CN102169346B - Intelligent control method for coordinating multiple-robot system - Google Patents

Intelligent control method for coordinating multiple-robot system Download PDF

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CN102169346B
CN102169346B CN 201110040377 CN201110040377A CN102169346B CN 102169346 B CN102169346 B CN 102169346B CN 201110040377 CN201110040377 CN 201110040377 CN 201110040377 A CN201110040377 A CN 201110040377A CN 102169346 B CN102169346 B CN 102169346B
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robot
odor
time
odor source
source
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CN102169346A (en
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吕强
谢小高
罗平
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Shandong Evolver New Material Co ltd
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Hangzhou Dianzi University
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Abstract

The invention relates to an intelligent control method for coordinating a multiple-robot system. The multiple-robot system consumes excessive energy in the traditional method. The intelligent control method comprises the following steps of: according a kinematic model of a smell source releasing smell molecules, establishing an observation mode of a robot to the position of the smell source; within each sampling period, in case of any smell detected, estimating the position of the smell source according to Kalman filtering theory and the observation value of the robot to the position of the small source; based on the estimation value of the robot detecting the thickest smell source in the group to the position of the smell source, updating the estimation value of each robot to the position of the smell source, and using the estimation of the robot to the position of the smell source as the basis of estimation of the next position for the robot. The invention effectively improves the precision of positioning the smell source, guarantees less consumption of energy of the robot system, and meets the requirement for quick positioning in actual demands.

Description

A kind of intelligence control method of coordinating multi-robot system
Technical field
The invention belongs to technical field of automation, relate to a kind of intelligence control method of coordinating multi-robot system.
Background technology
There is very important meaning dangerous odor source location to human security, source of leaking as toxic gas in the source of location pollutant and the chemical plant etc.Therefore, how fast and effeciently locating dangerous odor source is an extremely important problem.Yet dangerous odor source orientation problem presents different characteristics under different environment.Usually, do not having under the condition of air-flow, the diffusion of scent molecule is a main strength, and it can drive scent molecule away from odor source.Maximum concentration will near appearance odor source.Therefore, we can use the method for gradient to locate odor source.Yet in the real world, air-flow is a kind of main strength that influences the smell diffusion, and it forms the plumage cigarette by influencing the motion of scent molecule.In the environment by high Reynolds number portrayal, the plumage cigarette presents uncontinuity and the intermittence of height, and this makes gradient method become infeasible.In addition, because extensibility and the robustness of multi-robot system make multi-robot system replace unit device robot system to become the main tool of dangerous odor source location.At present, the major control method that the coordination multi-robot system is located dangerous odor source is the colony intelligence technology, but, the position success rate of this technology is lower, also can make the too much energy of multi-robot system consumption, a chief reason is that this method has been utilized the concentration amplitude information, and the instability of concentration amplitude information tends to make the multi-robot system local convergence.In addition, just begun to start to walk for the research of the cooperation control method of multi-robot system in China, still do not proposed efficient ways.Under this background, the present invention has remedied the deficiencies in the prior art.
Summary of the invention
Target of the present invention is at the deficiencies in the prior art part, a kind of intelligence control method of coordinating multi-robot system has been proposed, this method is to be theoretical foundation with the Kalman filtering theory, design a kind of effective multi-robot system control method for coordinating, with can be fast and locate dangerous odor source exactly.This method has remedied the deficiency of traditional cooperative search mode, when guaranteeing that multi-robot system has high orientation precision and stability, also guarantees form simply and reduces the energy that multi-robot system consumes in the position fixing process.
The inventive method is made up of two algorithms, two algorithm parallel runnings, wherein first algorithm is responsible for estimating the odor source position, and offer second algorithm with the form of message, second algorithm is responsible for calculating robot's reposition according to the odor source position that state and first algorithm of current robot provides; Because the sampling period difference of two algorithms, if second algorithm do not obtain the up-to-date odor source location estimation value of first algorithm, then the odor source location estimation value that obtains with the last time is benchmark, if operation for the first time is benchmark with initial smell source position then.First algorithm is: at first, according to the kinematics model of odor source release scent molecule, set up robot for the observation model of odor source position; Then, in each sampling period, if detect smell, then use Kalman filtering theory and robot to the observed reading of odor source position, estimate the position of odor source; At last, based on the estimated value of the robot that detects maximum odorousness in the colony to the odor source position, upgrade each robot to the estimated value of odor source position, and use robot to the estimated value of the odor source position foundation as next step position of calculating robot.Second algorithm is: at first, set up two states of robot motion, namely state does not take place in odor detection event generation state and odor detection event; Then, in each sampling period, judge the residing state of robot, and according to different states and robot to the estimated value of odor source position, use diverse ways, produce next step position of robot; Secondly, design duration and the state conversion regime of these two states; At last, adopt consistency algorithm drive machines people to move next step position from current location to robot.
Technical scheme of the present invention is by means such as Data Detection, on-line optimization, the assessments of odor source position probability distribution, has established a kind of intelligence control method of coordinating multi-robot system, utilizes this method can effectively improve dangerous odor source locating accuracy.
The inventive method (
Figure 8667DEST_PATH_IMAGE002
) move in the individual robot, wherein the sampling period of first algorithm is
Figure 786130DEST_PATH_IMAGE004
, concrete steps are as follows:
(1) utilize the kinematics model of scent molecule, set up the observation model of odor source position, concrete grammar is:
A. set up the motion model of scent molecule group, obtain the position of scent molecule group:
The motion model of scent molecule group is:
Figure 640691DEST_PATH_IMAGE006
Wherein,
Figure 870815DEST_PATH_IMAGE008
Refer to that scent molecule group exists
Figure 603279DEST_PATH_IMAGE010
Position constantly;
Figure 297566DEST_PATH_IMAGE012
Refer to that scent molecule group exists
Figure 385345DEST_PATH_IMAGE010
The differential of moment position;
Figure 368345DEST_PATH_IMAGE014
Be
Figure 701237DEST_PATH_IMAGE010
Average wind speed degree constantly;
Figure 187713DEST_PATH_IMAGE016
Represent a stochastic process, it is zero that this process is obeyed average, and variance is
Figure 711973DEST_PATH_IMAGE018
Gaussian distribution;
To the motion model of scent molecule group the time period [
Figure 916689DEST_PATH_IMAGE020
,
Figure 850010DEST_PATH_IMAGE022
] (
Figure 456572DEST_PATH_IMAGE024
) in carry out integration, obtain scent molecule group and exist
Figure 653198DEST_PATH_IMAGE020
Constantly discharged by odor source, at current time
Figure 2011100403776100002DEST_PATH_IMAGE025
The time the position:
Figure 2011100403776100002DEST_PATH_IMAGE027
Wherein, [
Figure 521709DEST_PATH_IMAGE020
,
Figure 524300DEST_PATH_IMAGE025
] refer to time period of integration,
Figure 47686DEST_PATH_IMAGE020
Refer to that odor source discharges the time of scent molecule group,
Figure 149634DEST_PATH_IMAGE022
Refer to the current time;
Figure 2011100403776100002DEST_PATH_IMAGE029
Refer in the current time
Figure 2011100403776100002DEST_PATH_IMAGE031
The position of scent molecule group; Be constantly
Figure 2011100403776100002DEST_PATH_IMAGE035
The position of odor source;
B. determine the discrete motion model of scent molecule group:
By definition
Figure 2011100403776100002DEST_PATH_IMAGE037
With
Figure 2011100403776100002DEST_PATH_IMAGE039
, with the position discretize of scent molecule group; Wherein constantly discrete
Figure 2011100403776100002DEST_PATH_IMAGE041
Be that odor source discharges scent molecule group's time
Figure 2011100403776100002DEST_PATH_IMAGE042
Round values; Constantly discrete
Figure 14428DEST_PATH_IMAGE043
It is the current time Round values;
Figure DEST_PATH_IMAGE046
Refer to the subtle change of time; Thereby the discrete motion model of scent molecule group is:
Wherein, the odor source position is static within a certain period of time, so have
Figure DEST_PATH_IMAGE050
Figure DEST_PATH_IMAGE052
The expression odor source exists Constantly discharge scent molecule group,
Figure 119973DEST_PATH_IMAGE053
Position constantly;
Figure DEST_PATH_IMAGE055
Be illustrated in the time period [
Figure 658402DEST_PATH_IMAGE041
,
Figure 121744DEST_PATH_IMAGE043
] interior wind promotes the displacement of scent molecule group; The expression stochastic process, obeying average is zero, variance
Figure 901799DEST_PATH_IMAGE059
Normal distribution.
Consider scent molecule group all possibilities of release time, namely
Figure 861663DEST_PATH_IMAGE061
Figure 15564DEST_PATH_IMAGE063
Then the discrete motion model of scent molecule group further is expressed as follows:
Figure 835752DEST_PATH_IMAGE065
Wherein, For
Figure 802888DEST_PATH_IMAGE053
The position that moment scent molecule is rolled into a ball;
Figure DEST_PATH_IMAGE069
For
Figure 677041DEST_PATH_IMAGE043
The position of moment odor source; For
Figure 300920DEST_PATH_IMAGE043
Wind promotes the mobile distance of scent molecule group constantly;
Figure 445594DEST_PATH_IMAGE073
Be to measure noise, and obey zero-mean,
Figure DEST_PATH_IMAGE075
The normal distribution of variance.
C. by definition , can obtain the observation model of odor source position:
Figure DEST_PATH_IMAGE079
Wherein,
Figure DEST_PATH_IMAGE081
Be iIndividual robot is constantly
Figure DEST_PATH_IMAGE083
To the odor source position
Figure 808311DEST_PATH_IMAGE084
Measured value.
(2) observation model of use odor source position produces robot to the observed reading of odor source position, and uses the Kalman filtering theory, obtains the estimated value of odor source position.Concrete grammar is:
A. before obtaining the observed reading of robot to the odor source position, obtain priori estimates and the priori covariance matrix of odor source position.
Figure 671225DEST_PATH_IMAGE086
Figure 895533DEST_PATH_IMAGE088
Wherein,
Figure DEST_PATH_IMAGE090
The expression robot exists to the odor source position Posterior estimate constantly;
Figure DEST_PATH_IMAGE094
Be that robot exists to the odor source position
Figure 534193DEST_PATH_IMAGE043
Priori estimates constantly;
Figure DEST_PATH_IMAGE096
Be to exist about the odor source position
Figure 756227DEST_PATH_IMAGE092
Posteriority covariance matrix constantly;
Figure DEST_PATH_IMAGE098
Exist about the odor source position
Figure 345252DEST_PATH_IMAGE043
Priori covariance matrix constantly.
B. work as robot by the observation model to the odor source position, when obtaining the observed reading of odor source position, upgrade the priori estimates of following formula odor source position, calculate the posterior estimate of odor source position, concrete computing formula is as follows:
Figure DEST_PATH_IMAGE100
Figure 310934DEST_PATH_IMAGE102
Figure 430200DEST_PATH_IMAGE104
Wherein,
Figure DEST_PATH_IMAGE106
Be to measure noise covariance matrix;
Figure DEST_PATH_IMAGE108
It is the Kalman gain; The expression robot exists to the odor source position
Figure 259354DEST_PATH_IMAGE043
Posterior estimate constantly; Be to exist about the odor source position Posteriority covariance matrix constantly.
(3) use detects the robot of Cmax amplitude to the estimated value of odor source position, upgrades current robot to the estimated value of odor source position, that is:
Figure DEST_PATH_IMAGE114
Wherein,
Figure DEST_PATH_IMAGE116
With
Figure DEST_PATH_IMAGE118
Be to regulate parameter;
Figure 974555DEST_PATH_IMAGE120
Expression the
Figure DEST_PATH_IMAGE122
Individual robot exists to the odor source position
Figure 948327DEST_PATH_IMAGE043
Estimated value constantly, in addition the
Figure 512163DEST_PATH_IMAGE122
Individual robot also is the robot that obtains the Cmax amplitude information.
(4) go on foot the estimated value of restarting to carry out and provide the odor source position from (2)
The sampling period of second algorithm of this method is
Figure DEST_PATH_IMAGE124
(
Figure 941188DEST_PATH_IMAGE043
), namely the sampling period of two of this method algorithms is inconsistent, two algorithm executed in parallel.In second algorithm of this method, robot has two states, and a state is: odor detection event generation state; Another state is: state does not take place in the odor detection event.Concrete steps are as follows:
In the sampling period
Figure 330635DEST_PATH_IMAGE125
The interior state of judging robot; If the state of robot is odor detection event generation state, execution in step a; Otherwise execution in step b.
If the current state of robot a., namely odor detection event generation state is just from the odor detection event state-transition not to take place to come, and then execution in step 1.; Otherwise execution in step 2..
1. based on the latest estimated value of odor source position (the estimated value relation that this estimated value and first algorithm provide is to satisfy when the sampling period
Figure 785068DEST_PATH_IMAGE129
The time, ), then next step position of robot is the latest estimated value of odor source position, namely
Wherein,
Figure DEST_PATH_IMAGE135
Be
Figure DEST_PATH_IMAGE137
Constantly the iThe position of individual robot;
Figure DEST_PATH_IMAGE139
It is the duration of this state;
Figure 381014DEST_PATH_IMAGE140
Be illustrated in
Figure DEST_PATH_IMAGE141
The robot that obtains is to the estimated value of odor source position constantly.
2. it is mobile to adopt consistency algorithm control robot to continue, and the execution time is
Figure 851048DEST_PATH_IMAGE142
Second.Surpass when the duration of this state
Figure 562652DEST_PATH_IMAGE142
After second, the state of robot is automatically changeb to the odor detection event state does not take place.
If the current state of robot b., namely not generation of odor detection event state is just to come from odor detection event generation state-transition, and then execution in step 1.; Otherwise execution in step 2..
1. based on the latest estimated value of odor source position With the velocity information of wind, next step position of calculating robot.
Figure 769959DEST_PATH_IMAGE144
Figure 25491DEST_PATH_IMAGE146
Wherein:
Figure DEST_PATH_IMAGE148
With
Figure DEST_PATH_IMAGE150
Be respectively that wind exists
Figure DEST_PATH_IMAGE152
The axle and
Figure 858230DEST_PATH_IMAGE154
Axial speed;
Figure 781187DEST_PATH_IMAGE156
Be iIndividual robot exists
Figure 90945DEST_PATH_IMAGE124
Constantly exist for odor source position latest estimated value
Figure 332309DEST_PATH_IMAGE152
Axial coordinate;
Figure 385715DEST_PATH_IMAGE158
The iIndividual robot exists
Figure 163178DEST_PATH_IMAGE160
The position exists constantly
Figure 643838DEST_PATH_IMAGE152
Axial coordinate;
Figure 139542DEST_PATH_IMAGE162
With
Figure 668743DEST_PATH_IMAGE164
The iIndividual robot exists
Figure 628609DEST_PATH_IMAGE166
The position exists constantly
Figure 716388DEST_PATH_IMAGE152
The axle and
Figure DEST_PATH_IMAGE167
Axial coordinate;
Figure 433809DEST_PATH_IMAGE169
It is the duration of state.
2. it is mobile to adopt consistency algorithm control robot to continue, and the execution time is
Figure 766701DEST_PATH_IMAGE169
Second.In mobile process, if robot detects odorousness information, then the state-transition of robot is odor detection event generation state; If in the time
Figure 581073DEST_PATH_IMAGE169
After second, do not detect odorousness, recomputate next step position of robot.Concrete grammar is:
Figure 341219DEST_PATH_IMAGE171
Wherein,
Figure 243371DEST_PATH_IMAGE175
With Be respectively control
Figure 843296DEST_PATH_IMAGE152
The axle and
Figure 535309DEST_PATH_IMAGE154
The control parameter of direction of principal axis hunting zone,
Figure 537900DEST_PATH_IMAGE179
Produce an equally distributed random number in the scope.
И restarted to carry out from the step, and in the robot of colony, the detected odorousness of some robots reaches preset value, or judges odor source by vision sensor, notified the by wireless network then iIndividual robot, or surpass prior official hour search time, then finish operation.
A kind of intelligence control method of coordinating multi-robot system that the present invention proposes, this method has remedied the deficiency of classic method, and improve the odor source locating accuracy effectively, and guarantee the less consumption of multi-robot system energy, satisfy requiring the requirement of location fast in the reality simultaneously.
The intelligence control method that the present invention proposes can be estimated the probability distribution of odor source position effectively, allows the Security Officer understand the situation of present dangerous smell diffusion better, further remedies the deficiency of classic method.In addition, at any time, can know the possible position of dangerous odor source.
Embodiment
Leaking with the industrial gasses conveyance conduit is example:
Here leaking with the industrial gasses conveyance conduit is that example is described.May set up 2 dimension local coordinate systems by the gas leakage point, and (every 1 second, the record primary air velocity recorded 100 altogether for robot installation wind gage is measured local wind speed.In case the quantity of wind speed information has surpassed 100, then replace old wind speed information with new wind speed information) and the position of odometer metering robot in local coordinate system, be robot mounting industrial toxic gas pick-up unit simultaneously.And maximum line velocity and the angular velocity of setting robot.For iIndividual robot begins to carry out following steps:
1, search smell clue.
Multi-robot system at first edge and the current wind speed direction of intersecting advances, search for the smell clue, in case detect the smell clue, then start the intelligence control method of coordinating multi-robot system, and the initialization robot is to estimated value and the covariance matrix of odor source position, and the current state of robot is odor detection event generation state.Began to carry out the 2nd step; Otherwise continued to carry out the 1st step.
2, the intelligence control method of coordination multi-robot system begins to carry out, and namely two algorithms are based on different sampling period executed in parallel.
For first algorithm (sampling period is 1 second), carry out following steps:
(1) calculates the move distance that scent molecule is rolled into a ball.
Figure 452764DEST_PATH_IMAGE061
Figure DEST_PATH_IMAGE183
Wherein,
Figure DEST_PATH_IMAGE185
Be iWind speed constantly, Then, calculate the measurement noise covariance matrix.
Figure DEST_PATH_IMAGE189
Wherein,
Figure 430079DEST_PATH_IMAGE106
Be to measure noise covariance matrix; Standard deviation
Figure DEST_PATH_IMAGE191
Can specify in advance based on experience.
(2) based on the Kalman filtering theory, obtain robot to the estimated value of odor source position.
The first step before obtaining the observed reading of robot to the odor source position, obtains priori estimates and the priori covariance matrix of odor source position.
Figure 107923DEST_PATH_IMAGE086
Figure 648625DEST_PATH_IMAGE088
Wherein,
Figure 964200DEST_PATH_IMAGE090
The expression robot exists to the odor source position
Figure 564946DEST_PATH_IMAGE092
Posterior estimate constantly;
Figure 965971DEST_PATH_IMAGE094
Be that robot exists to the odor source position Priori estimates constantly;
Figure 854348DEST_PATH_IMAGE096
Be to exist about the odor source position
Figure 563678DEST_PATH_IMAGE092
Posteriority covariance matrix constantly;
Figure 514316DEST_PATH_IMAGE098
Exist about the odor source position
Figure 396821DEST_PATH_IMAGE043
Priori covariance matrix constantly.
Second step, when robot by to the observation model of odor source position, when obtaining the observed reading of odor source position, upgrade the priori estimates of following formula odor source position, calculate the posterior estimate of odor source position, concrete computing formula is as follows:
Figure DEST_PATH_IMAGE193
Figure 123207DEST_PATH_IMAGE100
Figure 65755DEST_PATH_IMAGE102
Figure 503690DEST_PATH_IMAGE104
Wherein,
Figure 127569DEST_PATH_IMAGE106
Be to measure noise covariance matrix;
Figure 334559DEST_PATH_IMAGE108
It is the Kalman gain;
Figure 385692DEST_PATH_IMAGE110
The expression robot exists to the odor source position
Figure 310923DEST_PATH_IMAGE043
Posterior estimate constantly;
Figure 472914DEST_PATH_IMAGE112
Be to exist about the odor source position
Figure 799990DEST_PATH_IMAGE043
Posteriority covariance matrix constantly.
(3) use detects the robot of Cmax amplitude to the estimated value of odor source position, upgrades current robot to the estimated value of odor source position, that is:
Figure 818761DEST_PATH_IMAGE114
Wherein, With
Figure DEST_PATH_IMAGE197
Be to regulate parameter;
Figure 611049DEST_PATH_IMAGE120
Expression the
Figure 576731DEST_PATH_IMAGE122
Individual robot exists to the odor source position
Figure 758314DEST_PATH_IMAGE043
Estimated value constantly, in addition the
Figure 151249DEST_PATH_IMAGE122
Individual robot also is the robot that obtains the Cmax amplitude information.
(4) restart to carry out from (1) step, and the estimated value of odor source position is provided
Figure 785492DEST_PATH_IMAGE110
For second algorithm, carry out following steps:
Judge the state of robot in each sampling period (0.01 second); If the state of robot is odor detection event generation state, execution in step a; Otherwise execution in step b.
If the current state of robot a., namely odor detection event generation state is just from the odor detection event state-transition not to take place to come, and then execution in step 1.; Otherwise execution in step 2..
Send a request message 1. for first algorithm, obtain the latest estimated value of current odor source position
Figure 351603DEST_PATH_IMAGE140
, next step position of calculating robot:
Figure 89490DEST_PATH_IMAGE133
Wherein,
Figure 715643DEST_PATH_IMAGE198
Be
Figure DEST_PATH_IMAGE199
Constantly the iThe position of individual robot; It is the duration of this state;
Figure 82350DEST_PATH_IMAGE140
Be illustrated in
Figure 176208DEST_PATH_IMAGE124
The robot that obtains is to the estimated value of odor source position constantly.
2. it is mobile to adopt consistency algorithm control robot to continue, and the execution time is 10 seconds.After the duration of this state surpassed 10 seconds, the state of robot was automatically changeb to the odor detection event state does not take place.
If the current state of robot b., namely not generation of odor detection event state is just to come from odor detection event generation state-transition, and then execution in step 1.; Otherwise execution in step 2..
Send a request message 1. for first algorithm, obtain the latest estimated value of odor source position , and the velocity information of the wind of measuring according to air velocity transducer, next step position of calculating robot.
Figure DEST_PATH_IMAGE202
Figure 18317DEST_PATH_IMAGE203
Wherein:
Figure DEST_PATH_IMAGE204
With Be respectively that wind exists
Figure 812278DEST_PATH_IMAGE152
The axle and
Figure 717917DEST_PATH_IMAGE154
Axial speed;
Figure 814049DEST_PATH_IMAGE156
Be iIndividual robot exists Constantly exist for odor source position latest estimated value
Figure 827059DEST_PATH_IMAGE152
Axial coordinate;
Figure 965917DEST_PATH_IMAGE158
The iIndividual robot exists
Figure 487028DEST_PATH_IMAGE160
The position exists constantly
Figure 2323DEST_PATH_IMAGE152
Axial coordinate;
Figure 659700DEST_PATH_IMAGE162
With
Figure DEST_PATH_IMAGE205
The iIndividual robot exists
Figure 907142DEST_PATH_IMAGE166
The position exists constantly
Figure 977866DEST_PATH_IMAGE152
The axle and Axial coordinate;
Figure DEST_PATH_IMAGE207
It is the duration of state.
2. it is mobile to adopt consistency algorithm control robot to continue, and the execution time is 30 seconds.In mobile process, if robot detects odorousness information, then the state-transition of robot is odor detection event generation state; If after 30 seconds time, do not detect odorousness, recomputate next step position of robot.Concrete grammar is:
Figure 239095DEST_PATH_IMAGE171
Figure 719755DEST_PATH_IMAGE208
Wherein, With
Figure 744659DEST_PATH_IMAGE212
Be respectively The axle and
Figure 792305DEST_PATH_IMAGE167
The control parameter of direction of principal axis hunting zone,
Figure 509725DEST_PATH_IMAGE179
Figure 904934DEST_PATH_IMAGE181
Produce an equally distributed random number in the scope.
И restarted to carry out from the step, and in the robot of colony, the detected odorousness of some robots reaches preset value, or judges odor source by vision sensor, notified the by wireless network then iIndividual robot, or surpass prior official hour search time, then stop execution in step, finish.

Claims (1)

1.一种协调多机器人系统的智能控制方法，其特征在于该方法包括两个步骤：首先在时刻k1所在的采样周期内计算得到气味源位置的估计值 ，然后在时刻k2所在的采样周期内基于估计值
Figure 786613DEST_PATH_IMAGE001
计算得到机器人的位置，其中k1> k2； 1. An intelligent control method for coordinating a multi-robot system, characterized in that the method comprises two steps: first calculating the estimated value of the odor source position in the sampling period where k1 is located , and then based on the estimated value in the sampling period of time k 2
Figure 786613DEST_PATH_IMAGE001
Calculate the position of the robot, where k 1 > k 2 ; 所述的气味源位置的估计值
Figure 566350DEST_PATH_IMAGE001
的具体计算方法如下： An estimate of the location of the odor source
Figure 566350DEST_PATH_IMAGE001
The specific calculation method is as follows: (1)利用气味分子团的运动学模型，建立气味源位置的观测模型，具体方法是： (1) Utilize the kinematic model of the odor molecular cluster to establish the observation model of the location of the odor source, the specific method is: a.建立气味分子团的运动模型，得到气味分子团的位置： a. Establish the motion model of the odor molecular cluster and obtain the position of the odor molecular cluster: 气味分子团的运动模型为：
Figure 23876DEST_PATH_IMAGE002
The motion model of the odor molecular cluster is:
Figure 23876DEST_PATH_IMAGE002
 其中,r(t)指气味分子团在
Figure 149833DEST_PATH_IMAGE003
时刻的位置；
Figure 972296DEST_PATH_IMAGE004
指气味分子团在时刻位置的微分；u(t)是在
Figure 500546DEST_PATH_IMAGE003
时刻的均值风速度；
Figure 982474DEST_PATH_IMAGE005
表示一个随机过程，该过程服从均值为零，方差为
Figure 975838DEST_PATH_IMAGE006
的高斯分布； Among them, r(t) refers to the odor molecular group in
Figure 149833DEST_PATH_IMAGE003
position at the moment;
Figure 972296DEST_PATH_IMAGE004
Refers to the odor molecule group in Differential of position at time; u(t) is at
Figure 500546DEST_PATH_IMAGE003
The mean wind speed at all times;
Figure 982474DEST_PATH_IMAGE005
represents a random process with mean zero and variance
Figure 975838DEST_PATH_IMAGE006
Gaussian distribution; 对气味分子团的运动模型在时间段[
Figure 344547DEST_PATH_IMAGE007
,
Figure 143876DEST_PATH_IMAGE008
]（
Figure 480310DEST_PATH_IMAGE009
）内进行积分，获得气味分子团在
Figure 972472DEST_PATH_IMAGE010
时刻被气味源释放，在当前时刻
Figure 531541DEST_PATH_IMAGE011
时的位置： The motion model for odorant molecular clusters in the time period [
Figure 344547DEST_PATH_IMAGE007
,
Figure 143876DEST_PATH_IMAGE008
](
Figure 480310DEST_PATH_IMAGE009
) to integrate, and obtain the odor molecular cluster in
Figure 972472DEST_PATH_IMAGE010
The moment is released by the scent source, at the current moment
Figure 531541DEST_PATH_IMAGE011
position at:
Figure 806664DEST_PATH_IMAGE012
Figure 806664DEST_PATH_IMAGE012
 其中，[
Figure 512452DEST_PATH_IMAGE010
,
Figure 660668DEST_PATH_IMAGE011
]指积分的时间段，
Figure 389590DEST_PATH_IMAGE010
指气味源释放气味分子团的时间，
Figure 468404DEST_PATH_IMAGE008
指当前时间；
Figure 28698DEST_PATH_IMAGE013
指的是在当前时间
Figure 111930DEST_PATH_IMAGE014
气味分子团的位置；
Figure 62568DEST_PATH_IMAGE015
是在时刻
Figure 820440DEST_PATH_IMAGE016
气味源的位置； in,[
Figure 512452DEST_PATH_IMAGE010
,
Figure 660668DEST_PATH_IMAGE011
] refers to the time period of integration,
Figure 389590DEST_PATH_IMAGE010
refers to the time it takes for an odor source to release an odorant cluster,
Figure 468404DEST_PATH_IMAGE008
means the current time;
Figure 28698DEST_PATH_IMAGE013
refers to the current time
Figure 111930DEST_PATH_IMAGE014
the position of the odorant cluster;
Figure 62568DEST_PATH_IMAGE015
is at the moment
Figure 820440DEST_PATH_IMAGE016
the location of the source of the odor; b.确定气味分子团的离散运动模型： b. Determine the discrete motion model of the odor cluster: 通过定义
Figure 235241DEST_PATH_IMAGE017
和
Figure 177789DEST_PATH_IMAGE018
，将气味分子团的位置离散化；其中离散时刻
Figure 927308DEST_PATH_IMAGE019
是气味源释放气味分子团时间
Figure 410242DEST_PATH_IMAGE020
的整数值；离散时刻
Figure 695861DEST_PATH_IMAGE021
是当前时间
Figure 871627DEST_PATH_IMAGE022
的整数值；是指时间的微小变化；从而气味分子团的离散运动模型为： by definition
Figure 235241DEST_PATH_IMAGE017
and
Figure 177789DEST_PATH_IMAGE018
, discretize the position of the odor molecular cluster; where the discrete time
Figure 927308DEST_PATH_IMAGE019
is the release time of odor molecules from the odor source
Figure 410242DEST_PATH_IMAGE020
Integer value of ; discrete time instant
Figure 695861DEST_PATH_IMAGE021
is the current time
Figure 871627DEST_PATH_IMAGE022
integer value of refers to the small change of time; thus the discrete motion model of the odor molecular cluster is:
Figure 332750DEST_PATH_IMAGE024
Figure 332750DEST_PATH_IMAGE024
 其中，气味源位置在一定时间内是静止的，所以有
Figure 456564DEST_PATH_IMAGE025
；
Figure 740915DEST_PATH_IMAGE026
表示气味源在
Figure 966491DEST_PATH_IMAGE019
时刻释放气味分子团，在
Figure 994490DEST_PATH_IMAGE027
时刻的位置；
Figure 238389DEST_PATH_IMAGE028
表示在时间段[
Figure 757225DEST_PATH_IMAGE019
,
Figure 719365DEST_PATH_IMAGE021
]内风推动气味分子团的移动距离；
Figure 285475DEST_PATH_IMAGE029
表示随机过程，服从均值为零，方差
Figure 400193DEST_PATH_IMAGE030
的正态分布； Among them, the position of the odor source is static within a certain period of time, so there is
Figure 456564DEST_PATH_IMAGE025
;
Figure 740915DEST_PATH_IMAGE026
Indicates that the source of the smell is
Figure 966491DEST_PATH_IMAGE019
Release odor molecules at all times, in
Figure 994490DEST_PATH_IMAGE027
position at the moment;
Figure 238389DEST_PATH_IMAGE028
Indicates that in the time period [
Figure 757225DEST_PATH_IMAGE019
,
Figure 719365DEST_PATH_IMAGE021
] Internal wind pushes the moving distance of the odor molecule group;
Figure 285475DEST_PATH_IMAGE029
Represents a random process with mean zero and variance
Figure 400193DEST_PATH_IMAGE030
normal distribution of 考虑到气味分子团释放时间的所有可能性，即 Considering all possibilities for the release time of the odorant cluster, i.e.
Figure 760767DEST_PATH_IMAGE031
Figure 760767DEST_PATH_IMAGE031
Figure 210203DEST_PATH_IMAGE032
Figure 210203DEST_PATH_IMAGE032
 则气味分子团的离散运动模型进一步表示如下： Then the discrete motion model of the odor molecular cluster is further expressed as follows: 其中，为时刻气味分子团的位置；为
Figure 236934DEST_PATH_IMAGE021
时刻气味源的位置；
Figure 247615DEST_PATH_IMAGE036
为
Figure 277888DEST_PATH_IMAGE021
时刻风推动气味分子团移动的距离；
Figure 374020DEST_PATH_IMAGE037
是测量噪声，并且服从零均值，
Figure 397208DEST_PATH_IMAGE038
方差的正态分布； in, for The position of the odor cluster at any time; for
Figure 236934DEST_PATH_IMAGE021
The location of the odor source at any time;
Figure 247615DEST_PATH_IMAGE036
for
Figure 277888DEST_PATH_IMAGE021
The distance that the wind pushes the odor molecule group to move;
Figure 374020DEST_PATH_IMAGE037
is the measurement noise and has zero mean,
Figure 397208DEST_PATH_IMAGE038
Normal distribution of variance; c.通过定义
Figure 324713DEST_PATH_IMAGE039
，得到气味源位置的观测模型： c. by definition
Figure 324713DEST_PATH_IMAGE039
, to obtain the observation model for the location of the odor source:
Figure 463570DEST_PATH_IMAGE040
Figure 463570DEST_PATH_IMAGE040
 其中，
Figure 860048DEST_PATH_IMAGE041
是第i个机器人在时刻
Figure 172081DEST_PATH_IMAGE042
对气味源位置
Figure 157354DEST_PATH_IMAGE035
的测量值； in,
Figure 860048DEST_PATH_IMAGE041
is the i-th robot at time
Figure 172081DEST_PATH_IMAGE042
location of odor source
Figure 157354DEST_PATH_IMAGE035
measured value; (2)使用气味源位置的观测模型，产生机器人对气味源位置的观测值，并使用Kalman滤波理论，获得气味源位置的估计值；具体方法是： (2) Use the observation model of the location of the odor source to generate the observed value of the location of the odor source by the robot, and use the Kalman filter theory to obtain an estimated value of the location of the odor source; the specific method is: d.在获得机器人对气味源位置的观测值之前，获得气味源位置的先验估计值和先验协方差矩阵； d. Obtain the prior estimate and prior covariance matrix of the odor source location before obtaining the robot's observations of the odor source location;
Figure 778697DEST_PATH_IMAGE043
Figure 778697DEST_PATH_IMAGE043
Figure 849421DEST_PATH_IMAGE044
Figure 849421DEST_PATH_IMAGE044
 其中,
Figure 965145DEST_PATH_IMAGE045
表示机器人对气味源位置在
Figure 617974DEST_PATH_IMAGE046
时刻的后验估计值；
Figure 98634DEST_PATH_IMAGE047
是机器人对气味源位置在
Figure 453392DEST_PATH_IMAGE021
时刻的先验估计值；
Figure 310490DEST_PATH_IMAGE048
是关于气味源位置在
Figure 322220DEST_PATH_IMAGE046
时刻的后验协方差矩阵；
Figure 973781DEST_PATH_IMAGE049
关于气味源位置在
Figure 81415DEST_PATH_IMAGE021
时刻的先验协方差矩阵； in,
Figure 965145DEST_PATH_IMAGE045
Indicates that the robot's position of the odor source is
Figure 617974DEST_PATH_IMAGE046
The posterior estimate of time;
Figure 98634DEST_PATH_IMAGE047
is the robot's position on the odor source at
Figure 453392DEST_PATH_IMAGE021
A priori estimate of time;
Figure 310490DEST_PATH_IMAGE048
is about the location of the odor source in
Figure 322220DEST_PATH_IMAGE046
Posterior covariance matrix at time;
Figure 973781DEST_PATH_IMAGE049
Regarding the location of the odor source in
Figure 81415DEST_PATH_IMAGE021
The prior covariance matrix of time; e.当机器人通过对气味源位置的观测模型，获得气味源位置的观测值时，更新气味源位置的先验估计值，计算出气味源位置的后验估计值，具体计算公式如下： e. When the robot obtains the observed value of the odor source position through the observation model of the odor source position, update the prior estimate value of the odor source position and calculate the posterior estimate value of the odor source position. The specific calculation formula is as follows:
Figure 476624DEST_PATH_IMAGE050
Figure 476624DEST_PATH_IMAGE050
Figure 838466DEST_PATH_IMAGE051
Figure 838466DEST_PATH_IMAGE051
Figure 988825DEST_PATH_IMAGE052
Figure 988825DEST_PATH_IMAGE052
 其中，
Figure 255858DEST_PATH_IMAGE053
是测量噪声协方差矩阵；
Figure 766343DEST_PATH_IMAGE054
是Kalman增益；表示机器人对气味源位置在
Figure 490902DEST_PATH_IMAGE021
时刻的后验估计值；是关于气味源位置在
Figure 795293DEST_PATH_IMAGE021
时刻的后验协方差矩阵； in,
Figure 255858DEST_PATH_IMAGE053
is the measurement noise covariance matrix;
Figure 766343DEST_PATH_IMAGE054
is the Kalman gain; Indicates that the robot's position of the odor source is
Figure 490902DEST_PATH_IMAGE021
The posterior estimate of time; is about the location of the odor source in
Figure 795293DEST_PATH_IMAGE021
Posterior covariance matrix at time; (3)使用检测到最大浓度幅度的机器人对气味源位置的估计值，更新当前机器人对气味源位置的估计值，即： (3) Using the estimated value of the odor source location detected by the robot that detected the maximum concentration range, update the current robot's estimated value of the odor source location, namely:
Figure 318678DEST_PATH_IMAGE057
Figure 318678DEST_PATH_IMAGE057
 其中，和
Figure 98470DEST_PATH_IMAGE059
是调节参数；
Figure 639173DEST_PATH_IMAGE060
表示第
Figure 344960DEST_PATH_IMAGE061
个机器人对气味源位置在
Figure 493176DEST_PATH_IMAGE021
时刻的估计值，此外第
Figure 222098DEST_PATH_IMAGE061
个机器人也是获得最大浓度幅度信息的机器人； in, and
Figure 98470DEST_PATH_IMAGE059
is the adjustment parameter;
Figure 639173DEST_PATH_IMAGE060
Indicates the first
Figure 344960DEST_PATH_IMAGE061
The location of the odor source by a robot is
Figure 493176DEST_PATH_IMAGE021
The estimated value of time, in addition to the first
Figure 222098DEST_PATH_IMAGE061
A robot is also the robot that obtains the maximum concentration amplitude information; (4)从第(2)步重新开始执行并提供气味源位置的估计值
Figure 300912DEST_PATH_IMAGE055
； (4) Restart from step (2) and provide an estimate of the location of the odor source
Figure 300912DEST_PATH_IMAGE055
; 所述的机器人的位置的具体计算方法如下： The specific calculation method of the position of the robot is as follows: І在采样周期
Figure 861206DEST_PATH_IMAGE062
内判断机器人的状态；如果机器人的状态是气味检测事件发生状态，执行步骤a；否则执行步骤b； ІDuring the sampling period
Figure 861206DEST_PATH_IMAGE062
Determine the state of the robot; if the state of the robot is the state of the smell detection event, perform step a; otherwise, perform step b; a.如果机器人的当前状态，即气味检测事件发生状态是刚从气味检测事件不发生状态转变过来，则执行步骤①；否则执行步骤②； a. If the current state of the robot, that is, the occurrence state of the odor detection event has just transitioned from the non-occurrence state of the odor detection event, then perform step ①; otherwise, perform step ②; ①基于气味源位置的最新估计值
Figure 367274DEST_PATH_IMAGE063
，则机器人下一步的位置为气味源位置的最新估计值，即 ①Based on the latest estimate of the location of the odor source
Figure 367274DEST_PATH_IMAGE063
, then the robot's next step position is the latest estimated value of the odor source position, namely
Figure 895076DEST_PATH_IMAGE064
Figure 895076DEST_PATH_IMAGE064
 其中，
Figure 839899DEST_PATH_IMAGE065
是时刻第i个机器人的位置；
Figure 947980DEST_PATH_IMAGE067
是这一状态的持续时间；
Figure 385915DEST_PATH_IMAGE068
表示在
Figure 868849DEST_PATH_IMAGE069
时刻获得的机器人对气味源位置的估计值； in,
Figure 839899DEST_PATH_IMAGE065
yes The position of the i-th robot at any time;
Figure 947980DEST_PATH_IMAGE067
is the duration of this state;
Figure 385915DEST_PATH_IMAGE068
expressed in
Figure 868849DEST_PATH_IMAGE069
The estimated value of the robot's location of the odor source obtained at all times; ②采用一致性算法控制机器人继续移动，执行时间为
Figure 647143DEST_PATH_IMAGE067
秒；当该状态的持续时间超过
Figure 495014DEST_PATH_IMAGE067
秒后，机器人的状态自动转变为气味检测事件不发生状态； ②A consensus algorithm is used to control the robot to continue to move, and the execution time is
Figure 647143DEST_PATH_IMAGE067
seconds; when the duration of the state exceeds
Figure 495014DEST_PATH_IMAGE067
Seconds later, the state of the robot automatically changes to the state where the smell detection event does not occur; b.如果机器人的当前状态，即气味检测事件不发生状态是刚从气味检测事件发生状态转变过来，则执行步骤③；否则执行步骤④； b. If the current state of the robot, that is, the state where the odor detection event does not occur, is just transitioned from the state where the odor detection event occurred, then perform step ③; otherwise, perform step ④; ③基于气味源位置的最新估计值和风的速度信息，计算机器人下一步的位置； ③ based on the latest estimate of the location of the odor source The speed information of the wind, calculate the next position of the robot;
Figure 706869DEST_PATH_IMAGE070
Figure 706869DEST_PATH_IMAGE070
Figure 33945DEST_PATH_IMAGE071
Figure 33945DEST_PATH_IMAGE071
 其中：
Figure 131345DEST_PATH_IMAGE072
和
Figure 606189DEST_PATH_IMAGE073
分别是风在轴和轴方向的速度；是第i个机器人在
Figure 279168DEST_PATH_IMAGE069
时刻对于气味源位置最新估计值在
Figure 658328DEST_PATH_IMAGE074
轴方向的坐标；
Figure 694417DEST_PATH_IMAGE077
第i个机器人在
Figure 382887DEST_PATH_IMAGE078
时刻位置在
Figure 770006DEST_PATH_IMAGE074
轴方向的坐标；
Figure 185813DEST_PATH_IMAGE079
和
Figure 341988DEST_PATH_IMAGE080
第i个机器人在
Figure 201359DEST_PATH_IMAGE081
时刻位置在
Figure 810195DEST_PATH_IMAGE074
轴和轴方向的坐标；
Figure 807418DEST_PATH_IMAGE083
是状态的持续时间； in:
Figure 131345DEST_PATH_IMAGE072
and
Figure 606189DEST_PATH_IMAGE073
Respectively, the wind is in axis and speed in the direction of the axis; is the i-th robot in
Figure 279168DEST_PATH_IMAGE069
The latest estimate of the location of the odor source at time is
Figure 658328DEST_PATH_IMAGE074
Coordinates in the axis direction;
Figure 694417DEST_PATH_IMAGE077
The i-th robot is in
Figure 382887DEST_PATH_IMAGE078
time position at
Figure 770006DEST_PATH_IMAGE074
Coordinates in the axis direction;
Figure 185813DEST_PATH_IMAGE079
and
Figure 341988DEST_PATH_IMAGE080
The i-th robot is in
Figure 201359DEST_PATH_IMAGE081
time position at
Figure 810195DEST_PATH_IMAGE074
axis and Coordinates in the axis direction;
Figure 807418DEST_PATH_IMAGE083
is the duration of the state; ④采用一致性算法控制机器人继续移动，执行时间为
Figure 837691DEST_PATH_IMAGE083
秒；在移动的过程中，如果机器人检测到气味浓度信息，则机器人的状态转变为气味检测事件发生状态；如果在时间
Figure 933823DEST_PATH_IMAGE083
秒后，没有检测到气味浓度，重新计算机器人下一步的位置；具体方法是： ④Using a consensus algorithm to control the robot to continue to move, the execution time is
Figure 837691DEST_PATH_IMAGE083
seconds; in the process of moving, if the robot detects the smell concentration information, the state of the robot will change to the state of smell detection event occurrence; if the time
Figure 933823DEST_PATH_IMAGE083
Seconds later, if no odor concentration is detected, recalculate the next position of the robot; the specific method is:
Figure 691432DEST_PATH_IMAGE084
Figure 691432DEST_PATH_IMAGE084
Figure 822199DEST_PATH_IMAGE085
Figure 822199DEST_PATH_IMAGE085
 其中，
Figure 23373DEST_PATH_IMAGE086
和
Figure 419851DEST_PATH_IMAGE087
分别是控制轴和
Figure 717157DEST_PATH_IMAGE075
轴方向搜索范围的控制参数，
Figure 26916DEST_PATH_IMAGE088
在
Figure 415084DEST_PATH_IMAGE089
范围内产生一个均匀分布的随机数； in,
Figure 23373DEST_PATH_IMAGE086
and
Figure 419851DEST_PATH_IMAGE087
control respectively axis and
Figure 717157DEST_PATH_IMAGE075
Control parameters for the search range in the axis direction,
Figure 26916DEST_PATH_IMAGE088
exist
Figure 415084DEST_PATH_IMAGE089
Generate a uniformly distributed random number within the range; И从第І步重新开始执行，直到群体机器人中，某一个机器人检测到的气味浓度达到预先设定值，或通过视觉传感器判断出气味源，然后通过无线网络通知第i个机器人，或搜索时间超过事先规定的时间时，则结束。 Иrestart from step І until the odor concentration detected by a certain robot in the group of robots reaches the preset value, or the odor source is judged by the visual sensor, and then the i-th robot is notified through the wireless network, or the search time When the time specified in advance is exceeded, it ends.
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