CN112650268A - Robot motion control method, device, robot and storage medium - Google Patents
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Abstract
The application is applicable to 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, wherein the outer ring controller is an active disturbance rejection controller; and the preset inner ring controller acquires the zero moment point deviation value and calculates to obtain a moment compensation value of the tail end joint of the robot. And after the moment compensation value is calculated, the moment compensation value and the moment expected value of the tail end joint of the robot are obtained, a moment deviation value is generated, and the moment deviation value is provided for a tail end joint actuator of the robot so as to control the gait motion of the robot. The gait control method and the gait control device combine the attitude angle feedback value and the zero moment point measurement value to control the gait of the robot, and accuracy of the gait control of the robot is improved.
Description
Technical Field
The present application relates to the field of robot control technologies, and in particular, to a method and an apparatus for controlling a motion of a robot, and a storage medium.
Background
A key problem in the research of the humanoid robot is that the walking speed is improved, the walking stability can be kept, and the stability of the humanoid robot during walking can be improved through reasonable gait control. The conventional gait control method of the robot generally comprises the steps of calculating a moment compensation value of a tail end joint of the robot according to attitude angle information of the robot obtained through measurement, and controlling the gait of the robot according to the moment compensation value and an expected value of the tail end joint, wherein the gait control accuracy of the robot is not high.
Disclosure of Invention
In view of this, embodiments of the present application provide a method and an apparatus for controlling a motion of a robot, and a storage medium, 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 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;
a preset outer ring controller obtains the preset attitude angle deviation value and calculates the expected value of the zero moment point of the robot, wherein the outer ring controller is an active disturbance rejection controller;
acquiring a zero moment point expected value and 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 to obtain 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;
providing the moment deviation value to an end joint actuator of the robot to control gait motions of the robot.
In a possible implementation manner, the outer-loop controller calculates a zero-order value and a first-order value of the preset attitude angle expected value according to the preset attitude angle expected value, and calculates a zero-moment point expected value of the robot according to the zero-order value and the first-order value of the preset attitude angle expected value and the preset attitude angle feedback value.
In a possible implementation manner, the inner ring controller is a variable PD controller, the inner ring controller receives a zero moment point expected value of the robot and a zero moment point measured value at a current time, a first order output value of the inner ring controller at a previous time, and a first derivative of the zero moment point measured value at the current time, calculates a zero order value of a moment compensation value of a terminal joint of the robot at the current time, a first order value of the moment compensation value, and a second order value of the moment compensation value, and uses the zero order value of the moment compensation value as an output of the inner ring controller, and uses the first order value of the moment compensation value and the second order value output of the moment compensation value as inputs of the inner ring controller at the next time.
In a possible implementation manner, the inner ring controller is an active disturbance rejection controller, and a tracking differentiator of the inner ring controller receives the zero moment point expected value of the robot output by the outer ring controller, and outputs a zeroth order value and a first order value of the zero moment point expected value of the robot; an extended state observer of the inner ring controller receives a zero moment point measured value of the robot and outputs a zero moment point feedback value after extended observation processing; and a nonlinear state error feedback device of the inner ring controller receives a zero-order value and a first-order value of a zero moment point expected value of the robot, receives a zero moment point feedback value and outputs a moment compensation value of a tail end joint of the robot.
In a possible implementation manner, the zero moment point measurement value of the robot is obtained by detecting the contact force between the robot and the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force between the robot and the ground or is calculated through robot dynamics.
In one possible implementation manner, the preset attitude angle is a forward pitch attitude angle, and the torque compensation value of the end joint of the robot is a torque compensation value of a forward joint of the robot, so as to control the motion of the forward joint of the robot.
In a possible implementation manner, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint of the robot is a moment compensation value of a lateral joint of the robot, so as to control the movement of the lateral joint of the robot.
A second aspect of an embodiment of the present application provides a motion control apparatus for a robot, including:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for 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 first calculation module is used for presetting an outer ring controller to obtain the preset attitude angle deviation value and calculating the zero moment point expected value of the robot, wherein the outer ring controller is an active disturbance rejection controller;
the second acquisition module is used for 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 second calculation module is used for presetting an inner ring controller to obtain the zero moment point deviation value and calculating to obtain a moment compensation value of a tail end joint of the robot;
the third acquisition module is used for 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;
and the control module is used for providing the moment deviation value for an end joint actuator of the robot so as to control the gait motion of the robot.
In a possible implementation manner, the first computing module is specifically configured to:
and the outer ring controller calculates a zero-order value and a first-order value of the preset attitude angle expected value according to the preset attitude angle expected value, and calculates a zero-moment point expected value of the robot according to the zero-order value and the first-order value of the preset attitude angle expected value and the preset attitude angle feedback value.
In a possible implementation manner, the inner-loop controller is a variable PD controller, and the second calculating module is specifically configured to: the inner ring controller receives a zero moment point expected value of the robot, a zero moment point measured value at the current moment, a first-order output value of the inner ring controller at the previous moment and a first derivative of the zero moment point measured value at the current moment, calculates a zero-order value of a moment compensation value, a first-order value of the moment compensation value and a second-order value of the moment compensation value of a tail end joint of the robot at the current moment, 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 output of the moment compensation value as the input of the inner ring controller at the next moment.
In a possible implementation manner, the inner-loop controller is an active disturbance rejection controller, and the second calculation module is specifically configured to: a tracking differentiator of the inner ring controller receives the expected value of the zero moment point of the robot 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 of the robot; an extended state observer of the inner ring controller receives a zero moment point measured value of the robot and outputs a zero moment point feedback value after extended observation processing; and a nonlinear state error feedback device of the inner ring controller receives a zero-order value and a first-order value of a zero moment point expected value of the robot, receives a zero moment point feedback value and outputs a moment compensation value of a tail end joint of the robot.
In a possible implementation manner, the zero moment point measurement value of the robot is obtained by detecting the contact force between the robot and the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force between the robot and the ground or is calculated through robot dynamics.
In one possible implementation manner, the preset attitude angle is a forward pitch attitude angle, and the torque compensation value of the end joint of the robot is a torque compensation value of a forward joint of the robot, so as to control the motion of the forward joint of the robot.
In a possible implementation manner, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint of the robot is a moment compensation value of a lateral joint of the robot, so as to control the movement of the lateral joint of the robot.
A third aspect of embodiments 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, wherein the processor, when executing the computer program, implements the motion control method of the robot according to the first aspect.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for controlling motion of a robot as described in the first aspect above.
A fifth aspect of embodiments of the present application provides a computer program product, which, when run on a terminal device, causes the terminal device to execute the method for controlling the motion of a robot according to any one of the first aspect.
Compared with the prior art, the embodiment of the application has the advantages that: 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 method 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, wherein the outer ring controller is an active disturbance rejection controller; acquiring a zero moment point expected value and a zero moment point measured value of the robot, and generating a zero moment point deviation value; and the preset inner ring controller acquires the zero moment point deviation value and calculates to obtain a moment compensation value of the 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 measurement value, and the zero moment point is an important index for stable walking of the robot. Meanwhile, the disturbance error of the preset attitude angle measurement value can be compensated by adopting the active disturbance rejection controller to calculate the expected value of the zero moment point of the robot body, and the accuracy of the output expected value of the zero moment point is improved. After the moment compensation value is calculated, the moment expected value of the tail end joint of the robot is obtained, a moment deviation value is generated, and the moment deviation value is provided for a tail end joint actuator of the robot so as to control the gait motion of the robot, so that the gait control accuracy of the robot is improved.
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Fig. 1 is a schematic implementation flowchart 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 provided in an embodiment of the present application;
fig. 3 is a schematic diagram illustrating a motion control method of a robot according to an embodiment of the present disclosure;
FIG. 4 is a flow chart of an active disturbance rejection control algorithm provided by an embodiment of the present application;
fig. 5 is a detailed flowchart of a method for controlling the motion of a robot according to an embodiment of the present disclosure;
fig. 6 is a detailed flowchart of a method for controlling the movement of a robot according to another embodiment of the present application;
fig. 7 is a schematic view of a motion control device of a robot according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a robot provided in 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 particular system structures, 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 explain the technical solution described in the present application, the following description will be given by way of specific examples.
It will 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 present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application 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 this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In addition, in the description of the present application, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
The existing robot motion control method generally calculates a moment compensation value of a foot joint of the robot according to attitude angle information of the robot obtained through measurement, and plans a gait of the robot according to the moment compensation value of the foot joint and an expected value, wherein the gait planning accuracy is not high.
Therefore, the application provides a motion control method of the robot, which can improve the gait planning accuracy of the robot.
The following is an exemplary description of a motion control method of a robot provided by the present application.
Referring to fig. 1, a method for controlling a motion of a robot according to an embodiment of the present application includes:
s101: the method comprises the steps of obtaining 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 preset attitude angle is a forward pitch attitude angle or a lateral roll attitude angle, as shown in fig. 2, in the robot coordinate system, the forward pitch attitude angle is a shift angle of the robot in the front-back direction, that is, a shift angle of the robot on the xoz plane. The lateral roll attitude angle is the offset angle of the robot in the left-right direction, namely the offset angle of the robot on the yoz plane. The preset attitude angle expected value of the robot is set according to the state of the robot, for example, if the robot needs to stand on the ground with both feet, the preset attitude angle expected value may be 0. The preset attitude angle deviation value is a difference value between a preset attitude angle expected value and a preset attitude angle feedback value.
S102: and a preset outer ring controller acquires the preset attitude angle deviation value and calculates the expected value of the zero moment point of the robot, wherein the outer ring controller is an active disturbance rejection controller.
The expected value of the zero moment point may be a coordinate value of the y axis or the x axis in the robot coordinate system shown in fig. 2. If the preset attitude angle is the forward pitching attitude angle, the zero moment point is the coordinate value of the x axis, and if the preset attitude isAnd if the attitude angle is a lateral rolling attitude angle, the zero moment point is a coordinate value of the y axis. As shown in fig. 3, according to the preset attitude angle expected value θdAnd calculating a preset attitude angle deviation value according to the preset attitude angle measurement value theta, inputting the preset attitude angle deviation value into an outer ring controller, and outputting a zero moment point expected value p of the robot by the outer ring controllerd. An Active Disturbance Rejection Control (ADRC) is a controller that employs an ADRC algorithm.
In a possible implementation mode, the preset attitude angle deviation value is input into an ADRC algorithm model of the outer ring controller, and the expected value of the zero moment point 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 preset attitude angle deviation value is as follows: and the outer ring controller calculates a zero-order value and a first-order value of the preset attitude angle expected value according to the preset attitude angle expected value, and calculates a zero-moment point expected value of the robot according to the zero-order value and the first-order value of the preset attitude angle expected value and a preset attitude angle feedback value. Specifically, a tracking differentiator of the outer ring controller receives a preset attitude angle expected value and outputs a zero-order value and a first-order value of the preset attitude angle expected value of the robot; an extended state observer of the outer ring controller receives a preset attitude angle feedback value of the robot and outputs a preset attitude angle observation value after extended observation processing, wherein the extended observation processing comprises but is not limited to smoothing and filtering processing; and a nonlinear state error feedback device of the outer ring controller receives a zero-order value and a first-order value of the preset attitude angle expected value, receives the preset attitude angle observed value and outputs a zero moment point expected value of the robot. 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 of 0 or more, and v (k) represents the k-thTracking the input value of the differentiator, h represents the integration step length (period), and r represents the tracking factor; v. of1(k) And v2(k) Denotes an output value at the k-th time of the tracking differentiator, and v is set to 0 when k is equal to 01(k)＝0，v2(k)＝0；fhan(m,v2(k) R, h) represents m, v2(k) R, a non-linear function of h, fhan (m, v)2(k) R, h) is defined as
The fhan function can solve the problem of high-frequency oscillation generated when the system enters a steady state after the function is directly discretized.
The extended state observer corresponds to the formula of
Wherein y (k) represents the feedback value at the k-th time and also represents the input value at the k-th time of the extended state observer, b0Representing the control input coefficient, h the integration step (period), delta the filter factor, beta1、β2And beta3Respectively representing the output error gain parameter, z1(k)、z2(k)、z3(k) Represents an output value at the k-th time of the extended state observer, and when k is 0, z is1(k)、z2(k)、z3(k) Are all 0.
fal (e, α, δ) is a non-linear function, defined as:
The nonlinear state error feedback has the formula
Wherein alpha is1And alpha2Are all [0,1 ]]Constant of between, gamma1And gamma2Respectively, an error gain parameter, fal (n)1,α1δ) denotes e ═ n1、α＝α1Value of the time non-linear function, fal (n)2,α2δ) denotes e ═ n2、α＝α2Value of the time non-linear function u0Representing the output value of the nonlinear state error feedback at time k.
After obtaining the output value of the error feedback device at the k-th time, the following formula is adopted
u＝u0-z3(k)/b0(formula 4)
The value u input to the controlled object at the k-th time is calculated, and u is also the output value at the k-th time of the ADRC algorithm. The control target is a device that performs further calculation based on the input value u, and for example, the control target is an actuator of the robot, and the actuator plans the gait of the robot based on the input value.
Correspondingly, the process that the outer ring controller calculates the expected value of the zero moment point of the robot according to the preset attitude angle deviation value comprises the following steps: taking a preset attitude angle expected value as an input value v (k) of a tracking differentiator at the k moment, and calculating v according to a formula 11(k) And v2(k) Then v is1(k) Zeroth order value, v, representing a preset attitude angle desired value2(k) And a first order value representing the preset attitude angle expected value. Taking a preset attitude angle feedback value as a feedback value y (k) of the extended state observer at the k moment, and calculating z according to a formula 21(k)、z2(k) And z3(k) Then z is1(k)、z2(k) And z3(k) And the observed value is a preset attitude angle observed value. The nonlinear state error feedback receives zeroth order value and first order value of attitude angle expected value and receives z order value in attitude angle observed value1(k) And z2(k) U is calculated according to equation 30Finally according to z3(k) And calculating u by formula 4, wherein u is the expected value of the zero moment point. Because z is introduced into ADRC algorithm3(k)，z3(k) Characterizing gross disturbancesIs thus according to z3(k) And the expected value of the zero moment point calculated by the formula 4 can compensate the disturbance error of the preset attitude angle feedback value, so that the accuracy of the output expected value of the zero moment point is 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 a possible implementation manner, the zero point moment point measurement value may be calculated according to a contact force between the robot and the ground, 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 point moment point measurement value is a coordinate value. Wherein the zero moment point is related to the current pose of the robot, e.g. when the biped robot is standing on one foot and only the right foot is grounded, the zero moment point is located on the right foot of the robot. The deviation value of the zero moment point is the difference value between the expected value of the zero moment point and the measured value of the zero moment point. S104: and the preset inner ring controller acquires the zero moment point deviation value and calculates to obtain a moment compensation value of the tail end joint of the robot.
As shown in FIG. 3, the inner loop controller expects a value p according to the zero moment pointdAnd calculating the moment compensation value tau of the tail joint of the robot by using the zero moment point measured value pc. The moment compensation value of the tail end joint of the robot is a moment compensation value of a forward joint or a moment compensation value of a 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 the 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 a lateral rolling attitude angle, the moment compensation value of the end joint is a 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 ADRC or a variable PD controller (i.e., a VPD controller), which is a controller employing a VPD algorithm.
In one possible implementation mode, the inner ring controller is a VPD controller, the zero moment point deviation value is input into a VPD algorithm model of the inner ring controller, and a moment compensation value of a tail end joint of the robot is output.
In one possible implementation manner, the inner ring controller is a VPD controller, and the process of calculating the torque compensation value of the end joint of the robot according to the zero torque point deviation value by the inner ring controller is as follows: the inner ring controller receives a zero moment point expected value output by the outer ring controller, calculates a zero order value of a moment compensation value at the current moment, a first order value of the moment compensation value and a second order value of the moment compensation value according to the zero moment point expected value, a zero moment point measured value at the current moment, a first order output value of the inner ring controller at the previous moment and a first order derivative of the zero moment point measured value obtained after the first order derivative processing is carried out on the zero moment point 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 the first order value of the moment compensation value and the second order value output of the moment compensation value as the input of the inner ring controller at the next moment. And the inner ring 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 value of the zero moment point at the next moment and the measured value of the zero moment point at the next moment.
In one possible implementation, the VPD algorithm is defined as:
wherein k represents an integer of 0 or more, k' represents an integer of 0 or more, vd(k) And vel (k) represents the input value at the k-th time, v (k) represents the feedback value at the k-th time,
indicating that the feedback value v (k) is subjected to first derivative processing, vel (k') being the first order at time kOutput value, dt is the integration step (period), kp、kdAnd kvEach represents an error gain parameter, and u represents an output value at the k-th time. When k is 0, v (k) is 0,
v(k)＝0。
compared with the traditional PID algorithm, the VPD algorithm can effectively solve the contradiction between the rapidity and the overshoot of the response.
Correspondingly, the process of calculating the compensation value of the moment of the tail end joint of the robot by the inner ring controller according to the zero moment point deviation value is as follows.
Taking the expected value of the zero moment point as the input value v at the k momenta(k) Taking the zero moment point measurement value at the current moment as a feedback value v (k) at the kth moment, taking a first-order output value of the inner loop controller at the previous moment as vel (k), and taking a first-order derivative of the zero moment point measurement value obtained after the first-order derivative processing is carried out on the zero moment point measurement value at the current moment as a first-order derivative of the zero moment point measurement value
Substituting the equation 5 to calculate pos (k '), and then pos (k') is the moment compensation value at the current moment, i.e. the zeroth order value of the moment compensation value. According to equation 5, the first derivative vel (k ') of pos (k'), i.e. the first order value of the torque compensation value, can also be calculated. According to the vel (k '), the second derivative acc (k '), i.e. the second value of the moment compensation value, of pos (k ') can be further calculated. The first order value of the moment compensation value and the second order value of the moment compensation value are output by the inner ring controller and are used as the input of the inner ring controller at the next moment.
Because the VPD algorithm can effectively solve the contradiction between the rapidity and the overshoot of the response of the control method, the compensation value of the moment of the foot joint of the robot is calculated by the VPD algorithm, and the accuracy of the calculation result can be improved.
In a possible implementation mode, the inner ring controller is ADRC, the zero moment point deviation value of the robot is input into an ADRC algorithm model of the inner ring controller, and a moment compensation value of a tail end joint of the robot is output.
In another possible implementation manner, the inner ring controller is ADRC, and the process of calculating the torque compensation value of the end joint of the robot according to the zero torque point deviation value by the inner ring controller is as follows: and the tracking differentiator of the inner ring controller receives the zero moment point expected value output by the outer ring controller and outputs a zero-order value and a first-order value of the zero moment point expected value. And the extended state observer of the inner ring 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. And the nonlinear state error feedback device receives a zero-order value and a first-order value of the zero-moment-point expected value, receives a zero-moment-point feedback value and outputs the moment compensation value.
If the ADRC algorithm described in equations 1 to 4 is used, the method for the inner ring controller to calculate the moment compensation value of the end joint of the robot is as follows.
Taking the expected value of the zero moment point as an input value v (k) of a tracking differentiator at the k time, and calculating v according to a formula 11(k) And v2(k) Then v is1(k) Zero order value, v, representing the desired value of the zero moment point2(k) A first order value representing the desired value for the zero moment point. Taking the measured value of the zero moment point as a feedback value y (k) of the k-th moment of the extended state observer, and calculating z according to a formula 21(k)、z2(k) And z3(k) Then z is1(k)、z2(k) And z3(k) And the feedback value is a zero moment point feedback value. The nonlinear state error feedback device receives a zeroth order value and a first order value of a zero moment point expected value and receives z in a zero moment point feedback value1(k) And z2(k) U is calculated according to equation 30Finally according to z3(k) And calculating u by formula 4, wherein u is a moment compensation value.
Because z is introduced into ADRC algorithm3(k)，z3(k) The observed value characterizing the total disturbance, therefore, according to equation 4 and z3(k) The compensation value of the moment of the tail end joint of the robot can be calculated to compensate the disturbance error of the measured value of the zero moment point, andthe accuracy of the torque compensation value of the output end 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 expectation value is obtained when the robot is subjected to gait planning in advance, and can be the moment expectation value of the tail end joint on a yoz plane or the moment expectation value of the foot tail end joint on an xoz plane. The moment deviation value is the difference between the expected moment value and the moment compensation value.
In one possible implementation manner, a gait planning strategy is acquired in advance, and the expected moment value of the tail 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 an expected value of the moment of the tail end joint of the robot is determined according to the gait planning strategy at each moment.
S106: providing the moment deviation value to an end joint actuator of the robot to control gait motions of the robot.
As shown in fig. 3, the torque is compensated for by the value τcAnd torque desired value τdAnd the control device is provided for the actuator to control the gait motion of the robot. The moment compensation values provided for the actuator comprise a moment compensation value on a yoz plane and a moment compensation value on an xoz plane, the moment expected values provided for the actuator comprise a moment expected value on the yoz plane and a moment expected value on a xoz plane, and the actuator can be a steering engine.
Specifically, the compensation value of the moment of the tail end joint of the robot on the yoz plane is added with the expected moment value of the tail end joint on the yoz plane, the moment compensation value of the tail end joint on the xoz plane is added with the expected moment value of the tail end joint on the xoz plane, the final moment of the tail end joint on the yoz plane and the final moment on the xoz plane are obtained, and the gait of the robot is controlled according to the final moment of the tail end joint on the yoz plane and the final moment on the xoz plane.
In the above embodiment, 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 are obtained, and a preset attitude angle deviation value is generated; the method 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, wherein the outer ring controller is an active disturbance rejection controller; acquiring a zero moment point expected value and a zero moment point measured value of the robot, and generating a zero moment point deviation value; and the preset inner ring controller acquires the zero moment point deviation value and calculates to obtain a moment compensation value of the 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 measurement value, and the zero moment point is an important index for stable walking of the robot. Meanwhile, the disturbance error of the preset attitude angle measurement value can be compensated by adopting the active disturbance rejection controller to calculate the expected value of the zero moment point of the robot body, and the accuracy of the output expected value of the zero moment point is improved. After the moment compensation value is calculated, the moment expected value of the tail end joint of the robot is obtained, a moment deviation value is generated, and the moment deviation value is provided for a tail end joint actuator of the robot so as to control the gait motion of the robot, so that the gait control accuracy of the robot is improved.
In one embodiment, the outer loop controller is an ADRC and the inner loop controller is a VPD controller. Correspondingly, a specific flow of the motion control method of the robot is shown in fig. 5, and the expected value θ of the attitude angle on the yoz plane is firstly setydInputting the data into an outer ring controller, adopting ADRC algorithm to calculate thetaydOutput v as input value of tracking differentiator in ADRC algorithm1And v2The measured value theta of the offset angle on the yoz planeyAs input value of the extended state observer, output z1、z2And z3According to v again1、v2、z1、z2Calculate u0Finally according to u0Calculating the output value u1，u1I.e. the expected value p of the y-axis coordinate in the expected value of the zero moment point of the robotyd. Then the expected value p of the y-axis coordinateydY-axis coordinate of the measured value pyAnd pyFirst derivative of
Inputting into an inner ring controller, wherein the inner ring controller calculates an output value u by adopting a VPD algorithm2，u2I.e. the moment compensation value tau on the yoz planecy. The compensation value tau of the moment on the xoz plane is calculated by the same methodcx. Finally, compensating the moment on the yoz plane by the value taucyXoz plane of moment compensation value taucxAnd corresponding torque expectation τdy、τdxAnd inputting an actuator to control the gait of the robot.
In the embodiment, the outer ring controller adopts an ADRC algorithm, the inner ring controller adopts a VPD algorithm, and error disturbance is compensated when the expected value of the zero moment point of the robot is calculated; when the moment compensation value of the tail end joint of the robot is calculated, the contradiction between the rapidity and the overshoot of the response of the control method is solved, and therefore the gait planning accuracy of the robot is improved.
In another embodiment, the outer loop controller is ADRC and the inner loop controller is ADRC. Correspondingly, the specific flow of the motion control method of the robot is as shown in fig. 6, and firstly, the expected value θ of the attitude angle on the yoz plane isydInputting the data into an outer ring controller, adopting ADRC algorithm to calculate thetaydOutput v as input value of tracking differentiator in ADRC algorithm1And v2The attitude angle measurement value theta on the yoz planeyAs input value of the extended state observer, output z1、z2And z3According to v again1、v2、z1、z2Calculate u0Finally according to u0Calculating the output value u3，u3I.e. the expected value p of the y-axis coordinate in the expected value of the zero moment point of the robotyd. Then the expected value p of the y-axis coordinateydInput inner loop controlThe inner ring controller adopts ADRC algorithm to convert p intoydV 'is output as an input value of a tracking differentiator in the ADRC algorithm'1And v'2Measuring value p of the y-axis coordinate in the zero moment point measuring valueyZ 'is output as an input value of the extended state observer'1、z′2And z'3And according to v'1、v′2、z′1、z′2U 'is calculated'0Finally according to u'0Calculating the output value u4，u4I.e. the moment compensation value tau on the yoz planecy. The moment compensation value v on the xoz plane is calculated by the same methodcx. Finally, compensating the moment on the yoz plane by the value taucyXoz plane of moment compensation value taucxAnd corresponding torque expectation τdy、τdxAnd inputting an actuator to control the gait of the robot.
In the above embodiment, the outer loop controller adopts an ADRC algorithm, and the inner loop controller adopts an ADRC algorithm, so that when the zero moment point expected value of the robot and the moment compensation value of the foot joint of the robot are calculated, error disturbance can be compensated, thereby improving the gait planning accuracy of the robot.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 7 shows a block diagram of a motion control device of a robot according to an embodiment of the present application, which corresponds to the motion control method of a robot according to the above-described embodiment.
As shown in fig. 7, the motion control apparatus of the robot includes,
the first acquisition module 10 is configured to acquire 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-loop controller, obtain the preset attitude angle deviation value, and calculate a zero-moment-point expected value of the robot, where the outer-loop controller is an active disturbance rejection controller;
the second obtaining module 30 is configured to obtain a zero moment point expected value of the robot, obtain a zero moment point measured value of the robot, and generate a zero moment point deviation value;
the second calculation module 40 is used for presetting an inner ring controller to obtain the zero moment point deviation value and calculating to obtain a moment compensation value of a tail end joint of the robot;
the third acquisition module 50 is used for acquiring a moment compensation value of a tail end joint of the robot and a moment expected value obtained through robot gait planning and generating a moment deviation value;
a control module 60 for providing the moment bias values to the end joint actuators of the robot to control gait motions of the robot.
In a possible implementation manner, the first computing module 20 is specifically configured to:
and the outer ring controller calculates a zero-order value and a first-order value of the preset attitude angle expected value according to the preset attitude angle expected value, and calculates a zero-moment point expected value of the robot according to the zero-order value and the first-order value of the preset attitude angle expected value and the preset attitude angle feedback value.
In a possible implementation manner, the inner loop controller is a variable PD controller, and the second calculating module 40 is specifically configured to: the inner ring controller receives a zero moment point expected value of the robot, a zero moment point measured value at the current moment, a first-order output value of the inner ring controller at the previous moment and a first derivative of the zero moment point measured value at the current moment, calculates a zero-order value of a moment compensation value, a first-order value of the moment compensation value and a second-order value of the moment compensation value of a tail end joint of the robot at the current moment, 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 output of the moment compensation value as the input of the inner ring controller at the next moment.
In a possible implementation manner, the inner-loop controller is an active disturbance rejection controller, and the second calculating module 40 is specifically configured to: a tracking differentiator of the inner ring controller receives the expected value of the zero moment point of the robot 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 of the robot; an extended state observer of the inner ring controller receives a zero moment point measured value of the robot and outputs a zero moment point feedback value after extended observation processing; and a nonlinear state error feedback device of the inner ring controller receives a zero-order value and a first-order value of a zero moment point expected value of the robot, receives a zero moment point feedback value and outputs a moment compensation value of a tail end joint of the robot.
In a possible implementation manner, the zero moment point measurement value of the robot is obtained by detecting the contact force between the robot and the ground through a six-dimensional force sensor of the robot, and is calculated according to the contact force between the robot and the ground or is calculated through robot dynamics.
In one possible implementation manner, the preset attitude angle is a forward pitch attitude angle, and the torque compensation value of the end joint of the robot is a torque compensation value of a forward joint of the robot, so as to control the motion of the forward joint of the robot.
In a possible implementation manner, the preset attitude angle is a lateral roll attitude angle, and the moment compensation value of the end joint of the robot is a moment compensation value of a lateral joint of the robot, so as to control the movement of the lateral joint of the robot.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
Fig. 8 is a schematic structural diagram of a robot provided in 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 said memory 12 and executable on said processor 11. The processor 11, when executing the computer program 13, implements the steps in the above-described control method embodiment of the robot, such as the steps S101 to S106 shown in fig. 1. Alternatively, the processor 11 executes the computer program 13 to implement the functions of the modules/units in the device embodiments, such as the functions of the first acquiring 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, which are stored in the memory 12 and executed by the processor 11 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 13 in the terminal device.
Those skilled in the art will appreciate that fig. 8 is merely an example of a robot and is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, 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 (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc. 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 Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the robot. Further, the memory 12 may also include both an internal storage unit and an external storage device of the robot. The memory 12 is used for storing the computer program and 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-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
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 ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
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 implementation. 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-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method for controlling the movement of a robot, comprising:
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;
a preset outer ring controller obtains the preset attitude angle deviation value and calculates the expected value of the zero moment point of the robot, wherein the outer ring controller is an active disturbance rejection controller;
acquiring a zero moment point expected value and 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 to obtain 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;
providing the moment deviation value to an end joint actuator of the robot to control gait motions of the robot.
2. The method as claimed in claim 1, wherein the outer loop controller calculates a zeroth order value and a first order value of the expected value of the preset attitude angle according to the expected value of the preset attitude angle, and calculates the expected value of the zero moment point of the robot according to the zeroth order value and the first order value of the expected value of the preset attitude angle and the feedback value of the preset attitude angle.
3. The method as claimed in claim 1 or 2, wherein the inner loop controller is a variable PD controller, the inner loop controller receives a zero moment point expected value of the robot and a zero moment point measured value at a current time, a first order output value of the inner loop controller at a previous time, and a first order derivative of the zero moment point measured value at the current time, calculates a zero order value of a moment compensation value of a distal joint of the robot at the current time, a first order value of the moment compensation value, and a second order value of the moment compensation value, and outputs the zero order value of the moment compensation value as an output of the inner loop controller, and outputs the first order value of the moment compensation value and the second order value of the moment compensation value as inputs of the inner loop controller at a next time.
4. The method for controlling the movement of the robot according to claim 1 or 2, wherein the inner-loop controller is an active disturbance rejection controller, and the tracking differentiator of the inner-loop controller receives the zero moment point expected value of the robot output by the outer-loop controller and outputs a zero-order value and a first-order value of the zero moment point expected value of the robot; an extended state observer of the inner ring controller receives a zero moment point measured value of the robot and outputs a zero moment point feedback value after extended observation processing; and a nonlinear state error feedback device of the inner ring controller receives a zero-order value and a first-order value of a zero moment point expected value of the robot, receives a zero moment point feedback value and outputs a moment compensation value of a tail end joint of the robot.
5. The method of claim 1, wherein the zero moment point measurement of the robot is calculated by detecting a contact force of the robot with the ground through a six-dimensional force sensor of the robot, or calculated by a robot dynamics.
6. The method of controlling motion of a robot according to claim 1, wherein the preset attitude angle is a forward pitch attitude angle, and the moment compensation value of the end joint of the robot is a moment compensation value of a forward joint of the robot to control motion of the forward joint of the robot.
7. The motion control method of a robot according to claim 1, wherein the preset posture angle is a lateral roll posture angle, and the moment compensation value of the end joint of the robot is a moment compensation value of a lateral joint of the robot to control the motion of the lateral joint of the robot.
8. A motion control apparatus for a robot, comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for 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 first calculation module is used for presetting an outer ring controller to obtain the preset attitude angle deviation value and calculating the zero moment point expected value of the robot, wherein the outer ring controller is an active disturbance rejection controller;
the second acquisition module is used for 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 second calculation module is used for presetting an inner ring controller to obtain the zero moment point deviation value and calculating to obtain a moment compensation value of a tail end joint of the robot;
the third acquisition module is used for 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;
and the control module is used for providing the moment deviation value for an end joint actuator of the robot so as to control the gait motion 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, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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| CN116442240A (en) * | 2023-05-26 | 2023-07-18 | 中山大学 | Robot zero-force control method and device based on high-pass filtering decoupling |
| CN116442240B (en) * | 2023-05-26 | 2023-11-14 | 中山大学 | Robot zero-force control method and device based on high-pass filtering decoupling |
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