CN109164812A - Mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known - Google Patents

Mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known Download PDF

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CN109164812A
CN109164812A CN201811235990.1A CN201811235990A CN109164812A CN 109164812 A CN109164812 A CN 109164812A CN 201811235990 A CN201811235990 A CN 201811235990A CN 109164812 A CN109164812 A CN 109164812A
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robot
target
environment
selection
barrier
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CN109164812B (en
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张葛祥
黄振
王学渊
荣海娜
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Southwest Jiaotong University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • 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
    • G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • 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
    • G05D1/0212—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
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • 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
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle

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  • Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
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  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Electromagnetism (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
  • Feedback Control In General (AREA)

Abstract

Be fusion enzyme numerical value film control method the invention discloses mobile robot multirow under a kind of circumstances not known, calculate the linear distance and angle of target and robot, judge environment locating for robot, judge linear distance between robot and target whether be history minimum value, judge target and barrier or wall surface whether in robot the same side, the more action selections of progress, execute the behavior of selection and judge whether mobile robot reaches target.Enzyme numerical value membranous system and multirow are blending algorithm combination by the present invention, robot and target spacing are introduced from judgement and target, barrier or wall surface whether in the judgement of robot the same side, the Deadlock of autonomous under mobile robot circumstances not known is solved the problems, such as to a certain extent and goes the long way round.A variety of behavior controllers are merged using enzyme numerical value film controller, robot is made to adapt to complex environment.

Description

Mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known
Technical field
The present invention relates to Study of Intelligent Robot Control technical field, mobile robot multirow is under specifically a kind of circumstances not known Merge enzyme numerical value film control method.
Background technique
It is minimus branch in Natural computation that film, which calculates (or membranous system), is a kind of function and structure from cell, device The computation model taken out in the information processing cooperation mode of cell masses such as official and tissue, has concurrency, uncertainty, distribution The good characteristics such as formula.Research shows that: theoretically film computation model has the computing capability same with Turing machine, or even also surmounts The possibility of Turing machine limitation.Enzyme numerical value membranous system is one of membranous system, has distribution, concurrency, easy programming, module The good characteristic of change is suitble to robot control.
Summary of the invention
It is fusion enzyme numerical value film control method the object of the present invention is to provide mobile robot multirow under a kind of circumstances not known. Mobile robot obtains environmental information using sensor, classifies to varying environment, according to the difference, target and machine of environment The distance and angle in the human world, select from a variety of behaviors and execute one kind, until reaching target point.
Realize that the technical solution of the object of the invention is as follows:
Mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known, which is characterized in that including
Step 1: calculating the angle of the linear distance CurDist and target of target and robot relative to robot forward direction Spend Angle；
Step 2: the information obtained according to robot sensor mounted judges environment locating for robot, including a left side Wall, You Qiang, corridor, left corner, right corner, front wall, upper left side, upper right side, two sides, dead angle and clear, are used respectively CI=1,2 ..., 11=0 indicates that wherein i=1,2 ..., 11 respectively corresponds above-mentioned 11 kinds of environment；Locating environment is divided into 4 classes: wall Noodles type Ewa, correspond to the environment of Zuo Qiang, You Qiang, corridor, left corner and right corner；Obstacle identity Eob, corresponding front wall, upper left The environment of side and upper right side；Dead zone type Ede, the environment of corresponding two sides and dead angle；Clear type Eno, corresponding clear Environment；
Step 3: judge whether the linear distance CurDist between robot and target is history minimum M inDist: when It is history minimum value when MinDist > CurDist, is indicated with variable IfMin=1, and enable MinDist=CurDist；Otherwise, IfMin=0；Step 4: judge target and barrier or wall surface whether in robot the same side:
Judge that target on the left side of robot or right side, works as the target of Angle > 0 on the robot right side according to angle A ngle Side, when the target of Angle < 0 is on the left of robot；
Such as C1=0 or C4=0 or C7=0, then disturbance in judgement object or metope are located on the left of robot, with variable IfLeft=1 It indicates；Such as C2=0 or C5=0 or C8=0, then disturbance in judgement object or metope are located on the right side of robot, with variable IfLeft=0 table Show；
Work as Angle > 0, when IfLeft=1, target and barrier or wall surface be not in robot the same side, with variable IfSame =0 indicates；
Work as Angle > 0, when IfLeft=0, target and barrier or wall surface are in robot the same side, IfSame=1；When When Angle < 0, IfLeft=1, IfSame=1；When Angle < 0, IfLeft=0, IfSame=0；
Step 5: after carrying out more action selections, exports behavior variable and give execution system:
When robot is in CiWhen=0, i=9,10 environment, it is judged as dead zone type, selects
When robot is in CiWhen=0, i=11 environment, it is judged as accessible type: if IfMin=1 selects Comgr=1, If IfMin=0 is selected
When robot is in CiWhen=0, i=6,7,8 environment, it is judged as obstacle identity:
If IfMin=0 selects corresponding avoid-obstacle behavior: i=6 selectionI=7 selectionI=8 choosing It selects
If IfMin=1, target and barrier are further judged whether in robot the same side, when IfSame=1 selects phase The avoid-obstacle behavior answered: i=6 selectionI=7 selectionI=8 selectionWhen IfSame=0 is selected Select Comgr=1；
When robot is in CiWhen=0, i=1,2,3,4,5 environment, it is judged as wall surface type:
If IfMin=0 is selected accordingly with wall behavior: the selection of i=1 or 4The selection of i=2 or 5i =3 selections
If IfMin=1, further judge that target and wall surface whether in robot the same side, work as IfSame=1, select phase Answer with wall behavior: i=1 or 4 selectionThe selection of i=2 or 5I=3 selectionWork as IfSame =0 selection Comgr=1；
Above-mentioned behavior variable is respectively as follows: front obstacle avoidanceLeft barrier avoidanceRight obstacle Object avoidanceLeft side wall surface is with wallRight side wall surface is with wallPassage lanesTend to target Comgr、 Pivot turn ComdeAnd rotation
Step 6: the system that executes executes the behavior that step 5 exports；
Step 7: judging whether mobile robot reaches target, that is, judge whether CurDist is equal to 0: indicating machine equal to 0 Device people reaches target, then finishing control；Do not continue for 0 return step 1.
Further, the information obtained in the step 2 according to robot sensor mounted, judges locating for robot Environment method are as follows: the information that the sensor obtains is 8 distance d on robot peripheryx, x=1,2 ... 8；Wherein d1、d2 For the distance that the sensor of robot forward right side obtains, d3For the distance that the sensor on the right side of robot obtains, d4For the robot right side The distance that the sensor of rear side obtains, d5For the distance that the sensor of robot left rear side obtains, d6For the sensing on the left of robot The distance that device obtains, d7、d8For the distance obtained positioned at the sensor of robot front left side；Work as dx< t, t are distance threshold, then pass Sensor detects barrier, and by corresponding distance dxBinarization, 1 representative detect barrier, and obstacle is not detected in 0 representative Object；
Later according to upper table determine robot locating for environment.
The present invention provides a kind of more action amalgamation enzymes for robot control field, membranous system control field under circumstances not known Enzyme numerical value membranous system and multirow are blending algorithm combination, introduce robot and target spacing from judgement by numerical value film control method And whether target, barrier (or wall surface) to a certain extent solve mobile robot unknown in the judgement of robot the same side The Deadlock of autonomous and problem of going the long way round under environment.A variety of behavior controllers are merged using enzyme numerical value film controller, make machine Device people adapts to complex environment.
Detailed description of the invention
Fig. 1 is more action amalgamation flow charts；
Fig. 2 is a kind of ten robot environment's ideographs；
Fig. 3 is robot distance sensor pattern；
Fig. 4 is more action amalgamation enzyme numerical value membrane structure figures of the invention；
Fig. 5 is the comparison present invention and experimental result picture of the fuzzy logic control under G type and Cyclotron obstacle environment.
Specific embodiment
Specific implementation of the invention is described further with reference to the accompanying drawing.
More action amalgamation enzyme numerical value film control flow chart such as Fig. 1.
The particularly relevant technology that the present invention uses is as follows:
1) mobile robot is placed in circumstances not known using circumstances not known and robot target as input, gives robot Target point (x to be achievedg,yg).According to range formulaCalculate target and shifting The distance CurDist of mobile robot and angle of the target relative to robot forward direction is calculated according to angle calculation formula Angle (taking is positive direction on the right side of robot forward direction).
2) control of mobile robot
A) acquisition and determination of mobile robot local environment
There are many positional relationships relative to robot for barrier in environment, in order to which mobile robot copes with complicated ring Environmental form locating for mobile robot is divided into (following Fig. 2): Zuo Qiang, You Qiang, corridor, left corner, You Qiang by border, the present invention Angle, front wall, upper left side, upper right side, two sides, dead angle, clear.Use CI=1 ..., 11Indicate (CI=1 ..., 11=0 indicate in pair Answer environmental pattern: Zuo Qiang, You Qiang, corridor, left corner, right corner, front wall, upper left side, upper right side, two sides, dead angle, accessible Object).
The information that mobile robot is obtained according to sensor mounted judges environment locating for robot.With moving machine (such as Fig. 3) is specifically described for device people carries 8 range sensors, and 8 sensors are with annular spread in mobile robot On.8 sensors can obtain 8 range information (d on robot periphery1、d2…d8), (wherein d1、d2For positioned at the robot right side The range information that the sensor of front side obtains, d3For the range information that the sensor on the right side of robot obtains, d4Behind the robot right side The range information that the sensor of side obtains, d5For the range information that the sensor of robot left rear side obtains, d6For on the left of robot Sensor obtain range information, d7、d8For the range information obtained positioned at the sensor of robot front left side).Given threshold T works as dx< t (x=1,2 ... 8) when, it is believed that sensor detects barrier, and by corresponding distance value dtBinarization, 1 represents Detect barrier, 0 representative is not detected.It is so treated, the binary system sensing of current robot local environment can be obtained Device distance value.A kind of a kind of ten corresponding ten binary sensor distance values (such as table 1) of environment.By current binary sensor away from Binary sensor distance value corresponding with a kind of ten environmental forms from value compares, and judges current local environment, and It exports to more action amalgamation enzyme numerical value membranous systems.The environment of input is divided into 4 major class by enzyme numerical value membranous system: metope type is (left Wall, You Qiang, corridor, left corner, right corner environment correspond to such), (front wall, upper left side, upper right side environment are corresponding for obstacle identity Such), dead zone type (two sides, dead angle environment correspond to such), clear type (clear environment corresponds to such).Respectively With variable Ewa、Eob、Ede、EnoIt indicates.
1. environmental form of table and binary sensor value mapping table
B) judge whether the distance between robot and target are history minimum value
History minimum value between robot and target saves (being initialized with CurDist) with variable MinDist, passes through The comparison of CurDist and MinDist judges whether the distance between robot and target CurDist are minimum value.MinDist> When CurDist, it is history minimum value (being indicated with variable IfMin=1), and by MinDist=CurDist.
C) judge target, barrier (or wall surface) whether in robot the same side
The angle A ngle of input can judge target on the left side of robot or right side.Angle > 0, target is in machine On the right side of people；Angle < 0, target is on the left of robot.The position of barrier (or wall surface) can pass through the environment C of inputI=1 ..., 11 It determines.C7=0 indicates upper left side environment, i.e., disturbance in judgement level is on the left of robot (being indicated with variable IfLeft=1)；C8=0 Indicate that upper right side environment, i.e. barrier are located on the right side of robot (being indicated with variable IfLeft=0).C1=0 indicates left wall environment Or C4=0 indicates left corner, judges that metope is located on the left of robot (being indicated with variable IfLeft=1)；C2=0 indicate right wall or C5=0 indicates right corner, and disturbance in judgement level is on the right side of robot (being indicated with variable IfLeft=0).
According to above-mentioned judgement, that is, it can determine target, barrier (or wall surface) whether in robot the same side.Work as Angle > 0, When IfLeft=1, target, barrier (or wall surface) (are not indicated) in robot the same side with variable IfSame=0；Angle > 0, When IfLeft=0, IfSame=1；When Angle < 0, IfLeft=1, IfSame=1；When Angle < 0, IfLeft=0, IfSame=0.It is summarized as following formula
D) more action selections
Invention defines five kinds of behaviors, avoidance (front, left, right barrier avoidance), with wall (left side, right side wall Face is with wall and passage lanes), tend to target, pivot turn, rotation behavior.Avoid-obstacle behavior variable is used respectivelyWith wall behavior variableTend to goal behavior variable Comgr, pivot turn behavior variable Comde, rotation behavior variableIt indicates.
When meeting specific condition, corresponding behavior (i.e. corresponding behavior variate-value assignment 1) is selected, and export behavior Variable.
When robot is in CiWhen=0 (i=9,10) environment, environmental form is judged for dead zone type, robot is because advancing Direction is obstructed, and pivot turn behavior is selected
When robot is in C11When=0 environment, it is judged as accessible type.If IfMin=1 at this time, selection tends to target Behavior Comgr=1；If IfMin=0, rotation behavior is selected
When robot is in CiWhen=0 (i=6,7,8) environment, it is judged as obstacle identity.If IfMin=0 at this time, choosing Select corresponding avoid-obstacle behaviorIf IfMin=1 judges mesh Whether mark, barrier work as IfSame=1, select corresponding avoid-obstacle behavior in robot the same sideWork as IfSame=0, selection tends to goal behavior Comgr =1.
When robot is in CiWhen=0 (i=1,2..5) environment, it is judged as wall surface type.If IfMin=0 at this time, selection Accordingly with wall behaviorIf IfMin=1 sentences Whether disconnected target, wall surface are worked as IfSame=1, are selected accordingly with wall behavior in robot the same sideWork as IfSame=0, selection tends to target line For Comgr=1.
More action amalgamation enzyme numerical value membranous systems export behavior variable and give execution system.
3) corresponding behavior is executed
Execute the behavior of enzyme numerical value membranous system output.
4) judge whether mobile robot reaches target
Judge whether distance value CurDist is equal to 0.Indicate that mobile robot reaches target equal to 0, then finishing control. Do not continue to obtain ambient condition for 0 mobile robot, determine process performing, until reaching target.
The present invention is emulated in PC machine, CPU 2.8HZ, 4GB RAM, software platform MATLAB2012, Windows7OS and Webots.By taking mobile robot Epuck as an example, Epuck robot has 8 infrared sensors, and two-wheel is poor Dynamic driving.
Referring to attached drawing 4,5, the present invention takes following steps:
Step 1. is using circumstances not known and robot target as input
Mobile robot Epuck is placed in circumstances not known shown in Fig. 5, Epuck is obtained according to distance and angle calculation formula To current Epuck and target distance DcurWith angle A ngle, it is input in the more action amalgamation enzyme numerical value membranous systems of Fig. 4.Angle Angle passes through variables Agr1、Agr2It saves, Agr1=Angle, Agr2=-Angle.
The control of step 2. mobile robot
A) acquisition and determination of mobile robot local environment type
Environmental pattern is divided into 11 kinds: Zuo Qiang, You Qiang, corridor, left corner, right corner, front wall, upper left side, upper right side, two Side, dead angle, clear, use CI=1 ..., 11Indicate (CI=1 ..., 11=0 is respectively at corresponding environmental pattern: Zuo Qiang, You Qiang, walking Corridor, left corner, right corner, front wall, upper left side, upper right side, two sides, dead angle, clear).Epuck passes through 8 infrared sensings 8 range information (sensor values d on device acquisition robot periphery1、d2…d8).8 sensors are with annular spread in mobile machine People is upper (such as Fig. 3), (wherein d1、d2For the range information obtained positioned at the sensor of robot forward right side, d3For on the right side of robot Sensor obtain range information, d4For the range information that the sensor of robot right lateral side obtains, d5For robot left rear side Sensor obtain range information, d6For the range information that the sensor on the left of robot obtains, d7、d8For positioned at robot The range information that the sensor of front left side obtains).Threshold value 70, works as dx> 70 (x=1,2 ... 8) when, it is believed that sensor detects barrier Hinder object, and by dxSet 1, dx< 70, dxIt sets 0 representative and barrier is not detected.(value of Epuck sensor with barrier distance Increase and reduce).8 sensors treated value composition one group of binary sensor value, such as: when accessible be [0 000 000 0], 11 kinds of environment binary system groups (being shown in Table 1) of currently available binary system group and definition are compared, judges current machine Device people's local environment CI=1 ..., 11, and export and give Fig. 4 enzyme numerical value membranous system.The environment of input is divided into 4 by enzyme numerical value membranous system Major class: metope type (Zuo Qiang, You Qiang, corridor, left corner, right corner environment correspond to such), obstacle identity (front wall, upper left Side, upper right side environment correspond to such), dead zone type (two sides, dead angle environment correspond to such), clear type (clear Environment corresponds to such).Variable E is used respectivelywa、Eob、Ede、EnoIt indicates.This step is by Fig. 4 film JudgeEnvironmentModel It completes, in the sub- film, 11 rule Pr altogetherI=1,2..11,Case.Regular 1-5 (i.e. PrI=1,2..5, Case) it and will be locating for robot Environment is divided into metope type (Ewa=1), rule 6,7,8 is divided into obstacle identity (Eob=1), rule 9,10 is divided into dead (dead zone type directly corresponds to pivot turn behavior to area's type, therefore realizes at this and directly distribute Comde=1), rule 11 is divided into nothing Obstacle identity (Eno=1).
This sentences the execution that rule 9 illustrates rule, and rule executive mode is all the same later.Rule 9 is Pr9,Case:C9+2 (Ec→)1|Comde+1|ET。Pr9, Case is regular name, is separated with colon and expression formula, C9+ 2 be to be worth generation rule, 1 | Comde+1|ETIt is enzyme variable E in bracket to be worth allocation rulec(when enzyme variable is greater than a certain variable in value generation rule, it should Rule could activate execution；E is needed hereinc> C9).Work as Ec> C9When, rule 9 activates, and is worth generation rule generation value C9+ 2, value generates It, can be by clear 0 (the i.e. C of variable in generation rule after rule executes9Can by it is clear 0), the value of generation is distributed by allocation rule, C9+ 2 points It is 2 parts, portion gives variable Comde, portion is to ET, i.e. Comde=(C9+ 2)/2, ET=(C9+2)/2。
B) judge whether the distance between robot and target are history minimum value
This step is completed in Fig. 4 film JudgeDistanceIfMinimal.Rule 1 judges whether it is history minimum History minimum value is exported and is saved by value, rule 2.Rule 1,2 executes, Dmin=1 is expressed as history minimum value, Output=Dcur。
C) judge target, barrier (or wall surface) whether in robot the same side
Judge target, barrier whether in robot the same side by being advised in Fig. 4 film JudgeRobotStateObstacle Then 2-7,10,11 is completed.
Rule 4,5 judges the position of target and robot.Agr1When (i.e. Angle < 0) < 0, enzyme variable Ea[0]>Agr1, swash Rule 4 living,Indicate target on the left of robot.Agr2When (i.e. Angle > 0) < 0, enzyme variable Ea[0]>Agr2, activation Rule 5,Indicate target on the right side of robot.
Rule P r2、3,obstaclenFor the positional relationship of disturbance in judgement object and the machine human world.As environmental pattern C7=0 When (upper left side), barrier is located on the left of robot, activates rule P r2,obstaclen: variable Oleft[- 1]=1, Oright[-1] =0；Environmental pattern C8When=0 (upper right side), barrier is located on the right side of robot, activates rule P r3,obstaclen: variable Oright[- 1]=1, Oleft[- 1]=0.
Rule P r6.7.10.11,obstaclenPass throughOleft、OrightValue, obtain barrier, target and machine The relationship in the human world.Work as Oleft=1 (barrier is on the robot left side),When (target is on the right of robot), barrier is indicated Target activates rule P r on the right side on the left of robot6,obstaclen: enzyme variable EOGlr=2；Work as Oright=1,When, table Show that barrier, on a left side, activates rule P r in right target7,obstaclen: enzyme variable EOGrl=2；Work as Oleft=1,When, table Show that barrier, target all on a left side, activate rule P r10,obstaclen: enzyme variable Eogleft=2；Work as Oright=1,When, Indicate that barrier, target all on the right side, activate rule P r11,obstaclen: enzyme variable Eogright=2.
Judge whether target, wall surface are complete by rule 2-7,10,11 in JudgeRobotStateWall in robot the same side At.Principle is identical, and so it will not be repeated.
D) selection that multirow is
Invention defines 5 kinds of behaviors, avoidance (front, left, right barrier avoidance), with wall (left side, right side wall surface With wall and passage lanes), tend to target, pivot turn, rotation behavior.Avoid-obstacle behavior variable is used respectively With wall behavior variableTend to goal behavior variable Comgr, original place U-turn behavior variable Comde, rotation behavior variableIt indicates (such as Fig. 4).Behavior variable is equal to 1, indicates this kind of behavior of selection Variable.
When robot is in CiWhen=0 (i=9,10) environment, environmental form is judged for dead zone type, robot is because advancing Direction is obstructed, and pivot turn behavior is selectedThis part is by rule 9 in Fig. 4 film JudgeEnvironmentModel Or 10 complete.Variable ET=1, the evolutionary computation of membranous system is terminated, is exported
When robot is in C11When=0 environment, it is judged as accessible type (Eno=1).If D at this timemin=1, selection becomes To goal behavior Comgr=1；If Dmin=0, select rotation behaviorThis part is by Fig. 4 film SelectGoalReachingCase is completed.If Dmin=1, rule 1 can not execute, and then rule 2 can not execute, and rule 3 is without enzyme Variable event evolves can all execute every time,And then rule 4 executes, Comgr=1, ET=1 indicates to terminate the evolution of membranous system It calculates.If Dmin=0, rule 1,2 executes,ET=1.
When robot is in CiWhen=0 (i=6,7,8) environment, it is judged as obstacle identity (Eob=1).Fig. 4 film Which kind of behavior SelectObstacleAvoidanceCase and JudgeRobotStateObstacle judgement selects.If Dmin= Rule 1 executes in 0, SelectObstacleAvoidanceCaseAnd then rule 2 or 3 or 4 executes, selection is kept away accordingly Barrier behaviorAfter rule 5 executesSo that Rule can not execute in JudgeRobotStateObstacle.If DminIn=1, SelectObstacleAvoidanceCase Rule 1 can not execute, and then rule 2,3,4 can not execute, after rule 5 executesIf target, barrier are in machine People the same side (Eogleft=2 or Eogright=2), rule 12 or 13 activates,OrIf target, obstacle Object is not in robot the same side (EOGlr=2 or EOGrl=2), rule 8 or 9 activates,ET=1.
When robot is in CiWhen=0 (i=1,2..5) environment, judge environmental form for wall surface type (Ewa=1).Fig. 4 Which kind of behavior sub- film SelectWallFollowCase and JudgeRobotStateWall judgement selects.Principle with avoidance situation, So it will not be repeated.
Step 3. executes corresponding behavior
Execute the behavior of membranous system output.
Step 4. judges whether mobile robot reaches target
Judge distance value DcurWhether 0 is equal to.Indicate that mobile robot reaches target equal to 0, then finishing control.It is not 0 Then mobile robot continues to obtain ambient condition, determines process performing, until reaching target.
It can be seen that from the experimental result of Fig. 5 compared to fuzzy logic control, multirow is that nexus controls (MBCMC) walking Path is shorter (Fig. 5 is left), and can get rid of the dead zone that fuzzy logic control can not be got rid of (Fig. 5 is right).

Claims (2)

1. mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known, which is characterized in that including
Step 1: calculating the angle of the linear distance CurDist and target of target and robot relative to robot forward direction Angle；
Step 2: the information obtained according to robot sensor mounted judges environment locating for robot, including Zuo Qiang, the right side Wall, corridor, left corner, right corner, front wall, upper left side, upper right side, two sides, dead angle and clear, use C respectivelyI=1,2 ..., 11 =0 indicates that wherein i=1,2 ..., 11 respectively corresponds above-mentioned 11 kinds of environment；Locating environment is divided into 4 classes: wall surface type Ewa, Correspond to the environment of Zuo Qiang, You Qiang, corridor, left corner and right corner；Obstacle identity Eob, corresponding front wall, upper left side and upper right side Environment；Dead zone type Ede, the environment of corresponding two sides and dead angle；Clear type Eno, the environment of corresponding clear；
Step 3: judge whether the linear distance CurDist between robot and target is history minimum M inDist: when It is history minimum value when MinDist > CurDist, is indicated with variable IfMin=1, and enable MinDist=CurDist；Otherwise, IfMin=0；
Step 4: judge target and barrier or wall surface whether in robot the same side:
Judge that target on the left side of robot or right side, works as the target of Angle > 0 on the right side of robot according to angle A ngle, when The target of Angle < 0 is on the left of robot；
Such as C1=0 or C4=0 or C7=0, then disturbance in judgement object or metope are located on the left of robot, with variable IfLeft=1 table Show；
Such as C2=0 or C5=0 or C8=0, then disturbance in judgement object or metope are located on the right side of robot, with variable IfLeft=0 table Show；
Work as Angle > 0, when IfLeft=1, target and barrier or wall surface be not in robot the same side, with variable IfSame=0 It indicates；Work as Angle > 0, when IfLeft=0, target and barrier or wall surface are in robot the same side, IfSame=1；Work as Angle When < 0, IfLeft=1, IfSame=1；When Angle < 0, IfLeft=0, IfSame=0；
Step 5: after carrying out more action selections, exports behavior variable and give execution system:
When robot is in CiWhen=0, i=9,10 environment, it is judged as dead zone type, selects
When robot is in CiWhen=0, i=11 environment, it is judged as accessible type: if IfMin=1 selects Comgr=1, if IfMin=0 selection
When robot is in CiWhen=0, i=6,7,8 environment, it is judged as obstacle identity:
If IfMin=0 selects corresponding avoid-obstacle behavior: i=6 selectionI=7 selectionI=8 selection
If IfMin=1, target and barrier are further judged whether in robot the same side, when IfSame=1 selects phase
The avoid-obstacle behavior answered: i=6 selectionI=7 selectionI=8 selectionWork as IfSame=0 Select Comgr=1；
When robot is in CiWhen=0, i=1,2,3,4,5 environment, it is judged as wall surface type:
If IfMin=0 is selected accordingly with wall behavior: the selection of i=1 or 4The selection of i=2 or 5 I=3 choosing It selects
If IfMin=1, further judge that target and wall surface whether in robot the same side, work as IfSame=1, selection is corresponding With wall behavior: the selection of i=1 or 4The selection of i=2 or 5I=3 selection=1；Work as IfSame=0 Select Comgr=1；
Above-mentioned behavior variable is respectively as follows: front obstacle avoidanceLeft barrier avoidanceRight barrier avoidanceLeft side wall surface is with wallRight side wall surface is with wallPassage lanesTend to target Comgr, original place tune Head ComdeAnd rotation
Step 6: the system that executes executes the behavior that step 5 exports；
Step 7: judging whether mobile robot reaches target, that is, judge whether CurDist is equal to 0: indicating robot equal to 0 Target is reached, then finishing control；Do not continue for 0 return step 1.
2. mobile robot multirow is fusion enzyme numerical value film control method under a kind of circumstances not known as described in claim 1, It is characterized in that, the information obtained in the step 2 according to robot sensor mounted judges environment locating for robot Method are as follows: the information that the sensor obtains is 8 distance d on robot peripheryx, x=1,2 ... 8；Wherein d1、d2For robot The distance that the sensor of forward right side obtains, d3For the distance that the sensor on the right side of robot obtains, d4For the biography of robot right lateral side The distance that sensor obtains, d5For the distance that the sensor of robot left rear side obtains, d6It is obtained for the sensor on the left of robot Distance, d7、d8For the distance obtained positioned at the sensor of robot front left side；Work as dx< t, t are distance threshold, then sensor detects To barrier, and by corresponding distance dxBinarization, 1 representative detect barrier, and barrier is not detected in 0 representative；
Later according to upper table determine robot locating for environment.
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