CN116954235B - AGV trolley navigation control method and system - Google Patents
AGV trolley navigation control method and system Download PDFInfo
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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
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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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
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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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
- G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
- G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
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Abstract
The invention discloses a navigation control method and a system of an AGV (automatic guided vehicle). The method comprises the steps of firstly, carrying out fusion calculation on Bluetooth estimated coordinates and geomagnetic estimated coordinates in a decision layer to calculate the position of the AGV, thereby reducing positioning errors and not consuming additional hardware resources; and then repeatedly calculating the shortest linear distance between the current position of the AGV trolley and the position to be reached by the AGV trolley until the position to be reached by the AGV trolley is reached, so that the whole process is simple in algorithm, short in time consumption and low in hardware requirement, and the requirements of practical application can be well met.
Description
Technical Field
The invention relates to the technical field of navigation, in particular to a navigation control method and system for an AGV trolley.
Background
AGVs (Automatic Guided Vehicle, automatic navigation trolleys) are unmanned automatic transport equipment, can bear a certain weight to run between a departure place and a destination autonomously, are important component equipment of an automatic logistics system and a flexible manufacturing system, and have good market prospect and application value.
The AGV is divided into a track type AGV and a non-track type AGV, wherein the track type AGV is AGV equipment moving according to a preset track, the non-track type AGV is AGV equipment with an autonomous navigation function, the conventional non-track type AGV is characterized in that an environment profile of a space where the non-track type AGV is located is scanned and analyzed through a laser radar navigator fixedly arranged on the non-track type AGV to obtain environment data, then the AGV carries out navigation movement according to the environment data, but only a single laser radar navigator scans the environment profile in a narrow place with few reference points, the obtained environment data is easy to deviate, and therefore the AGV cannot normally navigate. If a plurality of laser radar navigator are arranged to scan and obtain the environmental profile with a plurality of angles, the technical problem is overcome, and the production cost of AGV equipment is increased.
Chinese patent application number CN201510761432.9 discloses a visual AGV navigation system comprising: vision sensor, image acquisition card, image processor, PC host computer and actuating system, wherein: the visual sensor is connected with the image acquisition card through a USB interface, the image acquisition card is connected with the image processor, the image processor is connected with the PC host through an RS232 interface, a USB interface and a JTAG interface, and the image processor is connected with the driving system through a PWM output interface; the image processor comprises a filtering processing unit, an edge processing unit and a threshold processing unit which are sequentially connected. Although the navigation system can realize automatic navigation of the AVG, the whole algorithm is complex and takes a long time.
Therefore, there is a need for a low cost, stable and reliable positioning navigation method for non-rail AGVs.
Disclosure of Invention
In order to solve the technical problems, the invention provides an AGV trolley navigation control method and system.
In order to achieve the above purpose, the invention is implemented according to the following technical scheme:
the first object of the invention is to provide a navigation control method for an AGV, which comprises the following steps:
s1, drawing an indoor coordinate grid diagram, and marking the positions and coordinates of all obstacles in the coordinate grid diagram;
s2, setting a plurality of Bluetooth beacons in an indoor area, installing a Bluetooth receiver, iBeacon software and a Hall sensor on an AGV trolley to respectively receive Bluetooth and geomagnetic signals, and calculating Bluetooth estimated coordinates and geomagnetic estimated coordinates;
s3, fusing the Bluetooth estimated coordinates and the geomagnetic estimated coordinates in a decision layer to calculate the current position of the AGV；
S4, obtainingCoordinates of arrival position of AGV trolleyThen according to the formulaObtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move towards the position to be reached of the AGV trolley along the shortest linear distance;
s5, acquiring a road image in front of the AGV in real time through a visual sensor on the AGV;
s6, controlling the AGV to move leftwards or rightwards when an obstacle exists right in front of the AGV, and collecting road images in front of the AGV in real time until no obstacle exists right in front of the AGV; obtaining the coordinates of the current position of the AGV trolley again, obtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move along the shortest linear distance to the position to be reached of the AGV trolley;
s7, repeating the steps S5-S6 until the AGV trolley reaches the position where the AGV trolley is to be reached.
Further, the step S2 specifically includes: suppose that the bluetooth estimate coordinates are:during which the geomagnetic estimation coordinate set is: />The geomagnetic estimation coordinate set is weighted after average, and the coordinates are as follows: />Respectively giving weight to the coordinates>Andbthe final position estimation coordinates after fusion are obtained as follows: />And wherein: /> <b。
Further, the weight ratio of the Bluetooth and geomagnetic positioning results is set to be 1:N, namely:the method comprises the steps of carrying out a first treatment on the surface of the And finally, writing the fused final position estimation coordinates as: />。
A second object of the present invention is to provide an AGV cart navigation control system, including a plurality of bluetooth beacons disposed in an indoor area, an AGV cart processor mounted on the AGV cart, a bluetooth receiver mounted on the AGV cart processor, and iBeacon software and hall sensors, visual sensors and a driving system, wherein: the visual sensor is connected with the AGV trolley processor through a USB interface, and the visual sensor is connected with the driving system through a PWM output interface; the AGV trolley processor is used for executing the AGV trolley navigation control method.
Compared with the prior art, the method has the advantages that the position of the AGV is calculated by fusing the Bluetooth estimated coordinates and the geomagnetic estimated coordinates in the decision layer, so that the positioning error is reduced, and additional hardware resources are not consumed; and then repeatedly calculating the shortest linear distance between the current position of the AGV trolley and the position to be reached by the AGV trolley until the position to be reached by the AGV trolley is reached, so that the whole process is simple in algorithm, short in time consumption and low in hardware requirement, and the requirements of practical application can be well met.
Drawings
Fig. 1 is a drawing of an indoor coordinate grid.
Fig. 2 is a schematic diagram of an online positioning stage of an indoor positioning algorithm of a position fingerprint.
Fig. 3 is a decision layer fusion structure diagram.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. The specific embodiments described herein are for purposes of illustration only and are not intended to limit the invention.
The embodiment provides an AGV dolly navigation control system, include set up a plurality of bluetooth beacons, install AGV dolly treater on the AGV dolly at indoor region, install bluetooth receiver and iBeacon software and hall sensor, vision sensor and actuating system on the AGV dolly treater, wherein: the visual sensor is connected with the AGV trolley processor through a USB interface, and is connected with the driving system through a PWM output interface; the AGV trolley processor is used for executing the following AGV trolley navigation control method so as to achieve that the AGV trolley reaches the position where the AGV trolley is to be reached.
By utilizing the system, the AGV trolley navigation control can be realized, and the specific steps are as follows:
s1, drawing an indoor coordinate grid diagram as shown in FIG. 1, and marking the positions and coordinates of all the obstacles in the coordinate grid diagram (larger dots in FIG. 1 represent the obstacles);
setting a plurality of Bluetooth beacons in an indoor area, installing a Bluetooth receiver, iBeacon software and a Hall sensor on an AGV trolley to respectively receive Bluetooth and geomagnetic signals, and calculating Bluetooth estimated coordinates and geomagnetic estimated coordinates;
the embodiment constructs a Bluetooth and geomagnetic fingerprint database based on an indoor positioning algorithm of a position fingerprint, and is divided into an off-line database building stage and an on-line positioning stage:
(1) Off-line warehouse building stage
In the off-line database establishment stage, firstly, data information acquisition is carried out to establish a fingerprint database of each position, namely, a certain number of reference points with moderate intervals are selected in an indoor designated area for sampling, the position fingerprint information of the points comprises received RSSI sequences of a plurality of APs and coordinates of the current position, and then the fingerprint data are stored in the position fingerprint database.
(2) On-line positioning stage
As shown in FIG. 2, in the online positioning stage, the actual position of the user needs to be estimated by using an established fingerprint database, the Bluetooth receiver and the iBeacon software can be installed on the AGV trolley to collect the RSSI signals of a plurality of APs currently received, and then the RSSI signals are sequentially compared with the RSSI data in the pre-stored position fingerprint database to obtain fingerprint data closest to the currently collected RSSI signals, so that the actual position of the current AGV trolley can be estimated.
Then, matching estimation is carried out by using a K nearest neighbor algorithm, and then Bluetooth estimated coordinates and geomagnetic estimated coordinates are calculated respectively.
The K-nearest neighbor algorithm is a position fingerprint positioning algorithm which is more commonly used, and the existence of the K-nearest neighbor algorithm in a positioning space is assumedmA number of sampling points are used to sample the sample,the RSSI vector of the to-be-positioned site is +.>First, theiRSSI vector of each sampling point is +.>The position coordinates are +.>The Euclidean distance between two points can be calculated as: />The method comprises the steps of carrying out a first treatment on the surface of the Wherein the method comprises the steps ofrssi j Indicating receipt of the firstjThe signal strengths of the individual APs,rssi ij is the firstiThe first of the sampling pointsjThe intensity of the APs. And then to the obtainedmSorting the distances, selecting the smallest distanceKSampling points, and taking the average value of the coordinates as an estimation result, namely:the method comprises the steps of carrying out a first treatment on the surface of the In->Represent the firstiCoordinates of the sampling points, +.>Is the corresponding estimated value. Besides the estimation error, the effect of localization can also be evaluated by a cumulative distribution function (Cumulative Distribution Function, CDF), the +.>Representation ofXLess than or equal to->The probability of occurrence of all values of (a), namely:the method comprises the steps of carrying out a first treatment on the surface of the The whole positioning process is analyzed, two reasons can greatly influence the positioning precision, namely the accuracy of fingerprint library construction. And secondly, the algorithm used in the online matching can preferably meet the accuracy of the matching algorithm and can not cause excessive hardware cost, so that the positioning accuracy can be improved, and the method is convenient for large-scale popularization.
And S2, fusing the Bluetooth estimated coordinates and the geomagnetic estimated coordinates in a decision layer to calculate the position of the user.
The embodiment adopts an accurate positioning function called iBeacon which is introduced in 2013 by apple corporation, the Bluetooth technology is utilized, peripheral electronic equipment can sense Bluetooth signals sent by the device, and then indoor positioning is realized through combination of software and hardware. The coverage of the iBeacon signal is about 5080 and m, and the user can detect the iBeacon signal through an application program on a mobile terminal such as a mobile phone. When the iBeacon bluetooth beacon is in operation, the device will transmit data packets outwards at intervals which may be divided into 300 ms, 500 ms or 900 ms. A complete iBeacon system should contain one or several iBeacon beacons that transmit unique identification codes over a distance and on the corresponding receiving device can find the iBeacon signal. The signal will be stronger nearer to the beacon, will be decaying continuously as the distance increases, and will not be detected when the distance exceeds a certain value.
The present embodiment employs a magnetic sensor principle similar to the "hall effect" of a smart phone, specifically, the earth itself has a strong magnetic field, and the magnetic field strengths at different locations are different. The magnetic induction in the x, Y and three directions can be detected by the magnetic sensor, wherein the x and Y directions are parallel to the ground at the point and the axis is perpendicular to the ground at the point. Utilize hall sensor who installs on the AGV dolly to gather the geomagnetic data of three axles, with triaxial data conversion to the module, no matter the AGV dolly gesture at this moment, this module is comparatively stable.
Assuming that the components of the magnetometer triads at a certain point areThe modulus of the magnetic field strength at this point can be obtained as: />The principle is that the voltage passing through the side of the constant current conductor can change linearly along with the change of the external magnetic field. So that the magnitude of the surrounding geomagnetic field intensity can be estimated by measuring the voltage on the side of the energized conductor.
Information fusion is a technology that combines multiple sensors to make them exert their own advantages. The method has certain information complementation capability, can obtain data information which is not acquired by a single sensor, and increases the reliability of judgment. In general, information may be fused at the decision layer, feature layer, or data layer. In the embodiment, decision layer fusion is adopted, namely, different sensors are utilized to monitor a certain measured object, each sensor independently completes a series of processes of data preprocessing, characteristic information extraction, target discrimination and the like, initial analysis of the measured object is obtained, and then fusion is carried out in the decision layer, so that a final result is obtained. Compared with the other two fusion technologies, the decision layer fusion technology has the advantages of strong flexibility, less data processing amount in the fusion stage, good instantaneity and good fault tolerance. The decision layer fusion structure diagram is shown in fig. 3.
Firstly, bluetooth information and geomagnetic information are collected respectively, and then respective fingerprint databases are constructed. On the basis, the matching estimation is carried out by using a K nearest neighbor algorithm, then geomagnetic and Bluetooth positioning values are calculated respectively, and then the geomagnetic and Bluetooth positioning values are weightedAnd determining a final result. Suppose that the bluetooth estimate coordinates are:during which the geomagnetic estimation coordinate set is:the geomagnetic estimation coordinate set is weighted after average, and the coordinates are as follows:respectively giving weight to the coordinates>Andbthe final position estimation coordinates after fusion are obtained as follows: />On the one hand, the weight value of the two is +.>And b is affected by bluetooth and geomagnetic estimation accuracy. On the other hand, because the beacons of Bluetooth are more, fingerprint database data of the Bluetooth are more than that of geomagnetic fingerprint database, so that the result of geomagnetic estimation is output for a plurality of times while the 1-time Bluetooth estimation result is output, and an estimation set of geomagnetic positioning is obtained. Since the frequencies of the Bluetooth and geomagnetic results are different, the contributions to positioning are different, so that when the results are fused, the weight ratio of the Bluetooth and geomagnetic positioning results is set to be 1:N, namely:and finally, writing the fused final position estimation coordinates as: />。
It should be noted that, if the electromagnetic signal interference is small, the accuracy of bluetooth will be greatly improved, and the weight value can be flexibly adjusted.
Thus, the current position of the AGV is written asThe current position of the hypothetical AGV is represented by the smaller dot in the upper left corner of FIG. 1;
s4, obtaining coordinates of the position to be reached of the AGV trolley(the position where the AGV is to be reached is shown by the smaller dot in the lower right hand corner of FIG. 1) and then +.>Obtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move towards the position to be reached of the AGV trolley along the shortest linear distance;
s5, acquiring a road image in front of the AGV in real time through a visual sensor on the AGV;
s6, controlling the AGV to move leftwards or rightwards when an obstacle exists right in front of the AGV, and collecting road images in front of the AGV in real time until no obstacle exists right in front of the AGV; obtaining the coordinates of the current position of the AGV trolley again, obtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move along the shortest linear distance to the position to be reached of the AGV trolley;
s7, repeating the steps S5-S6 until the AGV trolley reaches the position where the AGV trolley is to be reached.
In summary, in the embodiment, the position of the AGV is calculated by fusing the bluetooth estimated coordinates and the geomagnetic estimated coordinates in the decision layer, so that the positioning error is reduced and no additional hardware resource is consumed; and then repeatedly calculating the shortest linear distance between the current position of the AGV trolley and the position to be reached by the AGV trolley until the position to be reached by the AGV trolley is reached, wherein the whole process is simple in algorithm, short in time consumption and low in hardware requirement.
The technical scheme of the invention is not limited to the specific embodiment, and all technical modifications made according to the technical scheme of the invention fall within the protection scope of the invention.
Claims (3)
1. The AGV trolley navigation control method is characterized by comprising the following steps of:
s1, drawing an indoor coordinate grid diagram, and marking the positions and coordinates of all obstacles in the coordinate grid diagram;
s2, setting a plurality of Bluetooth beacons in an indoor area, installing a Bluetooth receiver, iBeacon software and a Hall sensor on an AGV trolley to respectively receive Bluetooth and geomagnetic signals, and calculating Bluetooth estimated coordinates and geomagnetic estimated coordinates; the method specifically comprises the following steps:
suppose that the bluetooth estimate coordinates are:
L W ＝(x，y)；
the geomagnetic estimation coordinate set during this period is:
D W ＝{(x 1 ，y 1 )，(x 2 ，y 2 )，…，(x N ，y N )}；
the geomagnetic estimated coordinate set is weighted by average, and the average coordinates are as follows:
the coordinates are respectively assigned with weights a and b, and the final position estimated coordinates after fusion are obtained as follows:
wherein: a is less than b;
the weight ratio of the Bluetooth and geomagnetic positioning results is set to be 1:N, namely:
and finally, writing the fused final position estimation coordinates as:
s3, fusing the Bluetooth estimated coordinates and the geomagnetic estimated coordinates in a decision layer to calculate the current position (x i ，y i )；
S4, obtaining the coordinate (x) i ’，y i '), then according to the formulaObtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move towards the position to be reached of the AGV trolley along the shortest linear distance;
s5, acquiring a road image in front of the AGV in real time through a visual sensor on the AGV;
s6, controlling the AGV to move leftwards or rightwards when an obstacle exists right in front of the AGV, and collecting road images in front of the AGV in real time until no obstacle exists right in front of the AGV; obtaining the coordinates of the current position of the AGV trolley again, obtaining the shortest linear distance between the current position of the AGV trolley and the position to be reached of the AGV trolley, and controlling the AGV trolley to move along the shortest linear distance to the position to be reached of the AGV trolley;
s7, repeating the steps S5-S6 until the AGV trolley reaches the position where the AGV trolley is to be reached.
2. The AGV car navigation control method according to claim 1, wherein the step S1 specifically includes:
s11, respectively acquiring Bluetooth and geomagnetic information of indoor areas, and further constructing respective fingerprint databases;
and S12, performing matching estimation by using a K neighbor algorithm, and then respectively calculating Bluetooth estimated coordinates and geomagnetic estimated coordinates.
3. The utility model provides an AGV dolly navigation control system, its characterized in that, include set up a plurality of bluetooth beacons, install AGV dolly treater on the AGV dolly at indoor region, install bluetooth receiver and iBeacon software and hall sensor, vision sensor and actuating system on the AGV dolly treater, wherein: the visual sensor is connected with the AGV trolley processor through a USB interface, and the visual sensor is connected with the driving system through a PWM output interface; the AGV trolley processor is configured to execute the AGV trolley navigation control method according to claim 1 or 2.
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