CN110160527A - A kind of Mobile Robotics Navigation method and apparatus - Google Patents
A kind of Mobile Robotics Navigation method and apparatus Download PDFInfo
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- CN110160527A CN110160527A CN201910370245.6A CN201910370245A CN110160527A CN 110160527 A CN110160527 A CN 110160527A CN 201910370245 A CN201910370245 A CN 201910370245A CN 110160527 A CN110160527 A CN 110160527A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C17/00—Compasses; Devices for ascertaining true or magnetic north for navigation or surveying purposes
- G01C17/02—Magnetic compasses
- G01C17/28—Electromagnetic compasses
- G01C17/32—Electron compasses
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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Abstract
The invention discloses a kind of Mobile Robotics Navigation methods, comprising: initialization, time are estimated from increasing, reading sensing data, pose and slide coefficient and calculates left and right wheels expectation rotation speed.A kind of Mobile Robotics Navigation device, including positioning system, electronic compass, odometer and computer are also disclosed, positioning system, electronic compass, odometer telecommunications connect computer, and computer is for executing Mobile Robotics Navigation method disclosed by the invention.Compared with existing disclosed technical solution, the present invention considers the slip properties of Different Ground type, the pose and slide coefficient of robot can be estimated simultaneously, and then skidding effect can be considered in navigation algorithm kind, run duration and energy consumption are comprehensively considered during path optimizing, promote the runing time of battery supply apparatus people.
Description
Technical field
The present invention relates to robotic technology fields, more particularly to a kind of Mobile Robotics Navigation method and apparatus.
Background technique
In recent years, autonomous robot has played important function in fields such as space exploration, military mission, agriculturals.In future,
It is intended that these robots can execute various tasks in unstructured and dynamic outdoor environment, and increase independence.
However, the energy in battery and/or fuel that robot is carried by is limited, which has limited its service lifes.In order to
It allows the robot to execute wider task in the case where not charging or refueling, energy conservation is very important.Therefore, pass through
Good navigation mechanism can reduce the consumption of the energy to the full extent.
" Sun Shiying, Zhao Xiaoguang, borderland, Tan Min are intended to the service robot navigation of detection based on interaction between pedestrian to document
[J] Central China University of Science and Technology journal (natural science edition), 2017,45 (10): 80-84. " is in people and robot coexisted environment
Robot navigation's problem, propose it is a kind of based between pedestrian interaction be intended to detection service robot air navigation aid.Patent
CN201610203026.5 provides the method and navigating robot of a kind of robot navigation, this method comprises: when detecting machine
When device people is mobile, the collected image is handled, is obtained in the image in the image of preset position by real-time capture setting
Path profile, the path profile in the image obtained after processing is compared with preset path map, obtains the robot
Instantaneous position generates the robot and is moved to the mesh according to the instantaneous position, the destination of the robot and the path map
Ground movement routine, it is mobile by the movement routine of generation to control the robot.The present invention passes through image processing techniques, control
Robot is mobile by preset movement routine, and the navigation of robot is made to become more accurate.Patent CN201510891364.8 is mentioned
For a kind of robot navigation method and system, wherein method includes: by being taken the photograph according to what is be arranged in navigation instruction control robot
As head obtains the identification point around robot；Preset map is inquired according to the identification point of surrounding, determines the current location of robot,
Wherein, preset map includes: the identification point on each navigation path and each navigation path；According to the current location of robot
Preset map is inquired with target position, is obtained and the matched navigation path in current location and target position；According to current location and
Navigation path determines the direction of travel and travelling route of robot, so that robot can be according to direction of travel and traveling road
Line is moved to target position, realizes navigation, avoids the setting of the access point apparatus of higher cost, and change to the construction in place
It makes, saves cost, reduce the construction requirement to place applied by it.
Traditional navigation means seldom consider influence of the Different Ground type to robot energy consumption, most for realizing route
It is short to plan a biggish road of resistance sometimes, improve the energy consumption of robot.
Summary of the invention
To solve the above problems, the invention discloses a kind of Mobile Robotics Navigation methods, specifically includes the following steps:
S101: initialization enables time t=1, sets sampling time interval T, robot width B, determines the state of t moment
Optimal estimation valueWhereinRespectively indicate the robot of t moment
The optimal estimation of the optimal estimation value, the optimal estimation value of north orientation coordinate, the optimal estimation value, left slip ratio in direction of east orientation coordinate
Value, the optimal estimation value of right slip ratio and the sideslip factor optimal estimation value, set process noise and observation noise variance Q and
R sets the state optimization evaluated error covariance of t moment For 6 dimension square matrixes；Enable the best navigation spots of t momentFor machine
People's initial coordinate；
S102: enable t from increasing 1；
S103: reading the robot position data of t moment from positioning system, and the robot of t moment is read from electronic compass
Bearing data obtains the observation vector of t momentWhereinIndicate the robot east orientation coordinate inspection of t moment
Measured value,Indicate the robot north orientation coordinate measurement value of t moment,Indicate the robot angle detecting value of t moment；From mileage
Meter reads the rotary speed data of the robot left and right wheels of t momentWhereinIndicate the rotation of robot revolver
Speed detection value,Indicate robot right wheel rotation speed detected value；
S104: y is utilizedtAnd wtEstimate the pose of the robot of t momentWith slide coefficientSuch as
Under:
S1041: status predication estimation obtains the status predication estimated value of t momentIts
InRespectively indicate the prediction of the predictive estimation value, north orientation coordinate of the east orientation coordinate of the robot of t moment
Estimated value, the predictive estimation value in direction, the predictive estimation value of left slip ratio, the predictive estimation value of right slip ratio, the sideslip factor
Predictive estimation value, can be by state transition equationIt releases, state transition equation is specific as follows:
And status predication evaluated error covariance is calculated, as follows:Wherein, F is
Relative toJacobian matrix,For the state optimization evaluated error covariance of t moment,For 6 dimension square matrixes, Q was indicated
The variance of journey noise, the transposition of F ' expression F；
S1042: calculating observation newly ceasesWith new breath covarianceWherein
Calculate new breath covariance estimated value
Wherein, NwForThe sliding window width of estimation calculates decay factor γ, as follows:
Wherein, α is a real number greater than 1, and R indicates the variance of observation noise, the transposition of H ' expression H；
S1043: adjustmentIt enablesAnd recalculate new breath covariance
S1044: state optimization estimation is carried out, the state optimization estimated value of t moment is obtainedIt is as follows: Wherein,And calculate state optimization evaluated error covarianceWherein I6Table
Show 6 dimension unit matrix；
S105: according to step S104 obtain t moment robot pose and slide coefficient, calculate the t+1 moment a left side,
Right wheel it is expected rotation speedWithIt is as follows:
Firstly, the set of the possible rotation speed of the left and right wheel for generating one group of t+1 moment at random WithEach set has L element, whereinIndicate the possible rotation speed of the revolver at the t+1 moment generated at random, It indicates
The possible rotation speed of the right wheel at the t+1 moment generated at random, then willWithIn speed pairIt is brought intoF is state transition equation, obtains corresponding position
Predicted valueRemember coordinate pointsCalculate each Ot+1,iCorresponding mesh
Scalar functions Ji, objective function Ji=Ji,1+Ji,2
Wherein, k1、k2Respectively rotational resistance coefficient of energy dissipation and advance resistance coefficient of energy dissipation,
Wherein, OTIndicate the coordinate of terminal,With ε (Ot+1,i,OT) respectively indicate Ot+1,iWithIt is European away from
From, Ot+1,iWith OTEuclidean distance；Find out JiTake O when minimumt+1,i, the as best navigation spots at t+1 moment
Wherein, the set for the possible rotation speed of the random left and right wheel for generating one group of t+1 moment that the step S105 is related to
Method it is as follows:
S1051: in t=1 to t=NuMoment settingWithWherein vmIt indicates
The wheel rotation speed upper limit,Indicate that 0 arrives vmBe uniformly distributed, NuIt is greater than 1 positive integer for one；In t > NuMoment
It calculatesWhereinWithFor sequenceIt is equal
Value and variance,WithFor sequenceMean value and variance,Indicate t-NuAll revolvers of+1 moment to t moment it is expected rotation speed,Indicate t-NuAll right wheels of+1 moment to t moment it is expected rotation speed, settingWithWhereinIndicate Gaussian Profile；
S1052: the distribution set according to step S1051, i.e.,With The set of the random possible rotation speed of the left and right wheel for generating one group of t+1 moment WithWherein each set has L element.
The invention also discloses a kind of Mobile Robotics Navigation devices, which is characterized in that including positioning system, electronics sieve
Disk, odometer and computer, positioning system, electronic compass, odometer telecommunications connect computer；
Positioning system is used to read the robot position data of t moment；
Electronic compass is used to read the robot bearing data of t moment；
Odometer is used to read the rotary speed data of the robot left and right wheels of t moment；
Computer is used for using the method claimed in claims 1-2 to the robot position data, robot side
It is handled to the rotary speed data of data and robot left and right wheels, realizes Mobile Robotics Navigation.
The invention also discloses a kind of computer-readable storage medias, which is characterized in that the computer-readable storage medium
Several Navigators are stored in matter, several Navigators by processor for being called and executing the claim 1-2
Step in the Mobile Robotics Navigation method of any one.
The invention also discloses a kind of difference to turn to wheeled mobile robot, including navigation device, which is characterized in that described
Navigation device is navigation device as claimed in claim 3.
The invention also discloses a kind of caterpillar mobile robots, including navigation device, which is characterized in that the navigation dress
It is set to navigation device as claimed in claim 3.
Compared with existing technology, the present invention considers the slip properties of Different Ground type, can estimate simultaneously
The pose and slide coefficient of robot, and then skidding effect can be considered in navigation algorithm kind, it is comprehensive during path optimizing
It closes and considers run duration and energy consumption, promote the runing time of battery supply apparatus people.
Detailed description of the invention
With reference to the accompanying drawing, specific embodiments of the present invention will be described in detail:
Fig. 1 is a kind of Mobile Robotics Navigation apparatus structure block diagram.
Specific embodiment
In order to further explain feature of the invention, reference should be made to the following detailed description and accompanying drawings of the present invention.Institute
Attached drawing is only for reference and purposes of discussion, is not used to limit protection scope of the present invention.
The invention discloses a kind of Mobile Robotics Navigation methods, specifically includes the following steps:
S101: initialization enables time t=1, sets sampling time interval T, robot width B, determines the state of t moment
Optimal estimation valueWhereinRespectively indicate the robot of t moment
The optimal estimation of the optimal estimation value, the optimal estimation value of north orientation coordinate, the optimal estimation value, left slip ratio in direction of east orientation coordinate
Value, the optimal estimation value of right slip ratio and the sideslip factor optimal estimation value, set process noise and observation noise variance Q and
R sets the state optimization evaluated error covariance of t moment For 6 dimension square matrixes；Enable the best navigation spots of t momentFor machine
People's initial coordinate；
It determinesCan be used following method: east orientation coordinate, north orientation coordinate and the direction of artificial detection robot, and will knot
Fruit assigns respectivelyForIt may be set to 0；According to the parameter of sensor itself or by being exported to it
The statistics of noise can determine Q and R, state optimization evaluated error covarianceIt can be set as a diagonal matrix, diagonal element
Element is all 0.01；
S102: enable t from increasing 1；
S103: reading the robot position data of t moment from positioning system, and the robot of t moment is read from electronic compass
Bearing data obtains the observation vector of t momentWhereinIndicate the robot east orientation coordinate inspection of t moment
Measured value,Indicate the robot north orientation coordinate measurement value of t moment,Indicate the robot angle detecting value of t moment；From mileage
Meter reads the rotary speed data of the robot left and right wheels of t momentWhereinIndicate the rotation of robot revolver
Speed detection value,Indicate robot right wheel rotation speed detected value；
S104: y is utilizedtAnd wtEstimate the pose of the robot of t momentWith slide coefficientSuch as
Under:
S1041: status predication estimation obtains the status predication estimated value of t momentIts
InRespectively indicate the prediction of the predictive estimation value, north orientation coordinate of the east orientation coordinate of the robot of t moment
Estimated value, the predictive estimation value in direction, the predictive estimation value of left slip ratio, the predictive estimation value of right slip ratio, the sideslip factor
Predictive estimation value, can be by state transition equationIt releases, state transition equation is specific as follows:
And status predication evaluated error covariance is calculated, as follows:Wherein, F is
Relative toJacobian matrix,For the state optimization evaluated error covariance of t moment,For 6 dimension square matrixes, Q was indicated
The variance of journey noise, the transposition of F ' expression F；
S1042: calculating observation newly ceasesWith new breath covarianceWherein
Calculate new breath covariance estimated value
Wherein, NwForThe sliding window width of estimation calculates decay factor γ, as follows:
Wherein, α is a real number greater than 1, and R indicates the variance of observation noise, the transposition of H ' expression H；
S1043: adjustmentIt enablesAnd recalculate new breath covariance
S1044: state optimization estimation is carried out, the state optimization estimated value of t moment is obtainedIt is as follows:
Wherein,And calculate state optimization evaluated error covarianceWherein I6Indicate 6 dimensions
Unit matrix；
S105: according to step S104 obtain t moment robot pose and slide coefficient, calculate the t+1 moment a left side,
Right wheel it is expected rotation speedWithIt is as follows:
Firstly, the set of the possible rotation speed of the left and right wheel for generating one group of t+1 moment at random WithEach set has L element, whereinIndicate the possible rotation speed of the revolver at the t+1 moment generated at random, It indicates
The possible rotation speed of the right wheel at the t+1 moment generated at random, then willWithIn speed pairIt is brought intoObtain corresponding position prediction valueWherein f is state transition equation, is usedReplacementInI.e.
It canConcrete form；Remember coordinate pointsCalculate each Ot+1,iCorresponding objective function
Ji, objective function Ji=Ji,1+Ji,2
Wherein, k1、k2Respectively rotational resistance coefficient of energy dissipation and advance resistance coefficient of energy dissipation,
Wherein, OTIndicate the coordinate of terminal,With ε (Ot+1,i,OT) respectively indicate Ot+1,iWithIt is European away from
From, Ot+1,iWith OTEuclidean distance；Find out JiTake O when minimumt+1,i, the as best navigation spots at t+1 moment
Preferably, the collection for the possible rotation speed of the random left and right wheel for generating one group of t+1 moment that the step S105 is related to
The method of conjunction is as follows:
S1051: in t=1 to t=NuMoment settingWithWherein vmIt indicates
The wheel rotation speed upper limit,Indicate that 0 arrives vmBe uniformly distributed, NuIt is greater than 1 positive integer for one；In t > NuMoment
It calculatesWhereinWithFor sequenceIt is equal
Value and variance,WithFor sequenceMean value and variance,Indicate t-NuAll revolvers of+1 moment to t moment it is expected rotation speed,Indicate t-NuAll right wheels of+1 moment to t moment it is expected rotation speed, settingWithWhereinIndicate Gaussian Profile；
S1052: the distribution set according to step S1051, i.e.,With The set of the random possible rotation speed of the left and right wheel for generating one group of t+1 moment WithWherein each set has L element.
The invention also discloses a kind of Mobile Robotics Navigation devices, as shown in Fig. 1, which is characterized in that including positioning
System, electronic compass, odometer and computer, positioning system, electronic compass, odometer telecommunications connect computer；
Positioning system is used to read the robot position data of t moment；
Electronic compass is used to read the robot bearing data of t moment；
Odometer is used to read the rotary speed data of the robot left and right wheels of t moment；
Computer is used for using the method claimed in claims 1-2 to the robot position data, robot side
It is handled to the rotary speed data of data and robot left and right wheels, realizes Mobile Robotics Navigation.
The invention also discloses a kind of computer-readable storage medias, which is characterized in that the computer-readable storage medium
Several Navigators are stored in matter, several Navigators by processor for being called and executing the claim 1-2
Step in the Mobile Robotics Navigation method of any one.
The invention also discloses a kind of difference to turn to wheeled mobile robot, including navigation device, which is characterized in that described
Navigation device is navigation device as claimed in claim 3.
The invention also discloses a kind of caterpillar mobile robots, including navigation device, which is characterized in that the navigation dress
It is set to navigation device as claimed in claim 3.
Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above method embodiment can pass through
The relevant hardware of program instruction is completed, and program above-mentioned can be stored in a computer readable storage medium, the program
When being executed, step including the steps of the foregoing method embodiments is executed；And storage medium above-mentioned includes: ROM, RAM, magnetic disk or light
The various media that can store program code such as disk.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of Mobile Robotics Navigation method, which comprises the following steps:
S101: initialization enables time t=1, sets sampling time interval T, robot width B, determines the state optimization of t moment
Estimated valueWhereinRespectively indicate the east orientation of the robot of t moment
The optimal estimation value of coordinate, the optimal estimation value of north orientation coordinate, the optimal estimation value in direction, the optimal estimation value of left slip ratio,
The optimal estimation value of right slip ratio and the optimal estimation value of the sideslip factor set the variance Q and R of process noise and observation noise,
Set the state optimization evaluated error covariance of t momentFor 6 dimension square matrixes；Enable the best navigation spots of t momentFor machine
People's initial coordinate；
S102: enable t from increasing 1；
S103: reading the robot position data of t moment from positioning system, and the robot direction of t moment is read from electronic compass
Data obtain the observation vector of t momentWhereinIndicate the robot east orientation coordinate measurement value of t moment,Indicate the robot north orientation coordinate measurement value of t moment,Indicate the robot angle detecting value of t moment；It is read from odometer
The rotary speed data of the robot left and right wheels of t momentWhereinIndicate the inspection of robot revolver rotation speed
Measured value,Indicate robot right wheel rotation speed detected value；
S104: y is utilizedtAnd wtEstimate the pose of the robot of t momentWith slide coefficientIt is as follows:
S1041: status predication estimation obtains the status predication estimated value of t momentWhereinThe prediction for respectively indicating the predictive estimation value, north orientation coordinate of the east orientation coordinate of the robot of t moment is estimated
Evaluation, the predictive estimation value in direction, the predictive estimation value of left slip ratio, the predictive estimation value of right slip ratio, the sideslip factor it is pre-
Estimated value is surveyed, it can be by state transition equationIt releases, state transition equation is specific as follows:
And status predication evaluated error covariance is calculated, as follows:Wherein, F isRelative toJacobian matrix,For the state optimization evaluated error covariance of t moment,For 6 dimension square matrixes, Q indicates process noise
Variance, the transposition of F ' expression F；
S1042: calculating observation newly ceasesWith new breath covarianceWherein
Calculate new breath covariance estimated value
Wherein, NwForThe sliding window width of estimation calculates decay factor γ, as follows:
Wherein, α is a real number greater than 1, and R indicates the variance of observation noise, the transposition of H ' expression H；
S1043: adjustmentIt enablesAnd recalculate new breath covariance
S1044: state optimization estimation is carried out, the state optimization estimated value of t moment is obtainedIt is as follows: Its
In,And calculate state optimization evaluated error covarianceWherein I6Indicate that 6 dimensions are single
Position battle array；
S105: according to the pose and slide coefficient of the robot of the step S104 t moment obtained, the left and right wheel at t+1 moment is calculated
It is expected that rotation speedWithIt is as follows:
Firstly, the set of the possible rotation speed of the left and right wheel for generating one group of t+1 moment at random WithEach set has L element, whereinIndicate the possible rotation speed of the revolver at the t+1 moment generated at random, It indicates
The possible rotation speed of the right wheel at the t+1 moment generated at random, then willWithIn speed pairIt is brought intoF is state transition equation, obtains corresponding position
Predicted valueRemember coordinate pointsCalculate each Ot+1,iCorresponding mesh
Scalar functions Ji, objective function Ji=Ji,1+Ji,2
Wherein, k1、k2Respectively rotational resistance coefficient of energy dissipation and advance resistance coefficient of energy dissipation,
Wherein, OTIndicate the coordinate of terminal,With ε (Ot+1,i,OT) respectively indicate Ot+1,iWithEuclidean distance,
Ot+1,iWith OTEuclidean distance；Find out JiTake O when minimumt+1,i, the as best navigation spots at t+1 moment
2. Mobile Robotics Navigation method as described in claim 1, which is characterized in that the random life that the step S105 is related to
Method at the set of the possible rotation speed of the left and right wheel at one group of t+1 moment is as follows:
S1051: in t=1 to t=NuMoment settingWithWherein vmIndicate wheel
The rotation speed upper limit,Indicate that 0 arrives vmBe uniformly distributed, NuIt is greater than 1 positive integer for one；In t > NuMoment calculatesWhereinWithFor sequenceMean value with
Variance,WithFor sequenceMean value and variance,Table
Show t-NuAll revolvers of+1 moment to t moment it is expected rotation speed,Indicate t-Nu+ 1 moment
All right wheels to t moment it is expected rotation speed, settingWithIts
InIndicate Gaussian Profile；
S1052: the distribution set according to step S1051, i.e.,With
The set of the random possible rotation speed of the left and right wheel for generating one group of t+1 moment WithWherein each set has L element.
3. a kind of Mobile Robotics Navigation device, which is characterized in that including positioning system, electronic compass, odometer and computer,
Positioning system, electronic compass, odometer telecommunications connect computer；
Positioning system is used to read the robot position data of t moment；
Electronic compass is used to read the robot bearing data of t moment；
Odometer is used to read the rotary speed data of the robot left and right wheels of t moment；
Computer is used for using the method claimed in claims 1-2 to the robot position data, robot direction number
Accordingly and the rotary speed data of robot left and right wheels is handled, and realizes Mobile Robotics Navigation.
4. a kind of computer-readable storage media, which is characterized in that be stored with several lead on the computer readable storage medium
Voyage sequence, several Navigators are used for the mobile machine for any one of being called by processor and being executed the claim 1-2
Step in people's air navigation aid.
5. a kind of difference turns to wheeled mobile robot, including navigation device, which is characterized in that the navigation device is wanted for right
Navigation device described in asking 3.
6. a kind of caterpillar mobile robot, including navigation device, which is characterized in that the navigation device is claim 3 institute
The navigation device stated.
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| CN112219087A (en) * | 2019-08-30 | 2021-01-12 | 深圳市大疆创新科技有限公司 | Pose prediction method, map construction method, movable platform and storage medium |
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