CN108897220B - Self-adaptive stable balance control method and system and biped humanoid robot - Google Patents
Self-adaptive stable balance control method and system and biped humanoid robot Download PDFInfo
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Abstract
The invention relates to a self-adaptive stable balance control method and system and a biped humanoid robot, which can realize self-adaptive stable balance of the biped humanoid robot. The self-adaptive stable balance control method comprises the following steps: (1) establishing a state space model of the biped humanoid robot:
the method comprises the following steps of (1) determining an optimized control algorithm, wherein Y is C × X, X is a state function of the bipedal humanoid robot, Y is an output function, U is an input function, A is a state matrix, B is a coefficient matrix of the input function, C is a coefficient matrix of the output function, and (2) determining the optimized control algorithm, wherein the state model of the bipedal humanoid robot can be converted into:
the selection of the controller parameter K needs to enable the characteristic value of the matrix (A-BK) to meet the set condition, so that the state of the biped humanoid robot can be converged and stably balanced. The self-adaptive stable balance control system adopts the method to make the biped humanoid robot self-adaptively balance. The biped humanoid robot comprises the control system. The invention is used for enabling the biped humanoid robot to realize stable balance by utilizing the biped humanoid robot.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a self-adaptive stable balance control method and system and a biped humanoid robot.
Background
A biped humanoid robot is a robot which simulates the movement characteristics of human standing, walking, jumping and the like. It is completely different from the movement of other types of robots, such as common wheels, drapes, quadrupeds, etc. In nature, animals walking with both feet have strong terrain adaptability and other incomparable advantages; meanwhile, the biped humanoid robot relates to the cross fusion of multiple disciplines (such as bionics, electromechanical control theory, mechanical design and manufacture, computer science, sensor technology and the like); therefore, the standing and walking research of the biped humanoid robot becomes a hotspot and a difficulty in the academic and industrial circles at home and abroad.
At present, many humanoid robots capable of realizing biped walking capability have been successfully developed at home and abroad, such as ATLAS and Petman of Boston power company in America, ASIMO of Honda company in Japan, European open source robot iCub, HIT and GoRoBoT of Harbin university in China, KDW of defense science and technology university, BHR of Beijing science and technology university, THBIP of Qinghua university and the like.
The biggest advantages of the large-scale biped humanoid robot (height more than 1 m) are: the system can become a universal robot platform and becomes the most main human-computer interaction interface of the future Internet of things (because most buildings and tools in the human world are designed according to the height and the shape of people at present). The stability is the premise and the foundation of gait research of the large biped robot. Gait refers to the relationship between each joint in time and space during standing or walking, and can be described by the movement track of the joint.
The inventor of the invention finds that the existing bipedal humanoid robot technology at least has the following problems:
(1) although the biped humanoid robot can basically realize biped walking, the biped robot is a microminiature robot; the large robot is very easy to generate unstable disturbance problems such as 'toppling'. Moreover, the current engineering method for solving the disturbance resistance of the robot is extremely lacking.
(2) At present, the simulation of biped robots mostly establishes a positive kinematics model and an inverse kinematics model, and then solves the models by using a numerical method or an analytical method. And establishing a dynamic model mainly by adopting a Lagrange method or a Newton-Euler method. However, these methods based on cartesian coordinate system and space coordinate system change are suitable for precise control and calculation of the arm of the industrial robot, and are not suitable for the control of the nonlinear change of the complex bipedal humanoid robot with 12 degrees of freedom.
Disclosure of Invention
In view of the above, the present invention provides a self-adaptive stable balance control method and system and a biped humanoid robot, and mainly aims to enable the biped humanoid robot to realize stable balance by itself.
In order to achieve the purpose, the invention mainly provides the following technical scheme:
in one aspect, an embodiment of the present invention provides a method for controlling adaptive stable balance, which is used for enabling a biped humanoid robot to adaptively stabilize balance, and is characterized by including the following steps:
(1) establishing a state space model of the biped humanoid robot as follows:
Y＝C×X；
wherein X is a state function of the biped humanoid robot; y is an output function; u is an input function and reflects the control input of the current state of the biped humanoid robot; a is a state matrix of the biped humanoid robot; b is a coefficient matrix of the input function; c is a coefficient matrix of the output function;
determining a coefficient matrix A, B, C by using a solution method of a Jacobian matrix;
(2) determining an optimized control algorithm:
let the input function U and the state function X have the following relationship: u ═ K × X; wherein the state model of the biped humanoid robot is convertible into:
the matrix K is a controller parameter and plays a role in controlling the input function U; the selection of the controller parameter K needs to enable the characteristic value of the matrix (A-BK) to meet a set condition, namely the state of the biped humanoid robot can be converged and is in a stable balance state;
when the biped humanoid robot is disturbed by the outside or the self, the self-adaptive stable balance control method optimizes a controller parameter K through the steps according to the current state of the biped humanoid robot and the control input of the current state, and then adjusts the control input of the current state, so that the biped humanoid robot realizes stable balance.
The object of the present invention and the technical problems solved thereby can be further achieved by the following technical measures.
Preferably, the biped humanoid robot comprises N joints; the state function of the biped humanoid robot embodies the angle theta and the angular speed omega of each joint; the input function representing the angular acceleration of each of said joints
Preferably, the angles corresponding to each joint of the biped humanoid robot are respectively: theta1、θ2、…、ωN(ii) a The angular speed corresponding to each joint of the biped humanoid robot is respectively as follows: omega1、ω2、…、ωN(ii) a The angular acceleration corresponding to each joint of the biped humanoid robot is as follows:
wherein the state function X of the biped humanoid robot is established as follows:
the state space model of the biped humanoid robot in the step (1) is established as follows:
preferably, the setting conditions are:
the eigenvalues of the matrix (A-BK) are all less than 0; or
Some eigenvalues of the matrix (A-BK) are less than 0, and others are equal to 0; or
The eigenvalues of the matrix (a-BK) are all equal to 0.
Preferably, the output torque of the driving mechanism in the biped humanoid robot to each joint is calculated through the controller parameter K, so that the driving mechanism drives the biped humanoid robot to finally move to a balanced and stable state.
Preferably, the number of joints of the biped humanoid robot is 6, which are respectively: shoulder joints, hip joints, knee joints, front and rear ankle joints, and left and right ankle joints.
On the other hand, the embodiment of the invention also provides an adaptive stable balance control system, which is used for the biped humanoid robot, wherein the adaptive stable balance control system controls the adaptive stable balance of the biped humanoid robot by using any one of the adaptive stable balance control methods.
Preferably, the adaptive stability control system includes:
a controller;
a sensor unit connected with the controller;
the driving mechanism is connected with the controller;
the sensor unit is used for sensing the current motion state and stress state of the biped humanoid robot and sending the current motion state and stress state as signals to the controller; the controller optimizes a controller parameter K according to the signal, calculates the output torque of the driving mechanism, and enables the state of the double-foot humanoid robot to be converged through the driving of the driving mechanism, so that stable balance is realized.
Preferably, the sensor unit includes:
a position sensor for sensing an angle and an angular velocity of each joint in the bipedal humanoid robot;
an acceleration sensor for sensing an acceleration of each joint in the bipedal humanoid robot;
and the force sensor is used for sensing the force applied to each joint in the biped humanoid robot and the foot pressure of the biped humanoid robot.
Preferably, the drive mechanism comprises a plurality of motors; wherein,
the number of the motors is consistent with that of the joints of the biped humanoid robot, and the motors are driven in a one-to-one correspondence manner.
In another aspect, an embodiment of the present invention further provides a bipedal humanoid robot, where the bipedal humanoid robot includes any one of the adaptive stable balance control systems described above.
Compared with the prior art, the self-adaptive stable balance control method and system and the biped humanoid robot provided by the invention have the following beneficial effects:
the self-adaptive stable balance control method provided by the embodiment of the invention determines an optimized control algorithm by establishing a state space model of the biped humanoid robot, performing linear processing on a controller model and then solving a matrix coefficient for converging the error of a state function of the biped robot; thus, when the biped humanoid robot is disturbed by the outside or by itself, the adaptive stable balance control method in the embodiment optimizes the controller parameter K according to the control algorithm, further adjusts the control input of the current state, and finally converges the state of the biped humanoid robot to realize the adaptive balance of the biped humanoid robot. Here, the adaptive stable balance control method according to the embodiment of the present invention enables the biped humanoid robot to perform adaptive balance by itself, is not limited to the size of the robot, and is capable of enabling not only a small biped humanoid robot to perform adaptive balance, but also a large biped humanoid robot (greater than 1 meter) to perform adaptive balance.
Further, the state function obtained by the adaptive stable balance control method provided by the embodiment reflects the angle and angular speed of each joint of the biped humanoid robot; the input function embodies the input function of angular acceleration of each joint; when the biped humanoid robot is disturbed by the outside or the self, the output torque of each joint by the driving mechanism is calculated according to the controller parameter K optimized by the self-adaptive balance algorithm, the joint angle of the biped humanoid robot is adjusted, and the self-adaptive stable balance of the biped humanoid robot is realized.
Further, according to the adaptive stable balance control method provided by this embodiment, the optimized controller parameter K is determined by obtaining the angles and angular speed states of the 6 joints, namely, the shoulder joint, the hip joint, the knee joint, the front and rear ankle joints, and the left and right ankle joints of the two-legged humanoid robot, and combining the adaptive balance algorithm, so as to adjust the output torque of the driving mechanism of the two-legged humanoid robot to each joint, and reduce the corresponding adjustment to the angle of the joint, thereby enabling the two-legged humanoid robot to be adaptively stable and balanced well.
On the other hand, an embodiment of the present invention further provides an adaptive stability balance control system, which controls adaptive stability balance of the biped humanoid robot through any one of the adaptive stability balance control methods described above, so that the adaptive stability balance control system provided in this embodiment has the beneficial effects described in any one of the foregoing, which are not repeated herein.
In another aspect, an embodiment of the present invention further provides a biped humanoid robot, which includes the adaptive stable balance control system described above, so as to implement adaptive stable balance by using the adaptive stable balance control method described above, and therefore the biped humanoid robot provided in this embodiment has any of the above beneficial effects, which are not described herein again.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
Fig. 1 is a schematic flow chart of adaptive balance stabilization of a biped humanoid robot driven by an adaptive balance control method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an adaptive steady-state control system provided by an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a bipedal humanoid robot provided by an embodiment of the invention;
fig. 4 is a shoulder joint angle change curve of the biped humanoid robot in the simplified model according to embodiment 6 of the present invention;
FIG. 5 is a graph showing the angle change of the left and right ankles of the biped humanoid robot in the simplified model according to embodiment 6 of the present invention;
fig. 6A and 6B are vertical reaction force variation curves in the simplified model according to embodiment 6 of the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined object, the following detailed description of the embodiments, structures, features and effects according to the present invention will be made with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "an embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
The self-adaptive stable balance control method and system and the biped humanoid robot provided by the embodiment of the invention are provided based on the problems found by the inventor in the background technology, and the specific design idea is as follows:
the inventor of the invention innovatively proposes an anti-disturbance balance control strategy by utilizing the limbs of the inventor; and according to actual engineering experience and requirements, a system state function is directly established under a generalized coordinate system according to the states of the biped humanoid robot (such as the relative angles and angular velocities of joints of the biped humanoid robot) for analysis, so that the calculation is simplified, and the characteristics of the biped humanoid robot system can be accurately described. See the following examples for specific design.
Example 1
As shown in fig. 1, the present embodiment provides an adaptive stable balance control method for enabling a bipedal humanoid robot to adaptively stabilize balance, including the following steps:
step one, establishing a state space model of the biped humanoid robot as follows:
Y＝C×X；
wherein X is a state function of the biped humanoid robot (i.e., a function that can reflect a system state of the biped robot, such as the angle of each joint of the biped humanoid robot mentioned in embodiment 2, or the displacement of four limbs of the biped humanoid robot); y is an output function and reflects a certain attribute of the state of the biped humanoid robot, such as the joint angle of the state of the biped humanoid robot; u is an input function and reflects the control input of the current state of the biped humanoid robot, such as input torque; a is a state matrix of the biped humanoid robot; b is a coefficient matrix of the input function; c is the coefficient matrix of the output function.
The coefficient matrix A, B, C is determined using a solution to the Jacobian matrix.
Step two, determining an optimized control algorithm (namely an adaptive balance algorithm):
let the input function U and the state function X have the following relationship: u ═ K × K; wherein the state model of the biped humanoid robot can be converted into:
the matrix K is a controller parameter and plays a role in controlling the input function U; the selection of the controller parameter K needs to enable the characteristic value of the matrix (A-BK) to meet a set condition, namely the state of the biped humanoid robot can be converged and is in a stable balance state.
When the biped humanoid robot is disturbed by the outside or by itself, the adaptive stable balance control method in the embodiment optimizes the controller parameter K through the steps according to the current state (such as the posture) of the biped humanoid robot and the control input (such as the mechanical signal) of the current state, and then adjusts the control input of the current state, so that the state of the biped humanoid robot is converged, and the adaptive stable balance is realized.
The adaptive stable balance control method provided by the embodiment determines an optimized control algorithm by establishing a state space model of the biped humanoid robot, performing linear processing on a controller model and then solving a matrix coefficient for converging errors of a state function of the biped robot; thus, when the biped humanoid robot is disturbed by the outside or by itself, the adaptive stable balance control method in the embodiment optimizes the controller parameter K according to the control algorithm, further adjusts the control input of the current state, and finally converges the state of the biped humanoid robot to realize the adaptive balance of the biped humanoid robot. Here, the adaptive stable balance control method of the present embodiment not only enables the biped humanoid robot to perform adaptive balance by itself, but also enables the small biped humanoid robot to perform adaptive balance, not limited to the size of the robot, and is crucial to enable the large biped humanoid robot (higher than 1 meter) to perform adaptive balance.
Example 2
Preferably, the present embodiment provides an adaptive stable balance control method, and compared with embodiment 1, the present embodiment further performs the following design:
the adaptive stable balancing method in this embodiment abstracts each joint and joint angle of the robot and establishes a state space basic model of the system, aiming at the multi-joint characteristics of the biped humanoid robot.
Here, the biped humanoid robot is set to include N joints; the state function of the biped humanoid robot embodies the angle theta and the angular speed omega of each joint; the input function representing the angular acceleration of each of said joints
Determining the corresponding angles of all joints of the biped humanoid robot, which are respectively as follows: theta1、θ2、…、θN；
Vector x ═ θ1，θ2，…、θNThe angular positions of all joints in the biped humanoid robot system are represented;
Delta(x)＝dx/dt＝{ω1，ω2，…，ωNthe angular velocities of the respective joints are denoted;
the angular acceleration corresponding to each joint of the biped humanoid robot is respectively as follows:
accordingly, the state function X of the bipedal humanoid robot in the present embodiment is established as:
further, the state space model of the biped humanoid robot in the step (1) is as follows:
in this embodiment, the output torque of the drive mechanism of the bipedal humanoid robot for each joint is calculated based on the controller parameter K.
Here, the controller parameter K is selected such that the eigenvalues of the matrix (a-BK) satisfy the setting conditions: the eigenvalues of the matrix (A-BK) are all less than 0; or the characteristic values of the matrix (A-BK) are less than 0 and the matrix (A-BK) is equal to 0; or the eigenvalues of the matrix (a-BK) are all equal to 0. The state of the biped humanoid robot can be converged and is in a stable balance state.
The state function obtained by the adaptive stable balance control method provided by the embodiment reflects the angle and the angular speed of each joint of the biped humanoid robot; the input function embodies the input function of angular acceleration of each joint; when the biped humanoid robot is disturbed by the outside or the self, the output torque of each joint by the driving mechanism is calculated according to the controller parameter K optimized by the self-adaptive balance algorithm, the joint angle of the biped humanoid robot is adjusted, and the self-adaptive stable balance of the biped humanoid robot is realized.
Example 3
Preferably, the present embodiment provides an adaptive stable balance control method, compared with embodiment 2, the present embodiment mainly obtains states of 6 joints of the biped humanoid robot; as shown in fig. 3, from top to bottom, a shoulder joint 11, a hip joint 12, a crotch joint 13, a knee joint 14, left and right ankle joints 15, and front and rear ankle joints 16; the angles are represented by θ 1, θ 2, θ 3, θ 4, θ 5, and θ 6, respectively. The robot has 6 degrees of freedom, assuming sufficient friction on the bottom surface and no horizontal sliding.
In this embodiment, the biped humanoid robot spatial state function X:
the state space model of the biped humanoid robot is as follows:
by using a solution method of the Jacobian matrix, the coefficient matrix A, B, C is determined to be:
wherein the controller parameter K is:
according to the self-adaptive stable balance control method provided by the embodiment, the optimized controller parameter K is determined by acquiring the angles and the angular speed states of 6 joints, namely, a shoulder joint, a hip joint, a knee joint, a front ankle joint, a rear ankle joint, a left ankle joint and a right ankle joint of the two-foot humanoid robot and combining the self-adaptive balance algorithm, so that the output torque of a driving mechanism of the two-foot humanoid robot to each joint is adjusted, the corresponding adjustment to the angles of the joints is reduced, and the two-foot humanoid robot can be well self-adaptively stably balanced.
Example 4
On the other hand, the present embodiment provides an adaptive stability balance control system for a biped humanoid robot, wherein the adaptive stability balance control system in the present embodiment controls the adaptive stability balance of the biped humanoid robot by the adaptive stability balance control method in any one of the embodiments.
Preferably, as shown in fig. 2, the adaptive stabilization balancing system 2 in the present embodiment includes a controller 21, a sensor unit 23, and a driving mechanism 24. Wherein the sensor unit 23 is connected with the controller 21; the drive mechanism 24 is connected to the controller 21. The sensor unit 23 is configured to sense a current state (e.g., an angular position and an angular velocity of 6 joints of the robot mentioned in the above embodiment) and a stress state of the biped humanoid robot, and send the current state and the stress state as a signal to the controller 21; the controller 21 optimizes the controller parameter K according to the signal, calculates the output torque of the driving mechanism, and drives the driving mechanism 24 to converge the state of the biped humanoid robot, thereby realizing stable balance.
The sensor unit 23 includes: a position sensor 232, an acceleration sensor 231, and a force sensor 233. Wherein the position sensor 232 is used to sense the angle and angular velocity of each joint in the bipedal humanoid robot. An acceleration sensor 231 for sensing an acceleration of each joint in the bipedal humanoid robot; the force sensor 233 is used to sense the force and foot pressure applied to each joint in the bipedal humanoid robot.
Preferably, the drive mechanism 24 in this embodiment includes a plurality of motors; the number of the motors is consistent with that of the joints of the biped humanoid robot, and the motors are driven in a one-to-one correspondence manner.
Here, the adaptive stability balance control system provided in this embodiment controls the adaptive stability balance of the two-legged humanoid robot through the adaptive stability balance control method described in any of the above embodiments, and therefore, the adaptive stability balance control system provided in this embodiment has the beneficial effects described in any of the above embodiments, which are not repeated herein.
Example 5
On the other hand, as shown in fig. 3, the present embodiment provides a bipedal humanoid robot, wherein the bipedal humanoid robot of the present embodiment includes the adaptive stability balance control system described in embodiment 4, that is, the adaptive stability balance control method described in any one of embodiments 1 to 3 is adopted to achieve adaptive stability balance. Therefore, the biped humanoid robot in this embodiment has the beneficial effects described in any of the above embodiments, which are not described herein again.
Example 6
In this embodiment, an example of a simplified model is selected to illustrate a specific implementation manner of the adaptive stable balance control method provided in the foregoing embodiment. The method comprises the following specific steps:
as shown in fig. 1, when the shoulders of the biped humanoid robot are disturbed by the outside, the shoulder joint θ 1 is a movable joint, and θ 2 θ 3 θ 4 θ 5 θ 6 is fixed and is a fixed quantity of 0. Here, it is considered that when the biped robot simulator receives an external force, the whole biped robot simulator is unstable, and one angular velocity is generated at the angle θ 6 of the front and rear ankle joints 16. At the moment, a space state model of the biped humanoid robot is established as follows:
here, it is assumed that the shoulder mass of the bipedal humanoid robot is m1, the body mass excluding the shoulder is m2, the effective length of the shoulder is L1, and the effective length of the body excluding the shoulder is L2. The body motion angle is similar to theta 6 processing. The motor force for driving the shoulder joint is u; from mechanical analysis of m1, m 2:
and (3) performing linearization processing at the lowest point of the shoulder, obtaining matrixes A and B by a method of solving a Jacobian matrix, and then solving a matrix coefficient for converging the error of the state function of the bipedal humanoid robot system so as to determine an optimized control algorithm.
The model after linearization at the lowest point of the shoulder was:
here, u is motor power and is a system controllable variable.
Let the input function U and the system state X be related as follows: u ═ K × X;
the controller parameter K is related to the angle, velocity of the body other than the shoulder (i.e., the angle, velocity of the left and right ankle joints 16). Let u be k1 θ 6+ k2 ω 6 in another form of the system state equation:
combining the coefficient matrices of X yields:
namely:
here, by selection of the controller parameter k1k2, it is necessary that the eigenvalues of the matrix (a-BK) satisfy the following condition: the eigenvalues of the first, matrix (A-BK) are all less than 0, or a part of the eigenvalues of the second, matrix (A-BK) are less than 0, while the remaining part of the eigenvalues are equal to 0; or thirdly, all the eigenvalues of the matrix (a-BK) are equal to 0, so that the robot system can be guaranteed to converge at a position where θ 6 is 0 and ω 6 is 0. In the above steps, the gait change curves of the joints of the bipedal humanoid robot are shown in fig. 4 and 5; and the change curves of the reaction force in the vertical direction of the robot are shown in fig. 6A and 6B.
In summary, the adaptive stable balance control method and system and the biped humanoid robot provided by the embodiment of the invention solve the matrix coefficient for converging the error of the state function of the biped robot by establishing the state space model of the biped humanoid robot and performing linear processing on the controller model, so as to determine the optimized control algorithm, namely the adaptive balance algorithm; thus, when the biped humanoid robot is disturbed by the outside or by itself, the adaptive stable balance control method in the embodiment optimizes the controller parameter K according to the adaptive balance algorithm, further adjusts the control input of the current state, and finally converges the state of the biped humanoid robot to realize the adaptive balance of the biped humanoid robot. Here, the adaptive stable balance control method and system and the biped humanoid robot according to the embodiments of the present invention enable the biped humanoid robot to perform adaptive balance by itself, and are not limited to the size of the robot, and not only enable a small biped humanoid robot to perform adaptive balance, but also enable a large biped humanoid robot (more than 1 meter) to perform adaptive balance.
In summary, it is readily understood by those skilled in the art that the advantageous modes described above can be freely combined and superimposed without conflict.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and any simple modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are still within the scope of the technical solution of the present invention.
Claims (8)
1. A self-adaptive stable balance control method is used for enabling a biped humanoid robot to be self-adaptively stable and balanced, and is characterized by comprising the following steps:
(1) establishing a state space model of the biped humanoid robot as follows:
Y＝C×X；
wherein X is a state function of the biped humanoid robot; y is an output function; u is an input function and reflects the control input of the current state of the biped humanoid robot; a is a state matrix of the biped humanoid robot; b is a coefficient matrix of the input function; c is a coefficient matrix of the output function;
determining a coefficient matrix A, B, C by using a solution method of a Jacobian matrix;
(2) determining an optimized control algorithm:
let the input function U and the state function X have the following relationship: u ═ K × X; wherein the state model of the biped humanoid robot is convertible into:
the matrix K is a controller parameter and plays a role in controlling the input function U; the selection of the controller parameter K needs to enable the characteristic value of the matrix (A-BK) to meet a set condition, namely the state of the biped humanoid robot can be converged and is in a stable balance state;
when the biped humanoid robot is disturbed by the outside or the self, the self-adaptive stable balance control method optimizes a controller parameter K through the steps according to the current state of the biped humanoid robot and the control input of the current state, and further adjusts the control input of the current state to ensure that the biped humanoid robot realizes stable balance;
the biped humanoid robot comprises N joints; the state function of the biped humanoid robot embodies the angle theta and the angular speed omega of each joint; the input function representing the angular acceleration of each of said joints
The corresponding angle of each joint of the biped humanoid robot is as follows: theta1、θ2、…、θN(ii) a The angular speed corresponding to each joint of the biped humanoid robot is respectively as follows: omega1、ω2、…、ωN(ii) a The angular acceleration corresponding to each joint of the biped humanoid robot is as follows:
the state function X of the biped humanoid robot is established as follows:
the state space model of the biped humanoid robot in the step (1) is established as follows:
the setting conditions are as follows:
the eigenvalues of the matrix (A-BK) are all less than 0; or
Some eigenvalues of the matrix (A-BK) are less than 0, and others are equal to 0; or
The eigenvalues of the matrix (a-BK) are all equal to 0.
2. The adaptive stability balance control method according to claim 1, wherein the controller parameter K is used to calculate an output torque of the driving mechanism of the bipedal humanoid robot for each joint, so that the driving mechanism drives the bipedal humanoid robot to finally move to a stable balance state.
3. The adaptive stability balance control method according to claim 1 or 2, wherein the bipedal humanoid robot has 6 joints, each of which is: shoulder joints, hip joints, knee joints, front and rear ankle joints, and left and right ankle joints.
4. An adaptive stability balance control system for use in a biped humanoid robot, the adaptive stability balance control system controlling adaptive stability balance of the biped humanoid robot by an adaptive stability balance control method according to any one of claims 1 to 3.
5. The adaptive stability balancing control system of claim 4, comprising:
a controller;
a sensor unit connected with the controller;
the driving mechanism is connected with the controller;
the sensor unit is used for sensing the current motion state and stress state of the biped humanoid robot and sending the current motion state and stress state as signals to the controller; the controller optimizes a controller parameter K according to the signal, calculates the output torque of the driving mechanism, and enables the state of the double-foot humanoid robot to be converged through the driving of the driving mechanism, so that stable balance is realized.
6. The adaptive stability balancing control system of claim 5, wherein the sensor unit comprises:
a position sensor for sensing an angle and an angular velocity of each joint in the bipedal humanoid robot;
an acceleration sensor for sensing an acceleration of each joint in the bipedal humanoid robot;
and the force sensor is used for sensing the force applied to each joint in the biped humanoid robot and the foot pressure of the biped humanoid robot.
7. The adaptive stability balancing control system of claim 5, wherein the drive mechanism includes a plurality of motors; wherein,
the number of the motors is consistent with that of the joints of the biped humanoid robot, and the motors are driven in a one-to-one correspondence manner.
8. A biped humanoid robot characterized in that it comprises an adaptive stability and balance control system according to any one of claims 4-7.
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| CN109941371B (en) * | 2019-04-22 | 2021-09-17 | 青岛黄海学院 | Biped robot and walking control method thereof |
| CN110702312B (en) * | 2019-10-17 | 2025-03-11 | 杨聪智 | Robot center of gravity balancing method |
| CN110789633B (en) * | 2019-11-04 | 2022-02-08 | 上海硅族智能科技有限公司 | Flexible linear drive control method and control system |
| CN113050409B (en) * | 2019-12-28 | 2023-12-01 | 深圳市优必选科技股份有限公司 | Humanoid robot, control method thereof and computer-readable storage medium |
| CN113070880B (en) * | 2021-03-31 | 2022-09-09 | 深圳市优必选科技股份有限公司 | Motion control method and device, robot control equipment and readable storage medium |
| CN115616898B (en) * | 2022-10-26 | 2025-02-14 | 浙江大学 | A humanoid robot standing method with variable load based on model reference adaptive control |
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