CN111479216A - Unmanned aerial vehicle cargo conveying method based on UWB positioning - Google Patents
Unmanned aerial vehicle cargo conveying method based on UWB positioning Download PDFInfo
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- CN111479216A CN111479216A CN202010281125.1A CN202010281125A CN111479216A CN 111479216 A CN111479216 A CN 111479216A CN 202010281125 A CN202010281125 A CN 202010281125A CN 111479216 A CN111479216 A CN 111479216A
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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
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
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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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- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems
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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
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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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
Abstract
The invention discloses an unmanned aerial vehicle cargo conveying method based on UWB positioning, and relates to the field of unmanned aerial vehicle positioning and cargo conveying. First, the UWB base station 1 and the UWB base station 2 are constructed, and the distance between the two UWB base stations is calculated. Then, the distance between the random UWB base stations and other base stations is calculated aiming at n random UWB base stations, and an optional UWB base station i is selected, so that the absolute position of each UWB base station is calculated. And taking the base station i as a starting point, and the base stations j and p as end points respectively, placing the mobile terminal between the starting point and the end points, measuring the distance difference between the two UWB base stations and the mobile terminal, and positioning the mobile terminal. And continuously selecting other UWB base stations as termination points, and repeatedly calculating to obtain the three-dimensional space positioning of the mobile terminal. The mobile terminal is carried on the unmanned aerial vehicle, and the unmanned aerial vehicle path is planned in real time. And adding unmanned planes one by one, and calculating respective optimal paths to form efficient transportation of the unmanned plane cluster. The invention improves the positioning precision of the unmanned aerial vehicle and the efficiency of cargo transportation.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle positioning and cargo transportation, in particular to an unmanned aerial vehicle cargo transportation method based on UWB positioning.
Background
UWB (Ultra Wide Band) is a carrier-free communication technology that uses non-sinusoidal narrow pulses on the nanosecond to microsecond level to transmit data. UWB enables large-scale, fast data transmission over a short range by transmitting very low power signals over a wide frequency spectrum; the method has the advantages of strong anti-interference capability, low transmitting power and the like. By utilizing the advantages, the real-time path planning of the unmanned aerial vehicle cluster can be realized in a small-range indoor environment.
The three-dimensional path planning of the unmanned aerial vehicle cluster in the space has various methods, and the path planning of a plurality of moving objects is met in the limited space, so that the collision among the moving objects is avoided. A more advanced algorithm can ensure that each moving object moves according to the shortest path on the premise that collision does not occur.
The space three-dimensional path planning technology can enable a plurality of unmanned aerial vehicles to move in a three-dimensional space, and the space utilization rate can be greatly improved.
Disclosure of Invention
The invention provides an unmanned aerial vehicle cargo transportation method based on UWB positioning, aiming at improving the positioning accuracy of an unmanned aerial vehicle, and the method can be used for planning a path in real time through information transmission between the unmanned aerial vehicle and a base station, enhancing the information transmission speed between the unmanned aerial vehicle and the base station, and realizing space path planning of an unmanned aerial vehicle cluster and cargo transportation in a three-dimensional space.
The unmanned aerial vehicle cargo conveying method comprises the following steps:
step one, building two different UWB base stations: the UWB base station 1 and the UWB base station 2 are respectively used as a local node and a remote node, and the distance s between the two UWB base stations is calculated by utilizing a TOA algorithm through sending data frames;
the method comprises the following specific steps:
step 101, the local node sends a data frame to the remote node, receives a reply frame of the remote node, and records sending and receiving time respectively.
The method specifically comprises the following steps: the UWB base station 1 sends a data frame to the UWB base station 2, the UWB base station 2 sends a reply frame to the UWB base station 1 after receiving the data frame, the UWB base station 1 records the sending time of the data frame and the receiving time of the reply frame, the UWB base station 2 records the receiving time of the data frame and the sending time of the reply frame, and sends the four recorded times to the master control end.
Step 102, obtaining data frame transmission time difference T by using sending and receiving timeToTTime difference of transmission T from the reply frameTAT；
TToTCalculating the data frame transmission time after the UWB base station 2 receives the data frame of the UWB base station 1;
TTATcalculating the transmission time of the reply frame after the UWB base station 1 receives the reply frame of the UWB base station 2;
step 103, utilizing the data frame transmission time difference TToTTime difference of transmission T from the reply frameTATCalculating the one-way transmission time of radio waves in the air;
one-way propagation time TTOFThe calculation formula of (2) is as follows:
TTOF＝(TToT+TTAT)/2
104, calculating the distance s between the two UWB base stations by utilizing the one-way transmission time of the radio waves in the air;
the calculation formula is as follows: s ═ c · TTOF(ii) a c is the propagation velocity of the electromagnetic wave, i.e., the speed of light.
And step two, aiming at n random UWB base stations, selecting one UWB base station i, and calculating the distance from the base station i to other base stations by using a TOA algorithm, thereby calculating the absolute position of each UWB base station in space.
sijFor the distance from UWB base station i to UWB base station j, then base station i existsBase station j as the center of circle, sijIs a circle of radii. In the same way, n-1 circles which take the base station as the center of a circle and the distance as the radius can be obtained in total, and the intersection point of the circles is the relative position of the base station i in practice.
Since errors exist, the minimum variance point of all the intersection points is taken as the point closest to the actual position of the base station i.
The absolute position of each UWB base station in space can be determined by the actual position of the base station i and the relative distance between the UWB base station and other base stations.
And step three, taking the base station i as a starting point, taking the base station j and the base station p as termination points respectively, placing the mobile terminal between the starting point and the termination points, and measuring the distance difference between the two UWB base stations and the mobile terminal by using the TDOA so as to position the mobile terminal.
The method comprises the following specific steps:
firstly, a mobile terminal is placed between a UWB base station i and a UWB base station j, the distance between the mobile terminal and the two base stations is respectively differentiated, and the calculation formula is as follows:
(X0,Y0,Z0) Position coordinates of the mobile terminal; (X)1,Y1,Z1) As position coordinates of UWB base station i, (X)2,Y2,Z2) Position coordinates of a UWB base station j;
the position of the mobile terminal must be focused on UWB base station i and UWB base station j, and the distance difference between the two focuses is always R21On the hyperbola of (a).
Then, the mobile terminal is placed between the UWB base station i and the UWB base station p again, and another position hyperbola of the mobile terminal is obtained by utilizing the TOA;
and finally, two hyperbolas at the two positions of the mobile terminal have at most two intersection points, and the accurate position of the mobile terminal is calculated by utilizing the intersection points.
And step four, continuously selecting other UWB base stations as termination points, and repeatedly calculating the accurate positioning of each UWB base station and the mobile terminal, thereby obtaining the three-dimensional space positioning of the mobile terminal.
And fifthly, carrying the mobile terminal on an unmanned aerial vehicle, and planning the path of the unmanned aerial vehicle in real time by utilizing three-dimensional space positioning to transport goods.
The specific path planning method comprises the following steps:
firstly, regarding the coverage range of all UWB base stations as a three-dimensional space and dividing the space into a plurality of sub-cube spaces; setting each vertex of each subcube as a node, and enabling the unmanned aerial vehicle to start from one node, advance along the edge of the cube and reach the other node; all edges of the subcube build a 3 x N matrix, initially marking the vectors of all unoccupied edges as 0.
Then, after the starting node of the unmanned aerial vehicle is determined, according to the position of a target node, calculating an optimal route corresponding to the minimum number of nodes required to pass through to the target node by using a network shortest path Dijkstra algorithm, searching a matrix, judging whether edges required by the optimal route are completely usable, if at least one edge on the optimal route is occupied, recalculating the optimal route, and if not, writing vectors of all edges required by the optimal route to be 1;
finally, the drone starts the travel cargo delivery according to the optimal path marked 1.
And step six, repeating the step three to the step five, adding the unmanned aerial vehicles one by one, calculating respective optimal paths, and finally forming the unmanned aerial vehicle cluster to carry out efficient transportation in a three-dimensional space.
Compared with the prior art, the invention has the following beneficial effects:
an unmanned aerial vehicle cargo conveying method based on UWB positioning can improve the positioning accuracy of an unmanned aerial vehicle and improve cargo conveying efficiency.
Drawings
Fig. 1 shows an unmanned aerial vehicle cargo transportation method based on UWB positioning according to the present invention.
Detailed Description
The present invention will be described in further detail and with reference to the accompanying drawings so that those skilled in the art can understand and practice the invention.
An unmanned aerial vehicle cargo conveying system based on UWB positioning is characterized in that different UWB base stations are built, a mobile terminal is placed in a coverage area common to the base stations, and accurate positioning of the base stations and the mobile terminal is calculated by utilizing TOA (Time of Arrival algorithm) or TDOA (Time Difference of Arrival algorithm); the mutual communication between the base stations is realized within a certain range. Utilizing two TOA base stations to send data frames and reply, thereby obtaining the distance between the two base stations; and positioning by measuring the transmission delay difference between two different base stations and the mobile terminal by using the TDOA. Then, the mobile terminal is arranged on the unmanned aerial vehicle, and the base station is used for determining the position of the mobile terminal. Further through setting up a plurality of UWB basic stations, utilize the data of a plurality of basic stations to carry out three-dimensional space positioning to unmanned aerial vehicle, reuse algorithm revises unmanned aerial vehicle's position, and the more of basic station figure, unmanned aerial vehicle positioning accuracy is higher. Finally, adding a cargo conveying function of the unmanned aerial vehicle, and carrying out real-time three-dimensional space path planning and cargo conveying by using positioning data; and then, the number of the unmanned aerial vehicles is gradually increased to form an unmanned aerial vehicle cluster, so that efficient cargo transportation can be realized in a certain three-dimensional area.
As shown in fig. 1, the method comprises the following steps:
step one, building two different UWB base stations: the UWB base station 1 and the UWB base station 2 are respectively used as a local node and a remote node, and the distance s between the two UWB base stations is calculated by utilizing a TOA algorithm through sending data frames;
the method comprises the following specific steps:
step 101, the local node sends a data frame to the remote node, receives a reply frame of the remote node, and records sending and receiving time respectively.
The method specifically comprises the following steps: the UWB base station 1 sends a data frame to the UWB base station 2, the UWB base station 2 sends a reply frame to the UWB base station 1 after receiving the data frame, the UWB base station 1 records the sending time of the data frame and the receiving time of the reply frame, the UWB base station 2 records the receiving time of the data frame and the sending time of the reply frame, and sends the four recorded times to the master control end.
Step 102, obtaining data frame transmission time difference T by using sending and receiving timeToTTime difference of transmission T from the reply frameTAT；
TToTCalculating the data frame transmission time after the UWB base station 2 receives the data frame of the UWB base station 1;
TTATcalculating the transmission time of the reply frame after the UWB base station 1 receives the reply frame of the UWB base station 2;
step 103, utilizing the data frame transmission time difference TToTTime difference of transmission T from the reply frameTATCalculating the one-way transmission time of radio waves in the air;
one-way propagation time TTOFThe calculation formula of (2) is as follows:
TTOF＝(TToT+TTAT)/2
104, calculating the distance s between the two UWB base stations by utilizing the one-way transmission time of the radio waves in the air;
the calculation formula is as follows: s ═ c · TTOF(ii) a c is the propagation velocity of the electromagnetic wave, i.e., the speed of light.
And step two, aiming at n random UWB base stations, selecting one UWB base station i, and calculating the distance from the base station i to other base stations by using a TOA algorithm, thereby calculating the absolute position of each UWB base station in space.
sijThe distance from the UWB base station i to the UWB base station j is determined, and the base station i exists with the base station j as the center of a circle and s as the center of a circleijIs a circle of radii. In the same way, n-1 circles which take the base station as the center of a circle and the distance as the radius can be obtained in total, and the intersection point of the circles is the relative position of the base station i in practice.
Since the circles do not necessarily intersect at one point due to the existence of errors, the minimum variance point of all the intersections is taken as the point closest to the actual position of the base station i. Therefore, the relative positions of the n base stations can be obtained, and then the absolute position of any one base station is given, namely the absolute position of each base station on the space can be determined.
And step three, taking the base station i as a starting point, taking the base station j and the base station p as termination points respectively, placing the mobile terminal between the starting point and the termination points, and measuring the distance difference between the two UWB base stations and the mobile terminal by using the TDOA so as to position the mobile terminal.
The method comprises the following specific steps:
firstly, a mobile terminal is placed between a UWB base station i and a UWB base station j, the distance between the mobile terminal and the two base stations is respectively differentiated, and the calculation formula is as follows:
(X0,Y0,Z0) Position coordinates of the mobile terminal; (X)1,Y1,Z1) As position coordinates of UWB base station i, (X)2,Y2,Z2) Position coordinates of a UWB base station j;
the position of the mobile terminal must be focused on UWB base station i and UWB base station j, and the distance difference between the two focuses is always R21On the hyperbola of (a).
Then, the mobile terminal is placed between the UWB base station i and the UWB base station p again, and another position hyperbola of the mobile terminal is obtained by using the TDOA;
and finally, the two hyperbolas at the two positions of the mobile terminal have at most two intersection points, and the accurate position of the mobile terminal is calculated according to the intersection points of the two or more hyperbolas.
Because of positioning error, the hyperbola intersection points that a plurality of basic stations formed to same unmanned aerial vehicle can't coincide, consequently can produce a plurality of intersection points. These intersection points should be a collection of points scattered around the actual point, the minimum variance point of which is close to the actual location point. According to the statistical principle, the minimum variance point is closer to the actual location point as the number of base stations increases.
And step four, continuously selecting other UWB base stations as termination points, and repeatedly calculating the accurate positioning of each UWB base station and the mobile terminal, thereby obtaining the three-dimensional space positioning of the mobile terminal.
And fifthly, carrying the mobile terminal on an unmanned aerial vehicle, and planning the path of the unmanned aerial vehicle in real time by utilizing three-dimensional space positioning to transport goods.
The specific path planning method comprises the following steps:
firstly, the range covered by all UWB base stations is regarded as a three-dimensional space at the master control end and divided into a plurality of sub-cube spaces, so that each side of the cube space and the unmanned aerial vehicle on each vertex can not collide with each other. Setting each vertex of each subcube as a node, and enabling the unmanned aerial vehicle to start from one node, advance along the edge of the cube and reach the other node; A3N matrix is built on the edges of all the subcubes in the whole space at the master control end, all the edges are represented by a column vector, the vectors of all the edges are initially marked as 0, and then the edges are written as 1 when occupied.
Then, after the starting node of the unmanned aerial vehicle is determined, according to the position of a target node, calculating an optimal route corresponding to the minimum number of nodes required to pass through to the target node by using a network shortest path Dijkstra algorithm, searching a matrix, judging whether edges required by the optimal route are completely usable, if at least one edge on the optimal route is occupied, recalculating the optimal route, and if not, writing vectors of all edges required by the optimal route to be 1;
finally, the drone starts the travel cargo delivery according to the optimal path marked 1.
The pseudo code is as follows:
Begin
input Total Path matrix I Path matrix J
Input start node A termination node B
While (all paths A to B)
If an edge belongs to min (node a to node B) and the edge is 0
The vector of the edge in the path matrix J is 1
If an edge written 1 in a J is also written 1 in I
The edge is kept unchanged, and the other edges are equal to 0, and the calculation is repeated
All edges written as 1 in Else If J are 0 in I
Writing these edges as 1 in I
Start flying
END
And step six, repeating the step three to the step five, adding the unmanned aerial vehicles one by one, calculating respective optimal paths, and finally forming the unmanned aerial vehicle cluster to carry out efficient transportation in a three-dimensional space.
Simultaneously, the structure of the unmanned aerial vehicle is designed, so that the unmanned aerial vehicle structure can be carried with mechanical arms or a containing device, and the transportation of goods is realized.
Claims (3)
1. An unmanned aerial vehicle cargo conveying method based on UWB positioning is characterized by comprising the following steps:
step one, building two different UWB base stations: the UWB base station 1 and the UWB base station 2 are respectively used as a local node and a remote node, and the distance s between the two UWB base stations is calculated by utilizing a TOA algorithm through sending data frames;
step two, aiming at n random UWB base stations, selecting one UWB base station i, calculating the distance from the base station i to other base stations by using a TOA algorithm, and thus calculating the absolute position of each UWB base station in space;
sijthe distance from the UWB base station i to the UWB base station j is determined, and the base station i exists with the base station j as the center of a circle and s as the center of a circleijIs a circle of radius; in a similar way, n-1 circles which take the base station as the center of a circle and take the distance as the radius can be obtained in total, and the intersection point of the circles is the relative position of the base station i in practice;
taking the minimum variance point of all the intersection points as the point closest to the actual position of the base station i due to the existence of errors;
the absolute position of each UWB base station on the space can be determined by the actual position of the base station i and the relative distance between the UWB base station i and each other base station;
thirdly, taking the base station i as a starting point, taking the base station j and the base station p as termination points respectively, placing the mobile terminal between the starting point and the termination points, and measuring the distance difference between the two UWB base stations and the mobile terminal by using the TDOA so as to position the mobile terminal;
the method comprises the following specific steps:
firstly, a mobile terminal is placed between a UWB base station i and a UWB base station j, the distance between the mobile terminal and the two base stations is respectively differentiated, and the calculation formula is as follows:
(X0,Y0,Z0) Position coordinates of the mobile terminal; (X)1,Y1,Z1) As position coordinates of UWB base station i, (X)2,Y2,Z2) Position coordinates of a UWB base station j;
the position of the mobile terminal must be focused on UWB base station i and UWB base station j, and the distance difference between the two focuses is always R21On the hyperbola of (a);
then, the mobile terminal is placed between the UWB base station i and the UWB base station p again, and another position hyperbola of the mobile terminal is obtained by utilizing the TOA;
finally, the two position hyperbolas of the mobile terminal have at most two intersection points, and the accurate position of the mobile terminal is calculated by utilizing the intersection points;
step four, continuously selecting other UWB base stations as termination points, and repeatedly calculating the accurate positioning of each UWB base station and the mobile terminal, thereby obtaining the three-dimensional space positioning of the mobile terminal;
step five, the mobile terminal is carried on the unmanned aerial vehicle, and the unmanned aerial vehicle path is planned in real time by utilizing three-dimensional space positioning to carry out cargo transportation;
and step six, repeating the step three to the step five, adding the unmanned aerial vehicles one by one, calculating respective optimal paths, and finally forming the unmanned aerial vehicle cluster to carry out efficient transportation in a three-dimensional space.
2. The UWB positioning-based unmanned aerial vehicle cargo transportation method of claim 1, wherein the first step is specifically:
step 101, a local node sends a data frame to a remote node, receives a reply frame of the remote node, and records sending and receiving moments respectively;
the method specifically comprises the following steps: the UWB base station 1 sends a data frame to the UWB base station 2, the UWB base station 2 sends a reply frame to the UWB base station 1 after receiving the data frame, the UWB base station 1 records the sending time of the data frame and the receiving time of the reply frame, the UWB base station 2 records the receiving time of the data frame and the sending time of the reply frame, and sends the four recorded times to the master control end;
step 102, obtaining data frame transmission time difference T by using sending and receiving timeToTTime difference of transmission T from the reply frameTAT；
TToTCalculating the data frame transmission time after the UWB base station 2 receives the data frame of the UWB base station 1;
TTATcalculating the transmission time of the reply frame after the UWB base station 1 receives the reply frame of the UWB base station 2;
step 103, utilizing the data frame transmission time difference TToTTime difference of transmission T from the reply frameTATCalculating the one-way transmission time of radio waves in the air;
one-way propagation time TTOFThe calculation formula of (2) is as follows:
TTOF＝(TToT+TTAT)/2
104, calculating the distance s between the two UWB base stations by utilizing the one-way transmission time of the radio waves in the air;
the calculation formula is as follows: s ═ c · TTOF(ii) a c is the propagation velocity of the electromagnetic wave, i.e., the speed of light.
3. The UWB positioning-based unmanned aerial vehicle cargo transportation method of claim 1, wherein the specific path planning mode in the fifth step is as follows:
firstly, regarding the coverage range of all UWB base stations as a three-dimensional space and dividing the space into a plurality of sub-cube spaces; setting each vertex of each subcube as a node, and enabling the unmanned aerial vehicle to start from one node, advance along the edge of the cube and reach the other node; establishing a 3-N matrix by the edges of all the subcubes, and initially marking vectors of all the unoccupied edges as 0;
then, after the starting node of the unmanned aerial vehicle is determined, according to the position of a target node, calculating an optimal route corresponding to the minimum number of nodes required to pass through to the target node by using a network shortest path Dijkstra algorithm, searching a matrix, judging whether edges required by the optimal route are completely usable, if at least one edge on the optimal route is occupied, recalculating the optimal route, and if not, writing vectors of all edges required by the optimal route to be 1;
finally, the drone starts the travel cargo delivery according to the optimal path marked 1.
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| CN113030854A (en) * | 2021-03-18 | 2021-06-25 | 大连交通大学 | Three-dimensional positioning system based on UWB positioning |
| CN113490272A (en) * | 2021-09-08 | 2021-10-08 | 中铁工程服务有限公司 | UWB positioning-based safe hoisting early warning method, system and medium |
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