CN112731954B - Robot motion control method and device, robot and storage medium - Google Patents
Robot motion control method and device, robot and storage medium Download PDFInfo
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Abstract
The application is suitable for the technical field of robot control, and particularly relates to a motion control method and device for a robot, the robot and a storage medium. The motion control method of the robot comprises the steps that a preset outer ring controller obtains a preset attitude angle deviation value and calculates a zero moment point expected value of the robot, the outer ring controller is a PD-variable controller, and a preset inner ring controller obtains the zero moment point deviation value and calculates a moment compensation value of a tail end joint of the robot. After the output torque compensation value is calculated, the torque compensation value and the torque expected value of the tail end joint of the robot are obtained, the torque deviation value is generated, and the torque deviation value is provided for the tail end joint actuator of the robot so as to control the gait movement of the robot, so that the accuracy of the gait control of the robot is improved. The application combines the attitude angle feedback value and the zero moment point measurement value to control the gait of the robot, thereby improving the accuracy of the robot gait control.
Description
Technical Field
The application belongs to the technical field of robot control, and particularly relates to a motion control method and device of a robot, the robot and a storage medium.
Background
One key problem in the research of humanoid robots is to improve walking speed and keep walking stability, and reasonable gait control can improve the stability of the humanoid robots during walking. The existing gait control method of the robot generally calculates a moment compensation value of an end joint of the robot according to the measured attitude angle information of the robot, and then controls the gait of the robot according to the moment compensation value of the end joint and a moment expected value, so that the accuracy of the gait control of the robot is not high.
Disclosure of Invention
In view of this, the embodiments of the present application provide a method, an apparatus, a robot, and a storage medium for controlling movement of a robot, which can improve accuracy of gait control of the robot.
A first aspect of an embodiment of the present application provides a motion control method for a robot, including:
Acquiring a preset attitude angle expected value of a robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generating a preset attitude angle deviation value;
The outer ring controller is preset, the deviation value of the preset attitude angle is obtained, the expected value of the zero moment point of the robot is calculated, and the outer ring controller is a PD-variable controller;
Acquiring a zero moment point expected value of the robot, acquiring a zero moment point measured value of the robot, and generating a zero moment point deviation value;
The preset inner ring controller obtains the zero moment point deviation value and calculates a moment compensation value of the tail end joint of the robot;
Acquiring a moment compensation value of a tail end joint of the robot and a moment expected value obtained through gait planning of the robot, and generating a moment deviation value;
the moment offset value is provided to an end joint actuator of the robot to control gait motion of the robot.
In one possible implementation manner, the outer ring controller calculates a zero order value of a zero moment expected value, a first order value of the zero moment expected value and a second order value of the zero moment expected value at the current moment according to a preset attitude angle expected value, a preset attitude angle feedback value at the current moment, a first order output value of the outer ring controller at the previous moment, and a first derivative of the preset attitude angle feedback value obtained after performing first derivative processing on the preset attitude angle feedback value at the current moment, and takes the zero order value of the zero moment expected value and the second order value of the zero moment expected value as output of the outer ring controller at the next moment.
In one possible implementation manner, the inner ring controller is a variable PD controller, the inner ring controller receives the desired value of the zero moment point output by the outer ring controller, calculates the zero moment value of the moment compensation value at the current moment, the first moment value of the moment compensation value and the second moment value of the moment compensation value according to the desired value of the zero moment point, the measured value of the zero moment point at the current moment, the first-order output value of the inner ring controller at the previous moment, the first derivative of the measured value of the zero moment obtained after the first derivative processing of the measured value of the zero moment point at the current moment, and the first-order value of the moment compensation value and the second-order value of the moment compensation value as the output of the inner ring controller at the next moment.
In one possible implementation manner, the inner loop controller is an active disturbance rejection controller, and a tracking differentiator of the inner loop controller receives the desired value of the zero moment point output by the outer loop controller and outputs a zero order value and a first order value of the desired value of the zero moment point; the extended state observer of the inner loop controller receives the zero moment point measurement value and outputs a zero moment point feedback value after extended observation processing; the nonlinear state error feedback device of the inner loop controller receives the zero-order value and the first-order value of the zero moment point expected value, receives the zero moment point feedback value and outputs the moment compensation value.
In one possible implementation, the zero moment point measurement of the robot is obtained by detecting the contact force of the robot with the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force of the robot with the ground or is obtained through calculation of robot dynamics.
In one possible implementation, the preset attitude angle is a forward pitch attitude angle, and the moment compensation value of the end joint is a moment compensation value of a forward joint, so as to control the motion of the forward joint of the robot.
In one possible implementation, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint is a moment compensation value of a lateral joint, so as to control the motion of the lateral joint of the robot.
A second aspect of an embodiment of the present application provides a motion control apparatus of a robot, including:
the first acquisition module is used for acquiring a preset attitude angle expected value of the robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generating a preset attitude angle deviation value;
The first calculation module is used for presetting an outer ring controller to obtain the preset attitude angle deviation value and calculating a zero moment point expected value of the robot, wherein the outer ring controller is a PD-variable controller;
The second acquisition module is used for acquiring the expected value of the zero moment point of the robot, acquiring the measured value of the zero moment point of the robot and generating a deviation value of the zero moment point;
The second calculation module is used for presetting an inner ring controller to obtain the zero moment point deviation value and calculating a moment compensation value of the tail end joint of the robot;
The third acquisition module is used for acquiring a moment compensation value of the tail end joint of the robot and a moment expected value obtained through gait planning of the robot and generating a moment deviation value;
And the control module is used for providing the moment deviation value for an end joint actuator of the robot so as to control gait movement of the robot.
In one possible implementation manner, the first computing module is specifically configured to:
The outer ring controller calculates a zero order value of a zero moment point expected value, a first order value of the zero moment point expected value and a second order value of the zero moment point expected value at the current moment according to a preset attitude angle expected value, a preset attitude angle feedback value at the current moment, a first order output value of the outer ring controller at the previous moment and a first derivative of the preset attitude angle feedback value obtained after the first derivative treatment is carried out on the preset attitude angle feedback value at the current moment, and takes the zero order value of the zero moment point expected value and the second order value of the zero moment point expected value as output of the outer ring controller at the next moment.
In one possible implementation manner, the inner loop controller is a variable PD controller, and the second calculation module is specifically configured to:
the inner ring controller receives the expected zero moment value output by the outer ring controller, calculates the zero order value of the moment compensation value at the current moment, the first order value of the moment compensation value and the second order value of the moment compensation value according to the expected zero moment value, the zero moment measured value at the current moment, the first order output value of the inner ring controller at the previous moment and the first derivative of the zero moment measured value obtained after the first derivative processing of the zero moment measured value at the current moment, and takes the zero order value of the moment compensation value as the output of the inner ring controller and takes the first order value of the moment compensation value and the second order value of the moment compensation value as the input of the inner ring controller at the next moment.
In one possible implementation manner, the inner loop controller is an active disturbance rejection controller, and the second calculation module is specifically configured to:
The tracking differentiator of the inner ring controller receives the expected value of the zero moment point output by the outer ring controller and outputs a zero order value and a first order value of the expected value of the zero moment point; the extended state observer of the inner loop controller receives the zero moment point measurement value and outputs a zero moment point feedback value after extended observation processing; the nonlinear state error feedback device of the inner loop controller receives the zero-order value and the first-order value of the zero moment point expected value, receives the zero moment point feedback value and outputs the moment compensation value.
In one possible implementation, the zero moment point measurement of the robot is obtained by detecting the contact force of the robot with the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force of the robot with the ground or is obtained through calculation of robot dynamics.
In one possible implementation, the preset attitude angle is a forward pitch attitude angle, and the moment compensation value of the end joint is a moment compensation value of a forward joint, so as to control the motion of the forward joint of the robot.
In one possible implementation, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint is a moment compensation value of a lateral joint, so as to control the motion of the lateral joint of the robot.
A third aspect of an embodiment of the present application provides a robot, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the method for controlling movement of a robot according to the first aspect when executing the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of controlling movement of a robot as described in the first aspect above.
A fifth aspect of an embodiment of the application provides a computer program product for, when run on a terminal device, causing the terminal device to perform the method of controlling movement of a robot as described in any of the first aspects above.
Compared with the prior art, the embodiment of the application has the beneficial effects that: the method comprises the steps of obtaining a preset attitude angle expected value of a robot and a preset attitude angle feedback value of the robot detected by a preset inertia measurement sensor of the robot, generating a preset attitude angle deviation value, obtaining the preset attitude angle deviation value by a preset outer ring controller, calculating a zero moment expected value of the robot, obtaining the zero moment expected value of the robot, obtaining a zero moment measured value of the robot by the outer ring controller, generating a zero moment deviation value, obtaining the zero moment deviation value by a preset inner ring controller, and calculating a moment compensation value of a tail end joint of the robot. The moment compensation value of the tail end joint of the robot is calculated through the preset attitude angle feedback value and the zero moment point measured value, the coupling relation of the preset attitude angle feedback value and the zero moment point measured value is combined, and the zero moment point is an important index for the robot to walk stably, so that the accuracy of the calculated moment compensation value is improved compared with the moment compensation value of the tail end joint of the robot calculated through the attitude angle feedback value. Meanwhile, the PD-variable controller is adopted to calculate the expected value of the zero moment point of the robot, so that the contradiction between the response overshoot and the response rapidity is solved, and the accuracy of the expected value of the zero moment point of the output is improved. After the output torque compensation value is calculated, the torque compensation value of the tail end joint of the robot and the torque expected value obtained through the gait planning of the robot are obtained, the torque deviation value is generated, and the torque deviation value is provided for the tail end joint actuator of the robot so as to control the gait movement of the robot, so that the accuracy of the gait control of the robot is improved.
Drawings
Fig. 1 is a schematic implementation flow chart of a motion control method of a robot according to an embodiment of the present application;
fig. 2 is a schematic view of a coordinate system of a robot according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a method for controlling motion of a robot according to an embodiment of the present application;
FIG. 4 is a flowchart of an active disturbance rejection control algorithm provided by an embodiment of the present application;
FIG. 5 is a flowchart of a method for controlling motion of a robot according to an embodiment of the present application;
fig. 6 is a specific flowchart of a motion control method of a robot according to another embodiment of the present application;
FIG. 7 is a schematic view of a motion control apparatus of a robot according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a robot according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to illustrate the technical scheme of the application, the following description is made by specific examples.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application, the terms "first," "second," "third," etc. are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
The existing motion control method of the robot generally calculates a moment compensation value of a foot joint of the robot according to the measured attitude angle information of the robot, and plans the gait of the robot according to the moment compensation value of the foot joint and a moment expected value, wherein the gait planning accuracy is not high.
Therefore, the application provides a motion control method of a robot, which can improve the accuracy of gait control of the robot.
The motion control method of the robot provided by the application is exemplified below.
Referring to fig. 1, a motion control method of a robot according to an embodiment of the present application includes:
S101: acquiring a preset attitude angle expected value of a robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generating a preset attitude angle deviation value.
The preset attitude angle is a forward pitch attitude angle or a side roll attitude angle, as shown in fig. 2, and in the robot coordinate system, the forward pitch attitude angle is an offset angle of the robot along the front-rear direction, that is, an offset angle of the robot on a xoz plane. The lateral rolling attitude angle is the offset angle of the robot along the left-right direction, namely the offset angle of the robot on the yoz plane. The expected value of the preset attitude angle of the robot is set according to the state of the robot, for example, if the robot is required to stand on the ground with feet, the expected value of the preset attitude angle can be 0. The preset attitude angle deviation value is the difference value between the expected value of the preset attitude angle and the feedback value of the preset attitude angle.
S102: and acquiring the preset attitude angle deviation value by a preset outer ring controller and calculating a zero moment point expected value of the robot, wherein the outer ring controller is a PD-variable controller.
The zero moment point is a coordinate value, and may be a y-axis coordinate value or an x-axis coordinate value in the robot coordinate system shown in fig. 2. And if the preset attitude angle is a forward pitching attitude angle, the zero moment point is an x-axis coordinate value, and if the preset attitude angle is a side rolling attitude angle, the zero moment point is a y-axis coordinate value. As shown in fig. 3, a preset attitude angle deviation value is calculated according to a preset attitude angle expected value θ d and a preset attitude angle measurement value θ, and is input into an outer ring controller, and the outer ring controller outputs a zero moment point expected value p d of the robot. A variable PD controller (i.e., VPD controller) is a controller that employs a VPD algorithm.
In one possible implementation, the preset attitude angle deviation value is input into a VPD algorithm model of the outer ring controller, and the zero moment point expected value of the robot is output.
In another possible implementation manner, the process of calculating the expected value of the zero moment point of the robot by the outer ring controller according to the deviation value of the set attitude angle is as follows: the outer ring controller calculates a zero order value of a zero moment point expected value at the current moment, a first order value of the zero moment point expected value and a second order value of the zero moment point expected value according to a preset attitude angle expected value at the current moment, a preset attitude angle feedback value at the current moment, a first order output value of the outer ring controller at the previous moment and a first order derivative of the preset attitude angle feedback value obtained after the first derivative processing is carried out on the preset attitude angle feedback value at the current moment, and takes the zero order value of the zero moment point expected value and the second order value of the zero moment point expected value as output of the outer ring controller at the next moment. And the outer ring controller calculates the zero order value, the first order value and the second order value of the zero moment expected value at the next moment according to the first order value of the zero moment expected value at the current moment, the second order value of the zero moment expected value at the current moment, the preset attitude angle expected value at the next moment and the preset attitude angle feedback value at the next moment.
In one possible implementation, the VPD algorithm is defined as:
Wherein k represents an integer greater than or equal to 0, k' represents an integer greater than or equal to 0, v d (k) and vel (k) represent input values at the kth time, v (k) represents feedback values at the kth time, The first derivative process performed on the feedback value v (k) is represented by vel (k') representing the first-order output value at the kth time, dt representing the integration step (period), k p、kd and k v representing the error gain parameter, respectively, and u representing the output value at the kth time. When k=0, v (k) =0,/>v(k)＝0。
Compared with the traditional PID algorithm, the VPD algorithm can effectively solve the contradiction between the rapidity and overshoot of the response.
Correspondingly, the method for calculating the expected value of the zero moment point of the robot by the outer ring controller according to the preset attitude angle deviation value is as follows.
Taking a preset attitude angle expected value as an input value v d (k) at a kth moment, taking a preset attitude angle feedback value at a current moment as a feedback value v (k) at the kth moment, taking a first-order output value of an outer ring controller at the last moment as a vel (k), and taking a first derivative of the preset attitude angle feedback value obtained by performing first derivative processing on the preset attitude angle feedback value at the current moment as a first derivative of the preset attitude angle feedback valueSubstituting the value into the formula 1, and calculating pos (k '), wherein pos (k') is the expected value of the zero moment point at the current moment, namely the zero order value of the expected value of the zero moment point. According to equation 1, the first derivative vel (k ') of pos (k'), i.e., the first order value of the zero moment point desired value, can also be calculated. From vel (k '), the second derivative acc (k ') of pos (k '), i.e. the second value of the zero moment point desired value, can be further calculated. The first order value of the zero moment point expected value and the second order value of the zero moment point expected value are output by the outer loop controller as inputs to the outer loop controller at a next time.
Because the VPD algorithm is adopted, the contradiction between the response rapidity and the overshoot of the control method can be effectively solved, and therefore, the VPD controller adopting the VPD algorithm calculates the expected value of the zero moment point of the robot, and the accuracy of the calculation result can be improved.
S103: and acquiring a zero moment point expected value of the robot, acquiring a zero moment point measured value of the robot, and generating a zero moment point deviation value.
In one possible implementation, the zero moment point measurement value may be calculated according to a contact force between the robot and the ground, where the contact force between the robot and the ground is measured by a six-dimensional force sensor or a torque sensor of the robot, and the zero moment point measurement value is a coordinate value. Wherein the zero moment point expected value is related to the current pose of the robot, e.g. when a biped robot stands on one foot and only the right foot is grounded, the zero moment point expected value is located on the right foot of the robot. The zero moment point offset value is the difference between the desired value of the zero moment point and the measured value of the zero moment point.
S104: and acquiring the zero moment point deviation value by a preset inner ring controller and calculating to obtain a moment compensation value of the tail end joint of the robot.
As shown in fig. 3, the inner loop controller calculates a moment compensation value τ c of the last foot joint of the robot from the zero moment point desired value pd and the zero moment point measured value p. The moment compensation value of the end joint of the robot is the moment compensation value of the forward joint or the moment compensation value of the lateral joint. The moment compensation value of the forward joint is used for controlling the movement of the forward joint of the robot, and the moment compensation value of the lateral joint is used for controlling the movement of the lateral joint of the robot.
If the preset attitude angle is a forward pitching attitude angle, the moment compensation value of the tail end joint is the moment compensation value of the forward joint, namely the moment compensation value of the robot on the xoz plane; if the preset attitude angle is the lateral rolling attitude angle, the moment compensation value of the tail end joint is the moment compensation value of the lateral joint, namely the moment compensation value of the robot on the yoz plane.
The inner loop controller may be an active disturbance rejection controller (Active Disturbance Rejection Control, abbreviated as ADRC), or may be a VPD controller, where ADRC is a controller that uses ADRC algorithm.
In one possible implementation, the inner loop controller is a VPD controller, the zero moment point deviation value is input into a VPD algorithm model of the inner loop controller, and the moment compensation value of the end joint of the robot is output.
In one possible implementation, the inner loop controller is a VPD controller, and the process of calculating the moment compensation value of the end joint of the robot according to the zero moment point deviation value by the inner loop controller is as follows: the inner ring controller receives the expected zero moment value output by the outer ring controller, calculates the zero order value of the moment compensation value at the current moment, the first order value of the moment compensation value and the second order value of the moment compensation value according to the expected zero moment value, the zero moment measured value at the current moment, the first order output value of the inner ring controller at the previous moment and the first derivative of the zero moment measured value obtained after the first derivative processing of the zero moment measured value at the current moment, and takes the zero order value of the moment compensation value as the output of the inner ring controller and takes the first order value of the moment compensation value and the second order value of the moment compensation value as the input of the inner ring controller at the next moment. The inner loop controller calculates the zero order value of the moment compensation value at the next moment, the first order value of the moment compensation value and the second order value of the moment compensation value according to the first order value of the moment compensation value at the current moment, the second order value of the moment compensation value at the current moment, the expected zero moment point value at the next moment and the measured zero moment point value at the next moment.
If the VPD algorithm described in equation 1 is adopted, the method for calculating the moment compensation value of the end joint of the robot by the inner loop controller according to the zero moment point deviation value is as follows. Taking a desired value of a zero moment point as an input value v d (k) at a kth moment, taking a measured value of the zero moment point at a current moment as a feedback value v (k) at the kth moment, taking a first-order output value of an inner loop controller at the last moment as vel (k), and taking a first derivative of the measured value of the zero moment point obtained by performing first derivative processing on the measured value of the zero moment point at the current moment as a first derivativeSubstituting the value into the formula 1 to calculate pos (k '), and then pos (k') is the moment compensation value at the current moment, namely the zero order value of the moment compensation value. According to equation 1, the first derivative vel (k ') of pos (k'), i.e., the first order value of the torque compensation value, can also be calculated. From vel (k '), the second derivative acc (k ') of pos (k '), i.e. the second value of the torque compensation value, can be further calculated. The first order value of the torque compensation value and the second order value of the torque compensation value are output by the inner ring controller and serve as inputs of the inner ring controller at the next moment.
Because the VPD algorithm is adopted, the contradiction between the response rapidity and the overshoot of the control method can be effectively solved, the moment compensation value of the tail end joint of the robot is calculated by adopting the VPD algorithm, and the accuracy of the calculation result can be improved.
In one possible implementation, the inner loop controller is an ADRC, the zero moment point deviation value of the robot is input into an ADRC algorithm model of the inner loop controller, and the moment compensation value of the end joint of the robot is output.
In another possible implementation, the inner loop controller is ADRC, and the process of calculating the moment compensation value of the end joint of the robot according to the zero moment point offset value by the inner loop controller is: the tracking differentiator of the inner loop controller receives the desired value of the zero moment point output by the outer loop controller and outputs a zero order value and a first order value of the desired value of the zero moment point. The extended state observer of the inner loop controller receives the zero moment point measurement value and outputs a zero moment point feedback value after extended observation processing, wherein the extended observation processing comprises but is not limited to smoothing and filtering processing. The nonlinear state error feedback device of the inner loop controller receives the zero-order value and the first-order value of the zero moment point expected value, receives the zero moment point feedback value and outputs the moment compensation value.
In one possible implementation, the calculation flow of the ADRC algorithm is shown in fig. 4, and the ADRC algorithm includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback.
The tracking differentiator corresponds to the formula
Wherein k represents an integer greater than or equal to 0, v (k) represents an input value of the kth time tracking differentiator, h represents an integration step size (period), and r represents a tracking factor; v 1 (k) and v 2 (k) represent the output values of the tracking differentiator at the kth time, v 1(k)＝0,v2(k)＝0;fhan(m,v2 (k), r, h represent a nonlinear function of m, v 2 (k), r, h when k=0, fhan (m, v 2 (k), r, h) are defined as
Sign represents a mathematical sign function.
The fhan function can solve the problem of high-frequency oscillation generated when the system enters a steady state after direct discretization.
The corresponding formula of the extended state observer is
Where y (k) represents a feedback value at the kth time and also represents an input value at the kth time of the extended state observer, b 0 represents a control input coefficient, h represents an integration step (period), δ represents a filter factor, β 1、β2 and β 3 each represent an output error gain parameter, z 1(k)、z2(k)、z3 (k) represents an output value at the kth time of the extended state observer, and when k=0, z 1(k)、z2(k)、z3 (k) are both 0.
Fal (e, α, δ) is a nonlinear function, and fal (e, α, δ) is defined as:
where fal (e, 0.5, δ) represents the value of the nonlinear function when α=0.5, and fal (e, 0.25, δ) represents the value of the nonlinear function when α=0.25.
The nonlinear state error feedback device has the formula of
Where α 1 and α 2 each represent a constant between [0,1], γ 1 and γ 2 are error gain parameters, respectively, fal (n 1,α1, δ) represents a value of a nonlinear function when e=n 1、α＝α1, fal (n 2,α2, δ) represents a value of a nonlinear function when e=n 2、α＝α2, and u 0 represents an output value of the nonlinear state error feedback device at the kth time.
After obtaining the output value of the error feedback device at the kth time, the following formula is adopted
U=u 0-z3(k)/b0 (equation 5)
The value u of the input control object at the kth moment is calculated, and u is also the output value of the ADRC algorithm at the kth moment. The control object is a device that performs further calculation based on the input value u, for example, the control object is an end joint actuator of the robot, and the end joint actuator plans the gait of the robot based on the input value.
Correspondingly, the method of calculating the moment compensation value of the end joint of the robot by the inner ring controller is as follows.
Taking the zero moment point expected value as the input value v (k) at the kth time of the tracking differentiator, v 1 (k) and v 2 (k) are calculated according to formula 2, v 1 (k) represents the zero order value of the zero moment point expected value, and v 2 (k) represents the first order value of the zero moment point expected value. Taking the measured value of the zero moment point as a feedback value y (k) of the kth moment of the extended state observer, and calculating z 1(k)、z2 (k) and z 3 (k) according to the formula 3, then z 1(k)、z2 (k) and z 3 (k) are zero moment point feedback values. The nonlinear state error feedback device receives the zero order value and the first order value of the expected value of the zero moment point, receives z 1 (k) and z 2 (k) in the feedback value of the zero moment point, calculates u 0 according to a formula 4, and finally calculates u according to z 3 (k) and a formula 5, wherein u is a moment compensation value. Because the observation value of z 3(k),z3 (k) representing the total disturbance is introduced into the ADRC algorithm, disturbance errors of measured values of zero moment points can be compensated by calculating the compensation value of the moment of the foot joint according to the formula 5 and z 3 (k), and the accuracy of the output compensation value of the moment of the foot joint is improved.
S105: and acquiring a moment compensation value of the tail end joint of the robot and a moment expected value obtained through gait planning of the robot, and generating a moment deviation value.
The moment expected value is obtained when the gait of the robot is planned in advance, and can be the moment expected value of the tail end joint on the yoz plane or the moment expected value of the foot tail end joint on the xoz plane. The torque offset value is the difference between the torque expected value and the torque compensation value.
In one possible implementation, a gait planning strategy is obtained in advance, and the expected value of the moment of the end joint of the robot is determined according to the gait planning strategy. For example, a walking route of the robot is determined according to the current position of the robot and the position to be reached, a gait planning strategy is determined according to the walking route, and the expected value of the moment of the tail end joint of the robot at each moment is determined according to the gait planning strategy.
S106: the moment offset value is provided to an end joint actuator of the robot to control gait motion of the robot.
As shown in fig. 3, the torque compensation value τ c and the torque desired value τ d are provided to the actuator to control the gait motion of the robot. The torque compensation value provided to the actuator comprises a torque compensation value on a yoz plane and a torque compensation value on a xoz plane, the torque expected value provided to the actuator comprises a torque expected value on a yoz plane and a torque expected value on a xoz plane, and the actuator can be a steering engine.
Specifically, the moment compensation value of the end joint of the robot on the yoz plane is added with the moment expected value of the end joint on the yoz plane, the moment compensation value of the end joint on the xoz plane is added with the moment expected value of the end joint on the xoz plane, and the final moment of the end joint on the yoz plane and the moment on the xoz plane are obtained, and the gait of the robot is controlled according to the final moment of the end joint on the yoz plane and the final moment on the xoz plane.
In the above embodiment, the preset attitude angle expected value of the robot and the preset attitude angle feedback value of the robot detected by the preset inertia measurement sensor of the robot are obtained, the preset outer ring controller obtains the preset attitude angle deviation value and calculates the zero moment expected value of the robot, the outer ring controller is a PD-variable controller, the zero moment expected value of the robot and the zero moment measured value of the robot are obtained, the zero moment deviation value is generated, and the preset inner ring controller obtains the zero moment deviation value and calculates the moment compensation value of the end joint of the robot. The moment compensation value of the tail end joint of the robot is calculated through the preset attitude angle feedback value and the zero moment point measured value, the coupling relation of the preset attitude angle feedback value and the zero moment point measured value is combined, and the zero moment point is an important index for the robot to walk stably, so that the accuracy of the calculated moment compensation value is improved compared with the moment compensation value of the tail end joint of the robot calculated through the attitude angle feedback value. Meanwhile, the PD-variable controller is adopted to calculate the expected value of the zero moment point of the robot, so that the contradiction between the response overshoot and the response rapidity is solved, and the accuracy of the expected value of the zero moment point of the output is improved. After the output torque compensation value is calculated, the torque compensation value of the tail end joint of the robot and the torque expected value obtained through the gait planning of the robot are obtained, the torque deviation value is generated, and the torque deviation value is provided for the tail end joint actuator of the robot so as to control the gait movement of the robot, so that the accuracy of the gait control of the robot is improved.
In one embodiment, the outer loop controller is a VPD controller and the inner loop controller is a VPD controller. Correspondingly, as shown in fig. 5, the specific flow of the motion control method of the robot is that firstly, the first derivative of the attitude angle expected value theta yd on the yoz plane and the attitude angle measurement value theta y、θy on the yoz plane are obtainedAnd inputting the output value u 1,u1 into an outer ring controller, wherein the outer ring controller calculates the output value u 1,u1 by adopting a VPD algorithm, namely the expected value o yd of the y-axis coordinate in the expected value of the zero moment point of the robot. The expected value of the y-axis coordinate, p yd, the measured value of the y-axis coordinate, p y, and the first derivative/>, of p y are then calculatedThe output value u 2,u2 is calculated by the inner ring controller by adopting the VPD algorithm, namely the torque compensation value tau cy on the yoz plane. The torque compensation value τ cx on the plane xoz is calculated by the same method. Finally, the moment compensation values tau cy on the yoz plane, the moment compensation value tau cx on the xoz plane and the corresponding moment expected value tau dy、τdx are input into the actuator to control the gait of the robot.
In the embodiment, the outer ring controller adopts the VPD algorithm, and the inner ring controller adopts the VPD algorithm, so that the contradiction between the response rapidity and the overshoot of the control method can be solved when the expected value of the zero moment point of the robot and the moment compensation value of the tail end joint of the robot are calculated, and the gait planning accuracy of the robot is improved.
In another embodiment, the outer loop controller is a VPD controller and the inner loop controller is an ADRC. Correspondingly, as shown in fig. 6, the specific flow of the motion control method of the robot is that firstly, the desired attitude angle value theta yd on the yoz plane and the first derivative of the attitude angle measurement value theta y、θy on the yoz plane are calculatedAnd inputting the output value u 3,u3 into an outer ring controller, wherein the outer ring controller calculates the output value u 3,u3 by adopting a VPD algorithm, namely the expected value o yd of the y-axis coordinate in the expected value of the zero moment point of the robot. Then inputting the expected value o yd of the y-axis coordinate into an inner loop controller, adopting an ADRC algorithm by the inner loop controller, taking p yd as the input value of a tracking differentiator in the ADRC algorithm, outputting v 1 and v 2, taking the measured value p y of the y-axis coordinates in the zero moment point measured value as the input value of the extended state observer, outputting z 1、z2 and z 3, calculating u 0 according to v 1、v2、Z1、z2, And finally, calculating an output value u 4,u4 according to u 0 to obtain a moment compensation value tau cy on the yoz plane. The torque compensation value τ cx on the plane xoz is calculated by the same method. Finally, the moment compensation values T cy and T cx on the yoz plane and the moment expected value T dy、τdx on the xoz plane are input into the actuator to control the gait of the robot.
In the embodiment, the outer ring controller adopts the VPD algorithm, the inner ring controller adopts the ADRC algorithm, the contradiction between the rapidity and the overshoot of the control method in response can be solved when the zero moment expected value of the robot is calculated, and the disturbance error is compensated when the moment compensation value of the tail end joint of the robot is calculated, so that the accuracy of gait planning of the robot is improved.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
Corresponding to the method for controlling the movement of the robot described in the above embodiments, fig. 7 shows a block diagram of the apparatus for controlling the movement of the robot according to the embodiment of the present application, and for convenience of explanation, only the parts related to the embodiment of the present application are shown.
As shown in fig. 7, the motion control apparatus of the robot includes,
A first obtaining module 10, configured to obtain a preset attitude angle expected value of a robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generate a preset attitude angle deviation value;
The first calculation module 20 is configured to preset an outer ring controller to obtain the preset attitude angle deviation value and calculate a zero moment point expected value of the robot, where the outer ring controller is a variable PD controller;
A second obtaining module 30, configured to obtain a desired value of a zero moment point of the robot, obtain a measured value of the zero moment point of the robot, and generate a deviation value of the zero moment point;
the second calculation module 40 is configured to preset the inner ring controller to obtain the zero moment point offset value and calculate a moment compensation value of the end joint of the robot;
the third obtaining module 50 is configured to obtain a torque compensation value of an end joint of the robot and a torque expected value obtained through gait planning of the robot, and generate a torque deviation value;
A control module 60 for providing the moment offset value to an end joint actuator of the robot to control gait movements of the robot.
In one possible implementation, the first computing module 20 is specifically configured to:
The outer ring controller calculates a zero order value of a zero moment point expected value, a first order value of the zero moment point expected value and a second order value of the zero moment point expected value at the current moment according to a preset attitude angle expected value, a preset attitude angle feedback value at the current moment, a first order output value of the outer ring controller at the previous moment and a first derivative of the preset attitude angle feedback value obtained after the first derivative treatment is carried out on the preset attitude angle feedback value at the current moment, and takes the zero order value of the zero moment point expected value and the second order value of the zero moment point expected value as output of the outer ring controller at the next moment.
In one possible implementation manner, the inner loop controller is a variable PD controller, and the second computing module 40 is specifically configured to:
the inner ring controller receives the expected zero moment value output by the outer ring controller, calculates the zero order value of the moment compensation value at the current moment, the first order value of the moment compensation value and the second order value of the moment compensation value according to the expected zero moment value, the zero moment measured value at the current moment, the first order output value of the inner ring controller at the previous moment and the first derivative of the zero moment measured value obtained after the first derivative processing of the zero moment measured value at the current moment, and takes the zero order value of the moment compensation value as the output of the inner ring controller and takes the first order value of the moment compensation value and the second order value of the moment compensation value as the input of the inner ring controller at the next moment.
In one possible implementation manner, the inner loop controller is an active-disturbance-rejection controller, and the second calculating module 40 is specifically configured to:
The tracking differentiator of the inner ring controller receives the expected value of the zero moment point output by the outer ring controller and outputs a zero order value and a first order value of the expected value of the zero moment point; the extended state observer of the inner loop controller receives the zero moment point measurement value and outputs a zero moment point feedback value after extended observation processing; the nonlinear state error feedback device of the inner loop controller receives the zero-order value and the first-order value of the zero moment point expected value, receives the zero moment point feedback value and outputs the moment compensation value.
In one possible implementation, the zero moment point measurement of the robot is obtained by detecting the contact force of the robot with the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force of the robot with the ground or is obtained through calculation of robot dynamics.
In one possible implementation, the preset attitude angle is a forward pitch attitude angle, and the moment compensation value of the end joint is a moment compensation value of a forward joint, so as to control the motion of the forward joint of the robot.
In one possible implementation, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint is a moment compensation value of a lateral joint, so as to control the motion of the lateral joint of the robot.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.
Fig. 8 is a schematic structural diagram of a robot according to an embodiment of the present application. As shown in fig. 8, the robot of this embodiment includes: a processor 11, a memory 12, and a computer program 13 stored in the memory 12 and executable on the processor 11. The processor 11, when executing the computer program 13, implements the steps in the above-described embodiment of the method for controlling the motion of the robot, such as steps S101 to S106 shown in fig. 1. Or the processor 11 when executing the computer program 13 performs the functions of the modules/units of the above-described device embodiments, such as the functions of the first acquisition module 10 to the control module 60 shown in fig. 7.
Illustratively, the computer program 13 may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 11 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 13 in the terminal device.
It will be appreciated by those skilled in the art that fig. 8 is merely an example of a robot and is not limiting of the robot, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the robot may also include input and output devices, network access devices, buses, etc.
The Processor 11 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 12 may be an internal storage unit of the robot, such as a hard disk or a memory of the robot. The memory 12 may also be an external storage device of the robot, such as a plug-in hard disk, a smart memory Card (SMART MEDIA CARD, SMC), a Secure Digital (SD) Card, a flash memory Card (F1 ash Card) or the like, which are provided on the robot. Further, the memory 12 may also include both an internal memory unit and an external memory device of the robot. The memory 12 is used for storing the computer program as well as other programs and data required by the robot. The memory 12 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. A method of controlling movement of a robot, comprising:
Acquiring a preset attitude angle expected value of a robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generating a preset attitude angle deviation value;
the outer ring controller is preset, the deviation value of the preset attitude angle is obtained, the expected value of the zero moment point of the robot is calculated, and the outer ring controller is a PD-variable controller; the variable PD controller is a controller adopting a VPD algorithm, wherein the VPD algorithm is defined as follows:
Wherein k represents an integer greater than or equal to 0, k' represents an integer greater than or equal to 0, v d (k) and vel (k) represent input values at the kth time, v (k) represents feedback values at the kth time, Representing the first derivative process performed on v (k), vel (k') representing the first order output value at the kth time, dt representing the integration step size, k p、kd and k v representing the error gain parameter, respectively, u representing the output value at the kth time;
Acquiring a zero moment point expected value of the robot, acquiring a zero moment point measured value of the robot, and generating a zero moment point deviation value;
The preset inner ring controller obtains the zero moment point deviation value and calculates a moment compensation value of the tail end joint of the robot;
Acquiring a moment compensation value of a tail end joint of the robot and a moment expected value obtained through gait planning of the robot, and generating a moment deviation value;
the moment offset value is provided to an end joint actuator of the robot to control gait motion of the robot.
2. The method according to claim 1, wherein the outer ring controller calculates a zero order value of a zero moment point expected value, a first order value of the zero moment point expected value, a second order value of the zero moment point expected value, and a zero order value of the zero moment point expected value as an output of the outer ring controller, and outputs the first order value of the zero moment point expected value and the second order value of the zero moment point expected value as an input of the outer ring controller at a next time, based on the preset attitude angle expected value, the preset attitude angle feedback value at a current time, the first order output value of the outer ring controller at a previous time, and the first derivative of the preset attitude angle feedback value at the current time, which is obtained after the first derivative processing.
3. The method according to claim 1 or 2, wherein the inner ring controller is a variable PD controller, the inner ring controller receives a zero moment expected value output by the outer ring controller, calculates a zero order value of a moment compensation value at a current time, a first order value of a moment compensation value, a second order value of a moment compensation value, and outputs the zero order value of the moment compensation value as an output of the inner ring controller at a next time based on the zero moment expected value, a zero moment measured value at a current time, a first order output value of the inner ring controller at a previous time, a first order derivative of the zero moment measured value obtained by performing a first derivative process on the zero moment measured value at the current time, and the second order value of the moment compensation value.
4. The method of motion control of a robot according to claim 1 or 2, wherein the inner loop controller is an active disturbance rejection controller, and a tracking differentiator of the inner loop controller receives the desired value of the zero moment point output by the outer loop controller and outputs a zero order value and a first order value of the desired value of the zero moment point; the extended state observer of the inner loop controller receives the zero moment point measurement value and outputs a zero moment point feedback value after extended observation processing; the nonlinear state error feedback device of the inner loop controller receives the zero-order value and the first-order value of the zero moment point expected value, receives the zero moment point feedback value and outputs the moment compensation value.
5. The method of claim 1, wherein the zero moment point measurement of the robot is calculated from the contact force of the robot with the ground or calculated from the robot dynamics by detecting the contact force of the robot with the ground by a six-dimensional force sensor of the robot.
6. The method of claim 1, wherein the preset attitude angle is a forward pitch attitude angle, and the moment compensation value of the distal joint of the robot is a moment compensation value of a forward joint of the robot to control the movement of the forward joint of the robot.
7. The method of claim 1, wherein the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the distal joint of the robot is a moment compensation value of a lateral joint of the robot to control the movement of the lateral joint of the robot.
8.A motion control apparatus of a robot, comprising:
the first acquisition module is used for acquiring a preset attitude angle expected value of the robot and a preset attitude angle feedback value of the robot detected by a preset inertial measurement sensor of the robot, and generating a preset attitude angle deviation value;
The first calculation module is used for presetting an outer ring controller to obtain the preset attitude angle deviation value and calculating a zero moment point expected value of the robot, wherein the outer ring controller is a PD-variable controller; the variable PD controller is a controller adopting a VPD algorithm, wherein the VPD algorithm is defined as follows:
Wherein k represents an integer greater than or equal to 0, k' represents an integer greater than or equal to 0, v d (k) and vel (k) represent input values at the kth time, v (k) represents feedback values at the kth time, Representing the first derivative process performed on v (k), vel (k') representing the first order output value at the kth time, dt representing the integration step size, k p、kd and k v representing the error gain parameter, respectively, u representing the output value at the kth time;
The second acquisition module is used for acquiring the expected value of the zero moment point of the robot, acquiring the measured value of the zero moment point of the robot and generating a deviation value of the zero moment point;
The second calculation module is used for presetting an inner ring controller to obtain the zero moment point deviation value and calculating a moment compensation value of the tail end joint of the robot;
The third acquisition module is used for acquiring a moment compensation value of the tail end joint of the robot and a moment expected value obtained through gait planning of the robot and generating a moment deviation value;
And the control module is used for providing the moment deviation value for an end joint actuator of the robot so as to control gait movement of the robot.
9. A robot comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the method according to any one of claims 1 to 7.
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