CN114564010A - Unilateral obstacle crossing control method for double-wheel foot robot - Google Patents
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Abstract
The invention provides a unilateral obstacle crossing control method of a double-wheel foot robot, which is used for solving the problem of complex unilateral obstacle crossing control mode of the double-wheel foot robot caused by a complex modeling mode. Firstly, establishing a two-wheel-foot simplified dynamic model containing six state quantities, namely a robot virtual leg attitude angle, a virtual leg attitude angular velocity, a machine yaw attitude angle, a machine yaw attitude angular velocity, a machine forward displacement and a machine forward linear velocity, and carrying out linearization and discretization processing; secondly, polynomial interpolation of state feedback matrix elements is carried out according to the length of a discrete virtual leg, Kalman filter is adopted to realize observation of each state, a linear quadratic regulator is utilized to carry out full-state feedback to realize state feedback balance control, finally, the support leg is subjected to lateral inclination angle attitude compensation, hip joint angles and knee joint angles are generated through support leg kinematic inverse solution, and unilateral obstacle-crossing attitude control is realized.
Description
Technical Field
The invention relates to the field of robot motion control, in particular to a unilateral obstacle crossing control method for a double-wheel foot robot.
Background
The double-wheel foot robot is a foot type and wheel type composite walking robot, is different from the existing double-wheel balance trolley, has the advantages of wheel type efficient movement and foot type complex environment walking, corresponding research has been carried out by domestic and foreign research institutions, and typically comprises a Handle wheel foot robot with Boston power in the United states, which can realize complex actions such as unilateral obstacle crossing, jumping, going down stairs, descending slopes and the like.
The double-wheel foot robot comprises a machine body, two supporting legs and two driving wheels, wherein each supporting leg is provided with one driving wheel, each supporting leg comprises a thigh and a shank, the connecting part of the thigh and the machine body is a hip joint, the connecting part of the thigh and the shank is called as a knee joint, most of the existing single-side obstacle crossing control technologies of the double-wheel foot robot adopt a whole body dynamics method, the method needs to carry out complex dynamics modeling on each rigid body and each joint, and meanwhile, the method is realized by means of an optimized control mode, therefore, the double-wheel foot robot is required to have higher modeling precision aiming at each rigid body, and meanwhile, the calculation force of the whole system also has great challenge.
Disclosure of Invention
In order to solve the problem that the unilateral obstacle crossing control mode of the double-wheel foot robot is complex due to a complex modeling mode, the invention provides a unilateral obstacle crossing control method of the double-wheel foot robot, on the basis of a linear and discretized simplified dynamic model of the double-wheel foot, the concept of virtual legs is introduced, two legs are simplified into one virtual leg, in the simplified model, the two wheels are independent, and the virtual leg is connected with the two wheels; posture control is realized by respectively controlling joint angles of the two supporting legs, and the controlled object is ensured not to roll. The method is characterized by fusing the virtual legs to establish a state feedback control model and finally performing unilateral obstacle crossing attitude compensation on the supporting legs to realize stable control.
The invention firstly establishes a two-wheel-foot simplified dynamic model containing six state quantities of a robot virtual leg attitude angle, a virtual leg attitude angular velocity, a machine body yaw attitude angle, a machine body yaw attitude angular velocity, a machine body forward displacement and a machine body forward linear velocity, carries out linearization and discretization treatment, then introduces a virtual leg concept, carries out polynomial interpolation of state feedback matrix elements aiming at the length of a discretized virtual leg, adopts a Kalman filter to realize observation of each state, utilizes a linear quadratic regulator to carry out full-state feedback to generate driving moments of two driving wheels to realize state feedback balance control, finally carries out side dip angle attitude compensation on a supporting leg on the basis of the state feedback balance control, generates a hip joint angle and a knee joint angle through the inverse solution of the supporting leg kinematics to realize unilateral obstacle-crossing attitude control, the method is simple and easy to implement, and the control effect is good.
The specific technical scheme is as follows:
establishing a two-wheel-foot simplified dynamic model containing six state quantities, namely a robot virtual leg attitude angle, a virtual leg attitude angular velocity, a machine yaw attitude angle, a machine yaw attitude angular velocity, machine forward displacement and machine forward linear velocity, serving as a model basis for control, and performing linearization and discretization;
step (2) the balance control of the double-wheel foot robot under the variable virtual leg length is carried out, and the change of the virtual leg of the unilateral obstacle crossing is supported;
and (3) stably adapting the posture under the unilateral obstacle crossing to complete unilateral obstacle crossing stable control.
Further, the step (2) comprises the following steps,
step 21: solving a state feedback matrix at the current moment:
obtaining by off-line calculation of a state feedback matrixState feedback matrix K under discrete virtual leg lengthdAnd further using the discrete virtual leg lengths and corresponding KdFitting a state feedback matrix K through 5-degree polynomial interpolation, and finally obtaining the state feedback matrix at the current moment according to the length of the variable virtual leg at the current moment, wherein the state feedback matrix K obtained through fitting is used for adapting to state feedback control of the variable virtual leg under various lengths;
step 22: estimating the system state at the current moment by adopting a Kalman filter according to a discrete model of the biped robot
Step 23: fusing the state feedback matrix K of step 21 and the system state of step 22
Establishing an expected state XdAnd estimated current time system state
The state error feedback control model obtains the driving moment U of the wheel at the current momentkAnd balance control under variable virtual leg length is realized.
Further, the step (3) comprises the following steps,
step 31: measuring the side-tipping attitude angle phi of the machine body in real time;
step 32: establishing a side inclination angle proportional control term and an integral control term of the machine body;
step 33: and (3) respectively carrying out attitude compensation on the heights of the left and right supporting legs at the current moment by utilizing the proportional control item and the integral control item established in the step (32), converting the height positions of the two compensated supporting legs into the joint angle of each supporting leg through inverse kinematics, realizing stable adaptation of the attitude by driving the joint, and realizing unilateral obstacle crossing stable control under the combined action of the state error feedback model in the step (23).
Has the advantages that:
the existing control method of the double-wheel foot robot is mainly researched on balance control of the robot such as advancing, steering and the like, the feedback control precision is insufficient aiming at the position change state of the robot body, and most of the control methods of the whole body dynamics are adopted to solve the problem of attitude control under the single-side obstacle crossing working condition, and the control process is complex. Compared with the prior art, the invention has the following advantages:
(1) a dynamic equation of a full state is established, so that the pose of the robot can be effectively controlled; (2) the virtual leg idea is adopted, and the virtual leg length is used as the input of the interpolation of the state feedback matrix elements, so that the stability under different virtual leg lengths can be effectively realized; (3) the state matrix elements are subjected to quintic polynomial interpolation, so that the accuracy of state feedback control can be improved; (4) the attitude compensation of the side-tipping angle is carried out according to the height of the supporting leg, so that the unilateral obstacle crossing of the robot can be effectively controlled, and the control method is simple and effective; (5) the invention has simple model and simple and effective control method.
Drawings
Fig. 1 is a two-wheel-foot robot model.
Fig. 2 is a unilateral obstacle crossing model of the two-wheel foot robot.
Fig. 3 is a schematic angle view of a virtual leg in a vertical direction.
Detailed Description
The following describes a unilateral obstacle crossing control method of a two-wheeled foot robot in detail with reference to the accompanying drawings and specific embodiments.
Meanwhile, it is described herein that the following embodiments are preferred and preferred embodiments for making the embodiments more detailed, and those skilled in the art can implement the embodiments in other alternative ways for some known technologies; also, the drawings are only for purposes of more particularly describing embodiments and are not intended to particularly limit the invention.
The invention is intended to cover alternatives, modifications, equivalents, and alternatives that may be included within the spirit and scope of the invention. In the following description of the preferred embodiments of the present invention, specific details are set forth in order to provide a thorough understanding of the present invention, and it will be apparent to those skilled in the art that the present invention may be practiced without these specific details.
As shown in fig. 1, step 1, two-wheel foot dynamics modeling is used as a model basis for control. The method specifically comprises the following steps:
step 11: a Lagrange equation is adopted to establish a two-wheel foot dynamics model containing six state quantities of a robot virtual leg attitude angle/attitude angular velocity, a yaw attitude/attitude angular velocity and a forward displacement/linear velocity.
In the formula, L is a Lagrangian function, Q is a generalized coordinate, and Q is a generalized force.
Kinetic energy of the system:
wherein T is the kinetic energy of the system, theta is the angle of the virtual leg in the vertical direction, gamma is the yaw angle of the machine body, x is the forward displacement of the robot, and IxxIs the moment of inertia of the body along the x-axis, IyyIs the moment of inertia of the body along the y-axis, IzzMoment of inertia of the machine body along the z-axis, mass of M wheels, mass of M machine body, length of l virtual leg, width between d wheels, radius of r wheels,
potential energy of the system:
V＝Mglcosθ
L＝T-V
step 12: and (3) two-wheel foot dynamics linearization:
wherein:
p1＝[(2m+M)Iyyr2+2IyyIw]+2Mml2r2+2Ml2Iw
p2＝(Ml2+Iyy)(Mr2+2mr2+2Iw)-M2l2r2
p3＝2d2r(m+Iw/r2)+rIzz
in the formula IwMoment of inertia of the wheel along the axis of rotation, taul、τrThe active driving torque of the left wheel and the active driving torque of the right wheel are respectively.
Step 13: and discretizing a two-wheel foot continuous dynamic model.
In the formula, Δ t is a discrete time.
And 2, controlling the balance of the double-wheel foot robot under the variable virtual leg length to support the change of the virtual leg with the unilateral obstacle crossing. The method specifically comprises the following steps:
step 21: and solving the state feedback matrix at the current moment. Obtaining state feedback matrix elements under the discrete virtual leg length through state feedback matrix off-line calculation, and performing 5-order polynomial interpolation according to the discrete virtual leg length and the matrix elements; measuring the hip joint and knee joint angles of the two supporting legs in real time, calculating the length of the virtual leg according to the leg kinematics relationship, and calculating a state feedback matrix at the current moment according to the fitted 5 th-order polynomial.
The state feedback matrix is calculated off line, the Riccati equation is adopted to solve, and the solution is as follows:
in the formula, the positive definite matrix P is obtained by the following equation,
wherein Q is a semi-positive definite real symmetric matrix, R is a positive definite real symmetric matrix, AdAnd BdThe elements of the matrix contain the virtual leg lengths and are obtained from the formula in step 13.
The state feedback matrix 5-degree polynomial interpolation is used for solving corresponding K matrix elements by setting discrete virtual leg length and setting according to Q, R matrix so as to adapt to state feedback control under variable virtual leg length, and the fifth-degree polynomial interpolation form is as follows:
Kij＝k5_ijl5+k4_ijl4+k3_ijl3+k2_ijl2+k1_ijl+k0_ij
in the formula KijIs the ith row and the jth column element, K, of the K matrixn_ijIs corresponding to KijThe polynomial coefficient of (1).
The virtual leg length is calculated by measuring the hip joint and knee joint angles of the two supporting legs in real time according to the leg kinematics relationship, and the following solution is obtained:
pf1x＝-l1sinθ11-l2sin(θ11+θ12)
pf1z＝-l1cosθ11-l2cos(θ11+θ12)
pf2x＝-l1sinθ21-l2sin(θ21+θ22)
pf2z＝-l1cosθ21-l2cos(θ21+θ22)
in the formula, pfiFoot position of the ith leg, pfixIs the x-direction position of the foot of the ith leg, pfizIs the foot z-direction position of the ith leg,/1Thigh length,. l2Length of lower leg, [ theta ]11Left leg hip angle θ12Angle of knee joint of left leg θ21Angle of hip joint of right leg θ22Right leg knee joint angle.
Step 22: estimating the system state at the current moment by adopting a Kalman filter according to the discrete model of the biped robot in the step 13
The method comprises the following specific steps:
wherein,
in the formula,
for the last discrete-time system state,
in order to be in a new state of the system,
estimated system state for the current time, Pk-1Is the covariance matrix of the last discrete time,
as a new covariance matrix, PkIs the current covariance matrix, y is the system output, Uk-1For the last discrete-time control input, Ad、BdObtaining the C matrix from a system output equation, Pk-1Is initially set to be an identity matrix and,
initially set to zero vector, Uk-1Initially set to a zero vector.
Step 23: and (3) fusing the state feedback matrix in the step (21) and the system state in the step (22), establishing a state error feedback control model, generating a wheel driving moment, and realizing balance control under the variable virtual leg length, wherein the control model is as follows:
in the formula of UkFor the current discrete-time wheel drive torque input, XdIs in the desired state.
As shown in fig. 2, step 3, the posture under the unilateral obstacle crossing is adapted stably, so that the controlled object is ensured not to turn on one side, and the unilateral obstacle crossing stable control is completed. The method specifically comprises the following steps:
step 31: and detecting the side inclination angle phi of the machine body in real time through the airborne inertia measurement unit.
Step 32: controlling the roll angle phi in a proportional-integral mode, and establishing a proportional control term and an integral control term of the roll angle of the machine body as follows:
proportional term pkp＝kpφ(φdPhi), integral term pki＝kIφ∑(φd-φ)Δt，
In the formula, kpφIs a proportionality coefficient, kIφIs an integral coefficient, phidFor the desired body roll angle, φ is the actual body roll angle, and Δ t is the time interval.
Step 33: according to the polarity directions of the left and right side legs, carrying out attitude compensation on the height of the supporting leg to generate a new foot end position; and (3) because the foot end position and each joint angle have a calculation relation, the angle of each joint can be obtained from the new foot end position through the inverse kinematics of the leg, the joint angle is further controlled to realize the posture adaptation, and the posture adaptation and the state error feedback model in the step 23 act together to realize the unilateral obstacle crossing stable control.
θij＝IK(pi_new)
Wherein, the left leg alpha is-1, the right leg alpha is 1,
for the amount of height compensation for the ith support leg,
new height position for ith support leg, pi_newIK represents the inverse kinematics calculation for the ith legijRepresenting the angle of the jth joint of the ith support leg.
The robot control system is used for controlling the motion of the double-wheel legged robot, and particularly ensures that the robot can realize stable unilateral obstacle crossing by setting six state quantities of an expected robot virtual leg attitude angle, a virtual leg attitude angular velocity, a machine body yaw attitude angle, a machine body yaw attitude angular velocity, a machine body forward displacement, a machine body forward linear velocity and an expected machine body side inclination angle. For example, the expected forward linear velocity of the machine body is set to be 1km/h, the expected yaw velocity and yaw angle are set to be 0, the expected attitude and attitude angular velocity of the virtual leg are set to be 0, the expected forward displacement is accumulated according to the velocity and time, and the robot runs according to the expected forward linear velocity of the machine body; when the moving road meets a slope, the robot is controlled to cross the obstacle on one side, namely one wheel rides on the slope, the other wheel keeps driving on a horizontal road surface, at the moment, the robot is ensured not to tilt forwards and backwards through the step (2), then the side inclination angle of the machine body reaches the expected side inclination angle of the machine body through proportional integral control, and the machine body is ensured not to turn over, so that the stable obstacle crossing on one side is realized.
Claims (10)
1. The utility model provides a unilateral control method that hinders more of two-wheeled foot robot for control two-wheeled foot robot is unilateral hinders more, two-wheeled foot robot include organism, two supporting legs, two drive wheels, a drive wheel is connected to every supporting leg, every supporting leg contains thigh and shank, the connecting portion of thigh and organism becomes hip joint, the connecting portion of thigh and shank is called knee joint, its characterized in that: the method comprises the steps of introducing a concept of virtual legs, simplifying two legs into one virtual leg, wherein in a simplified model, two driving wheels are independent of each other, and the virtual leg is connected with the two driving wheels, wherein the length of the virtual leg is equal to half of the sum of the distances from a hip joint to the center of the corresponding driving wheel of each supporting leg, the length of the virtual leg, hip joint angles and knee joint angles of the two supporting legs have a leg kinematics calculation relation, and the hip joint angles and the knee joint angles of the two supporting legs are obtained through real-time measurement;
the specific control process comprises the following steps of,
establishing a two-wheel-foot simplified dynamic model containing six state quantities, namely a robot virtual leg attitude angle, a virtual leg attitude angular velocity, a machine yaw attitude angle, a machine yaw attitude angular velocity, machine forward displacement and machine forward linear velocity, serving as a model basis for control, and performing linearization and discretization;
step (2) balance control of the double-wheel foot robot under the variable virtual leg length is carried out, and support is carried out on the change of the virtual leg with the unilateral obstacle crossing;
and (3) stably adapting the posture under the unilateral obstacle crossing to finish the unilateral obstacle crossing stable control.
2. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 1, characterized in that: the simplified dynamic linearization model of the double-wheel foot in the step (1) is as follows:
wherein:
p1＝[(2m+M)Iyyr2+2IyyIw]+2Mml2r2+2Ml2Iw
p2＝(Ml2+Iyy)(Mr2+2mr2+2Iw)-M2l2r2
p3＝2d2r(m+Iw/r2)+rIzz
wherein x is the forward displacement of the robot, gamma is the yaw angle of the robot body, theta is the angle of the virtual leg in the vertical direction, M body mass, l virtual leg length, g is the acceleration of gravity, r wheel radius, M wheel mass, IwMoment of inertia of the wheel along the axis of rotation, IxxIs the moment of inertia of the body along the x-axis, IyyIs the moment of inertia of the body along the y-axis, IzzMoment of inertia of the body along the z-axis, d width between wheels, τl、τrActive driving torques of the left and right wheels, A, B, C,X, y and U are respectively corresponding to corresponding matrixes in the formula.
3. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 2, characterized in that: the simplified dynamic discretization model of the double-wheel foot in the step (1) is as follows:
wherein Δ t is a discrete time, Ad、Bd、Xk、UkRespectively corresponding matrixes in the formula.
4. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 3, characterized in that: further, the step (2) comprises the following steps,
step 21: solving a state feedback matrix at the current moment:
obtaining a state feedback matrix K under the length of the discrete virtual leg through off-line calculation of the state feedback matrixdAnd further using the discrete virtual leg lengths and corresponding KdFitting a state feedback matrix K through 5-degree polynomial interpolation, and finally obtaining the state feedback matrix at the current moment according to the length of the variable virtual leg at the current moment, wherein the state feedback matrix K obtained through fitting is used for adapting to state feedback control of the variable virtual leg under various lengths;
step 22: estimating the system state at the current moment by adopting a Kalman filter according to a discrete model of the biped robot
Step 23: fusing the state feedback matrix K of step 21 and the system state of step 22
Establishing an expected state XdSystematic with estimated current timeState of
The state error feedback control model obtains the driving moment U of the wheel at the current momentkBalance control at variable virtual leg lengths is achieved.
5. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 4, wherein the unilateral obstacle crossing control method comprises the following steps: further, the off-line calculation of the state feedback matrix in step 21 is implemented by solving a ricack Riccati equation, wherein the specific equation is as follows:
in the formula, the positive definite matrix P is obtained by the following equation,
wherein Q is a semi-positive definite real symmetric matrix, R is a positive definite real symmetric matrix, AdAnd BdThe elements of the matrix contain the virtual leg length.
6. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 4, wherein the unilateral obstacle crossing control method comprises the following steps: further, the system state observation model in step 22 is as follows:
wherein,
in the formula,
for the last discrete-time system state,
in order to be in a new state of the system,
estimated system state for the current time, Pk-1Is the covariance matrix of the last discrete time, Pk′As a new covariance matrix, PkIs the current covariance matrix, y is the system output, Uk-1For the last discrete-time control input, Ad、BdAnd obtaining the C matrix from a system output equation.
7. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 4, wherein the unilateral obstacle crossing control method comprises the following steps: further, the state error feedback control model in step 23 is as follows:
in the formula, XdIs a desired state, is a set value.
8. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 1, characterized in that: further, the step (3) comprises the following steps,
step 31: measuring the side-tipping attitude angle phi of the machine body in real time;
step 32: establishing a side inclination angle proportional control term and an integral control term of the machine body;
step 33: and (3) respectively carrying out attitude compensation on the heights of the left and right supporting legs at the current moment by utilizing the proportional control item and the integral control item established in the step (32), converting the height positions of the two compensated supporting legs into the joint angle of each supporting leg through inverse kinematics, realizing stable adaptation of the attitude by driving the joint, and realizing unilateral obstacle crossing stable control under the combined action of the state error feedback model in the step (23).
9. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 8, wherein: further, the proportional control term and the integral control term in step 32 are specifically as follows:
pkp＝kpφ(φd-φ)
pki＝kIφ∑(φd-φ)Δt
in the formula, kpφIs a proportionality coefficient, kIφIs an integral coefficient, phidFor the desired body roll angle, φ is the actual body roll angle, and Δ t is the time interval.
10. The unilateral obstacle crossing control method of the two-wheeled foot robot according to claim 9, wherein: further, the attitude compensation for the height of the support leg in step 33 is specifically as follows,
wherein, the left leg alpha is-1, the right leg alpha is 1,
the height compensation amount for the ith support leg.
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| CN114578836B (en) * | 2022-02-11 | 2024-06-25 | 中国北方车辆研究所 | Jumping control method for double-wheel-foot robot |
| CN118306495A (en) * | 2024-04-08 | 2024-07-09 | 盐城工学院 | Balance control method and system for double-wheel-leg robot |
| CN118306495B (en) * | 2024-04-08 | 2024-10-22 | 盐城工学院 | Balance control method and system for double-wheel-leg robot |
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