CN112947065B - AZR adjusting method for walking real-time gait of biped robot - Google Patents

AZR adjusting method for walking real-time gait of biped robot Download PDF

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CN112947065B
CN112947065B CN202110100304.5A CN202110100304A CN112947065B CN 112947065 B CN112947065 B CN 112947065B CN 202110100304 A CN202110100304 A CN 202110100304A CN 112947065 B CN112947065 B CN 112947065B
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robot
azr
zmp
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walking
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CN112947065A (en
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卢志强
侯媛彬
孟芸
柴秀丽
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Henan University
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    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
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Abstract

The invention relates to an AZR (autoregressive moving distance) adjusting method for walking real-time gaits of a biped robot, which comprises the steps of constructing an online database by using measured and calculated data of an offline system of the robot, wherein the online database comprises a robot step size set S, AZR set H, a walking gaits set G and an energy consumption set E, and the distance d of a target travel of a given robot and an expected AZR position r are measured at the given robot AZR Planning the step length sequence with the lowest energy consumption
Figure DDA0002913319290000011
Each step length of the robot is taken out
Figure DDA0002913319290000012
And AZR variable η i Inquiring an on-line database to obtain a motor angle sequence g for gait control i According to the pressure set F of the walking steps of the robot i Calculating the real-time ZMP trajectory r ZMP By using r ZMP (n) and r AZR Deviation e of (n) i Obtaining AZR variable eta by PI correction method i Correction value η of i+1 And according to the correction value eta i+1 And step size s i+1 And inquiring an online database, and optimizing the gait track of the biped robot online. The invention can overcome the interference of robot modeling and environmental errors, realize gait control with high robustness and low energy consumption in the walking process of the biped robot, and better solve the walking problem of the biped robot with highly nonlinear characteristics.

Description

AZR adjusting method for walking real-time gait of biped robot
Technical Field
The invention relates to the field of motion design of biped robots, in particular to an AZR (autoregressive distance) adjusting method for walking real-time gait of a biped robot.
Background
Because the walking gait of the biped robot (humanoid robot) has a highly nonlinear characteristic, a modeling error inevitably exists in the modeling of the biped robot, and in order to meet the requirement of robustness, the prior method fixes the ZMP (Zero Moment Point, ZMP) track of the robot motion at the center of the supporting leg to realize the most stable walking, but the method is not an efficient method, so that the walking consumes more energy;
through research on an AZR (Allowable ZMP Region, AZR) method, the method is a better method for overcoming the balance between modeling errors and efficient walking of the robot, some edge regions are marked in the regions of the supporting legs to compensate the modeling errors, and the ZMP track of the walking of the robot is positioned in the AZR in the middle of the supporting legs;
the stability or energy consumption of the biped robot is related to a variable eta describing the AZR area size, if the AZR variable eta can be dynamically adjusted when the robot travels, the robot can obtain the optimal gait plan when the robot travels, and therefore a better compromise is obtained between the energy consumption and the stability.
Disclosure of Invention
The invention provides an AZR (amplitude-variation-ratio) adjusting method for walking real-time gait of a biped robot for realizing online optimization of walking of the biped robot
Figure BDA0002913319270000011
And passes through the AZR position r during the robot walking AZR (n) actual gait position r of biped robot ZMP Deviation e between (n) i Updating variable eta of AZR by PI correction method i And further according to the variable η of AZR i+1 And step length s i+1 And inquiring an online database to adjust the gait plan of the robot online. The interference of robot modeling and environmental errors is overcome, gait control with high robustness and low energy consumption is realized in the walking process of the biped robot, and the walking problem of the biped robot with highly nonlinear characteristics is well solved.
The invention provides an AZR (AZR) adjusting method for walking real-time gait of a biped robot, which comprises the following steps of:
step l: the method comprises the steps that an online database is built by using measurement and calculation data of a robot offline system, wherein the online database comprises a robot step size set S, AZR set H, a walking gait set G and an energy consumption set E;
step 2: given a robot target travel distance d and a desired AZR position r AZR Planning the step length sequence with the lowest energy consumption
Figure BDA0002913319270000012
And step 3: each step length of the robot is taken out
Figure BDA0002913319270000013
And AZR variable η i Inquiring an on-line database to obtain a motor angle sequence g for gait control i ；
And 4, step 4: according to the pressure set F of the steps during the walking of the robot i Calculating the real-time ZMP trajectory r ZMP (n) based on r ZMP (n) and r AZR (n) obtaining a deviation e in the Y-axis direction i ；
And 5: using the deviation e of the Y-axis direction i Obtaining AZR variable eta by PI correction method i Correction value η of i+1 And according to said correction value eta i+1 And step length s i+1 And inquiring an online database, and optimizing the gait track of the biped robot online.
Further, step 2 specifically includes:
step 2.1: the step length sequence comprises a start step, an end step and a plurality of loop steps s m A plurality of said cyclic steps s m Step length is equal, and according to the motion rule of the robot, the initial step is defined to comprise s 1 And s 2 Said stopping step comprising s c-1 And s c Let s stand for 1 ＝s c 、s 2 ＝s c-1 And the total length of the start step and the stop step is 1-2 times of the cycle step s m Step size of (2);
step 2.2: given the robot target travel distance d, the cycle step s is known m Is calculated by formula (1), said start step s is calculated by formula (1) 1 And s 2 Step length:
Figure BDA0002913319270000021
wherein d is b The total length of the start step and the stop step; c is the total number of steps;
step 2.3: given the expected AZR position r AZR Taking a cyclic step S from the set S m Forming a step sequence S m Said step length sequence S m The energy consumption function of (3) is expressed as formula (2);
Figure BDA0002913319270000022
wherein eta is AZR position r AZR Corresponding to the value of the variable of the area AZR,
Figure BDA0002913319270000023
indicating the step of the cycle s m The energy consumption of (2) is reduced,
Figure BDA0002913319270000024
represents the start of a step s 1 The energy consumption of (2) is reduced,
Figure BDA0002913319270000025
indicating a stop step s c The energy consumption of (2) is reduced,
Figure BDA0002913319270000026
and
Figure BDA0002913319270000027
the equivalent cycle step length is s when the moving distance of the swing foot in front of the body is unequal to the moving distance of the swing foot in the process of starting and stopping the robot walking 1 And s 2 Energy consumption of (2);
step 2.4: combining the formula (2) to obtain the optimal cycle step length
Figure BDA0002913319270000028
The optimal cycle step size
Figure BDA0002913319270000029
Correspondingly forming the step length sequence with the lowest energy consumption
Figure BDA00029133192700000210
The step length sequence with the lowest energy consumption
Figure BDA00029133192700000211
The constraint conditions shown in formula (3) are satisfied;
Figure BDA00029133192700000212
wherein the content of the first and second substances,
Figure BDA00029133192700000213
denotes s m The energy consumption value calculated when the kth value in the step set S is taken, k is 1,2, …, L, and L is the number of elements in the step set S.
Further, step 4 specifically includes:
step 4.1 the real-time ZMP trajectory r ZMP (n) is represented by:
r ZMP (n)＝[x ZMP (n) y ZMP (n) 0] T (4)；
wherein x and y respectively represent the front and side directions of the robot;
combining a formula (4), the robot walks the ith step, and a value set F is obtained by the robot sole pressure sensor at the sampling point n moment i (n) calculating the real-time ZMP trajectory r ZMP (n) represented by formula (5):
Figure BDA0002913319270000031
wherein the content of the first and second substances,
Figure BDA0002913319270000032
and
Figure BDA0002913319270000033
the position and pressure of the jth sensor in the x-axis direction and the y-axis direction, respectively, c n Is the number of sensors.
Further, the step 4 further includes:
step 4.2: get biped robot per step time T S For controlling the period, the biped robot has a step time T S Expressed as:
T S ＝N·t s (6)；
wherein N is the gait cycle of the biped robot;
step 4.3: defining the duty cycle of the robot motion as sigma ≡ 2N 1 The motion state of the robot is judged according to the value of the sampling point N;
if N is present 1 ＜n≤N 2 The biped robot is in a single support stage SSP;
if N is more than or equal to 1 and less than or equal to N 1 ，N 2 N is less than or equal to N, and the biped robot is in a DSP (digital signal processor) of a double-support stage;
wherein N is 1 ＝σN/2，N 2 ＝N-N 1 ，n＝1，2，…，N；
Step 4.4: when the biped robot is in the DSP stage of dual support, r ZMP (n) is located in the desired AZR region;
when the biped robot is in the single support stage SSP, the X-axis direction X of the movement is required ZMP (n) monotonically increases, and x ZMP (N 1 +1)≥x AZR (N 1 +1)、x ZMP (N 2 )≤x AZR (N 2 )。
Further, combining with the formula (5), the deviation value e of the Y-axis direction in step 4 i Expressed as:
Figure BDA0002913319270000034
wherein, y AZR When (n) is not less than 0, c o ＝1；y AZR When (n) < 0, c o ＝-1，l fw The robot is wide enough.
Further, the step 5 specifically includes:
step 5.1: establishing a PI model with an incremental transfer function, wherein the AZR variable eta i Correction value η of i+1 As expressed by equation (8):
η i+1 ＝η i +Δη i+1 (8)；
wherein, the increment is delta eta i+1 As expressed by equation (9):
Figure BDA0002913319270000041
wherein k is P Is the proportionality coefficient, T I Is the integration time constant, T S Is the control period;
step 5.2: according to said correction value eta i+1 And step size s i+1 Inquiring an online database to obtain a gait track g for controlling the biped robot to walk at the (i + 1) th step i+1 ，g i+1 As expressed by equation (10):
Figure BDA0002913319270000042
wherein q is the angle of the joint motor of the robot, m is the number of the joint motors, and N is the gait cycle.
Further, the step 5 further comprises:
at the calculation of Δ η i+1 When introducing a time constant of T L First order inertia element of
Figure BDA0002913319270000043
Smoothing is carried out:
Δη i+1 ＝K α Δη i +K 1 e i +K 2 e i-1 (11)；
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002913319270000044
through the technical scheme, the invention has the beneficial effects that:
the invention sets an online database, wherein the online database comprises a biped robot step size set S, AZR set H, a walking gait set G andand an energy consumption set E, wherein an element S of the set S is combined with an element eta of the set H, and an element G of G in the walking gait set, namely G ← (S, eta), is stored in the element G and is used for controlling the robot to walk, and the energy consumption is an element of the energy consumption set E
Figure BDA0002913319270000045
When the travel distance d and the AZR position r of the robot target are given AZR And then planning the step length sequence with the lowest energy consumption of the robot
Figure BDA0002913319270000046
In the step length sequence
Figure BDA0002913319270000047
Step length s of the ith step of robot walking is taken i And corresponding AZR variable η i E.g. H, inquiring an online database to obtain a gait track g of the angle of the robot joint motor i In the walking process of the biped robot, due to factors such as modeling errors and environmental changes, gait can be deviated, and the real-time ZMP trajectory r is calculated ZMP Obtaining and expecting AZR position r AZR Deviation value e of i Obtaining AZR variable eta by PI correction method i Correction value η of i+1 According to said correction value η i+1 And step length s i+1 And inquiring an online database, and optimizing the gait track of the biped robot online.
The method for adjusting the AZR of the real-time gait of the biped robot can perform compromise calculation on the stability and the energy consumption of the biped robot in the walking control of the biped robot with highly nonlinear characteristics, and realize that the gait of the biped robot keeps stable walking under the condition of lowest energy consumption by performing online adjustment on an AZR variable eta.
Drawings
FIG. 1 is a flow chart of the AZR adjustment method for real-time walking gait of a biped robot of the present invention;
FIG. 2 is a system working principle diagram of the AZR adjusting method for real-time walking gait of the biped robot.
Fig. 3 is a schematic diagram of the relationship between the AZR region and the robot support region of the AZR adjustment method for real-time walking gait of the biped robot of the present invention.
Fig. 4 is a motion energy consumption analysis diagram of robot gait planning of the AZR adjusting method of walking real-time gait of the biped robot of the invention.
FIG. 5 is a dynamic simulation diagram of robot gait movement in the AZR adjustment method of walking real-time gait of the biped robot of the present invention.
Fig. 6 is a schematic diagram of deviation value calculation in the AZR adjustment method of walking real-time gait of the biped robot of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1 and 2, an AZR adjusting method for a walking real-time gait of a biped robot according to an embodiment of the present invention includes the following steps:
step 1: the method comprises the steps that an online database is built by using measurement and calculation data of a robot offline system, wherein the online database comprises a robot step size set S, AZR set H, a walking gait set G and an energy consumption set E;
step 2: given a robot target travel distance d and a desired AZR position r AZR Planning the step length sequence with the lowest energy consumption
Figure BDA0002913319270000051
And step 3: each step length of the robot is taken out
Figure BDA0002913319270000052
And AZR variable η i Querying online dataA motor angle sequence g for gait control i ；
And 4, step 4: according to the pressure set F of the steps during the walking of the robot i Calculating the real-time ZMP trajectory r ZMP (n) based on r ZMP (n) and r AZR (n) obtaining a deviation e in the Y-axis direction i ；
And 5: using the deviation e of the Y-axis direction i Obtaining AZR variable eta by PI correction method i Correction value η of i+1 And according to said correction value eta i+1 And step size s i+1 And inquiring an online database, and optimizing the gait track of the biped robot online.
The method comprises the steps of constructing an online database, wherein the online database comprises a biped robot step size set S, AZR set H, a walking gait set G and an energy consumption set E, combining an element S of the set S with an element eta in the set H, and inquiring an element G of the G in the walking gait set, namely G ← (S, eta), wherein the element G stores a motor angle for controlling the robot to walk, and the energy consumption is an element of the energy consumption set E
Figure BDA0002913319270000061
Combining the expected AZR position r after the travel distance of the robot target is given by using the online database AZR Planning the step length sequence with the lowest energy consumption
Figure BDA0002913319270000062
And make the robot follow the step length sequence
Figure BDA0002913319270000063
When the robot walks with deviation due to interference of factors such as environment and the like, the method calculates r in the walking process of the robot in real time ZMP (n) track and sum position r AZR Deviation e between (n) i Obtaining variable eta of AZR by PI correction method i+1 Combined step length s i+1 And variable η of AZR i+1 And inquiring the online database again, and regulating the gait of the biped robot in the advancing process to complete the online gait optimization of the biped robot.
Example 2
As shown in fig. 4 and 5, based on the above embodiment 1, in this embodiment, to obtain the step length sequence with the lowest energy consumption
Figure BDA0002913319270000068
And optimizing the step 2, specifically:
step 2.1: the step length sequence comprises a start step, an end step and a plurality of loop steps s m A plurality of said cyclic steps s m Step length is equal, and according to the motion rule of the robot, the initial step is defined to comprise s 1 And s 2 Said stopping step comprising s c-1 And s c Let s 1 ＝s c 、s 2 ＝s c-1 And the total length of the start step and the stop step is 1-2 times of the cycle step s m Step size of (2);
step 2.2: given the robot target travel distance d, the cycle step s is known m Is calculated by the formula (1) said start step s 1 And s 2 Step length:
Figure BDA0002913319270000064
wherein d is b The total length of the start step and the stop step; c is the total number of steps;
step 2.3: given the expected AZR position r AZR Taking a cyclic step S from the set S m Forming a step sequence S m Said step length sequence S m The energy consumption function of (2);
Figure BDA0002913319270000065
wherein eta is AZR position r AZR Corresponding to the value of the variable of the area AZR,
Figure BDA0002913319270000066
indicating the step of the cycle s m The energy consumption of (2) is reduced,
Figure BDA0002913319270000067
indicates the start of step s 1 The energy consumption of (2) is reduced,
Figure BDA0002913319270000071
indicating a stop step s c The energy consumption of (2) is reduced,
Figure BDA0002913319270000072
and
Figure BDA0002913319270000073
the equivalent cycle step length is s when the moving distance of the swing foot in front of the body is unequal to the moving distance of the swing foot in the process of starting and stopping the robot walking 1 And s 2 Energy consumption of (2);
step 2.4: combining the formula (2) to obtain the optimal cycle step length
Figure BDA0002913319270000074
The optimal cycle step size
Figure BDA0002913319270000075
Correspondingly forming the step length sequence with the lowest energy consumption
Figure BDA0002913319270000076
The step length sequence with the lowest energy consumption
Figure BDA0002913319270000077
The constraint conditions shown in formula (3) are satisfied;
Figure BDA0002913319270000078
wherein the content of the first and second substances,
Figure BDA0002913319270000079
denotes s m The energy consumption value calculated when the kth value in the step set S is taken, k is 1,2, …, L, and L is the number of elements in the step set S.
Example 3
Based on the above embodiment 1, in the present embodiment, to obtain the real-time ZMP trajectory r ZMP (n) the step 4 is optimized, and specifically comprises the following steps:
step 4.1 the real-time ZMP trajectory r ZMP (n) is represented by:
r ZMP (n)＝[x ZMP (n) y ZMP (n) 0] T (4)；
wherein x and y respectively represent the front and side directions of the robot;
combining a formula (4), the robot walks the ith step, and a value set F is obtained by the robot sole pressure sensor at the sampling point n moment i (n) calculating the real-time ZMP trajectory r ZMP (n) represented by formula (5):
Figure BDA00029133192700000710
wherein the content of the first and second substances,
Figure BDA00029133192700000711
and f i j (n)∈F i (n) the position and pressure of the jth sensor in the x-axis direction and the y-axis direction, respectively, c n Is the number of sensors.
Example 4
As shown in FIG. 6, based on the above embodiment 3, in the present embodiment, the deviation e in the Y-axis direction is calculated i And optimizing the step 4, specifically:
step 4.2: get biped robot per step time T S For controlling the period, the biped robot has a step time T S Expressed as:
T S ＝N·t s (6)；
wherein N is the gait cycle of the biped robot;
step 4.3: defining the duty cycle of the robot motion as sigma ≡ 2N 1 The motion state of the robot is judged according to the value of the sampling point N;
if N is present 1 ＜n≤N 2 The biped robot is in a single support stage SSP;
if N is more than or equal to 1 and less than or equal to N 1 ，N 2 N is less than or equal to N, and the biped robot is in a DSP (digital signal processor) of a double-support stage;
wherein, N 1 ＝σN/2，N 2 ＝N-N 1 ，n＝1，2，…，N；
As an alternative embodiment, the foot length l is set as shown in FIG. 3 fl Wide foot l fw The biped robot has a stride of s and a biped Y-axis distance of w. For the example of the Left Foot (LF) in front and the Right Foot (RF) in back, AZR is defined by the point r in the first two-support stage DSP 1 、r 2 、r 3 、r 4 、r 5 、r 6 Hexagonal, then in single support SSP, AZR is the number of points r 4 、r 5 、r 6 、r 7 A rectangular area is formed, in the second dual-support stage DSP, AZR is formed by point r 5 、r 6 、r 7 、r 8 、r 9 、r 10 A hexagon is formed;
are used separately
Figure BDA0002913319270000081
And
Figure BDA0002913319270000082
representing the percentage of AZR in the foot length direction and the foot width direction, in the gait planning algorithm of this embodiment,
Figure BDA0002913319270000083
taking a fixed value and appointing a variable describing the AZR area
Figure BDA0002913319270000084
Step 4.4: when the biped robot is in the DSP stage of dual support, r ZMP (n) is located in the desired AZR region;
when the biped robot is in the single support stage SSP, the X-axis direction X of the movement is required ZMP (n) monotonically increases, and x ZMP (N 1 +1)≥x AZR (N 1 +1)、x ZMP (N 2 )≤x AZR (N 2 )。
As an alternative embodiment, as shown in FIG. 6, the deviation e of the Y-axis direction in step 4 is combined with the formula (5) i Expressed as:
Figure BDA0002913319270000085
wherein, y AZR When (n) is not less than 0, c o ＝1；y AZR When (n) < 0, c o ＝-1，l fw The robot is wide enough.
Example 5
In addition to the above embodiments, the embodiment of the present invention is different from the above embodiments in that the deviation e in the Y-axis direction is obtained i Then, the deviation e in the Y-axis direction is calculated i As feedback value, η to the variable AZR i Correcting, and inquiring the online database again to complete gait updating, which specifically comprises the following steps:
step 5.1: establishing a PI model with an incremental transfer function, wherein the AZR variable eta i Correction value eta of i+1 As expressed by equation (8):
η i+1 ＝η i +Δη i+1 (8)；
wherein, the increment is delta eta i+1 As expressed by equation (9):
Figure BDA0002913319270000091
wherein k is P Is the proportionality coefficient, T I Is the integration time constant, T S Is the control period;
step 5.2: according to said correction value eta i+1 And step length s i+1 Inquiring an online database to obtain a gait track g for controlling the biped robot to walk at the (i + 1) th step i+1 ，g i+1 As expressed by equation (10):
Figure BDA0002913319270000092
wherein q is the angle of the joint motor of the robot, m is the number of the joint motors, and N is the gait cycle.
As an implementation manner, the step 5 further includes:
at the calculation of Δ η i+1 When introducing a time constant of T L First order inertia element of
Figure BDA0002913319270000093
Smoothing is carried out:
Δη i+1 ＝K α Δη i +K 1 e i +K 2 e i-1 (11)；
wherein the content of the first and second substances,
Figure BDA0002913319270000094
the method comprises the steps of constructing an online database, wherein the online database comprises a biped robot step size set S, AZR set H, a walking gait set G and an energy consumption set E, combining an element S of the set S with an element eta in the set H, and inquiring an element G of the G in the walking gait set, namely G ← (S, eta), wherein the element G stores a motor angle for controlling the robot to walk, and the energy consumption is an element of the energy consumption set E
Figure BDA0002913319270000095
Combining the expected AZR position r after the travel distance of the robot target is given by using the online database AZR Planning the step length sequence with the lowest energy consumption
Figure BDA0002913319270000096
And make the robot follow the step length sequence
Figure BDA0002913319270000097
When the robot walks with deviation due to interference of factors such as environment and the like, the method calculates r in the walking process of the robot in real time ZMP (n) track and sum position r AZR Deviation e between (n) i Obtaining AZR variables by PI correctionη i+1 Combined step length s i+1 And variable η of AZR i+1 And thirdly, inquiring an online database, regulating and adjusting the gait of the biped robot in the advancing process, and completing the online gait optimization of the biped robot.
The following experiments were conducted to demonstrate the effects of the present invention
In experimental studies on biped robots, it is necessary to suggest that biped robot gait walking is based on the following assumptions:
(1) the biped robot body maintains an upright posture at all times. When a person walks, the pitching angle of the trunk is generally within 3 degrees, and most researches generally accept the assumption that the body of the biped robot is upright in the walking process.
(2) The feet of the biped robot are always parallel to the ground. Most of the common humanoid robots do not have toes, and cannot play a role in improving the driving performance when lifting and lowering feet.
(3) One gait cycle T of the biped robot, including Double Support (DSP) time T DSP And Single Support (SSP) time T SSP Defining the duty cycle of the DSP
Figure BDA0002913319270000101
When a person walks, the σ interval is about 15% to 25%, and σ is 25% in the algorithm of the present embodiment.
In the experiment, the target travel distance d is 100cm, and is taken
Figure BDA0002913319270000102
The step length sequence S is carried out according to the formulas (1) and (2) * The result of the planning is shown in fig. 4, where η is 0.2, 0.3, …, 1, when the loop step s is repeated m When the distance is 10cm, the energy consumption consumed by the robot movement is the minimum in the same row of data;
at this time, the total number of steps c is calculated to be 12, and the step s is started 1 ＝3cm、s 2 7cm, stop step s c-1 、s c Corresponding to the step length sequence S with the lowest energy consumption of 7cm and 3cm m ＝{3，7，10，10，10，10，10，10，10，10，7，3}。
By calculation, when the variable eta of AZR i Setting the robot to be a double-support stage DSP with two feet standing together, wherein the swing length L of the right foot is 0.8 rf Left foot swing length L, {3, 17, 20, 20, 17, 3}, and left foot swing length L lf ＝{10，20，20，20，20，10}；
Swing length L of right foot rf The middle two 3cm respectively correspond to the start step and the stop step, and the energy consumption is respectively
Figure BDA0002913319270000103
Figure BDA0002913319270000104
Swing length L of right foot rf Middle 17cm and left foot swing length L lf The middle 10cm represents the condition that the movement distance of the swinging foot is unequal at the front and the back of the supporting foot,
the total energy consumption for the robot to travel is obtained by the formula (2)
Figure BDA0002913319270000105
Wherein
Figure BDA0002913319270000106
Correspondingly taking each step g of the robot from the database i ＝[q 1 q 2 … q 16 ]Controlling the joint motion of the robot, wherein i is 1,2, …, 12, adding step 13 for enabling the two feet to be simultaneously connected when the robot stops moving, wherein the dynamic simulation of the gait motion of the robot is shown in figure 5, and the black point is the center of mass r of the body b (n) a motion trajectory.
According to the simulation data, performing actual measurement walking experiment on the robot;
in the experiment, the target stroke distance d is set to 100cm, and the AZR initial variable is set
Figure BDA0002913319270000108
T S ＝1.6s，k P ＝0.875，T I ＝3.2s，T L 1.6s, set along the AZR variable η 0.8 borderline at the single-prop stage SSP;
robot walkingIs e 0 ＝e -1 ＝0，
Figure BDA0002913319270000107
The eta value of the AZR controller is stabilized at 0.8 after the third step of robot walking, and the correction calculation data in the period are shown in the table 1:
TABLE 1 variable value and energy consumption of biped robot walking 100cm
Figure BDA0002913319270000111
In table s i The data in the parentheses correspond to the movement distances of the swing legs in the back and front of the body respectively,
Figure BDA0002913319270000112
to correspond to the actual η i The energy consumption of the calculation is calculated,
Figure BDA0002913319270000113
is composed of
Figure BDA0002913319270000114
Energy consumption value of (2). Calculate to be actual
Figure BDA0002913319270000115
While
Figure BDA0002913319270000116
I.e. AZR controller regulation eta during walking i The energy consumption is reduced by 12.13 percent.
The above-described embodiments are merely preferred embodiments of the present invention, and not intended to limit the scope of the invention, so that equivalent changes or modifications in the structure, features and principles described in the present invention should be included in the claims of the present invention.

Claims (3)

1. An AZR adjusting method for walking real-time gait of a biped robot is characterized by comprising the following steps:
step 1: the method comprises the steps that an online database is built by using measurement and calculation data of a robot offline system, wherein the online database comprises a robot step size set S, AZR set H, a walking gait set G and an energy consumption set E;
step 2: given a robot target travel distance d and a desired AZR position r AZR Planning the step length sequence with the lowest energy consumption
Figure FDA0003774716640000011
And step 3: each step length of the robot is taken out
Figure FDA0003774716640000012
And AZR variable η i Inquiring an on-line database to obtain a motor angle sequence g for gait control i ；
And 4, step 4: according to the pressure set F of the walking steps of the robot i Calculating the real-time ZMP trajectory r ZMP (n) based on r ZMP (n) and r AZR (n) obtaining a deviation e in the Y-axis direction i ；
And 5: using the deviation e of the Y-axis direction i Obtaining AZR variable eta by PI correction method i Correction value η of i+1 And according to said correction value eta i+1 And step size s i+1 Inquiring an online database, and optimizing the gait track of the biped robot online;
the step 2 specifically comprises the following steps:
step 2.1: the step length sequence comprises a start step, an end step and a plurality of loop steps s m A plurality of said cyclic steps s m Step length is equal, according to the robot motion rule, defining the starting step to include s 1 And s 2 Said stopping step comprising s c-1 And s c Let s 1 ＝s c 、s 2 ＝s c-1 And the total length of the start step and the stop step is 1-2 times of the cycle step s m Step size of (2);
step 2.2: given the robot target travel distance d, the loop step s is known m Is calculated by the formula (1) said start step s 1 And s 2 Step length:
Figure FDA0003774716640000013
wherein, d b The total length of the start step and the stop step; c is the total number of steps;
step 2.3: given the expected AZR position r AZR Taking a cyclic step S from the set S m Forming a step sequence S m The step size sequence S m The energy consumption function of (2);
Figure FDA0003774716640000014
wherein eta is AZR position r AZR Corresponding to the value of the variable of the area AZR,
Figure FDA0003774716640000015
indicating the step of the cycle s m The energy consumption of (2) is reduced,
Figure FDA0003774716640000016
indicates the start of step s 1 The energy consumption of (2) is reduced,
Figure FDA0003774716640000017
indicating a stop step s c The energy consumption of (2) is reduced,
Figure FDA0003774716640000018
and
Figure FDA0003774716640000019
the equivalent cycle step length is s when the distance of the swing foot before and after the robot is unequal in the process of starting and stopping the robot walking 1 And s 2 Energy consumption of (2);
step 2.4: combining the formula (2), and taking the optimal cycle step length
Figure FDA0003774716640000021
The optimal cycle step size
Figure FDA0003774716640000022
Correspondingly forming the step length sequence with the lowest energy consumption
Figure FDA0003774716640000023
The step length sequence with the lowest energy consumption
Figure FDA0003774716640000024
The constraint conditions shown in formula (3) are satisfied;
Figure FDA0003774716640000025
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003774716640000026
denotes s m Taking the energy consumption value calculated when the kth value in the step size set S is taken, wherein k is 1,2, …, and L is the number of elements in the step size set S;
the step 4 specifically comprises the following steps:
step 4.1 the real-time ZMP trajectory r ZMP (n) is represented by:
r ZMP (n)＝[x ZMP (n) y ZMP (n) 0] T (4)；
wherein x and y respectively represent the front and side directions of the robot;
combining a formula (4), the robot walks the ith step, and a value set F is obtained by the robot sole pressure sensor at the sampling point n moment i (n) calculating the real-time ZMP trajectory r ZMP (n) represented by formula (5):
Figure FDA0003774716640000027
wherein the content of the first and second substances,
Figure FDA0003774716640000028
and f i j (n)∈F i (n) the position and pressure of the jth sensor in the x-axis direction and the y-axis direction, respectively, c n Is the number of sensors;
the step 4 further comprises:
step 4.2: get biped robot per step time T S For controlling the period, the biped robot has a step time T S Expressed as:
T S ＝N·t s (6)；
wherein N is the gait cycle of the biped robot;
step 4.3: defining the duty cycle of the robot motion as sigma ≡ 2N 1 The motion state of the robot is judged according to the value of the sampling point N;
if N is present 1 ＜n≤N 2 The biped robot is in a single support stage SSP;
if N is more than or equal to 1 and less than or equal to N 1 ,N 2 N is less than or equal to N, and the biped robot is in a DSP (digital signal processor) of a double-support stage;
wherein N is 1 ＝σN/2，N 2 ＝N-N 1 ，n＝1,2,…,N；
Step 4.4: when the biped robot is in the DSP in the dual-support stage, r ZMP (n) is located in the desired AZR region;
when the biped robot is in the single support stage SSP, the X-axis direction X of the movement is required ZMP (n) monotonically increases, and x ZMP (N 1 +1)≥x AZR (N 1 +1)、x ZMP (N 2 )≤x AZR (N 2 )；
The step 5 specifically comprises:
step 5.1: establishing a PI model with an incremental transfer function, wherein the AZR variable eta i Correction value η of i+1 As expressed by equation (8):
η i+1 ＝η i +Δη i+1 (8)；
wherein, the increment is delta eta i+1 As expressed by equation (9):
Figure FDA0003774716640000031
wherein k is P Is the proportionality coefficient, T I Is the integration time constant, T S Is the control period;
step 5.2: according to said correction value eta i+1 And step size s i+1 Inquiring an online database to obtain a gait track g for controlling the biped robot to walk at the (i + 1) th step i+1 ，g i+1 As expressed by equation (10):
Figure FDA0003774716640000032
wherein q is the angle of the joint motor of the robot, m is the number of the joint motors, and N is the gait cycle.
2. The AZR regulation method for walking real-time gait of biped robot as claimed in claim 1, characterized by combining formula (5) and step 4. the deviation value e of Y-axis direction i Expressed as:
Figure FDA0003774716640000033
wherein, y AZR When (n) is not less than 0, c o ＝1；y AZR When (n) < 0, c o ＝-1，l fw The robot is wide enough.
3. The AZR adjustment method for walking real-time gait of a biped robot according to claim 1, characterized in that said step 5 further comprises:
at the calculation of Δ η i+1 When introducing a time constant of T L First order inertia element of
Figure FDA0003774716640000041
Smoothing is carried out:
Δη i+1 ＝K α Δη i +K 1 e i +K 2 e i-1 (11)；
wherein the content of the first and second substances,
Figure FDA0003774716640000042
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