CN107315346A - A kind of humanoid robot gait's planing method based on CPG models - Google Patents
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Abstract
The present invention relates to anthropomorphic robot technical field, more particularly to a kind of humanoid robot gait's planing method based on CPG models.It comprises the following steps：(1), according to the specific hardware parameter of robot, corresponding coupled oscillator model is set up：(2), improved model, increases centroid motion control item, the oscillator model after being improved：(3), using speed as input condition, using genetic algorithm optimization, the optimal value of the parameter in step (2) is obtained, the model for then again substituting into obtained parameter optimal value in step (2).Using this planing method, it is not easy to shake before and after occurring when robot urgency acceleration or quick movement and causes to fall down.
Description
Technical field
The present invention relates to anthropomorphic robot technical field, more particularly to a kind of humanoid robot gait based on CPG models
Planing method.
Background technology
Bionic center mode generator (Central Pattern Generator, CPG) is made up of neuron
Local concussion network, can produce stable PGC demodulation, and produce by self-oscillation by the mutual suppression between neuron
The rhythmic movement of raw body region of interest, is inspired by it, and some researchers propose to be based on bionic gait method.But
Have in CPG models quantity of parameters without clear and definite physical significance, it is difficult to determine value, cause CPG models to be difficult to direct application
In robot gait planning, therefore, Endo etc. simplifies CPG models, apery machine is planned using the less oscillator of parameter
The gait of device people；Ha etc. proposes linear coupling oscillator (Linear Coupled Oscillator) model, and is applied to
It can bear in the limited Mini humanoid robot of calculation cost.
But prior art it is this by linear coupling oscillator model be applied to humanoid robot gait planning when, work as machine
Still easily there is front and rear concussion and causes to fall down when suddenly accelerating or be quickly mobile in people.
The content of the invention
The technical problems to be solved by the invention are：A kind of humanoid robot gait planning side based on CPG models is provided
Method, using this planing method, is not easy to shake before and after occurring and causes to fall down when robot urgency acceleration or quick movement.
The technical solution adopted in the present invention is：A kind of humanoid robot gait's planing method based on CPG models, it is wrapped
Include following steps：
(1), according to the specific hardware parameter of robot, corresponding coupled oscillator model is set up：
OSCs(t)=OSCb(t)+OSCm(t)；
In formula, OSCm(t) movement locus of the both legs end relative to fixed barycenter is represented, that is, moves the output of oscillator；
OSCb(t) output of the barycenter relative to the movement locus, i.e. balance oscillator of reference frame is represented；OSCs(t) it is both legs end
Relative to the output of the movement locus of actual barycenter, i.e. coupled oscillator；
(2), improved model, increases centroid motion control item, the oscillator model after being improved：
OSCs(t)=OSCb(t)+OSCm(t)+effect；
In formula, effect represents the gain of robot initial position correspondence coupled oscillator；
(3), using speed as input condition, using genetic algorithm optimization, the optimal value of the parameter in step (2) is obtained, so
The model for afterwards again substituting into obtained parameter optimal value in step (2).
OSC in step (1)b(t) specific formula is：
OSCb(t)=ρbsin(ωbt+△b)+ub；
In formula, ρbFor the amplitude of balance oscillator, ωbFor the frequency of balance oscillator, △bFor the first phase of balance oscillator
Position, ubIt is the offset of balance oscillator；
OSC in step (1)m(t) specific formula is：
In formula, ρmTo move the amplitude of oscillator, ωmTo move the frequency of oscillator, △mFor the first phase of motion oscillations device
Position, T is a walking period time, and r represents double-legged supporting time in the ratio shared by total cycle.
The parameter that genetic algorithm optimization is utilized in step (3) is ρbAnd effect.
Genetic algorithm in step (3) first sets population scale, crossover probability, evolution probability and evolutionary generation limitation
Number, then chooses outstanding population using wheel disc gaming act, and optimization aim is given by：
Object:minimize f(ρb, offect) and=max | Xzmp(t)-Xfcenter|+ρb, t ∈ [0, T],
In formula, XzmpFor the X-axis coordinate of point of zero moment, its formula isWherein,
N is the connecting rod number of robot, miFor i connecting rod qualities, g is acceleration of gravity, xiAnd ziIt is i connecting rods x-axis and z-axis respectively
Position,WithIt is then its corresponding acceleration；
In formula, XfcenterFor the X-axis coordinate of robot supporting leg central point, its formula isWherein
XtipThe distance of origin, X are arrived for supporting leg leg pointheelIt is supporting leg leg with the distance to origin；
In formula, max | Xzmp(t)-Xfcenter| for point of zero moment in a cycle and supporting leg central point in X axis most
At a distance.
Using above method compared with prior art, the present invention has advantages below：Coupling of the application in prior art
Centroid motion is added in mode, and proposes a kind of algorithm for optimizing travelling control parameter and is advised with improving whole gait
The method of drawing, mainly by X axis ZMP stability margins in walking process and the oscillation amplitude of barycenter in combination as optimization mesh
Mark, using instrument of the genetic algorithm as solution, corresponding optimized parameter is asked under friction speed input, this makes it possible to
The more excellent parameter of robot is found under friction speed input, it is ensured that it has larger stability margin, it is possible to increase anthropomorphic robot
The stability of walking, the probability for reducing oscillation and divergence before and after robot and falling down.
Brief description of the drawings
Fig. 1 is coupled oscillator model in a kind of humanoid robot gait's planing method based on CPG models of the present invention
Illustrate figure.
Fig. 2 is the flow chart of genetic algorithm in a kind of humanoid robot gait's planing method based on CPG models of the present invention.
Embodiment
The present invention is described further with embodiment below in conjunction with accompanying drawing, but the present invention be not limited only to it is following
Embodiment.
A kind of humanoid robot gait's planing method based on CPG models, it comprises the following steps：
(1) according to the specific hardware parameter of robot, corresponding coupled oscillator model is set up：
OSCs(t)=OSCb(t)+OSCm(t)；
In formula, OSCm(t) movement locus of the both legs end relative to fixed barycenter is represented, that is, moves oscillator
The output of (Movement Oscillator)；OSCb(t) represent that barycenter relative to the movement locus of reference frame, that is, is balanced
The output of oscillator (Balance Oscillator)；OSCs(t) movement locus for both legs end relative to actual barycenter, i.e.,
The output of coupled oscillator；The convenient law of pose of barycenter and biped is described respectively for two oscillators, as shown in figure 1,
Mankind's walking experiment finds that when normally walking, model of human ankle and center of mass motion are close to sinusoidal fluctuation curve, and above-mentioned two is shaken
Son can represent stirring for ankle-joint and barycenter respectively, and coupled oscillator is stacked up by above-mentioned two oscillator, so can
To represent the overall walking curve of people.
OSC in step (1)b(t) specific formula is：
OSCb(t)=ρbsin(ωbt+△b)+ub；
In formula, ρbFor the amplitude of balance oscillator, ωbFor the frequency of balance oscillator, △bFor the first phase of balance oscillator
Position, ubIt is the offset of balance oscillator；
OSC in step (1)m(t) specific formula is：
In formula, ρmTo move the amplitude of oscillator, ωmTo move the frequency of oscillator, △mFor the first phase of motion oscillations device
Position, T is a walking period time, and r represents double-legged supporting time in the ratio shared by total cycle.
And according to above-mentioned formula, it can obtain in t, centroid position c (t), right crus of diaphragm terminal position r (t) and a left side
Pin terminal position l (t)；
In the cycle of walking one, two leg supporting times respectively account for typically,Interior right leg is the strong point,An interior left side
Leg is the strong point, and when it is to lead leg that right leg, which is the left leg of supporting leg, right crus of diaphragm coordinate is constant to be set to r0, thenWhen：
When it is to lead leg that left foot, which is supporting leg right crus of diaphragm, left foot coordinate is constant to be set to l0, thenWhen：
It is determined that after initial support point coordinates, each moment t center point coordinate c (t), right crus of diaphragm can be obtained by above formula
Coordinate r (t) and left foot l (t), it is known that inverse kinematics can obtain the multiple motors of robot both legs again again after this three point coordinates
Motor value, motor moves to the both legs walking that specified location realizes robot per the moment.
(2) improved model, increases centroid motion control item, the oscillator model after being improved：
OSCs(t)=OSCb(t)+OSCm(t)+effect；
In formula, effect represents the gain of robot initial position correspondence coupled oscillator；
9 parameters, wherein ρ can be obtained by the oscillator model in step (1)m, T and r given by speed task, and
ω after T confirmsm、ωbAlso with uniquely determining, △m、△b、ubIt can be determined by or so robot initial moment leg end demand position
Justice, is thus only left the amplitude ρ of balance oscillatorb, it influences this to balance to a certain extent, and experiment shows robot motion
The bigger barycenter of speed amplitude it is bigger, the speed of motion is smaller, and the amplitude of barycenter is smaller, but when barycenter amplitude increases,
Robot shaking amplitude is also with increase, the destabilizing factor as walking, once thanksing for your hospitality movable property life, easily makes to rock overshoot,
Finally fall down robot, so individually ρbNor optimal governing factor.
According to human body walking law discovery, always make center of gravity forward when suddenly accelerating, make center of gravity backward during anxious deceleration, with this
Carry out the change of inertia force caused by customer service velocity variations, keep the stability of walking.Inspired by this, the application is just in coupling
Centroid motion effect is added on co oscillation device model, so when increasing effect, robot barycenter is moved afterwards relatively, is subtracted
The machine hostage heart is relative during small effect is moved forward, and the relative position of robot barycenter can be adjusted by the way that the band for adjusting effect values is lower
Put, and then control machine people's balance.Experiment finds combination regulation ρbIt can effectively improve robot with effect value
Stability, but be only difficult to find suitable reference value by adjusting manually, it is desirable to ensure robot at various speeds steady
It is qualitative, it is necessary to robot parameter is optimized by input condition of speed, so the application is joined using genetic algorithm
Number optimization.
(3) using speed as input condition, using genetic algorithm optimization, the optimal value of the parameter in step (2) is obtained, then
The model that obtained parameter optimal value is substituted into step (2) again.
Genetic algorithm in step (3) first sets population scale, crossover probability, evolution probability and evolutionary generation limitation
Number, then chooses outstanding population using wheel disc gaming act, and optimization aim is given by：Object:minimize f(ρb,
Offect)=max | Xzmp(t)-Xfcenter|+ρb, t ∈ [0, T],
In formula, XzmpFor the X-axis coordinate of point of zero moment, its formula isWherein,
N is the connecting rod number of robot, miFor i connecting rod qualities, g is acceleration of gravity, xiAnd ziIt is i connecting rods x-axis and z-axis respectively
Position,WithIt is then its corresponding acceleration；
In formula, XfcenterFor the X-axis coordinate of robot supporting leg central point, its formula isWherein
XtipThe distance of origin, X are arrived for supporting leg leg pointheelIt is supporting leg leg with the distance to origin；
In formula, max | Xzmp(t)-Xfcenter| for point of zero moment in a cycle and supporting leg central point in X axis most
At a distance.
Population scale M=100, poor probability P are set in the applicationc=0.5, evolution probability Pe=0.02, evolutionary generation limit
T=1500 is made as, the process of genetic algorithm is as shown in Figure 2.
Claims (4)
1. a kind of humanoid robot gait's planing method based on CPG models, it is characterised in that it comprises the following steps：
(1), according to the specific hardware parameter of robot, corresponding coupled oscillator model is set up：
OSCs(t)=OSCb(t)+OSCm(t)；
In formula, OSCm(t) movement locus of the both legs end relative to fixed barycenter is represented, that is, moves the output of oscillator；OSCb
(t) output of the barycenter relative to the movement locus, i.e. balance oscillator of reference frame is represented；OSCs(t) it is both legs end phase
For the output of the movement locus of actual barycenter, i.e. coupled oscillator；
(2), improved model, increases centroid motion control item, the oscillator model after being improved：
OSCs(t)=OSCb(t)+OSCm(t)+effect；
In formula, effect represents the gain of robot initial position correspondence coupled oscillator；
(3), using speed as input condition, using genetic algorithm optimization, the optimal value of the parameter in step (2), Ran Houzai are obtained
The model that obtained parameter optimal value is substituted into step (2).
2. a kind of humanoid robot gait's planing method based on CPG models according to claim 1, it is characterised in that：
OSC in step (1)b(t) specific formula is：
OSCb(t)=ρbsin(ωbt+Δb)+ub；
In formula, ρbFor the amplitude of balance oscillator, ωbFor the frequency of balance oscillator, ΔbFor the initial phase of balance oscillator, ub
It is the offset of balance oscillator；
OSC in step (1)m(t) specific formula is：
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In formula, ρmTo move the amplitude of oscillator, ωmTo move the frequency of oscillator, ΔmFor the initial phase of motion oscillations device, T
For a walking period time, r represents double-legged supporting time in the ratio shared by total cycle.
3. a kind of humanoid robot gait's planing method based on CPG models according to claim 2, it is characterised in that：
The parameter that genetic algorithm optimization is utilized in step (3) is ρbAnd effect.
4. a kind of humanoid robot gait's planing method based on CPG models according to claim 3, it is characterised in that：
Genetic algorithm in step (3) first sets population scale, crossover probability, evolution probability and evolutionary generation limitation number, then adopts
Outstanding population is chosen with wheel disc gaming act, optimization aim is given by：
Object:minimize f(ρb, offect) and=max | Xzmp(t)-Xfcenter|+ρb, t ∈ [0, T],
In formula, XzmpFor the X-axis coordinate of point of zero moment, its formula isWherein, n is machine
The connecting rod number of device people, miFor i connecting rod qualities, g is acceleration of gravity, xiAnd ziIt is the position of i connecting rods x-axis and z-axis respectively
Put,WithIt is then its corresponding acceleration；
In formula, XfcenterFor the X-axis coordinate of robot supporting leg central point, its formula isWherein Xtip
The distance of origin, X are arrived for supporting leg leg pointheelIt is supporting leg leg with the distance to origin；
In formula, max | Xzmp(t)-Xfcenter| for point of zero moment in a cycle and supporting leg central point X axis most long distance
From.
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| WO2022247115A1 (en) * | 2021-05-26 | 2022-12-01 | 深圳市优必选科技股份有限公司 | Centroid trajectory generation method and apparatus, computer readable storage medium, and robot |
| CN114460849A (en) * | 2022-04-12 | 2022-05-10 | 北京晟海汇泽科技有限公司 | Bionic robot fish motion control method and device and bionic robot fish |
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