CN117260718B - Self-adaptive load compensation control method and system for four-legged robot - Google Patents
Self-adaptive load compensation control method and system for four-legged robot Download PDFInfo
- Publication number
- CN117260718B CN117260718B CN202311229197.1A CN202311229197A CN117260718B CN 117260718 B CN117260718 B CN 117260718B CN 202311229197 A CN202311229197 A CN 202311229197A CN 117260718 B CN117260718 B CN 117260718B
- Authority
- CN
- China
- Prior art keywords
- robot
- representing
- quadruped robot
- unknown
- quadruped
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 230000003044 adaptive effect Effects 0.000 claims description 31
- 239000011159 matrix material Substances 0.000 claims description 25
- 239000013598 vector Substances 0.000 claims description 18
- 230000001133 acceleration Effects 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000036544 posture Effects 0.000 claims description 6
- 239000002131 composite material Substances 0.000 claims description 2
- 238000013507 mapping Methods 0.000 claims 1
- 238000005457 optimization Methods 0.000 abstract description 8
- 230000005021 gait Effects 0.000 abstract description 6
- 230000004927 fusion Effects 0.000 abstract description 3
- 210000002414 leg Anatomy 0.000 description 22
- 230000008859 change Effects 0.000 description 5
- 210000001503 joint Anatomy 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 210000000689 upper leg Anatomy 0.000 description 2
- 101100001674 Emericella variicolor andI gene Proteins 0.000 description 1
- 108010065920 Insulin Lispro Proteins 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 101100313471 Streptomyces sp getA gene Proteins 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 210000003414 extremity Anatomy 0.000 description 1
- 230000008713 feedback mechanism Effects 0.000 description 1
- WNRQPCUGRUFHED-DETKDSODSA-N humalog Chemical compound C([C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@H](CS)NC(=O)[C@H]([C@@H](C)CC)NC(=O)[C@H](CO)NC(=O)[C@H]([C@@H](C)O)NC(=O)[C@H](CS)NC(=O)[C@H](CS)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](C(C)C)NC(=O)[C@@H](NC(=O)CN)[C@@H](C)CC)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CC=1C=CC(O)=CC=1)C(=O)N[C@@H](CS)C(=O)N[C@@H](CC(N)=O)C(O)=O)C1=CC=C(O)C=C1.C([C@@H](C(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](C)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC=1C=CC(O)=CC=1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C(C)C)C(=O)N[C@@H](CS)C(=O)NCC(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CCCNC(N)=N)C(=O)NCC(=O)N[C@@H](CC=1C=CC=CC=1)C(=O)N[C@@H](CC=1C=CC=CC=1)C(=O)N[C@@H](CC=1C=CC(O)=CC=1)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CCCCN)C(=O)N1[C@@H](CCC1)C(=O)N[C@@H]([C@@H](C)O)C(O)=O)C(C)C)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@H](CS)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC=1NC=NC=1)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](NC(=O)[C@@H](N)CC=1C=CC=CC=1)C(C)C)C1=CN=CN1 WNRQPCUGRUFHED-DETKDSODSA-N 0.000 description 1
- 229960002068 insulin lispro Drugs 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000087 stabilizing effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1633—Programme controls characterised by the control loop compliant, force, torque control, e.g. combined with position control
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Manipulator (AREA)
Abstract
The invention is suitable for the field of robots, and provides a self-adaptive load compensation control method and system for a quadruped robot. The method has the advantages that the pose and speed information of the robot is acquired by utilizing a multi-sensor fusion technology, and the motion of the four-foot robot is dynamically modeled. And converting the robot motion control problem into a mathematical programming problem by using a quadratic programming optimization technology, and adjusting control parameters in real time in an online updating mode. The stable gait control of the quadruped robot can be realized by iteratively solving the optimization problem, and the unknown effective load is subjected to self-adaptive compensation, so that better motion performance and robustness are realized. The motion control problem of the four-foot robot under the condition of unknown load is effectively solved, and the stability and the dynamic performance of the four-foot robot are improved.
Description
Technical Field
The invention relates to the field of robots, in particular to a self-adaptive load compensation control method and system for a quadruped robot.
Background
The four-foot robot is a robot simulating the walking mode of the limbs of animals. Such robots generally have a high degree of freedom of movement and complex dynamics. The control of the quadruped robot involves the problems of balance control, gait planning, motion control, compensation of external disturbance and the like. For robotic control, adaptive control is an important technique. The technique aims to enable the control system to automatically adapt to environmental changes, system uncertainties and the effects of unknown loads. The adaptive control method is generally based on a feedback mechanism, and realizes adaptive control on system dynamics through online estimation and adjustment of a system model and parameters.
In practical robotic applications, the load of the robot is often uncertain. The unknown load has an effect on the dynamic characteristics and control performance of the robotic system, so the load needs to be modeled and compensated for to achieve stable control and good performance. Quadratic programming is a mathematical optimization problem with the goal of minimizing quadratic objective functions under given constraints. In robotic control, quadratic programming is often used for solving optimization problems, such as motion planning, trajectory tracking, generation of control strategies, etc. By modeling system dynamic constraints and performance metrics, quadratic programming can provide an efficient and optimized control solution.
Disclosure of Invention
The invention provides a self-adaptive load compensation control method of a quadruped robot, which aims to solve the control problem of the quadruped robot under the condition of unknown load and improve the stability and performance of the quadruped robot.
The adaptive load compensation control method comprises the following steps:
Acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
establishing a dynamics model of the quadruped robot;
Estimating the mass and the generated torque of an unknown effective load through an adaptive control method according to the dynamic model, and carrying out online estimation on the dynamic model so as to compensate the influence of the unknown effective load;
Calculating joint moment of the quadruped robot through a quadratic programming method according to the state information;
And adjusting the joints of the quadruped robot in real time through a balance controller according to the joint moment.
Preferably, the kinetic model of the four-legged robot satisfies the following relation:
wherein m represents the mass of the quadruped robot, Representing the acceleration of the quadruped robot, r i representing the position vector of the inertial origin, r c representing the position vector of the centroid of the quadruped robot, i=1, 2, 3, 4 representing the number of legs of the quadruped robot, F b∈R3 representing the force applied to the quadruped robot by the unknown payload, F i representing the contact force ,F=(F1 T,F2 T,F3 T,F4 T)T,IG∈R3×3 on each leg of the quadruped robot representing the inertial matrix of the quadruped robot, d=r b×mb g representing the disturbance that is difficult to obtain due to the terms r b and m b, r b representing the position vector of the unknown payload, m b representing the mass of the unknown payload.
Preferably, the force F b applied by the unknown payload to the quadruped robot satisfies the following relationship:
Wherein, An acceleration representative of the unknown payload position.
Preferably, defining T b to represent the torque acting on the quadruped robot, T b satisfies the following relationship:
Preferably, in the step of calculating the joint moment of the quadruped robot by a quadratic programming method, a calculation formula of the quadratic programming method is as follows:
min(AF-B)TR(AF-B)+FTSF;
Wherein τ min and τ max represent minimum and maximum joint moments of the quadruped robot, F ix、Fiy and F iz represent contact force vectors of each foot of the quadruped robot, μ is a friction coefficient between a contact foot and the ground, J i represents jacobian matrix of i legs of the quadruped robot, D i represents matrix corresponding to vacated legs, diagonal matrices R and S represent weight matrices, and a and B are represented as follows:
F B represents the desired force on the four-legged robot torso and T B represents the torque on the four-legged robot torso.
In a second aspect, the present invention also provides an adaptive load compensation control system of a quadruped robot, the adaptive load compensation control system comprising:
The information acquisition module is used for acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
the model building module is used for building a dynamics model of the quadruped robot;
the self-adaptive module is used for estimating the mass and the generated torque of the unknown effective load through a self-adaptive control method according to the dynamic model, and carrying out on-line estimation on the dynamic model so as to compensate the influence of the unknown effective load;
The secondary planning module is used for calculating the joint moment of the quadruped robot through a secondary planning method according to the state information;
And the control module is used for adjusting the joints of the quadruped robot in real time through the balance controller according to the joint moment.
Compared with the prior art, the method has the beneficial effects that the pose and speed information of the robot is acquired by utilizing a multi-sensor fusion technology, and the dynamics modeling is carried out on the motion of the quadruped robot. And converting the robot motion control problem into a mathematical programming problem by using a quadratic programming optimization technology, and adjusting control parameters in real time in an online updating mode. The stable gait control of the quadruped robot can be realized by iteratively solving the optimization problem, and the unknown effective load is subjected to self-adaptive compensation, so that better motion performance and robustness are realized. The control problem of the four-legged robot under the condition of unknown load is effectively solved, and the stability and performance of the four-legged robot are improved.
Drawings
The present invention will be described in detail with reference to the accompanying drawings. The foregoing and other aspects of the invention will become more apparent and more readily appreciated from the following detailed description taken in conjunction with the accompanying drawings. In the accompanying drawings:
Fig. 1 is a flow chart of an adaptive load compensation control method of a four-legged robot according to an embodiment of the present invention;
Fig. 2 is a schematic diagram of a change of a load of 6kg standing time in a four-foot robot simulation environment according to the adaptive load compensation control method of the four-foot robot provided by the embodiment of the invention;
fig. 3 is a schematic diagram of a change of a moment when a load is 6kg under a simulation environment of a quadruped robot according to the adaptive load compensation control method of the quadruped robot provided by the embodiment of the invention;
Fig. 4 is a schematic diagram of a change of a load of 2.5kg in standing time under a real machine environment of a four-foot robot according to an adaptive load compensation control method of the four-foot robot provided by the embodiment of the invention;
Fig. 5 is a schematic diagram of a change of a moment when a load of 2.5kg moves in a real machine environment of the quadruped robot according to the adaptive load compensation control method of the quadruped robot provided by the embodiment of the invention;
Fig. 6 is a flowchart of an adaptive load compensation control system for a four-legged robot according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example one
Referring to fig. 1 to 5, the present invention provides an adaptive load compensation control method for a quadruped robot, the adaptive load compensation control method comprising the following steps:
S101, acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
S102, establishing a dynamics model of the quadruped robot;
In the embodiment of the invention, the single rigid body dynamics model of the four-foot robot is as follows:
wherein m represents the mass of the quadruped robot, Representing the acceleration of the quadruped robot, r i representing the position vector of the inertial origin, r c representing the position vector of the centroid of the quadruped robot, i=1, 2, 3, 4 representing the number of legs of the quadruped robot, F b∈R3 representing the force applied to the quadruped robot by the unknown payload, F i representing the contact force ,F=(F1 T,F2 T,F3 T,F4 T)T,IG∈R3×3 on each leg of the quadruped robot representing the inertial matrix of the quadruped robot, d=r b×mb g representing the disturbance that is difficult to obtain due to the terms r b and m b, r b representing the position vector of the unknown payload, m b representing the mass of the unknown payload.
In view of the practical situation, the following assumptions are used without loss of generality:
assuming that the time derivative of d has an upper bound, i.e
The term in the above formula (2)The expandable device can be expanded as follows:
The equation here represents the rate of change of (I Gwb) over time, which is equal to the inertial matrix (I G) times the angular acceleration Plus the angular velocity fork times the product of the inertia matrix I G and the angular velocity w b.
S103, estimating the mass of an unknown effective load and the generated torque through an adaptive control method according to the dynamics model;
In the embodiment of the invention, the force applied to the robot by the unknown load is defined as F b. The calculation formula is as follows:
Wherein, An acceleration representative of the unknown payload position.
It is assumed that the unknown payload remains in contact with the quadruped robot at all times, which means that the speed and acceleration between them are equal. This assumption means thatDuring this time, there is no relative sliding or loss of contact between the unknown payload and the robot.
In adaptive controllers for four-legged robots, a linear combination of position error and velocity error, s p, is commonly used. When s p =0 is satisfied, the method exhibits exponentially stable dynamics. Thus, the following compound errors are defined:
wherein e p=x-xd and Representing the linear position error and the linear velocity error of the load, respectively. In addition, λ p∈R3×3 is a positive diagonal matrix. Consider the following Liapunov function:
The above expression is developed.
Considering formula (4), formula (8) may be rewritten as:
wherein Y p∈R3 can be represented as:
For a pair of The rewrites of (2) are as follows:
F b The design is as follows:
Control law and estimated dynamics related terms, denoted by Y p, and a PD term Wherein the method comprises the steps ofIs a positive diagonal matrix that directs the system to track the desired translational motion.For an estimate of the mass m b of the unknown payload,Representing the estimation error of the unknown payload quality. Substituting it intoThe method can obtain the following steps:
V p (t) has positive and time-varying properties, Is negative half-definite. Based on the lispro theorem, the system is consistently stable. Thus, s p andWill remain bounded.
From the above equation, V p (t) has a finite limit. In addition, it can be easily demonstrated thatIs bounded. Thus, considerThe expression of (2) yieldsIs a bounded conclusion. Now due toIs uniformly continuous in time (whileIs bounded), V p (t) has a lower bound. Therefore, based on the lemma of Barbara, at t→infinity,When s p =0, we getA progressively stabilizing system is defined.
In the embodiment of the invention, in order to compensate the torque d generated by the unknown effective load in the motion process, an adaptive control method is adopted for estimation. Definition T b represents the torque acting on the quadruped robot, then there are:
the following composite errors are defined:
Wherein e o=log(RTRd) and Respectively, the direction error and the angular velocity error. In this context,AndThe actual and desired body directions are described separately. Function ofOne rotation matrix is mapped to a corresponding rotation vector.Is the actual angular velocity of the object,Is the desired angular velocity of the object,Is a positive diagonal matrix.
Consider the following Liapunov function:
Wherein, For a positive-to-negative diagonal matrix,As an estimate of d,To estimate the error. Since d is a constant value, the error is estimatedIs equal to the estimation errorIs a derivative of (a). By differentiating V o (t), its time derivative is obtained as:
Design T B The following are provided:
the stability of the li-apunov function demonstrates that the process follows the above equation.
S104, calculating joint moment of the quadruped robot through a quadratic programming method according to the state information;
In the embodiment of the invention, the supporting legs of the quadruped robot are controlled by adopting the balance controller. The balance controller forces PD control, which refers to proportional + differential control, of the centroid and body direction, which quickly predicts future changes and responds after the system stabilizes. The characteristic is rapidity and stability, and simultaneously ensures that the foot end force meets the friction constraint.
The goal of the balance controller is to solve for the optimal distribution of foot end force, denoted as F. From equations (1) (2) (3), its drive can be derived, approximating COM dynamics to the corresponding expected dynamics as:
since the kinetic model is linear, it can be expressed as a quadratic programming problem (QP problem) to calculate the ground contact force f. The quadratic programming calculation formula is as follows:
min(AF-B)TR(AF-B)+FTSF(30);
wherein τ min and τ max represent minimum and maximum joint moments of the quadruped robot, F ix、Fiy and F iz represent contact force vectors of each foot of the quadruped robot, μ is a friction coefficient between a contact foot and the ground, J i represents a jacobian matrix of i legs of the quadruped robot, D i represents a matrix corresponding to a vacated leg, and diagonal matrices R and S represent weight matrices. The representations of A and B are as follows:
as calculated, the motion controller requires accurate model parameters, which can be significantly affected if disturbed. Thus, the mass of the unknown load m b and the generated torque d are estimated separately using adaptive control. From this, the force F b exerted by the unknown load on the robot can be calculated. Then, using an inverse kinematics solver, the desired force F B and torque T B acting on the torso of the quadruped robot are calculated to track the desired motion of the quadruped robot.
In the embodiment of the invention, the control of the swing leg of the four-legged robot mainly comprises the calculation of the joint torque of the leg. Before this, the foot position of the leg needs to be planned to obtain the desired joint angle and joint speed. The trajectory of the foot placement follows the trajectory in the world coordinate system. The calculation of the joint moment of the swing leg comprises two components: a feedback term and a feedforward term. The control law of calculating the moment of the swing leg joint is as follows:
Wherein, Is the jacobian matrix of the legs,For a diagonal positive matrix to be defined,Is the position and velocity vector of leg i,For the position and velocity trajectory of the corresponding reference swing leg, andIs a feed forward torque.
Where x f denotes the x-coordinate of the thigh joint, y f denotes the y-coordinate of the thigh joint, v x is the speed of the robot in the x-direction, v y is the speed of the y-direction, p e 0,1 denotes the gait phase of the robot, where p denotes the proportion of the gait cycle of the stance phase, T swing is the duration of the swing phase of the leg, T stance is the duration of the stance phase of the leg, k x,ky >0.
In addition to translation, rotational movement of the body also affects the coordinates of the pivot point in the x-axis and y-axis. Here, the position of the landing point can be calculated in a similar way.
τff,i=JTfd (36);
Where K p and K d are positive diagonal matrices. The correction force f d represents the force applied to the foot. J represents the jacobian matrix for the current leg. From the above equation, it is possible to calculate the torque τ ff,i of each joint, which approximates the statics of a single leg when the legs of the four-legged robot do not move rapidly. By adjusting the values of K p and K d in f d, the foot can effectively track the position and velocity of the target.
And S105, adjusting the joints of the quadruped robot in real time through a balance controller according to the joint moment.
Compared with the prior art, the method has the beneficial effects that the pose and speed information of the robot is acquired by utilizing a multi-sensor fusion technology, and the dynamics modeling is carried out on the motion of the quadruped robot. And converting the robot motion control problem into a mathematical programming problem by using a quadratic programming optimization technology, and adjusting control parameters in real time in an online updating mode. The stable gait control of the quadruped robot can be realized by iteratively solving the optimization problem, and the unknown effective load is subjected to self-adaptive compensation, so that better motion performance and robustness are realized. The control problem of the four-legged robot under the condition of unknown load is effectively solved, and the stability and performance of the four-legged robot are improved.
Example two
Referring to fig. 6, the present invention further provides an adaptive load compensation control system 200 of a quadruped robot, the adaptive load compensation control system comprising:
S201, an information acquisition module, which is used for acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
s202, a model building module is used for building a dynamics model of the quadruped robot;
S203, an adaptive module is used for estimating the mass and the generated torque of an unknown effective load through an adaptive control method according to the dynamic model, and carrying out online estimation on the dynamic model so as to compensate the influence of the unknown effective load;
S204, a quadratic programming module is used for calculating the joint moment of the quadruped robot through a quadratic programming method according to the state information;
And S205, a control module adjusts the joints of the quadruped robot in real time through a balance controller according to the joint moment.
The adaptive load compensation control system 200 of the quadruped robot can implement the steps in the adaptive load compensation control method of the quadruped robot in the above embodiment, and can implement the same technical effects, and the description of the above embodiment is omitted herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
While the embodiments of the present invention have been illustrated and described in connection with the drawings, what is presently considered to be the most practical and preferred embodiments of the invention, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various equivalent modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (2)
1. The adaptive load compensation control method of the four-legged robot is characterized by comprising the following steps of:
Acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
establishing a dynamics model of the quadruped robot;
Estimating the mass and the generated torque of an unknown effective load through an adaptive control method according to the dynamic model, and carrying out online estimation on the dynamic model so as to compensate the influence of the unknown effective load;
Calculating joint moment of the quadruped robot through a quadratic programming method according to the mass of the unknown effective load, the generated torque and the state information;
The joints of the quadruped robot are adjusted in real time through a balance controller according to the joint moment;
the kinetic model of the four-legged robot satisfies the following relation:
;
;
wherein m represents the mass of the quadruped robot, Representing the acceleration of the four-legged robot,A position vector representing the origin of the inertial frame,A position vector representing the centroid of the quadruped robot, i=1, 2, 3,4 representing the number of legs of the quadruped robot,The force applied to the quadruped robot for the unknown payload,Representing the contact force on each leg of the four-legged robot,,Representing an inertial matrix of the four-legged robot,Representing due to itemsAndAnd the disturbance that is difficult to obtain,A position vector representing the unknown payload,Representing the quality of the unknown payload;
The force applied to the quadruped robot by the unknown payload The following relationship is satisfied:
;
Wherein, An acceleration representative of the unknown payload position;
Definition of the definition Representing the torque acting on the quadruped robotThe following relationship is satisfied:
;
the following composite errors are defined:
;
Wherein, AndRespectively indicating a direction error and an angular velocity error; And The actual and desired body directions are described separately; function ofMapping one rotation matrix to a corresponding rotation vector; is the actual angular velocity of the object, Is the desired angular velocity of the object,Is a positive diagonal matrix;
Consider the following Liapunov function:
;
Wherein, For a positive-to-negative diagonal matrix,Is thatIs used for the estimation of the (c),Is an estimation error; due toIs a constant value, thus estimating the errorIs equal to the estimation errorIs a derivative of (2); by differentiationThe time derivative obtained is:
;
;
;
;
Definition of the definition AndThe following are provided:
;
in the step of calculating the joint moment of the quadruped robot by a quadratic programming method, the quadratic programming method has a calculation formula as follows:
;
;
Wherein, AndRepresenting the minimum and maximum joint moments of the quadruped robot,、AndRepresenting the contact force vector for each foot of the four-foot robot,Is the coefficient of friction between the contact foot and the ground,Representing the four-legged robotThe jacobian matrix of the bar legs,Representing the matrix corresponding to the vacated leg, diagonal matrixAnd S represents a weight matrix and,AndIs represented as follows:
;
representing the desired force on the four-legged robot torso, Representing the torque on the four-legged robot torso.
2. An adaptive load compensation control system of a four-legged robot, wherein the adaptive load compensation control system adopts the adaptive load compensation control method of the four-legged robot according to claim 1, the adaptive load compensation control system comprising:
The information acquisition module is used for acquiring state information of the quadruped robot through a sensor on the quadruped robot, wherein the state information comprises joint angles, joint speeds and body postures;
The model building module is used for building a dynamics model of the quadruped robot; the kinetic model of the four-legged robot satisfies the following relation:
;
;
wherein m represents the mass of the quadruped robot, Representing the acceleration of the four-legged robot,A position vector representing the origin of the inertial frame,A position vector representing the centroid of the quadruped robot, i=1, 2, 3,4 representing the number of legs of the quadruped robot,The force applied to the quadruped robot for the unknown payload,Representing the contact force on each leg of the four-legged robot,,Representing an inertial matrix of the four-legged robot,Representing due to itemsAndAnd the disturbance that is difficult to obtain,A position vector representing the unknown payload,Representing the quality of the unknown payload;
the self-adaptive module is used for estimating the mass and the generated torque of the unknown effective load through a self-adaptive control method according to the dynamic model, and carrying out on-line estimation on the dynamic model so as to compensate the influence of the unknown effective load; the force applied to the quadruped robot by the unknown payload The following relationship is satisfied:
;
Wherein, An acceleration representative of the unknown payload position;
Definition of the definition Representing the torque acting on the quadruped robotThe following relationship is satisfied:
;
the secondary planning module is used for calculating joint moment of the quadruped robot through a secondary planning method according to the mass of the unknown effective load, the generated torque and the state information;
And the control module is used for adjusting the joints of the quadruped robot in real time through the balance controller according to the joint moment.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311229197.1A CN117260718B (en) | 2023-09-21 | 2023-09-21 | Self-adaptive load compensation control method and system for four-legged robot |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311229197.1A CN117260718B (en) | 2023-09-21 | 2023-09-21 | Self-adaptive load compensation control method and system for four-legged robot |
Publications (2)
Publication Number | Publication Date |
---|---|
CN117260718A CN117260718A (en) | 2023-12-22 |
CN117260718B true CN117260718B (en) | 2024-07-02 |
Family
ID=89213795
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311229197.1A Active CN117260718B (en) | 2023-09-21 | 2023-09-21 | Self-adaptive load compensation control method and system for four-legged robot |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117260718B (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118210324A (en) * | 2024-02-05 | 2024-06-18 | 广东工业大学 | Four-foot robot self-adaptive model predictive control method based on interference observer |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111891252A (en) * | 2020-08-06 | 2020-11-06 | 齐鲁工业大学 | Body posture slope self-adaptive control method of four-footed bionic robot |
CN114384918A (en) * | 2022-01-14 | 2022-04-22 | 厦门大学 | Diagonal gait compliance control method of four-footed robot based on drop foot point adjustment |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20120084849A (en) * | 2011-01-21 | 2012-07-31 | 신화플래닛 주식회사 | Op-code learing method of silf-accembly robot and control bord |
CN108187310B (en) * | 2017-12-21 | 2019-05-31 | 东南大学 | Feel that the limb motion of information and posture information is intended to understand and upper-limbs rehabilitation training robot and its control method based on power |
CN108563131B (en) * | 2018-07-12 | 2021-06-15 | 南京航空航天大学 | Self-adaptive compensation method for out-of-control fault of actuator of satellite attitude control system |
CN113608534B (en) * | 2021-08-04 | 2023-10-24 | 上海大学 | Unmanned ship tracking control method and system |
US12005583B2 (en) * | 2022-02-08 | 2024-06-11 | GM Global Technology Operations LLC | Robotic system for moving a payload with minimal payload sway and increased positioning accuracy |
CN116654145A (en) * | 2022-02-21 | 2023-08-29 | Oppo广东移动通信有限公司 | Balance control method for robot, and storage medium |
-
2023
- 2023-09-21 CN CN202311229197.1A patent/CN117260718B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111891252A (en) * | 2020-08-06 | 2020-11-06 | 齐鲁工业大学 | Body posture slope self-adaptive control method of four-footed bionic robot |
CN114384918A (en) * | 2022-01-14 | 2022-04-22 | 厦门大学 | Diagonal gait compliance control method of four-footed robot based on drop foot point adjustment |
Also Published As
Publication number | Publication date |
---|---|
CN117260718A (en) | 2023-12-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lee et al. | Planning and control for collision-free cooperative aerial transportation | |
Mesesan et al. | Dynamic walking on compliant and uneven terrain using dcm and passivity-based whole-body control | |
JP7324932B2 (en) | dynamic planning controller | |
US8428780B2 (en) | External force target generating device of legged mobile robot | |
Chen et al. | Nonsingular fast terminal sliding mode posture control for six-legged walking robots with redundant actuation | |
US8442680B2 (en) | Motion state evaluation apparatus of legged mobile robot | |
Kim et al. | Computationally-robust and efficient prioritized whole-body controller with contact constraints | |
CN117260718B (en) | Self-adaptive load compensation control method and system for four-legged robot | |
US8396593B2 (en) | Gait generating device of legged mobile robot | |
Li et al. | Dual-master/single-slave haptic teleoperation system for semiautonomous bilateral control of hexapod robot subject to deformable rough terrain | |
Lee et al. | Robust and adaptive dynamic controller for fully-actuated robots in operational space under uncertainties | |
CN114625129B (en) | Motion control method and system of position control leg-foot robot | |
JP6781101B2 (en) | Non-linear system control method, biped robot control device, biped robot control method and its program | |
CN108897220A (en) | A kind of adaptive stabilizing balance control method and system and biped anthropomorphic robot | |
US8442681B2 (en) | Desired motion evaluation apparatus of legged mobile robot | |
CN110244714A (en) | Robot list leg swing phase double-closed-loop control method based on sliding formwork control | |
CN114397810A (en) | Four-legged robot motion control method based on adaptive virtual model control | |
Figueroa et al. | A dynamical system approach for adaptive grasping, navigation and co-manipulation with humanoid robots | |
Li et al. | A novel bilateral haptic teleoperation approach for hexapod robot walking and manipulating with legs | |
CN116859969A (en) | Disturbance suppression and stability control method and device for foot robot | |
Ding et al. | Online center of mass detection for quadruped robots in trot gait motion | |
Zhu et al. | Motion control for underactuated robots adaptable to uneven terrain by decomposing body balance and velocity tracking | |
Lim et al. | Control design to achieve dynamic walking on a bipedal robot with compliance | |
Moya et al. | Delayed teleoperation with force feedback of a humanoid robot | |
Xie et al. | Gait optimization and energy-based stability for biped locomotion using large-scale programming |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant |