine loop interaction are exponentially reduced along with force applied by an operator and the movement speed of a mechanical arm, and the flexibility of man-machine loop interaction is improved; the damping coefficient is kept at a smaller value in the movement process, so that the energy consumption in the cooperation process is reduced; when the mechanical arm needs to execute fine work or emergency stop movement, the damping coefficient can rise exponentially, and the control precision and safety of the mechanical arm are improved.
(2) The invention also provides the mass parameter range of the admittance controller according to the kinematic constraint of the robot, considers the limitations of the speed, the acceleration and the variable acceleration of the robot arm, prevents the unstable movement of the robot arm caused by the undersize admittance parameter, and ensures the safety of the movement of the robot arm system.
(3) The self-adaptive admittance control method ensures that the mechanical arm can identify the movement intention of an operator in the man-machine loop cooperation process, and improves the flexibility of the mechanical arm system.
Drawings
Fig. 1 is a block diagram of the adaptive admittance control of the present invention.
Fig. 2 is a graph of the track following effect of the adaptive admittance of the present invention.
Fig. 3 is a graph showing the variation of the damping coefficient in the X direction according to the present invention.
Fig. 4 is a graph showing the variation of the damping coefficient in the Y direction according to the present invention.
The English meaning in the drawings is as follows:
desired traj-desired track, actual traj-tracking track.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a human-computer loop interaction self-adaptive admittance control method based on energy consumption under kinematic constraint comprises the following specific processes:
s1: modeling a mechanical arm. Setting up a kinematic model of the mechanical arm in the Simulink;
s2: generation of the desired trajectory. A track is planned on an XY plane in a task space, and the track is used as an expected track for tracking a later track of the mechanical arm;
s3: and (5) collecting a force signal. According to the actual motion trail x and the expected motion trail x of the mechanical arm d The deviation between the mechanical arm and the operator calculates the acting force f between the mechanical arm and the operator h For feedback control of the admittance controller, where k in equation (1) is the set environmental stiffness parameter.
f h ＝k(x-x d ) (1)
S4: and (3) considering the energy consumption in the impedance expression, minimizing the energy consumption in the man-machine interaction process, and solving the relation between the energy function and the damping, as shown in formulas (2) and (3).
S5: and updating the damping coefficient. Acquiring the speed v of the mechanical arm in Cartesian space, and obtaining the acting force f according to the step S3 h On-line calculation of damping coefficientWherein b 0 Is the initial damping value, e is a natural constant, alpha is a parameter, f h Is the force exerted on the robotic arm and v is the velocity of the robotic arm in cartesian space.
S6: admittance control. The impedance parameters m, b and the acting force f h Substitution formulaAnd calculating the displacement correction quantity of the tail end of the mechanical arm. Wherein->The acceleration and the velocity of the mechanical arm in cartesian space, respectively.
S7: and controlling the movement of the mechanical arm. The displacement correction quantity Deltax calculated by the admittance controller is added to the initial target position x d Obtaining a reference position x of the mechanical arm r As shown in equation (4). X is x r The expected motion angles of all joints of the mechanical arm are obtained through inverse kinematics solution, and the mechanical arm is realized through a position controllerAnd controlling the movement of the mechanical arm.
x r ＝x d +Δx (4)
Fig. 2 is a graph of the track following effect of the adaptive admittance control, the solid line is the desired track, the dotted line is the actual track, and the desired track coincides with the trace of the present invention. Fig. 3 and 4 are graphs showing changes in damping coefficient in X and Y directions, respectively.
The above embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (3)
1. An adaptive admittance control method based on energy consumption under kinematic constraint is characterized in that a man-machine loop interaction process is considered, an energy consumption minimum criterion is established according to interaction force and robot motion speed, an admittance control law is designed, and damping parameters are updated;
the damping update formula of the admittance controller of human-computer interaction is as follows:
wherein b is the updated damping value, b 0 Is the initial damping value, e is a natural constant, alpha is a parameter, f h Is the force exerted on the mechanical arm, v is the velocity of the mechanical arm in Cartesian space;
based on the energy consumption minimum criterion in the man-machine interaction process, the damping coefficient of the admittance controller of the man-machine interaction is updated, and the specific method is as follows:
s11, energy consumption in the human-computer interaction process can be represented by the following formula;
wherein f h Is the force exerted on the mechanical arm, v is the velocity of the mechanical arm in Cartesian space;
s12, considering the relation between energy consumption and damping, minimizing the energy consumption in the interaction process, and solving the partial guide of energy to the damping;
wherein f h Is the force exerted on the mechanical arm, v is the velocity of the mechanical arm in Cartesian space;
s13, obtaining the damping coefficient b of the admittance controller along with the operation force f applied on the mechanical arm h And the relation expression of the mechanical arm in the Cartesian space motion velocity v, wherein the damping update formula is as follows:
wherein b is the updated damping value, b 0 Is an initial damping value, e is a natural constant, and alpha is a parameter;
s14, knowing the speed of the mechanical armAcceleration->And become acceleration->According to the operating force f h And a damping coefficient b, and the damping coefficient,
setting the value range of the quality parameter m
The subscript min represents the minimum value, i.e., the lower limit, and the subscript max represents the maximum value, i.e., the upper limit.
2. The adaptive admittance control method based on energy consumption under the kinematic constraint of claim 1, wherein the damping update formula of the admittance controller of the machine-loop interaction is as follows:
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed, b is the updated damping value, b 0 Is the initial damping value, e is a natural constant, and α is a parameter.
3. The adaptive admittance control method based on energy consumption under the kinematic constraint according to claim 1 or 2, characterized in that the damping coefficient of the admittance controller in the loop interaction is updated based on the energy consumption minimum criterion, and the specific method is as follows:
s21, energy consumption in the interaction process of the mechanical arm and the environment can be represented by the following formula;
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed;
s22, in order to minimize energy consumption in the interaction process, solving the partial guide of energy to damping;
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed;
s23, deviation of damping coefficient b to admittance controller along with contact forceAnd speed deviation->The admittance controller damping update expression of the machine-loop interaction is as follows:
wherein,,f e is the actual contact force between the mechanical arm and the environment, f d Is the expected contact force between the mechanical arm and the environment, v is the speed of the mechanical arm in Cartesian space, v e Is the ambient speed, b is the updated damping value, b 0 Is an initial damping value, e is a natural constant, and alpha is a parameter;
s24, knowing the speed of the mechanical armAcceleration->And become acceleration->Is dependent on the force deviation->Damping coefficient b and ambient speed +.>Ambient acceleration->And environmental change acceleration->
Setting the value range of the quality parameter m
Wherein,,
the subscript min represents the minimum value, i.e., the lower limit, and the subscript max represents the maximum value, i.e., the upper limit.
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