CN109640253A - A kind of method for positioning mobile robot - Google Patents
A kind of method for positioning mobile robot Download PDFInfo
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- CN109640253A CN109640253A CN201811601879.XA CN201811601879A CN109640253A CN 109640253 A CN109640253 A CN 109640253A CN 201811601879 A CN201811601879 A CN 201811601879A CN 109640253 A CN109640253 A CN 109640253A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
- G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
- G01S11/06—Systems for determining distance or velocity not using reflection or reradiation using radio waves using intensity measurements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses a kind of method for positioning mobile robot, comprising the following steps: Bluetooth beacon deployment acquires radio signal strength characteristic and forms characteristic matrix, calculate the distance between point to be determined and four beacons, calculates (xw,yw), the characteristic calculated in signal strength characteristics data and set carries out similarity, calculates (xs,ys), fusion obtains final estimated location.The method have the advantages that: it does not need additional expensive device and does not need clock synchronization, therefore power consumption and cost are all lower, have stronger robustness.
Description
Technical field
The present invention relates to robot fields, more particularly to a kind of method for positioning mobile robot.
Background technique
With the fast development of wireless communication, Internet technology and artificial intelligence, location technology is got the attention.
It indoors in environment, is influenced since signal is blocked by building with multipath effect, Global Satellite Navigation System (Global
Navigation Satellite System, GNSS) positioning accuracy seriously restricted, be unable to satisfy indoor location service
Needs.Indoor positioning technologies complete the positioning to target labels mainly by building indoor locating system, by more base stations.Mesh
Before, indoor positioning technologies are broadly divided into based on ranging and without ranging two major classes.The common method based on ranging mainly has base
In received signal strength indicator (RSSI), based on signal transmission time (TOA), based on signal transmission time poor (TDOA) and being based on
Direction of arrival degree (AOA) scheduling algorithm.Wherein, RSSI positioning mode do not need that clock is synchronous and angle measurement, power consumption and cost compared with
It is low, and it is not required to additional hardware supported, therefore the present invention uses the distance measuring method based on RSSI.
Currently, extensive research has also been obtained based on RSSI positioning.Document " node positioning method based on RSSI, application
Number: CN201410834896.3 " discloses a kind of node positioning method based on RSSI, can certainly solve for any mesh
The problem of mark node calculates its node location, secondly, further correction can be carried out to node location to improve its essence
True property.Document " a kind of RSSI indoor positioning algorithms based on Grid Clustering, application number: CN201810371361.5 " be directed to due to
Complicated indoor environment and caused by the not high problem of positioning accuracy, propose a kind of indoor positioning of Grid Clustering based on RSSI
Algorithm.It is characterized in that not needing the prior information of acquisition indoor environment, complicated indoor environment is widely used in, it can be achieved that concentrating
The autonomous positioning of formula or distributed object label.The program is to need in advance a large amount of mark of arrangement on the ground based on RFID
Label, therefore higher cost, certain influence is also brought to environment.A kind of document " indoor positioning side MLE-PSO based on RSSI
Method, application number: CN201710234962.7 " discloses a kind of MLE-PSO indoor orientation method based on RSSI, can be significant
It improves and is based on indoor position accuracy, while guaranteeing acquisition data volume size, iteration time needed for the calculating speed of location algorithm, positioning
The dynamics performance capabilities such as number.
However, non line-of-sight communication is very significant with multipath effect due to indoor environment complexity, therefore it is based on triangle above
The method reliability of positioning is lower.Another localization method based on RSSI is information fingerprint positioning, it refers to acquisition positioning
Then the radio signal characteristics vector in region carries out matched localization method by radio signal characteristics vector.It is such fixed at present
Position technique study is less.
Summary of the invention
The technology of the present invention overcome the deficiencies in the prior art, solve traditional indoor locating system robustness based on fingerprint compared with
The problem of difference.
To solve the above problems, the invention discloses a kind of method for positioning mobile robot, specifically includes the following steps:
Step S1: 4 Bluetooth beacons are disposed in room area to be positioned first, four vertex is located at, is denoted as B1,
B2,B3,B4, the position of this four beacons it is known that be denoted as respectively
Step S2: the signal for the beacon radiation disposed in step S1 can form radio wave signal field indoors, undetermined
The different sample fingerprint points of the room area of position are denoted as RP, acquire radio signal strength characteristic, form characteristic square
Battle array
Wherein,Indicate beacon BiIn sample point RPjThe nothing at place
Line electrical signal intensity, N are sample point quantity, and the coordinate of each RP is (xj,yj)；A similarity system is distributed for each sample point
Number weight αj=1；
Step S3: acquisition point to be determined receives the signal strength data of four beacons, is denoted as respectively And it is calculated by the following formula between point to be determined and four beacons
Distance:
RSSI=A-10nlg (d),
In above formula, RSSI indicates that certain puts the signal strength data received in area to be targeted, and A indicates reference distance 1m
The unit of the received signal strength data at place, signal strength data is dBm, and n is path-loss factor, its value is actually measured
Empirical value, barrier is more, and n value is bigger, d indicate the distance between point to be determined and beacon；
Step S4: calculating the coordinate of point to be determined with following formula, and the coordinate that this method is calculated is denoted as (xw,
yw):
Wherein,Indicate the coordinate position of four beacons, wi, each letter of i=1,2,3,4 expression
The weight of cursor position, these weights are the distance between point to be determined and each beacon by calculating in step S3 di, i=
1,2,3,4 decision, g is a constant；
Step S5: successively strong to the signal of point to be determined by signal strength characteristics set obtained in scanning step S2
The characteristic spent in characteristic and set carries out similarity calculation, and the formula of similarity calculation is as follows:
Wherein, sjIndicate the similarity between point to be determined and j-th of sample point；
Step S6: a series of similarities calculated in step S5 are arranged in descending order, the highest K sample of similarity
Point is screened out, and the coordinate of point to be determined is calculated according to the position coordinates of this K sample point, what this method was calculated
Coordinate is denoted as (xs,ys), calculation method is as follows:
Wherein, C is the serial number set for being selected the sample point of the K come, has K element in set；
Step S7: two position coordinates (x obtained in step S4 and step S6 are soughtw,yw) and (xs,ys) be averaged, count
Final estimated location (x, y), if (xs,ys) and (xw,yw) the distance between less than one preset constant, τ, then
It calculates
Otherwise x=x is enabledw, y=yw, and to αjIt is updated, it is as follows: the sample of the K nearest with it is found around (x, y)
This point, serial number set are denoted as C ', askAndThen α is updatedjIt is as follows:Wherein δ > 0.
Compared with existing technology, the invention has the following advantages that
1. the present invention is based on Bluetooth technologies to carry out indoor positioning, since Bluetooth technology has been widely used for daily life
In, so that the proposed localization method of the invention is implemented without additional expensive device, cost is relatively low；
2. using the distance measuring method based on RSSI, does not need clock and synchronize, power consumption and cost are all lower；
3. merging traditional location fingerprint localization method and weighted mass center location algorithm, the robust of localization method is enhanced
Property.
Detailed description of the invention
Fig. 1 is flow chart of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing and specific implementation
The present invention is described in detail for example.
A kind of method for positioning mobile robot, as shown in Figure 1, specifically includes the following steps:
Step S1: 4 Bluetooth beacons are disposed in room area to be positioned first, four vertex is located at, is denoted as B1,
B2,B3,B4, the position of this four beacons it is known that be denoted as respectively
Step S2: the signal for the beacon radiation disposed in step S1 can form radio wave signal field indoors, undetermined
The different sample fingerprint points of the room area of position are denoted as RP, acquire radio signal strength characteristic, form characteristic square
Battle array
Wherein,Indicate beacon BiIn sample point RPjThe nothing at place
Line electrical signal intensity, N are sample point quantity, and the coordinate of each RP is (xj,yj)；A similarity system is distributed for each sample point
Number weight αj=1；
Step S3: acquisition point to be determined receives the signal strength data of four beacons, is denoted as respectively And it is calculated by the following formula between point to be determined and four beacons
Distance:
RSSI=A-10nlg (d),
In above formula, RSSI indicates that certain puts the signal strength data received in area to be targeted, and A indicates reference distance 1m
The unit of the received signal strength data at place, signal strength data is dBm, and n is path-loss factor, its value is actually measured
Empirical value, barrier is more, and n value is bigger, d indicate the distance between point to be determined and beacon；
Step S4: calculating the coordinate of point to be determined with following formula, and the coordinate that this method is calculated is denoted as (xw,
yw):
Wherein,Indicate the coordinate position of four beacons, wi, each letter of i=1,2,3,4 expression
The weight of cursor position, these weights are the distance between point to be determined and each beacon by calculating in step S3 di, i=
1,2,3,4 decision, g is a constant；
Step S5: successively strong to the signal of point to be determined by signal strength characteristics set obtained in scanning step S2
The characteristic spent in characteristic and set carries out similarity calculation, and the formula of similarity calculation is as follows:
Wherein, sjIndicate the similarity between point to be determined and j-th of sample point；
Step S6: a series of similarities calculated in step S5 are arranged in descending order, the highest K sample of similarity
Point is screened out, and the coordinate of point to be determined is calculated according to the position coordinates of this K sample point, what this method was calculated
Coordinate is denoted as (xs,ys), calculation method is as follows:
Wherein, C is the serial number set for being selected the sample point of the K come, has K element in set；
Step S7: two position coordinates (x obtained in step S4 and step S6 are soughtw,yw) and (xs,ys) be averaged, count
Final estimated location (x, y), if (xs,ys) and (xw,yw) the distance between less than one preset constant, τ, then
It calculates
Otherwise x=x is enabledw, y=yw, and to αjIt is updated, it is as follows: the sample of the K nearest with it is found around (x, y)
This point, serial number set are denoted as C ', askAndThen α is updatedjIt is as follows:Wherein δ > 0.
Above embodiments are provided just for the sake of the description purpose of the present invention, and are not intended to limit the scope of the invention.This
The range of invention is defined by the following claims.It does not depart from spirit and principles of the present invention and the various equivalent replacements made and repairs
Change, should all cover within the scope of the present invention.
Claims (1)
1. a kind of method for positioning mobile robot, which is characterized in that specifically includes the following steps:
Step S1: 4 Bluetooth beacons are disposed in room area to be positioned first, four vertex is located at, is denoted as B1,B2,
B3,B4, the position of this four beacons it is known that be denoted as respectively
Step S2: the signal for the beacon radiation disposed in step S1 can form radio wave signal field indoors, to be positioned
The different sample fingerprint points of room area are denoted as RP, acquire radio signal strength characteristic, form characteristic matrix
Wherein,Indicate beacon BiIn sample point RPjThe radio at place
Signal strength, N are sample point quantity, and the coordinate of each RP is (xj,yj)；A coefficient of similarity power is distributed for each sample point
Weight αj=1；
Step S3: acquisition point to be determined receives the signal strength data of four beacons, is denoted as respectively And it is calculated by the following formula between point to be determined and four beacons
Distance:
RSSI=A-10nlg (d),
In above formula, RSSI indicates that certain puts the signal strength data received in area to be targeted, and A is indicated at reference distance 1m
The unit of received signal strength data, signal strength data is dBm, and n is path-loss factor, its value is actually measured warp
Value is tested, barrier is more, and n value is bigger, and d indicates the distance between point to be determined and beacon；
Step S4: calculating the coordinate of point to be determined with following formula, and the coordinate that this method is calculated is denoted as (xw,yw):
Wherein,Indicate the coordinate position of four beacons, wi, each beacon position of i=1,2,3,4 expression
The weight set, these weights are the distance between point to be determined and each beacon by calculating in step S3 di, i=1,2,
3,4 decisions, g is a constant；
Step S5: successively special to the signal strength of point to be determined by signal strength characteristics set obtained in scanning step S2
The characteristic levied in data and set carries out similarity calculation, and the formula of similarity calculation is as follows:
Wherein, sjIndicate the similarity between point to be determined and j-th of sample point；
Step S6: a series of similarities calculated in step S5 are arranged in descending order, the highest K sample point quilt of similarity
It screens, the coordinate of point to be determined, the coordinate that this method is calculated is calculated according to the position coordinates of this K sample point
It is denoted as (xs,ys), calculation method is as follows:
Wherein, C is the serial number set for being selected the sample point of the K come, has K element in set；
Step S7: two position coordinates (x obtained in step S4 and step S6 are soughtw,yw) and (xs,ys) be averaged, calculate most
Whole estimated location (x, y), if (xs,ys) and (xw,yw) the distance between less than one preset constant, τ, then calculate
Otherwise x=x is enabledw, y=yw, and to αjIt is updated, it is as follows: the sample of the K nearest with it is found around (x, y)
Point, serial number set are denoted as C ', askAnd, then update αjIt is as follows:
Wherein δ > 0.
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