CN108614561A - A kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot - Google Patents
A kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot Download PDFInfo
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
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- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
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Abstract
The invention discloses a kind of Artificial Potential Field barrier-avoiding methods suitable for omnidirectional's wheel mobile robot, including：Step 1. obtains the initial position of mobile robot, final goal position；Step 2. clusters laser radar environmental data, and least square method is used in combination to complete local environment modeling；Step 3. obtain mobile robot current time position and laser radar scanning within the scope of localized target point；Step 4. combines fuzzy control, establishes fuzzy rule base, selects traveling mode, and according to the speed of the size of power and deflection metrization mobile robot；Step 5. controls robot ambulation；Whether step 6. detection mobile robot reaches final goal point, if not, the cycle of return to step 2 executes；If it is terminate traveling process.The present invention realizes selection itself the traveling mode that omnidirectional's wheel mobile robot can be adaptive, and different passage paths is taken for different barriers, has given full play to the advantage of omni-directional wheel, substantially increases the obstacle-crossing ability of robot.
Description
Technical field
The present invention relates to traffic information technical fields, and in particular to a kind of artificial gesture suitable for omnidirectional's wheel mobile robot
Field barrier-avoiding method.
Background technology
In the today for greatly developing intelligent automation, mobile robot is just leading this scientific and technological revolution.Mobile robot
Carrying task can not only be undertaken, operating efficiency is improved, also has its unique advantage at monitoring, emergent aspect.With moving machine
The continuous innovation of device people's technology is suffered from agricultural, industry, national defence industry etc. and is widely applied.
Path Planning Technique is one of mobile robot key technology, according to known to environmental information or unknown, Ke Yifen
For offline path planning and online path planning.The former path is more excellent, and the latter is real-time, there is stronger adaptability to changes.This hair
It is bright to belong to the unknown online real-time route planning of environment.
Path Planning Technique constantly develops in recent years, and main paths planning method has Artificial Potential Field Method, neural network
Algorithm, genetic algorithm, simulated annealing, particle cluster algorithm, ant group algorithm etc..Wherein Artificial Potential Field Method is because of its high efficiency advantage
It is widely used.Its basic thought is the thought according to gravitational field, and target point generates " gravitation " to mobile robot, barrier pair
Mobile robot generates " repulsion ", and movement of the robot in ambient enviroment is abstracted according to scene feature and kinetic characteristic
At the movement in a kind of artificial gravitational field, motion planning and the control of mobile robot are realized finally by resultant force is sought.Patent
On the basis of Artificial Potential Field Method, the method for proposing that virtual repulsion is added solves sensor blind area and keeps away CN107161143A
During barrier the problem of secondary collision；Patent CN104317291A optimizes the repulsion value calculating method of Artificial Potential Field Method, solves
Complicated shape robot considers the problems of its outer profile in path planning；Patent CN105629974A is in Artificial Potential Field Method
Improve gravitational potential function, it is proposed that time virtual drive power solves Artificial Potential Field Method and is typically absorbed in local minimum point
Problem.
But above each path planning algorithm does not all consider the spy of its motion mode of omnidirectional's wheel mobile robot pointedly
Different property.Omni-directional moving mechanism can be moved in a straight line without doing in advance because nonholonomic restriction is not present to any direction
Rotary motion can execute rotary motion while executing linear motion, or even can complete to rotate in place, flexible with movement,
The advantages of freely controlling.The moving process of more common wheeled mobile robot, all directionally movable robot is increasingly complex, point-to-point
Movement just there are a variety of move modes, above-mentioned paths planning method can not achieve to omnidirectional's wheel mobile robot mobile route
Optimum programming, cannot play the advantage of omni-directional wheel, so it is strong to be badly in need of a kind of high efficiency, high real-time, handling capacity, be suitable for complete
The barrier-avoiding method of orientation mobile robot.
Invention content
In view of this, to solve the above-mentioned problems, the present invention provides a kind of suitable for the artificial of omnidirectional's wheel mobile robot
Potential field barrier-avoiding method.
7. to achieve the above object and other purposes, the present invention provide a kind of suitable for the artificial of omnidirectional's wheel mobile robot
Potential field barrier-avoiding method, this approach includes the following steps：
Step 1. obtains the initial position of mobile robotFinal goal positionWherein, x is
Lateral coordinates, y are longitudinal coordinate,For mobile robot positive direction and abscissa angle；
Step 2. obtains environmental data using laser radar, is clustered to laser radar environmental data, and minimum two is used in combination
Multiplication completes local environment modeling；
Step 3. obtains within the scope of current time position (x', y', φ ') and the laser radar scanning of mobile robot
Localized target point (X', Y')；
Step 4. by car body by before left front, right, it is left back, right after be split and establish Artificial Potential Field Model respectively, in conjunction with
Fuzzy rule base is established in fuzzy control, selects traveling mode, and according to the speed of the size of power and deflection metrization mobile robot
Spend vx,vy,w；
Step 5., into mode and speed, controls robot ambulation according to selected row；
Whether step 6. detection mobile robot reaches final goal point, if not, the cycle of return to step 2 executes；If
It is to terminate traveling process.
Preferably, the step 2 includes following sub-step：
Step 21. obtains laser radar data, and using laser radar placement position as coordinate origin, environmental data is point number of clusters
According to { (Li, θi) | i=1,23...., n }；
Step 22. pre-processes laser radar point cluster data；
Step 23. clusters laser radar data using split-merge algorithms, and least square method completion office is used in combination
Portion's environmental modeling.
A kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 2, it is special
Sign is that the step 3 includes following sub-step：
Step 31：The speed of each wheel is obtained, and robot advance, translation are obtained according to the kinematics model of mobile mechanism
And rotary speed, kinematics model are as follows：
In formula：vxFor Robot X-axis speed；vyFor Robot Y-axis speed；W is robot rotary speed, counterclockwise
Direction is just；l1,l2Respectively robot vertical direction wheel spacing and lateral wheel spacing；w1,w2,w3,w4For robot four
The speed of a wheel；
Step 32：The speed of robot is integrated, robot current location moment position (x', y', φ ') is obtained；
Step 33：According to the local environment model that step 2 is established, the local mesh within the scope of present laser radar range finding is obtained
Punctuate (X', Y'),
In formula：xiIndicate the abscissa of all points in the robot left side, xjIndicate all points on the right of robot
Abscissa, yiIndicate the vertical mark of all points in the robot left side, yjIndicate the vertical seat of all points on the right of robot
Mark.
Preferably, the step 4 includes following sub-step：
Step 41. by robot car body be divided into it is left front, right before, it is left back, right after 4 parts, using electrostatic field potential field model, point
Not carry out Artificial Potential Field modeling, formula is as follows：
In formula：ε, δ are direct proportion gain coefficient, riIt is divided into corresponding 4 particles behind 4 parts, L for robot car bodyp
(ri) it is localized target point P to point riEuclidean distance, LriFor barrier to point riThe shortest distance, L0For barrier repulsion gesture
The effective range of field, Uatt(ri) it is the point-to-point r of localized targetiAttraction potential energy, Urep(ri) be barrier to point riRepulsive potential
Energy；
Step 42：The gradient for seeking established Artificial Potential Field Model obtains the attraction of localized target point, the row of barrier
Repulsion, and further obtain 4 points respectively suffered resultant force, formula are as follows：
Fsum(ri)=Fatt(ri)+Frep(ri)
In formula：Fatt(ri) it is point riBy the attraction of localized target point, Frep(ri) it is point riRepelled by barrier
Power, Fsum(ri) it is point riSuffered resultant force, grad [] are potential field gradient；
Step 43：Fuzzy rule is formulated according to quadrant residing for resultant force vector suffered by resultant force suffered by each section and each section,
Fuzzy reasoning table is as follows：
| Quadrantal points r belonging to serial number resultant forceiPoint | r1 | r2 | r3 | r4 | Traveling mode |
| ① | 1 | 1 | 2 | 2 | Traveling mode one |
| ② | 2 | 2 | 4 | 4 | Traveling mode one |
| ③ | 1 | 2 | 1 | 2 | Traveling mode two |
| ④ | 2 | 1 | 2 | 1 | Traveling mode two |
| ⑤ | 1 | 1 | 1 | 1 | Traveling mode three |
| ⑥ | 2 | 2 | 2 | 2 | Traveling mode three |
Wherein：r1, r2, r3, r4Correspond to respectively robot segmentation it is left front, right before, left back, right-rearward portion；
Step 44：Consider the deflection angle quantization gait of march v of the mould and force vector of resultant force suffered by each sectionx, vy, w；
Formula is as follows：
For traveling mode one：
For traveling mode two：
For traveling mode three：
In formula：
For r1,r2,r3,r4In resultant force suffered by four parts, force vector mould the maximum, α, beta, gamma is direct proportion gain system
Number.
Preferably, in the step 5, pass through following model cootrol robot ambulation：
Preferably, in the step S6, judge that the method whether robot reaches final goal is：
In formula, (X, Y) is final goal point coordinates, and (x, y) is current position coordinates, DarrTo reach threshold value.
By adopting the above-described technical solution, the present invention has the advantage that：
A kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot of the invention on the basis of original method, according to
The driving experience of people, propose by car body by before left front, right, it is left back, right after be split, establish Artificial Potential Field Model respectively, and
In conjunction with fuzzy control, fuzzy rule base is established, realizes itself traveling side of selection that omnidirectional's wheel mobile robot can be adaptive
Formula takes different passage paths for different barriers, has given full play to the advantage of omni-directional wheel, has substantially increased robot
Obstacle-crossing ability.Therefore, a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot of the invention has higher
Practicability.
Other advantages, target and the feature of the present invention will be illustrated in the following description to a certain extent, and
And to a certain extent, based on will be apparent to those skilled in the art to investigating hereafter, Huo Zheke
To be instructed from the practice of the present invention.The target and other advantages of the present invention can by following specification realizing and
It obtains.
Description of the drawings
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into
The detailed description of one step：
Fig. 1 is the special traveling schematic diagram of omnidirectional's wheel mobile robot；
Fig. 2 is laser radar data Modified geometrical schematic diagram；
Fig. 3 is laser radar data split-merge clustering algorithm schematic diagrames；
Fig. 4 is that walking localized target point obtains schematic diagram in mobile robot channel；
Fig. 5 is traditional artificial potential field barrier-avoiding method schematic diagram；
Fig. 6 is Artificial Potential Field method schematic diagram after omnidirectional's wheel mobile robot segmentation；
Fig. 7 is the method for the present invention overall flow schematic diagram.
Specific implementation mode
Illustrate that embodiments of the present invention, those skilled in the art can be by this specification below by way of specific specific example
Disclosed content understands other advantages and effect of the present invention easily.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also be based on different viewpoints with application, without departing from
Various modifications or alterations are carried out under the spirit of the present invention.
It please refers to Fig.1 to Fig. 7.It should be noted that the diagram provided in the present embodiment only illustrates this in a schematic way
The basic conception of invention, package count when only display is with related component in the present invention rather than according to actual implementation in schema then
Mesh, shape and size are drawn, when actual implementation kenel, quantity and the ratio of each component can be a kind of random change, and its
Assembly layout kenel may also be increasingly complex.
(it is with a kind of Mecanum wheel (omni-directional wheel mobile mechanism) mobile robot in the following with reference to the drawings and specific embodiments
Example) the invention will be further described, so that those skilled in the art can be better understood from the present invention and can be practiced,
But illustrated embodiment is not as a limitation of the invention.
As shown in Figure 1, for mode of progression of omnidirectional's wheel mobile robot from any to subsequent point, there are three types of modes, different
In the single traveling mode of wheeled robot.A kind of Artificial Potential Field avoidance suitable for omnidirectional's wheel mobile robot of the present embodiment
Method realizes omnidirectional's wheel mobile robot according to certain traveling mode of the selection of environment self-adaption, includes the following steps：
Step 1. obtains the initial position of mobile robotFinal goal position
Wherein, x is lateral coordinates, and y is longitudinal coordinate,For mobile robot positive direction and abscissa angle.
Step 2., as robot " visual field ", obtains environmental information using laser radar, completes local environment modeling.Laser
Radar o2D laser radars.
Step 21：2D laser radar datas are obtained, using laser radar placement position as coordinate origin, environmental data is point cluster
Data { (Li,θi) | i=1,2,3...., n }.Wherein, point cluster data is obtained with polar form.
Step 22：Laser radar point cluster data is pre-processed.
Step 221：Medium filtering is carried out to cluster data, obtains filtered cluster data { (Lj,θj) | j=1,2,
3...., m, m ＜ n }, algorithm is as follows：
For i=1to n；
J=1；
L=mid (Li,Li+1,Li+2)；
j++；
Step 222：The laser radar scanning one frame data about 100ms times, robot is in and is moved through in this 100ms
Cheng Zhong, origin is changed during laser beam flying, needs to make error compensation to laser radar data, as shown in Fig. 2, public
Formula is as follows：
For j=1to m
In formula：
T is the laser radar scanning period；
γ is the angular resolution of laser radar scanning；
V is robot straight trip speed；
StFor serial number i in current time laser radar data institute's ranging from；
S(t-T)For serial number i in last moment laser radar data institute's ranging from；
ΘjBy survey barrier and axis of abscissas angle；
SrealFor revised laser radar data.
Step 223：The laser radar data of polar form is converted into rectangular co-ordinate, using robot center as origin,
Horizontal axis is robot translation direction, and the longitudinal axis is robot straight trip direction.
In formula：L is robot longitudinal length, xjIndicate the abscissa of all points on the right of robot, yjIndicate all
The ordinate of point on the right of robot.
Step 23：Laser radar data is clustered using split-merge algorithms, is modeled；Approximating method is using most
Small square law, as shown in figure 3, algorithm is as follows：
(1) laser radar point cluster data is taken out, is put into List A；
(2) 2 points of head and the tail in A is taken to be fitted the L that is in line1；
(3) apart from straight line l in search List A1Farthest point, obtains distance d；
(4) if d is less than segmentation threshold dmax, go to (6)；
(5) otherwise, by L1It is divided into L2And L3, go to (2)；
(6) each intersegmental all the points of segmentation are taken, least square fitting is used；
(7) algorithm terminates, and obtains final line-segment sets { L1,L2,L3,...,Ln}。
Least square fitting formula is as follows：
In formula：For point set xi,yiArithmetic mean of instantaneous value.
Step 3：It obtains within the scope of current time position (x', y', φ ') and the laser radar scanning of mobile robot
Localized target point (X', Y').
Step 31：For all directionally movable robot traveling distance by encoder gathered data, the present embodiment is with Mike
It receives for nurse wheel robot, encoder can get the speed of each wheel, according to the kinematics model of Mecanum wheel mobile mechanism,
It is as follows that robot advance, translation and rotary speed, kinematics model can be obtained：
In formula：
vxFor Robot X-axis speed；
vyFor Robot Y-axis speed；
W is the rotary speed of robot, counterclockwise for just；
l1,l2Respectively robot vertical direction wheel spacing and lateral wheel spacing；
w1,w2,w3,w4The respectively speed of Mecanum wheel robot four wheels.
Step 32：The sampling period of encoder is 100ms, and integral and corresponding several is carried out to 3 direction speed of robot
What operation, can obtain robot current location moment position (x', y', φ ').
Step 33：As shown in figure 4, robot runs generally use walking manner placed in the middle in the channel, established according to step 2
Environmental model, obtain the localized target point (X', Y') within the scope of present laser radar range finding, formula is as follows：
In formula：xiIndicate the abscissa of all points in the robot left side, xjIndicate all points on the right of robot
Abscissa, yiIndicate the vertical mark of all points in the robot left side, yjIndicate the vertical seat of all points on the right of robot
Mark.
Step 4：For traditional artificial potential field barrier-avoiding method as shown in figure 5, regarding robot as entirety, target point generates attraction potential
, barrier, which generates, repels potential field, and the resultant force of robot attraction and repulsive force is the direction of advance of robot.But it is right
In omnidirectional's wheel mobile robot (the present embodiment is by taking Mecanum wheel robot as an example), the move mode from any to another point is not
It is single again, 3 kinds of traveling modes are shared as shown in Figure 1.Car body is divided into 4 parts by the present invention by driving experience, establishes people respectively
Work potential field model, as shown in Figure 6.Then according to 4 part resultant force situations, fuzzy rule base is established, selects suitable traveling mode；
And according to the speed v of the size of power and deflection metrization mobile robotx,vy,w。
Step 41：As shown in Figure 6 by robot car body be divided into it is left front, right before, left back, right 4 part of rear portion, using electrostatic field
Potential field model, carries out Artificial Potential Field modeling respectively, and formula is as follows：
In formula：
ε,δ：Direct proportion gain coefficient；
ri：Robot car body is divided into corresponding 4 particles behind 4 parts；
Lp(ri)：Localized target point P to point riEuclidean distance；
Lri：Barrier is to point riThe shortest distance；
L0：The effective range of barrier repulsion potential field；
Uatt(ri)：The point-to-point r of localized targetiAttraction potential energy；
Urep(ri)：Barrier is to point riRepulsion potential energy.
Step 42：Gradient is asked to established potential field, can be obtained the attraction of localized target point, the repulsive force of barrier, into
The synthesis of row power, obtaining 4 points, respectively suffered resultant force, formula are as follows：
Fatt(ri)=- grad [Uatt(ri)]=ε Lp(ri)
Fsum(ri)=Fatt(ri)+Frep(ri)
In formula：
Grad [] is potential field gradient；
Fatt(ri)：Point riBy the attraction of localized target point；
Frep(ri)：Point riBy the repulsive force of barrier；
Fsum(ri)：Point riSuffered resultant force.
Step 43：Mecanum wheel mobile robot is divided into 4 parts, and the suffered resultant force of each section has acquired, considered each
Quadrant residing for the suffered resultant force vector in part formulates fuzzy rule in conjunction with driving experience, and adaptive advances from 3 kinds as shown in Figure 7
Optimal traveling mode is selected in mode, passes through performance with improve Mecanum wheel robot.Fuzzy reasoning table is as follows：
| Quadrantal points r belonging to serial number resultant forceiPoint | r1 | r2 | r3 | r4 | Traveling mode |
| ① | 1 | 1 | 2 | 2 | Traveling mode one |
| ② | 2 | 2 | 4 | 4 | Traveling mode one |
| ③ | 1 | 2 | 1 | 2 | Traveling mode two |
| ④ | 2 | 1 | 2 | 1 | Traveling mode two |
| ⑤ | 1 | 1 | 1 | 1 | Traveling mode three |
| ⑥ | 2 | 2 | 2 | 2 | Traveling mode three |
Wherein：r1, r2, r3, r4Correspond to respectively robot segmentation it is left front, right before, left back, right-rearward portion.
Step 44：After selecting suitable traveling mode, the mould of resultant force suffered by consideration each section, the deflection angle of force vector,
Quantify gait of march vx, vy, w.Formula is as follows：
For traveling mode one：
For traveling mode two：
For traveling mode three：
In formula：
For r1, r2, r3, r4In resultant force suffered by four parts, force vector mould the maximum；α, beta, gamma are direct proportion gain system
Number.
Step 5：According to selected row into mode, gained speed controls the walking of Mecanum wheel mobile robot.Controlling party
Method is with reference to Mecanum wheel mobile mechanism kinematics model：
Step 6：Whether detection mobile robot reaches final goal point, if not, the cycle of return to step 2 executes.Detection
It is as follows whether robot reaches final goal point formula：
In formula：
(X,Y)：Final goal point coordinates；
(x,y)：Current position coordinates；
Darr：Reach threshold value.
Step 7：Mobile robot reaches final goal point, and traveling process terminates.
The present embodiment elaborates that one kind is suitable for from Mecanum wheel mobile robot (a kind of omnidirectional's wheel mobile robot)
The overall flow of the Artificial Potential Field barrier-avoiding method of omnidirectional's wheel mobile robot.Present omnidirectional's wheel mobile robot its motion mode
Particularity and traditional artificial potential field barrier-avoiding method limitation.A kind of people suitable for omnidirectional's wheel mobile robot of the invention
Work potential field barrier-avoiding method is on the basis of original method, according to the driving experience of people, propose by car body by before left front, right, it is left back, right after
It is split, establishes Artificial Potential Field Model respectively, and combine fuzzy control, establish fuzzy rule base, realize omni-directional wheel movement
Robot can be adaptive selection itself traveling mode, different passage paths is taken for different barriers, is given full play to
The advantage of omni-directional wheel, substantially increases the obstacle-crossing ability of robot.Therefore, a kind of omni-directional wheel that is suitable for of the present invention moves
The Artificial Potential Field barrier-avoiding method of robot has higher practicability.
Finally illustrate, the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although with reference to compared with
Good embodiment describes the invention in detail, it will be understood by those of ordinary skill in the art that, it can be to the skill of the present invention
Art scheme is modified or replaced equivalently, and without departing from the objective and range of the technical program, should all be covered in the present invention
Protection domain in.
Claims (6)
1. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot, which is characterized in that this method includes following
Step：
Step 1. obtains the initial position of mobile robotFinal goal positionWherein, x is laterally
Coordinate, y are longitudinal coordinate,For mobile robot positive direction and abscissa angle；
Step 2. obtains environmental data using laser radar, is clustered to laser radar environmental data, least square method is used in combination
Complete local environment modeling；
Step 3. obtains the part within the scope of the current time position (x ', y ', φ ') and laser radar scanning of mobile robot
Target point (X ', Y ')；
Step 4. by car body by before left front, right, it is left back, right after be split and establish respectively Artificial Potential Field Model, in conjunction with fuzzy
Fuzzy rule base is established in control, selects traveling mode, and according to the speed of the size of power and deflection metrization mobile robot
vx, vy, w；
Step 5., into mode and speed, controls robot ambulation according to selected row；
Whether step 6. detection mobile robot reaches final goal point, if not, the cycle of return to step 2 executes；If it is
Terminate traveling process.
2. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 1, feature
It is, the step 2 includes following sub-step：
Step 21. obtains laser radar data, and using laser radar placement position as coordinate origin, environmental data is point cluster data
{(Li, θi) | i=1,2,3...., n }；
Step 22. pre-processes laser radar point cluster data；
Step 23. clusters laser radar data using split-merge algorithms, and least square method is used in combination to complete local ring
Border models.
3. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 2, feature
It is, the step 3 includes following sub-step：
Step 31：The speed of each wheel is obtained, and robot is obtained according to the kinematics model of mobile mechanism and advances, translate and revolves
Rotary speed, kinematics model are as follows：
In formula：vxFor Robot X-axis speed；vyFor Robot Y-axis speed；W is robot rotary speed, counterclockwise
For just；l1, l2Respectively robot vertical direction wheel spacing and lateral wheel spacing；w1, w2, w3, w4For four wheels of robot
The speed of son；
Step 32：The speed of robot is integrated, robot current location moment position (x ', y ', φ ') is obtained；
Step 33：According to the local environment model that step 2 is established, the localized target point within the scope of present laser radar range finding is obtained
(X ', Y '),
In formula：xiIndicate the abscissa of all points in the robot left side, xiIndicate the cross of all points on the right of robot
Coordinate, yiIndicate the vertical mark of all points in the robot left side, yjIndicate the ordinate of all points on the right of robot.
4. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 3, feature
It is, the step 4 includes following sub-step：
Step 41. by robot car body be divided into it is left front, right before, it is left back, right after 4 parts, using electrostatic field potential field model, respectively into
Row Artificial Potential Field models, and formula is as follows：
In formula：ε, δ are direct proportion gain coefficient, riIt is divided into corresponding 4 particles behind 4 parts, L for robot car bodyp(ri) be
Localized target point P to point riEuclidean distance, LriFor barrier to point riThe shortest distance, L0For having for barrier repulsion potential field
Imitate range, Uatt(ri) it is the point-to-point r of localized targetiAttraction potential energy, Urep(ri) be barrier to point riRepulsion potential energy；
Step 42：The gradient for seeking established Artificial Potential Field Model obtains the attraction of localized target point, the repulsion of barrier
Power, and further obtain 4 points respectively suffered resultant force, formula are as follows：
Fatt(ri)=- grad [Uatt(ri)]=ε Lp(ri)
Fsum(ri)=Fatt(ri)+Frep(ri)
In formula：Fatt(ri) it is point riBy the attraction of localized target point, Frep(ri) it is point riBy the repulsive force of barrier,
Fsum(ri) it is point riSuffered resultant force, grad [] are potential field gradient；
Step 43：Fuzzy rule is formulated according to quadrant residing for resultant force vector suffered by resultant force suffered by each section and each section, is obscured
Rule list is as follows：
Wherein：r1, r2, r3, r4Correspond to respectively robot segmentation it is left front, right before, left back, right-rearward portion；
Step 44：Consider the deflection angle quantization gait of march v of the mould and force vector of resultant force suffered by each sectionx, vy, w；Formula
It is as follows：
For traveling mode one：
For traveling mode two：
For traveling mode three：
In formula：
For r1, r2, r3, r4In resultant force suffered by four parts, force vector mould the maximum, α, beta, gamma is direct proportion gain coefficient.
5. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 4, feature
It is, in the step 5, passes through following model cootrol robot ambulation：
6. a kind of Artificial Potential Field barrier-avoiding method suitable for omnidirectional's wheel mobile robot according to claim 5, feature
It is, in the step S6, judges that the method whether robot reaches final goal is：
(reach | do not reach)
In formula, (X, Y) is final goal point coordinates, and (x, y) is current position coordinates, DarrTo reach threshold value.
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