CN114932557A - Adaptive admittance control method based on energy consumption under kinematic constraint - Google Patents

Abstract

The invention discloses an adaptive admittance control method based on energy consumption under kinematic constraint, belonging to the field of human-computer loop interaction. The minimum criterion of energy consumption in the human-computer ring interaction process is provided, an admittance control law is designed on the basis of comprehensively considering the interaction force and the movement speed of the robot, damping parameters are updated, and the flexibility and the safety of the human-computer ring interaction are improved. The quality parameter range of the admittance controller is given according to the kinematic constraint of the robot, the speed, the acceleration and the variable acceleration limit of the robot are considered, and the safety of the robot system is improved. The admittance controller converts the acting force into the pose correction quantity of the tail end of the mechanical arm, and the pose correction quantity is superposed on the input of the robot system, and the robot motion control is realized through the position controller. The method can make the robot well conform to the intention of an operator, reduce the man-machine interaction force, improve the precision of the contact force with the environment, prevent the instability of the interaction process caused by the undersize admittance parameters, and improve the flexibility and the safety of the man-machine loop interaction.

Description

An adaptive admittance control method based on energy consumption under kinematic constraints

technical field

The invention relates to the technical field of human-machine-loop interaction, in particular to an adaptive admittance control method based on energy consumption under kinematic constraints.

Background technique

Human-machine interaction is that the operator pulls the robotic arm to complete a specific movement, and the most common one is human-machine teaching. There are multiple interaction modes of human-machine loop in the whole process from accepting teaching to realizing trajectory reproduction autonomously. To make the interaction process more compliant and safe, the robot needs to be able to adapt to the operator's intention and the dangers that may arise in the interaction.

The traditional admittance control method has the problems of poor compliance and poor safety. In the prior art, Chinese patent CN112276944A discloses a method for controlling human-machine cooperation system based on intention recognition, which uses a neural network recognition system to estimate human intentions. Although this method reduces the interaction force of human-machine cooperation, it does not consider mechanical The constraints of the arm itself cannot guarantee the safety of the robotic arm system. Chinese patent CN107053179B is a fuzzy reinforcement learning-based robotic arm compliance control method. The method adopts a fuzzy reinforcement learning algorithm and trains a real-time adjustment strategy of admittance parameters through online learning, so as to complete the active follow-up task of the robotic arm, but this method The slow convergence speed reduces the flexibility of human-machine collaboration. Chinese patent CN113352322A is an adaptive man-machine cooperative control method based on optimal admittance parameters. This method searches for optimal admittance parameters by means of integral reinforcement learning and introduces auxiliary force into the admittance control equation, but this method requires A lot of data training, and only suitable for specific tasks.

SUMMARY OF THE INVENTION

In order to overcome the above-mentioned defects in the prior art, the present invention proposes an adaptive admittance control method considering energy consumption under kinematic constraints, so as to improve the flexibility and safety of the interaction process of the human-machine loop.

To achieve the above object, the present invention adopts the following technical solutions, including:

An adaptive admittance control method based on energy consumption under kinematic constraints, considers the interaction process of human-machine loop, establishes the minimum capacity consumption criterion according to the interaction force and robot motion speed, designs the admittance control law, and updates the damping parameters.

Preferably, the damping update formula of the admittance controller for human-computer interaction is as follows:

where b is the updated damping value, b ₀ is the initial damping value, e is a natural constant, α is a parameter, f _h is the force applied to the manipulator, and v is the speed of the manipulator in Cartesian space.

Preferably, based on the minimum energy consumption criterion of the human-machine-loop interaction process, the damping coefficient of the admittance controller of the human-machine interaction is updated, and the specific method is as follows:

S11, the energy consumption in the process of human-computer interaction can be expressed by the following formula;

Among them, f _h is the force exerted on the manipulator, and v is the velocity of the manipulator in Cartesian space;

S12, consider the relationship between energy consumption and damping, minimize the energy consumption in the interaction process, and obtain the partial derivative of energy to damping;

Among them, f _h is the force exerted on the manipulator, and v is the velocity of the manipulator in Cartesian space;

S13, the relationship expression between the damping coefficient b of the admittance controller and the operating force f _h applied to the manipulator and the speed v of the manipulator in Cartesian space is obtained, and the damping update formula is:

Among them, b is the updated damping value, b ₀ is the initial damping value, e is a natural constant, and α is a parameter;

加速度

和变加速度

的限制，根据操作力f_h和阻尼系数b，S14, the speed of the robotic arm itself is known

acceleration

and variable speed

The limit of , according to the operating force f _h and the damping coefficient b,

Set the value range of the quality parameter m

Among them, the subscript min represents the minimum value, that is, the lower limit, and the subscript max represents the maximum value, which is the upper limit.

Preferably, the damping update formula of the machine-loop interaction admittance controller is as follows:

f_e是机械臂与环境间的实际接触力，f_d是机械臂与环境间的期望接触力，v是机械臂在笛卡尔空间的速度，v_e是环境速度，b为更新后的阻尼值，b₀是初始阻尼值，e是自然常数，α是参数。in,

f _e is the actual contact force between the manipulator and the environment, f _d is the expected contact force between the manipulator and the environment, v is the speed of the manipulator in Cartesian space, _ve is the environment 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, based on the minimum energy consumption criterion, the damping coefficient of the admittance controller in the machine-loop interaction is updated, and the specific method is as follows:

S21, the energy consumption during the interaction between the robotic arm and the environment can be expressed by the following formula;

f_e是机械臂与环境间的实际接触力，f_d是机械臂与环境间的期望接触力，v是机械臂在笛卡尔空间的速度，v_e是环境速度；in,

f _e is the actual contact force between the manipulator and the environment, f _d is the expected contact force between the manipulator and the environment, v is the speed of the manipulator in Cartesian space, and _ve is the speed of the environment;

S22, in order to minimize the energy consumption in the interaction process, obtain the partial derivative of the energy to the damping;

f_e是机械臂与环境间的实际接触力，f_d是机械臂与环境间的期望接触力，v是机械臂在笛卡尔空间的速度，v_e是环境速度；in,

f _e is the actual contact force between the manipulator and the environment, f _d is the expected contact force between the manipulator and the environment, v is the speed of the manipulator in Cartesian space, and _ve is the speed of the environment;

和速度偏差

的关系表达式，机环交互的导纳控制器阻尼更新表达式为：S23, the damping coefficient b to the admittance controller deviates with the contact force

and speed deviation

The relational expression of , the damping update expression of the admittance controller of the machine-loop interaction is:

f_e是机械臂与环境间的实际接触力，f_d是机械臂与环境间的期望接触力，v是机械臂在笛卡尔空间的速度，v_e是环境速度，b为更新后的阻尼值，b₀是初始阻尼值，e是自然常数，α是参数；in,

f _e is the actual contact force between the manipulator and the environment, f _d is the expected contact force between the manipulator and the environment, v is the speed of the manipulator in Cartesian space, _ve is the environment speed, b is the updated damping value , b ₀ is the initial damping value, e is a natural constant, α is a parameter;

加速度

和变加速度

的限制，根据作用力偏差

阻尼系数b以及环境速度

环境加速度

和环境变加速度

S24, the known speed of the manipulator

acceleration

and variable speed

limit, according to the force deviation

Damping coefficient b and ambient speed

environmental acceleration

and environmental changes

Set the value range of the quality parameter m

in,

The subscript min represents the minimum value, which is the lower limit, and the subscript max, which represents the maximum value, which is the upper limit.

The advantages of the present invention are:

(1) The present invention proposes the minimum energy consumption criterion for the interaction between the human-machine loop and the robot. The admittance control law is designed on the basis of comprehensively considering the interactive force and the motion speed of the robot, and the damping parameters are updated. As the force exerted by the operator and the movement speed of the robotic arm decrease exponentially, the flexibility of the man-machine-loop cooperation is improved; the damping coefficient is kept at a small value during the movement process, which reduces the energy consumption of the cooperation process; the robotic arm needs to perform fine During chemical work or emergency stop motion, the damping coefficient will increase exponentially, improving the control accuracy and safety of the robotic arm.

(2) The present invention also provides the quality parameter range of the admittance controller according to the kinematic constraints of the robot, and considers the limitations of the speed, acceleration and variable acceleration of the robot arm itself, so as to prevent the movement of the robot arm from being unstable due to too small admittance parameters, The safety of the movement of the robotic arm system is guaranteed.

(3) The adaptive admittance control method of the present invention ensures that the manipulator can recognize the movement intention of the operator in the process of man-machine-loop cooperation, and improves the flexibility of the manipulator system.

Description of drawings

FIG. 1 is a block diagram of the adaptive admittance control of the present invention.

FIG. 2 is an effect diagram of trajectory tracking of the adaptive admittance of the present invention.

FIG. 3 is a graph showing the change of the damping coefficient in the X direction according to the present invention.

FIG. 4 is a graph showing the change of the damping coefficient in the Y direction of the present invention.

The English meanings in the attached drawings are as follows:

desired traj-desired trajectory, actual traj-tracking trajectory.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in Figure 1, a man-machine-loop interaction adaptive admittance control method based on energy consumption under kinematic constraints, the specific process is as follows:

S1: Modeling of the robotic arm. Build the kinematics model of the robotic arm in Simulink;

S2: Generation of desired trajectory. Plan a trajectory in the XY plane of the task space, and this trajectory is used as the expected trajectory of the later trajectory tracking of the robotic arm;

S3: Collection of force signals. Calculate the force f _h between the manipulator and the operator according to the deviation between the actual motion trajectory x and the expected motion trajectory x _d of the manipulator, which is used for the feedback control of the admittance controller, where k in formula (1) is Set the environment stiffness parameter.

f _h =k(xx _d ) (1)

S4: Consider the energy consumption into the impedance expression, minimize the energy consumption in the human-computer interaction process, and find the relationship between the energy function and the damping, as shown in formulas (2) and (3).

其中b₀是初始阻尼值，e是自然常数，α是参数，f_h是施加在机械臂上的力，v是机械臂在笛卡尔空间的速度。S5: Update of damping coefficient. Collect the velocity v of the robotic arm in Cartesian space, obtain the force f _h according to step S3, and calculate the damping coefficient online

where b ₀ is the initial damping value, e is a natural constant, α is a parameter, f _h is the force exerted on the manipulator, and v is the velocity of the manipulator in Cartesian space.

计算出机械臂末端的位移修正量。其中

分别是机械臂在笛卡尔空间的加速度和速度。S6: Admittance control. Substitute the impedance parameters m, b and the force f _h into the formula

Calculate the displacement correction of the end of the robot arm. in

are the acceleration and velocity of the robotic arm in Cartesian space, respectively.

S7: Robotic arm motion control. The displacement correction amount Δx calculated by the admittance controller is superimposed on the initial target position x _d to obtain the reference position x _r of the manipulator, as shown in formula (4). The desired motion angle of each joint of the manipulator is obtained through inverse kinematics solution of x _r , and the motion control of the manipulator is realized by the position controller.

x _r =x _d +Δx (4)

FIG. 2 is a trajectory tracking effect diagram of adaptive admittance control, the solid line is the desired trajectory desired traj, the dotted line is the tracking trajectory actual traj, the desired trajectory of the present invention coincides with the tracking trajectory. Figures 3 and 4 are graphs of changes in the damping coefficient in the X and Y directions, respectively.

The above are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the present invention. within the scope of protection.

Claims (5)

1. An adaptive admittance control method based on energy consumption under kinematic constraint is characterized in that a human-computer loop interaction process is considered, a capability consumption minimum criterion is established according to interaction force and robot movement speed, an admittance control law is designed, and damping parameters are updated.

2. The adaptive admittance control method based on energy consumption under kinematic constraint according to claim 1, wherein the damping of the human-computer interaction admittance controller updates the formula as follows:

where b is the updated damping value, b ₀ Is an initial damping value, e is a natural constant, α 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.

3. The adaptive admittance control method based on energy consumption under kinematic constraint according to claim 1 or 2, wherein the damping coefficient of the admittance controller for human-computer interaction is updated based on the energy consumption minimum criterion of the human-computer loop interaction process, and the specific method is as follows:

s11, energy consumption in the process of man-machine interaction can be represented by the following formula;

wherein, f _h Is the force applied to the robotic arm, v is the velocity of the robotic arm in cartesian space;

s12, considering the relation between energy consumption and damping, minimizing the energy consumption in the interactive process, and calculating the partial derivative of the energy to the damping;

wherein, f _h Is the force applied to the robotic arm, v is the velocity of the robotic arm in cartesian space;

s13, obtaining the damping coefficient b of the admittance controller according to the operation force f applied on the mechanical arm _h And the relational expression of the motion speed v of the mechanical arm in the Cartesian space, wherein the damping updating formula is as follows:

where b is the updated damping value, b ₀ Is the initial damping value, e is the natural constant, α is the parameter;

s14, knowing the speed of the robot arm itself

Acceleration of a vehicle

And variable acceleration

In response to the operating force f _h And a damping coefficient b for the damping of the vibration,

setting the value range of the quality parameter m

The subscript min represents a minimum value, i.e., a lower limit, and the subscript max represents a maximum value, i.e., an upper limit.

4. The adaptive admittance control method based on energy consumption under kinematic constraint according to claim 1, wherein the damping update formula of the machine-loop interactive admittance controller 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 robot arm and the environment, v is the velocity of the robot arm in Cartesian space _e Is ambient velocity, b is the updated damping value, b ₀ Is the initial damping value, e is the natural constant, and α is the parameter.

5. The adaptive admittance control method based on energy consumption under kinematic constraint according to claim 1 or 4, wherein the damping coefficient of the admittance controller in the machine loop interaction is updated based on the energy consumption minimum criterion, and the specific method is as follows:

s21, energy consumption in the process of interaction between 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 robot arm and the environment, v is the velocity of the robot arm in Cartesian space _e Is the ambient velocity;

s22, in order to minimize the energy consumption in the interaction process, the partial derivative of the energy to the damping is obtained;

wherein,

f _e is the actual contact force between the mechanical arm and the environment, f _d Is the expected contact force between the robot arm and the environment, v is the velocity of the robot arm in Cartesian space _e Is the ambient velocity;

s23 deviation of damping coefficient b from admittance controller with contact force

And speed deviation

The relationship expression of (2) and the admittance controller damping updating expression of machine ring interaction are 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 robot arm and the environment, v is the velocity of the robot arm in Cartesian space _e Is the ambient velocity, b is the updated damping value, b ₀ Is the initial damping value, e is the natural constant, α is the parameter;

s24, knowing the robot arm speed

Acceleration of a vehicle

And variable acceleration

According to the applied force deviation

Damping coefficient b and ambient velocity

Ambient acceleration

And ambient variation of acceleration

Setting quality parametersValue range of m

Wherein,

the subscript min represents the minimum, i.e., lower limit, and the subscript max represents the maximum, i.e., upper limit.

Images