JP5147015B2 - Moving body position detection system - Google Patents

Description

  The present invention relates to a system for detecting the position of an object moving on a plane.

  Conventionally, methods such as a ceiling camera method, a ceiling ID installation method, an ultrasonic wave utilization method, and an RFID utilization method are known as methods for detecting the position of a moving body such as a transport machine, a robot, and a human in a building.

  The ceiling camera system is a method of determining a position by imaging a mark installed on an object using a camera installed on a ceiling or a wall and detecting the mark. The ceiling ID installation method detects the position and direction of the camera by installing an ID marker that reflects infrared rays on the ceiling, irradiating infrared rays from below and capturing the reflection with the camera. However, these methods cannot be established unless a structure such as a ceiling or a wall is located above. Further, when there is an object that blocks between the camera and the mark, the detection becomes impossible.

  In the ultrasonic usage method, multiple ultrasonic microphones are placed on the ceiling or wall, an ultrasonic speaker is installed on the object, and the time from when the sound generation command is sent to the ultrasonic speaker until the sound is heard by the ultrasonic microphone. Is measured, the distance between the ultrasonic speaker and the plurality of ultrasonic microphones is determined from this time, and the three-dimensional position of the speaker is calculated by triangulation. However, in this method, if an object enters between the speaker and the microphone, the sound is cut off and measurement is impossible. In addition, a large measurement error occurs due to reflection of ultrasonic waves by walls and columns.

  The RFID system is a method in which a large number of RFID tags are arranged on a floor, these RFID tags are received by an RFID receiver, and a detection position is specified by the ID of the received RFID tag. However, generally, since RFID tags are detected discontinuously, the position cannot be detected at a position where the RFID cannot be detected. Although it is possible to detect near-continuous tags by spreading RFID tags at a high density, the cost increases and the detection values are discrete in units of several centimeters, and the position can be located only with a resolution of several centimeters at the minimum. It cannot be specified.

  Furthermore, the method of detecting the position of the moving body moving on the plane using a pattern (pattern) arranged on the plane is not limited to the position detection of the moving body in the building as in the above various methods. It is known (see, for example, Patent Document 1).

  In the position detection system of Patent Document 1, a coding pattern obtained by coding a plane XY coordinate value is arranged on a plane. This coding pattern includes a plurality of grid-like reference lines, and a plurality of dots are arranged in association with the positions of the respective intersections of the reference lines. The position detection device provided in the moving body captures an image of an area on a plane where the moving body is located, processes the acquired image to identify the coding pattern, and restores the coding pattern to restore the moving body. An XY coordinate value on the plane is obtained.

JP 2006-141061 A

  As shown in Patent Document 1, in a position detection system that detects a position of a moving body that moves on a plane using a pattern arranged on the plane, one encoding pattern is assigned to each coordinate value on the plane. Since it corresponds, there exists a problem that the freedom degree of design of a pattern is low. In particular, in the position detection system of Patent Document 1, since dots are arranged around the intersection of the grid-like reference line, only a pattern close to the grid pattern can be applied.

  In view of the above points, the present invention detects the position of a moving body using a pattern drawn on a plane without using a pattern encoded in correspondence with the coordinate value of the plane as in the prior art. An object of the present invention is to provide a movable body position detection system capable of performing the above.

The moving object position detection system of the present invention is a moving object position detection system that detects the position of a moving object that moves on a plane, and includes a dot pattern consisting of a plurality of dots randomly arranged on the plane, Calculating a positional relationship between individual dots in the dot pattern and a plurality of dots positioned around the individual dots, and associating the positional relationship with the coordinate values on the plane of the individual dots to generate a reference feature amount A reference feature quantity storage means for storing the reference feature quantity database in a reference feature quantity database; an imaging means provided in the movable body for imaging a region on a plane on which the movable body is located; and an image acquired by the imaging means The selected dot is selected from a plurality of dots, and the positional relationship between the selected dot and a plurality of dots located around this dot is detected. And a reference feature amount having the highest degree of coincidence with the detected feature amount is selected from the reference feature amount database by comparing the detected feature amount with the reference feature amount database. And a feature value matching means for detecting the coordinate value of the reference feature value as the current position of the moving object on the plane.

  The moving body position detection system according to claim 2 of the present invention is the moving object position detection system according to claim 1, wherein the dot pattern divides the plane into a plurality of blocks and arranges dots at random positions in each block. It was created by.

  The moving body position detection system according to claim 3 of the present invention is the moving body position detection system according to claim 1 or 2, wherein the reference feature amount and the detected feature amount are within a region of a dot and a circle having a predetermined radius centered on the dot. It is characterized by including an array composed of the direction of each line segment connecting a plurality of positioned peripheral dots and an array composed of the length of each line segment.

  The moving body position detection system according to claim 4 of the present invention is the moving body position detection system according to claim 3, wherein the number of line segments in the detected feature amount of the dot selected from the image by the feature amount matching unit is greater than or equal to a threshold value. When it is determined that the number of line segments in the detected feature value of the dot selected from the image is less than a threshold while collating the detected feature value of the dot with the reference feature value database, The detected feature quantity of the dot and the reference feature quantity database are not collated, and other dots in the image are selected through the detected feature quantity calculating means.

  The moving object position detection system according to claim 5 of the present invention is the moving body position detection system according to any one of claims 1 to 4, wherein the feature amount matching unit determines the detected feature amount as a predetermined value in the reference feature amount database. It collates with the reference | standard feature-value of the collation range of the magnitude | size.

  The moving body position detection system according to claim 6 of the present invention is the moving body position detection system according to claim 5, wherein the collation range is determined by a maximum moving speed of the moving body and an image acquisition time interval of the imaging means. It is characterized in that it is set in a peripheral region that encompasses the possible range.

  A moving body position detection system according to a seventh aspect of the present invention is the moving body position detection system according to any one of the first to sixth aspects, wherein the fixed side device is fixed at a predetermined position, and the fixed body device moves together with the moving body and is fixed by wireless communication. A fixed-side device having the reference feature amount storage unit, while the movable-side device has the imaging unit, the detected feature amount calculating unit, and the feature amount collating unit. It is characterized by that.

  According to the moving body position detection system of the present invention, compared to a case where detection is performed using a pattern encoded in correspondence with a plane coordinate value as in a conventional position detection system, a pattern arranged on a plane is reduced. The degree of freedom in design can be improved.

  Exemplary embodiments of a mobile body position detection system according to the present invention will be described below in detail with reference to the accompanying drawings. Below, the example which the mobile body which moves on the floor in a building detects an own position is demonstrated.

(Embodiment 1)
FIG. 1 is a conceptual diagram of a moving body position detection system 1 according to the present embodiment. A left diagram of FIG. 2 is a diagram showing an example of a dot pattern 3 arranged on a floor surface 2, and a right diagram is a dot diagram. 6 is a diagram illustrating an example of an image obtained by capturing a partial region of a pattern 3. FIG. FIG. 3 is a conceptual diagram of collation processing in the moving body position detection system 1.

  A moving body position detection system 1 illustrated in FIG. 1 is provided in a dot pattern 3 arranged on a floor surface 2 in a building and a moving body (not shown), and moves on the floor surface 2 together with the moving body. The moving body position detecting device 10 is configured to be. Here, the moving body is, for example, a transport carriage, a robot, or a human. The dot pattern 3 is randomly arranged on the floor 2 by means such as printing or drawing. The moving body position detection apparatus 10 includes an imaging unit 11 and a control unit 15 that detects the position of the moving body by processing an image captured by the imaging unit 11.

  As shown in FIG. 3, the moving body position detection apparatus 10 calculates in advance the feature amounts of all the dots 5 in the dot pattern 3 on the floor 2 before detecting the moving body, and uses this as the reference feature amount. Accumulate in database 16. This feature amount is calculated by calculating the positional relationship between the individual dots 5 in the dot pattern 3 and the plurality of dots 5 located around the individual dots 5, and the calculated positional relationship is calculated on the floor 2 of the individual dots 5. Is associated with the coordinate value at. Hereinafter, this is referred to as “reference feature amount”.

  Further, when moving with the moving body, the moving body position detection device 10 picks up an area on the floor surface 2 where the mobile body position detection apparatus 10 is located, selects a predetermined dot 5A from a plurality of dots 5 in the acquired image, The feature amount of the dot 5A is calculated. This feature amount is obtained by calculating the positional relationship between the dot 5A in the image and a plurality of dots 5B located around the dot 5A. Hereinafter, this is referred to as “detected feature amount”.

  Then, the moving body detection device 10 collates the detected feature quantity of the dot 5A in the acquired image with the reference feature quantity database 16 created in advance, and selects the reference feature quantity having the highest degree of coincidence from the reference feature quantity database 16. The coordinate value of the selected reference feature value is detected as the current position of the moving object on the floor surface 2.

[Create dot pattern]
4A and 4B are diagrams for explaining an example of a method for creating the dot pattern 3 on the floor 2. The plurality of dots 5 constituting the dot pattern 3 are in principle randomly printed. However, if the dots 5 are completely randomly shot, the minimum number of dots 5 necessary for the imaging region of the imaging unit 11 is required. It can happen that there is no. In such a case, since it becomes impossible to detect the position of the moving body, the floor surface is such that the minimum required number of dots 5 are present in the image no matter which region on the floor surface 2 is imaged. It is necessary to hit the dots 5 uniformly on 2.

  In consideration of the above points, in the present embodiment, as shown in FIG. 4A, the floor surface 2 is divided into a plurality of square blocks (regions) 4, and each block 4 has a random position. A dot pattern 3 is created by hitting two dots 5. Various methods are conceivable for randomly placing dots 5 in each block 4, but in this embodiment, each block 4 is subdivided into 4 N square small blocks, and each block 4 A method is adopted in which a numerical value is randomly generated corresponding to the above, one small block is selected based on this numerical value, and the dot 5 is assigned to the center of the selected small block.

For example, as the simplest example, as shown in FIG. 4B, the block is divided into four (four to the power of 4) square small blocks 4a to 4d, and according to a randomly generated numerical value λ _ij. The dot 5 is hit on any one of the small blocks 4a to 4d. Here, i and j in λ _ij are numbers indicating the position of the block 4, i is a number in the block vertical direction, and j is a number in the block horizontal direction. As shown in FIG. 4B, if the range is 0 <λ _ij ≦ 0.25, the dot 5 is hit on the small block 4a. If the range is 0.25 <λ _ij ≦ 0.50, the dot 5 is hit on the small block 4b. If the range is 0.50 <λ _ij ≦ 0.75, the dot 5 is hit on the small block 4c. If the range is 0.75 <λ _ij ≦ 1.0, the dot 5 is hit on the small block 4d. For example, as shown in FIG. 4A, since λ ₁₁ is 0.78, dot 5 is hit on the small block 4d, and since λ ₁₂ is 0.32, dot 5 is hit on the small block 4a. . By performing this process for all the blocks 4 on the floor 2, the dot pattern 3 can be created. The above-described method for creating the dot pattern 3 is an example, and various other creation methods are conceivable.

[Create reference feature database]
Next, a method for calculating the reference feature amount of each dot 5 in the dot pattern 3 will be described. As shown in FIG. 5, a circle having a predetermined radius centered on a dot 5a to be calculated is assumed. Hereinafter, the dot 5a is referred to as “center dot 5a”. The radius of this circle is not particularly limited, but in this embodiment, the radius of the circle is 1.25 times the length of one side of the block 4. In the example shown in FIG. 5, there are five peripheral dots 5 b _{1 to 5} b 5 in a circle area centered on the center dot 5 a.

Next, draw a five arms connecting the center dot 5a and the peripheral dots _5b 1 _{~5b 5} (segment) to select based on the one of the arms of the arms 6a to 6e, the arm and the other 4 The direction of each arm 6a-6e is calculated | required from the angle which the arm makes. Further, the lengths of the five arms 6a to 6e are obtained.

Positional relationship between the center dots 5a and the peripheral dots _5b 1 _{~5b 5} is composed of a number of arms 6a to 6e, the arrangement direction of each arm 6a to 6e, the sequence length of each arm 6a to 6e . Taking the central dot 5a shown in FIG. 5 as an example, the number of arms is 5, and the arrangement of the directions of the arms 6a to 6e is (0, 90, 150, 240, 300) on the basis of the arm 6a. The array having a length of ˜6e is represented as (1, 0.5, 1.2, 0.5, 1.2), where the length of one side of the block 4 is 1. Hereinafter, the arrangement in the direction of the arm is omitted and referred to as “arm direction arrangement”, and the arrangement of the length of the arm is omitted and referred to as “arm length arrangement”.

  For all the dots 5 on the floor 2, the number of arms, the arrangement in the direction of the arm, and the arrangement of the lengths of the arms described above are calculated and associated with the coordinate values on the floor 2 of each dot 5. The reference feature amount. The reference feature values of all the dots 5 arranged on the floor surface 2 are accumulated in the reference feature value database 16.

[Moving object position detection processing]
Next, the process in which the moving body position detection apparatus 10 detects the position of the moving body on the floor 2 will be described. FIG. 6 is a block diagram of the moving body position detection apparatus 10. As shown in FIG. 6, the moving body position detection apparatus 10 includes an imaging unit 11, a dot pattern creation unit 12, a reference feature value calculation unit 13, a reference feature value storage unit 14, and a control unit 15.

  The imaging unit 11 is an image acquisition device such as a CCD camera. The imaging unit 11 is fixed to a moving body, and while moving with the moving body, captures an area on the floor surface 2 where the moving body is located at a predetermined time interval, and acquires an image as shown in FIG. . In the present embodiment, images are acquired at a time interval of about 10 ms, for example, using a high-speed camera. Moreover, as shown in FIG. 1, the distance between the imaging part 11 and the floor surface 2 is several centimeters, and the image with little influence of disturbance light is acquirable by using the illumination 11a.

  The dot pattern creation unit 12 calculates the positions of the individual dots 5 arranged on the floor 2 and creates the dot pattern 3. The procedure for creating the dot pattern 3 is as described above.

  The reference feature quantity calculation unit 13 calculates the reference feature quantity of all the dots 5 in the dot pattern 3 created by the dot pattern creation unit 12. The calculation procedure of the reference feature amount is as described above.

  The reference feature quantity storage unit 14 is a part that stores the reference feature quantity of each dot 5 calculated by the reference feature quantity calculation unit 13 and includes the reference feature quantity database 16 described above.

  The control unit 15 detects the position of the moving body on the floor 2 by processing the image picked up by the image pickup unit 11, and includes a detection feature amount calculation unit 17 and a feature amount comparison unit 18. Yes.

  As shown in FIG. 3, the detection feature amount calculation unit 17 selects a dot 5 </ b> A (hereinafter referred to as “center dot 5 </ b> A”) located near the center of the image from the plurality of dots 5 in the image acquired by the imaging unit 11. And the positional relationship between the selected dot 5A and a plurality of dots 5B located around the dot 5A is calculated as a detected feature amount of the dot 5A.

The detected feature amount is calculated in the same manner as the reference feature amount calculation method described above. In the acquired image shown in FIG. 3, a circle having a predetermined radius with the center dot 5A as the center is assumed. The radius of this circle is the same as the radius of the circle when the reference feature value is calculated. In the example shown in FIG. 3, there are five peripheral dots 5 </ b> B _{1 to 5} </ b> B 5 in a circular area centered on the central dot 5 </ b> A. Draw _five arms 6A to 6E that connect the center dot 5A and the peripheral dots 5B _{1 to} 5B ₅ and select any one of the five arms 6A to 6E as a reference. The direction of each arm is determined from the angles θ _{1 to} θ ₅ (θ ₁ is 0 °) formed by the four arms. Further, the lengths L _{1 to} L ₅ of the _five arms 6A to 6E are obtained. That is, the detected feature amount of the center dot 5A includes the number of arms 6A to 6E, the arm direction array (θ ₁ , θ ₂ , θ ₃ , θ ₄ , θ ₅ ), and the arm length array (L ₁ , L ₂ , L _3, represented de _L 4, _{L 5)} and.

  The feature amount collation unit 18 collates the detected feature amount of the dot 5A in the acquired image calculated by the detected feature amount calculation unit 17 with the reference feature amount database 16, and from the reference feature amount database 16, the degree of coincidence with the detected feature amount is the highest. A high standard feature value is selected. Then, the coordinate value of the selected reference feature value is detected as the current position of the moving object on the floor surface 2.

  7-10 is a flowchart which shows the flow of the process which the control part 15 of the moving body position detection apparatus 10 comprised as mentioned above performs. FIG. 7 is a main flowchart, and FIGS. 8 and 9 are sub-flowcharts of FIG. FIG. 10 is a sub-flowchart of FIGS. Hereinafter, the processing procedure executed by the control unit 15 will be described with reference to FIGS.

  As shown in FIG. 7, the moving body position detection device 10 repeats detection of the current position of the moving body at predetermined time intervals after the moving body starts moving on the floor surface 2. There are two procedures for detecting the current position of the moving object: a procedure SUB1 shown in FIG. 8 and a procedure SUB2 shown in FIG. First, the procedure shown in FIG. 8 will be described.

  As shown in FIG. 8, when acquiring image data from the imaging unit 11 (step S11), the control unit 15 selects one dot 5 (center dot 5A) from a plurality of dots 5 in the image, and detects a feature amount. The detection feature amount of the center dot 5A is calculated through the calculation unit 17 (step S12). Here, as described above, the detected feature amount is the number of arms connecting the center dot 5A and the plurality of peripheral dots 5B, the arm direction array, and the arm length array. When the number of arms of the center dot 5A is equal to or greater than the threshold (step S13: Yes), the control unit 15 collates the detected feature amount of the center dot 5A with the reference feature amount database 16 through the feature amount collation unit 18 (SUB3). ). On the other hand, if the number of arms in the center dot 5A is less than the threshold value (step S13: No), another dot 5 in the image is newly selected as the center dot 5A without collating with the reference feature amount database 16 (step S13). S14) Returning to step S12, the detection feature amount of the newly selected center dot 5A is calculated. Here, the threshold value of the number of arms in step 13 is appropriately set according to the density of the dots 5 of the dot pattern 3 or the like. In this embodiment, the number of arms is four.

  The reason why the threshold value is provided for the number of arms of the detected feature amount in step S13 is that, when the number of arms is small, the rate at which the collation result is determined as one decreases, and the purpose is to speed up the calculation. However, step S13 is not necessarily provided, and step S13 may be omitted.

  The process of matching the detected feature quantity with the reference feature quantity database (SUB3) is performed according to the procedure shown in FIG. First, a dot that matches the arrangement in the arm direction of the center dot 5A in the image is selected from the reference feature quantity database 16 (step S41).

  As described above, the reference feature quantity database 16 stores one type of array composed of angles formed by a specific reference arm and another arm as an arm direction array of each dot. Accordingly, there is a possibility that the reference arm in the arm direction arrangement of the center dot 5A in the image and the reference arm in the dot arm arrangement of the reference feature quantity database 16 do not necessarily match. Therefore, an array using each arm as a reference arm is created as an array in the arm direction of the center dot 5A in the image. That is, when the number of arms is five like the central dot 5A in the image shown in FIG. 3, five types of arm direction arrangements are made with the five arms as reference arms, and the five types of arm directions are formed. The arrangement is checked against the arrangement in the arm direction of the reference feature quantity database 16.

When the arm direction arrangements match, the degree of coincidence between the arm length arrangement of the reference feature database 16 with the matching arm direction arrangement and the arm length arrangement of the center dot 5A in the image is obtained (step S42). As described above, the arm length array of each dot in the reference feature quantity database 16 stores one kind of array in which the arm lengths are arranged in order from a specific reference arm. For this reason, when obtaining the degree of coincidence of the arm length arrays, an array in which the order of the arm lengths of the center dots 5A in the image is rearranged is also created. That is, when the number of arms is five like the central dot 5A in the image shown in FIG. 3, (L ₁ , L ₂ , L ₃ , L ₄ , L ₅ ), (L ₂ , L ₃ , L ₄ , L ₅ , L ₁ ), (L ₃ , L ₄ , L ₅ , L ₁ , L ₂ ), (L ₄ , L ₅ , L ₁ , L ₂ , L ₃ ), (L ₅ , L ₁ , L ₂ , L ₃ , L ₄ ), and the degree of coincidence between the five types of arm length arrays and the arm length array of the reference feature database 16 is determined. Then, the one having the highest degree of matching is selected from these (step S43).

  As an example of a method for obtaining the degree of matching of the arm length arrays, there is a method described below. The above five types of arm length arrays are divided by the size of each array to form a unit vector. Also, the arm length array of the reference feature amount is divided by the array size into a unit vector. Then, the inner product of each of the five types of arm length arrays (unit vectors) and the reference feature amount arm length array (unit vector) is calculated, and the value of the inner products is used as the degree of coincidence. That is, the one with the inner product value closest to 1 is assumed to have the highest degree of coincidence. Note that the use of the inner product value as the matching degree of the arm length array is merely an example, and other methods can be used.

  Note that the collation of the arm direction arrangement and the reference for the degree of coincidence of the arm length arrangements have an allowable range for errors caused by image resolution and the like.

  After the reference feature database matching process SUB3 is completed, as shown in FIG. 8, the control unit 15 determines whether there is one that matches the center dot 5A in the image (step S15). . If there is only one coincidence (step S15: Yes), the plane coordinate value of the coincident dot in the reference feature database 16 is detected as the current position of the moving object (step S16).

  On the other hand, if there are a plurality of matches (step S15: No), the collation result is not adopted, the process returns to step S14, and another dot 5 in the image is newly selected as the center dot 5A. The detected feature amount of the selected center dot 5A is calculated (step S12). Thereafter, the processes from step S12 to step S15 are repeated until the collation result is finally determined as one.

  Thereafter, the imaging unit 11 performs imaging at a predetermined time interval, and the control unit 15 repeats the above-described detection processing S11 to S16 of the current position of the moving body.

  Next, a case where the procedure shown in FIG. 9 is adopted as a procedure for detecting the current position of the moving body will be described.

As shown in FIG. 9, when acquiring image data from the imaging unit 11 (step S21), the control unit 15 selects the first dot 5 (first central dot 5A ₁ ) from the plurality of dots 5 in the image. and, through the detection feature quantity calculating unit 17 calculates the detected feature amount of the first central dot 5A ₁ (step S22). Control unit 15, when the arm number in the first center dot 5A ₁ is equal to or larger than the threshold (step S23: Yes), through the feature checker 18, the reference feature amount database detected feature amount of the first central dot 5A ₁ 16 is matched (SUB3). On the other hand, when the arm number in the first center dot 5A ₁ is less than the threshold value (step S23: No), without matching the reference feature quantity database 16, the first center dot 5A another dot 5 in the image newly selected as ₁ (step S24), and newly calculates the detected feature amount of the first central dot 5A ₁ selected returns to step S22.

Performs verification processing of steps S41~S43 of SUB3 shown in FIG. 10, the reference feature quantity database 16, selects the first center dot 5A ₁ the highest degree of coincidence dots in the image. When a plurality of dots are selected, these are set as “matching candidate group” (step S25).

Next, the control unit 15 selects the second dot 5 (second center dot 5A ₂ ) from the plurality of dots 5 in the image, and the detection feature of the second center dot 5A ₂ through the detection feature amount calculation unit 17. The amount is calculated (step S26). When the number of arms in the second center dot 5A ₂ is equal to or greater than the threshold value (step S27: Yes), the control unit 15 uses the feature amount matching unit 18 to detect the detected feature amount of the second center dot 5A _{2 in} the reference feature amount database. 16 is matched (SUB3). On the other hand, when the arm number of second central dot 5A ₂ is less than the threshold value (step S27: No), without matching the reference feature quantity database 16, the second center dot 5A another dot 5 in the image newly selected as ₂ (step S28), newly calculates the selected detection feature quantity of the second central dot 5A ₂ returns to step S26.

Performs verification processing of steps S41~S43 of SUB3 shown in FIG. 10, the reference feature quantity database 16, selects a second center dot 5A ₂ the highest degree of coincidence dots in the image. When a plurality of dots are selected, these are set as a “matching candidate group” (step S29).

Then, the control unit 15, a first matching candidate group of the center dot 5A ₁ in step S25, the combination of the second matching candidate group of the center dot 5A ₂ in step S29, to select an appropriate combination (step S30) . Specifically, the distance between the two dots, the equal to the first center dot 5A ₁ in the acquired image and the distance between the second center dot 5A _2, is selected as the optimum combination.

  Next, the control unit 15 detects the floor coordinate value of the midpoint of the two dots selected from each matching candidate group as the optimal combination as the current position of the moving object (step S31).

  In the processing of SUB1 described above, until the matching result of the reference feature value database 16 is finally determined to be one, the calculation of the detected feature value and the matching process are repeated by changing the center dot 5A in the image. In the SUB2 process described later, it is not necessary to perform these processes many times, and the current position can be specified by a single process. Therefore, the SUB2 process has an advantage that the detection time is faster than the SUB1 process.

  As described above, the moving body position detection system 1 according to the present embodiment has a dot pattern 3 composed of a plurality of dots 5 arranged on the floor 2, the individual dots 5, and positions around the dots 5. The reference feature database 16 for calculating the positional relationship with the plurality of dots 5 and storing the positional relationship as the reference feature in association with the coordinate values of the individual dots 5 on the floor, and the moving body are located. An imaging unit 11 that captures an area on the floor surface 2 and a predetermined center dot 5A is selected from a plurality of dots 5 in the image acquired by the imaging unit 11, and the center dot 5A is located around the center dot 5A. By detecting the positional relationship with the plurality of dots 5B as a detected feature amount of the dot 5A, the detected feature amount of the dot 5A is collated with the reference feature amount database 16, so that the dot 5 A feature amount matching unit 18 that selects a reference feature amount having the highest degree of coincidence with the detected feature amount and detects the coordinate value of the reference feature amount as the current position of the moving object on the floor 2 is provided. . That is, in this embodiment, since the method of encoding the dot pattern 3 corresponding to the floor surface coordinate value is not adopted, the pattern encoded corresponding to the floor surface coordinate value as in the conventional position detection system is used. The degree of freedom in designing the pattern on the floor surface can be improved as compared with the case where the detection is performed using it.

  Specifically, it is possible to arrange a random dot pattern on the floor surface as compared with the case where detection is performed using a pattern encoded corresponding to the floor surface coordinate value.

  Furthermore, when using a dot pattern encoded corresponding to the floor surface coordinate value as in the past, if the dirt of the dot size is attached to the floor surface, the encoded pattern of that portion cannot be restored. However, according to the moving object position detection system of the present embodiment, in the reference feature value database, the reference feature value having a center dot within a predetermined circle from the dot generated due to the attached dirt. The position detection function can be maintained by recalculating and updating the reference feature amount in addition to the dots generated due to the attached dirt.

  Furthermore, according to the moving body position detection system 1 of the present embodiment, although it depends on the spatial resolution of the image, it can be expected that the accuracy is equal to or greater than the spatial length corresponding to one pixel of the camera of the imaging unit 11.

(Embodiment 2)
Next, the moving body position detection system according to the second embodiment will be described. Note that the same components as those in the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  FIG. 11 is a block diagram of the moving body position detection apparatus 10 according to the second embodiment. In the first embodiment described above, the detected feature quantity of the center dot 5A in the acquired image is collated with all the reference feature quantities in the reference feature quantity database 16, and the reference feature having the highest degree of coincidence is obtained from the entire reference feature quantity database 16. The amount was selected. In this case, if the accumulation amount of the reference feature database 16 is enormous, the calculation time becomes long and the possibility that a plurality of data is extracted increases. For this reason, in the second embodiment, the detected feature amount of the center dot 5A in the acquired image is collated with the reference feature amount of the collation range of a predetermined size in the reference feature amount database 16. Other configurations are the same as those in the first embodiment. In the following description, the reference feature quantity in the reference range of a predetermined size in the reference feature quantity database 16 is referred to as “reference feature quantity data list 20”.

  When the detected feature amount of the center dot 5A in the image is collated with the reference feature amount data list 20, the calculation time becomes long if the size of the reference feature amount data list 20 (that is, the collation range) is large. For this reason, the collation range is a minimum necessary range. The size of the collation range can be determined as follows.

FIG. 12 conceptually shows the trajectory of the moving body that moves on the floor surface 2. Points P _{1 to} P _n in FIG. 12 respectively represent the position of the moving body at the time of image acquisition by the imaging unit 11, that is, the detection position of the moving body. The imaging unit 11 acquires images at regular time intervals. Point P ₁ is the initial position of the moving body (movement start position). An in-circle region C ₁ having a predetermined radius with the initial position P ₁ as the center is the above-described collation range. The collation range C _1, specifically, means a range for searching the position P ₂ of the mobile during the next image acquisition.

As shown in FIG. 12, collation range C ₁ is the region encompassing the movable range M ₁ from the initial position P ₁ of the moving body. The movable range M ₁ of the moving body means a moving range of the moving body determined from the maximum moving speed of the moving body and the image acquisition time interval. To explain with a specific example, if the image acquisition interval of the imaging unit 11 is 10 ms (1/100 second) and the maximum moving speed of the moving body is 1.0 m / s, the image acquisition interval of 10 ms for one time In between, the moving body advances 10 mm. In this case, the movable range M ₁ of the moving body is within a circular area having a radius of 10 mm with the moving body as the center. In other words, the movable range is a range in which the moving body can move between the time when the imaging unit 11 acquires an image and the time when the next image is acquired. Therefore, collation range C _1, it is necessary to set larger than the movable range M _1, as shown in FIG. 12 is set to be larger region around slightly larger than the movable range M _1, the next image the position P ₂ of the moving body can be reliably detected at the time of acquisition.

  The reference feature quantity data list 20 extracted from the reference feature quantity database 16 is temporarily stored in the storage unit 19 as shown in FIG.

  FIG. 13 is a flowchart showing a flow of processing executed by the control unit 15 of the moving object position detection apparatus 10 configured as described above. SUB1 and SUB2 in FIG. 13 are the same as the procedures shown in FIGS. Hereinafter, the procedure executed by the control unit 15 will be described with reference to FIG. Hereinafter, only the processing of SUB1 will be described, and description of the processing of SUB2 will be omitted.

First, the control unit 15 performs detection of the initial position P ₁ of the moving body. In process of detecting the initial position P _1, as in the first embodiment described above, to match the overall reference feature quantity database 16. Upon obtaining the image data of the initial position P ₁ of the moving object from the imaging unit 11 (SUB1: step S11), and selects one of the dot 5A (center dot 5A) a plurality of dots in an image, detected feature quantity calculating unit 17 Then, the detected feature amount of the center dot 5A is calculated (SUB1: step S12). When the number of arms of the center dot 5A is equal to or greater than the threshold (SUB1: Step S13: Yes), the control unit 15 collates the detected feature amount of the center dot 5A with the reference feature amount database 16 through the feature amount collation unit 18. (SUB3). On the other hand, when the number of arms in the center dot 5A is less than the threshold (SUB1: Step S13: No), another dot in the image is newly selected as the center dot 5A without collating with the reference feature amount database 16 ( SUB1: Step S14), returning to step S12, the detection feature amount of the newly selected center dot 5A is calculated. Here, the threshold value of the number of arms in step 13 is set to four as in the first embodiment.

The process of matching the detected feature quantity of the center dot 5A in the image with the reference feature quantity data list 20 (SUB3) is performed according to the procedure shown in FIG. The description is omitted here. After the reference feature database matching process SUB3 is completed, as shown in FIG. 10, the control unit 15 determines whether there is one that matches the center dot 5A in the image (SUB1: step). S15). If there is only one coincidence (SUB1: Step S15: Yes), the plane coordinate value on the floor F of the coincident dot in the reference feature database 16 is detected as the current position. The plane coordinate value, the current position of the initial position _{P 1} (SUB1: step S16).

  On the other hand, if there are multiple matches (SUB1: Step S15: No), the matching result is not adopted, and another dot 5 in the image is newly selected as the center dot 5A (SUB1: Step S14). Then, the detected feature amount of the newly selected center dot 5A is calculated (SUB1: step S12). Thereafter, the processes from step S12 to step S15 are repeated until the collation result is finally determined as one.

When the control unit 15 detects the initial position P ₁ of the moving object, the control unit 15 extracts, from the reference feature value database 16, a reference feature value data list 20 of dots in the collation range C ₁ centered on the initial position P _1. Is stored in the storage unit 19 (FIG. 13: step S1). Then, to start the process of detecting the current position of the mobile object _{(P 2)} (SUB1).

  When acquiring image data from the imaging unit 11 (SUB1: step S11), the control unit 15 selects one dot (center dot 5A) from a plurality of dots in the image, and through the detected feature amount calculation unit 17, the center dot is selected. The detection feature amount of 5A is calculated (SUB1: Step S12). When the number of arms in the center dot 5A is equal to or greater than the threshold (SUB1: Step S13: Yes), the control unit 15 sends the detected feature amount of the center dot 5A to the reference feature amount data in the storage unit 19 through the feature amount matching unit 18. The list 20 is checked (SUB3). On the other hand, when the number of arms in the center dot 5A is less than the threshold (SUB1: Step S13: No), another dot 5 in the image is newly selected as the center dot 5A without collating with the reference feature amount data list 20. (SUB1: Step S14), the process returns to Step S12 to calculate the detected feature amount of the newly selected center dot 5A.

Control unit 15, in step S41~ step S43 in SUB3 collates the reference feature amount data list 20 in the comparison range C _1, that coincides with the center dot 5A in the image is equal to or one (SUB1: Step S15). If a match was was one (SUB1: Step S15: Yes), the plane coordinates on the floor F of the matched dots of the reference feature amount data list 20, as the current position P ₂ of the mobile Detect (SUB1: Step S16).

After detecting the current position P ₂ of the moving body, the control unit 15 extracts the reference feature value data list 20 of the next collation range C ₂ from the reference feature value database 16 and stores it in the storage unit 19 ( FIG. 13: Step S1). As described above, the control unit 15 thereafter repeats the detection process of the current position (P ₃ , P ₄ ,..., P _n ,...) Of the moving body.

As described above, in the moving body position detection system 1 according to the second embodiment, the reference feature quantity data list 20 of dots in the collation range C _n narrowed down from the reference feature quantity database 16 around the movable range of the moving body is stored. Extract. Then, by collating the detected feature amount calculated by the detected feature amount calculating unit 17 with the reference feature amount data list 20 in the collation range C _n , the reference feature amount having the highest degree of coincidence with the detected feature amount is selected, After the coordinate value of the selected reference feature value is detected as the current position P _{n + 1} of the moving object on the floor 2, a reference feature value data list of P _{n + 1} in the next collation range centered on the current position P _{n + 1} is extracted. It is configured to do. By configuring as described above, in addition to the effect described in the first embodiment, there is an effect that the calculation speed of the position detection of the moving body can be further increased as compared with the first embodiment.

(Embodiment 3)
Next, the moving body position detection system 1 ′ according to the third embodiment will be described. In addition, about the structure same as the said Embodiment 1, 2, the same code | symbol is used and the description is abbreviate | omitted.

  FIG. 14 is a conceptual diagram of a moving body position detection system 1 ′ according to the third embodiment. When it is assumed that the position of a moving body is detected in various areas, it is necessary to have all the reference feature database 16 unique to the floor of each area, and the amount of storage in the reference feature database 16 is enormous. turn into. Even when detection is performed only within one area, if the floor area of the area is large, the amount of storage in the reference feature database becomes enormous. Therefore, in the present embodiment, the moving body position detection device 10 is constituted by a fixed side device 20 fixed at a predetermined position in the building and a moving body side device 30 provided in the moving body, and the fixed side device 20. The reference feature quantity database 16 of the dot pattern on the floor of the entire building is stored, and various data are transmitted and received between the fixed-side device 20 and the mobile-side device 30 by wireless communication. The method for creating the dot pattern 3, the method for calculating the reference feature amount of each dot in the dot pattern 3, and the method for calculating the detected feature amount of the dot selected from the acquired image have been described in the first and second embodiments. The method is the same.

Below, the example which performs the position detection of a mobile body in the area of several places is demonstrated. The fixed-side device 20 includes reference feature database 16 ₁ , 16 ₂ ,... Unique to the floor surface of a plurality of areas (area 1, area 2,..., Area m-1, area m,...). , 16 _m−1 , 16 _m ,.

FIG. 15 is a block diagram of the fixed device 20 and the mobile device 30. The fixed-side device 20 includes a dot pattern creation unit 12, a reference feature value calculation unit 13, a reference feature value storage unit 14a, a control unit 15a, and a wireless communication unit 21a. As described above, the reference feature value database 16 for all floors of the building is stored in the reference feature value storage unit 14a. The reference feature value database 16 is a reference feature value database 16 ₁ unique to each floor surface of a plurality of areas. , 16 ₂ ,..., 16 _m−1 , 16 _m ,. On the other hand, the mobile device 30 includes an imaging unit 11, a reference feature amount storage unit 14b, a control unit 15b, a storage unit 31, and a wireless communication unit 21b. Reference characteristic amount storage unit 14b is one which has a memory of a degree capable of storing the reference feature database 16 _m in one area which is transmitted from the fixed device 20.

As described below, the fixed-side device 20, the reference feature quantity database 16, selects the reference characteristic quantity database 16 _m of location area of a mobile, which the wireless communication unit 21a, the movable body side apparatus via the 21b 30. Here, the “location area of the moving object” means an area where the moving object is currently located. Mobile side apparatus 30 stores the reference feature database 16 _m of location area of the mobile object received from the fixed device 20 to the reference feature amount storage unit 14b. Then, a predetermined dot (center dot 5A) is selected from a plurality of dots 5 in the image picked up by the image pickup unit 11 to calculate a detected feature amount, and this is calculated as a reference feature amount database 16 of the area where the moving body is located. The current position of the moving body is detected by collating with a partial collation range of _m . Hereinafter, the collation range extracted from the reference feature value database 16 _{m of the} area where the mobile object is located is referred to as a reference feature value data list 20. The reference feature value data list 20 is temporarily stored in the storage unit 31.

Also in the third embodiment, as in the second embodiment described above, the size (collation range) of the reference feature amount data list 20 is set to a necessary minimum range. The concept of “collation range” is as described in the second embodiment. That is, the collation range C _n means a range in which the position P _{n + 1} of the moving object is searched at the time of the next image acquisition, and is a peripheral that includes the movable range M _n from the current position P _n of the moving object. Region (see FIG. 12).

  FIG. 16 is a flowchart showing a flow of processing executed by the control unit 15a of the fixed-side device 20 and the control unit 15b of the moving body-side device 30 configured as described above. In the detection process of the current position of the moving body, the procedure of SUB1 in FIG. 8 or SUB2 in FIG. 9 is performed as in the first and second embodiments. Also, the reference feature database matching process uses the procedure of SUB 3 in FIG. 10 as in the first and second embodiments. Hereinafter, the processing procedure executed by the control unit 15a and the control unit 15b will be described with reference to FIGS.

Control unit 15b of the movable body side apparatus 30 acquires the image data of the initial position P ₁ of the moving object from the imaging unit 11 (step S51), the position data of the dot group in the image on the fixed side unit 20 by the wireless communication It sends an initial position P ₁ of the moving body, and requests the reference feature database of location area of a mobile (step S52).

Control unit 15a of the stationary device 20 that has received the position data of the dot group in the image, performs a process of detecting the initial position P ₁ of the moving object as follows (SUB1). First, the control unit 15a selects one dot 5 (center dot 5A) from the plurality of dots 5 in the image, and calculates the detected feature amount of the center dot 5A through the detected feature amount calculation unit 17a (SUB1: step). S12). When the number of arms in the detected feature amount of the center dot 5A is equal to or greater than the threshold (SUB1: Step S13: Yes), the control unit 15a of the fixed-side device 20 detects the detected feature amount of the center dot 5A through the feature amount matching unit 18a. Is compared with the reference feature database 16 (SUB3). On the other hand, when the number of arms in the center dot 5A is less than the threshold (SUB1: Step S13: No), another dot 5 in the image is newly selected as the center dot 5A without collating with the reference feature quantity database 16. (SUB1: Step S14), the process returns to Step S12 to calculate the detected feature amount of the newly selected center dot 5A.

  The process of collating the detected feature quantity with the reference feature quantity database 16 performs steps S41 to S43 of SUB3 in FIG.

The control unit 15a of the fixed-side device 20 determines whether or not there is one that matches the center dot 5A in the image after performing the SUB3 collation process (SUB1: step S15). If a match was was one (SUB1: Step S15: Yes), the plane coordinates in the matching dot of reference feature value database 16, is detected as an initial position _{P 1} of the moving body (SUB1: Step S16). Then, the control unit 15a detects the location area of the mobile from the initial position _{P 1} of the moving body (16: step S62).

Control unit 15a of the stationary device 20 detects the initial position P ₁ and a predetermined area of the moving body, transmitting a reference feature amount database 16 _m-1 in the initial position data and the location area to the mobile body side apparatus 30 (step S62). Control unit 15b of the movable body side apparatus 30 receives the reference characteristic quantity database 16 _m-1 in the initial position data and the location area of the mobile (step S53), the reference, wherein the reference feature quantity database 16 _m-1 the location area The collation range is determined from the reference feature quantity database 16 _m-1 and the initial position P _{1 of the} location area stored in the quantity storage unit 14b (step S54). That is, the reference feature quantity data list 20 of all the dots 5 in the collation range C ₁ centered on the initial position P ₁ of the moving object is extracted from the reference feature quantity database 16 _{m-1 of} the location area, and this collation range. The C ₁ reference feature data list 20 is temporarily stored in the storage unit 31. And the detection process of the present position of a moving body is started (SUB1).

  When acquiring the image data from the imaging unit 11 (SUB1: Step S11), the control unit 15b of the mobile device 30 selects one dot 5 (center dot 5A) from the plurality of dots 5 in the image, and detects the feature amount. The detection feature amount of the center dot 5A is calculated through the calculation unit 17b (SUB1: Step S12). When the number of arms in the center dot 5A is equal to or greater than the threshold (SUB1: Step S13: Yes), the control unit 15b of the moving body device 30 stores the detected feature amount of the center dot 5A through the feature amount matching unit 18b. Are compared with the reference feature quantity data list 20 (SUB3). On the other hand, when the number of arms in the center dot 5A is less than the threshold (SUB1: Step S13: No), another dot 5 in the image is newly selected as the center dot 5A without collating with the reference feature amount data list 20. (SUB1: Step S14), the process returns to Step S12 to calculate the detected feature amount of the newly selected center dot 5A.

Or control unit 15b of the movable body side apparatus 30 in step S41~ step S43 in SUB3 collates the reference feature amount data list 20 in the comparison range _{C 1,} that coincides with the center dot 5A in an image is one It is determined whether or not (SUB1: Step S15). If a match was was one (SUB1: Step S15: Yes), the plane coordinates of the matched dots of the reference feature amount data list 20 is detected as the current position _{P 2} of the mobile (SUB1: Step S16).

Control unit 15b of the movable body side apparatus 30, after detecting the current position P ₂ of the mobile determines whether the mobile has reached the vicinity of the boundary of a location area (step S55). If the mobile does not reach the vicinity of the boundary of the location area (step S55: No), the process returns to step S54, the reference feature quantity database 16 _m-1 of the location area, and centered on the current position P ₂ of the mobile and it was extracted reference feature amount data list 20 in the comparison range C _2, and stores the reference feature amount data list 20 in the collation range C ₂ temporarily in the storage unit 31. Thereafter, the control unit 15b of the mobile device 30 repeats the detection process of the current position (P ₃ , P ₄ ,..., P _n ,...) Of the mobile device.

On the other hand, when the moving body reaches the vicinity of the boundary of the location area (step S55: Yes), the control unit 15b of the moving body side device 30 transmits the current position to the control unit 15a of the fixed side device 20, and the moving body to request the reference feature database 16 _m of location area around the current position (step S56).

Control unit 15a of the stationary device 20 transmits the reference feature database 16 _m of location area around the present position of the moving body in the moving body side device 30 (step S63). Control unit 15b of the movable body side apparatus 30 receives the reference characteristic quantity database 16 _m (step S57), which was stored in the reference characteristic quantity database 14b, the process returns to step S54, the reference feature quantity database 16 _m of location area decides from the current position _{P 2} a comparison range _{C 2.} Thereafter, the above process is repeated.

  As described above, the mobile body position detection system 1 ′ according to the third embodiment includes the fixed side device 20 fixed at a predetermined position, and the mobile side that can move with the mobile body and communicate with the fixed side device 20 by wireless communication. The apparatus 30 is provided, and the fixed-side device 20 has the reference feature value database 16, while the mobile-side device 30 has the imaging unit 11, the detected feature value calculation unit 17 b, and the feature value matching unit 18 b. With the configuration described above, the mobile device 30 can be used in various areas because the mobile device 30 does not have the reference feature database 16.

Further, in the moving body position detection system 1 ′ according to the third embodiment, the fixed-side device 20 selects the reference feature quantity database 16 _m of the moving object location from the reference feature quantity database 16 and moves this by wireless communication. It transmits to the body side device 30. On the other hand, the movable body side apparatus 30, from the reference feature quantity database 16 _m of location area of a mobile object with the received current position from the stationary device 20 determines the collation range for limiting to moving range near mobile. Then, by collating the detected feature amount calculated by the detected feature amount calculating unit 17b with the reference feature amount data list 20 in the collation range, the reference feature amount having the highest degree of coincidence with the detected feature amount is selected and selected. The coordinate value of the reference feature value thus detected is detected as the current position of the moving object on the floor surface. By the structure described above, the movable body side apparatus 30, the degree of memory capable of storing the reference feature database 16 _m of the location area of the mobile body among the reference feature quantity database 16 _m of the location area It is only necessary to have a calculation capability capable of performing position detection within the collation range narrowed around the movable range of the moving body. As a result, since the calculation load of the mobile device 30 is small, the calculation speed of position detection can be increased.

  In Embodiment 3 described above, the fixed feature device 20 transmits the reference feature amount database of the area where the moving object is located to the moving object side device 30, but the amount of data to be transmitted is allowed by the moving object device 30 side. Depends on the memory capacity. Therefore, when the memory capacity of the mobile device 30 is relatively large, the amount of data to be transmitted may be wider than the location area. On the other hand, when the memory capacity of the mobile device 30 is relatively small, the amount of data to be transmitted is set to be narrower than the location area (for example, the size of the room in the location area).

  In the above-described third embodiment, the mobile feature device 30 collates the detected feature value with the reference feature value data list. However, the fixed feature device 20 matches the detected feature value with the reference feature value data list. It is good also as a structure performed by.

  Furthermore, although Embodiment 1-3 mentioned above demonstrated the example which applied the mobile body position detection system of this invention to position detection, such as a conveyance trolley in a building, it is not limited to this, General The present invention can be widely applied to detection of the position of a moving body on a general plane.

1 is a conceptual diagram of a moving body position detection system according to a first embodiment. The left figure is a diagram showing an example of a dot pattern arranged on the floor surface, and the right figure is a diagram showing an example of an image obtained by imaging a partial region of the dot pattern. It is a conceptual diagram which shows the procedure of a mobile body position detection process. It is a figure explaining an example of the method of creating a dot pattern on a floor surface. It is a figure explaining an example of the method of creating a dot pattern on a floor surface. It is a figure explaining the standard feature-value of the dot in a dot pattern. 1 is a block diagram of a moving body position detection system according to a first embodiment. It is a flowchart which shows the flow of the process which the control part of a moving body position detection apparatus performs. It is a flowchart which shows the flow of the process which the control part of a moving body position detection apparatus performs. It is a flowchart which shows the flow of the process which the control part of a moving body position detection apparatus performs. It is a flowchart which shows the flow of the process which the control part of a moving body position detection apparatus performs. 6 is a block diagram of a moving body position detection system according to a second embodiment. FIG. It is the figure which showed notionally the locus | trajectory of the moving body which moves on a floor surface. 6 is a flowchart showing a flow of processing executed by a control unit of the mobile object position detection device according to Embodiment 2. FIG. 10 is a conceptual diagram of a moving body position detection system according to a third embodiment. FIG. 10 is a block diagram of a moving body position detection system according to a third embodiment. 10 is a flowchart showing a flow of processing executed by a control unit of the stationary device and the mobile device in Embodiment 3.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1,1 'Moving body position detection system 2 Floor surface 3 Dot pattern 4 Block 5 Dot 10 Moving body position detection apparatus 11 Imaging part 11a Illumination 12 Dot pattern creation part 13 Reference | standard feature-value calculation part 14, 14a, 14b Reference | standard feature-value storage 15, 15 a, 15 b Control unit 16 Reference feature database 17, 17 a, 17 b Detected feature calculation unit 18, 18 a, 18 b Feature verification unit 20 Fixed side device 21 a, 21 b Wireless communication unit 30 Mobile unit 31 Storage unit

Claims (7)

A moving body position detection system for detecting a position of a moving body moving on a plane,
A dot pattern consisting of a plurality of dots randomly arranged on the plane;
Calculating a positional relationship between individual dots in the dot pattern and a plurality of dots positioned around the individual dots, and associating the positional relationship with the coordinate values on the plane of the individual dots to provide a reference feature A reference feature amount storage means for storing the amount in a reference feature amount database;
An imaging means provided in the moving body for imaging a region on a plane on which the moving body is located;
A predetermined dot is selected from a plurality of dots in the image acquired by the imaging unit, and a positional relationship between the selected dot and a plurality of dots positioned around the dot is calculated as a detected feature amount of the selected dot. Detection feature amount calculating means for
By comparing the detected feature amount with the reference feature amount database, the reference feature amount having the highest degree of coincidence with the detected feature amount is selected from the reference feature amount database, and the coordinate value of the selected reference feature amount is Feature amount matching means for detecting the current position of the moving object on a plane;
A moving body position detection system comprising: The dot pattern is
The moving body position detection system according to claim 1, wherein the moving body position detection system is created by dividing the plane into a plurality of blocks and arranging dots at random positions in each block. The reference feature amount and the detected feature amount are:
An array composed of the direction of each line segment connecting a dot and a plurality of peripheral dots located in a circle area of a predetermined radius centered on the dot, and an array composed of the length of each line segment are included. Item 3. The moving object position detection system according to Item 1 or 2. The feature amount matching means includes:
When it is determined that the number of line segments in the detected feature amount of the dot selected from the image is equal to or greater than a threshold, the detected feature amount of the dot is checked against the reference feature amount database,
When it is determined that the number of line segments in the detected feature amount of the dot selected from the image is less than the threshold value, the detected feature amount is not compared with the reference feature amount database. 4. The moving body position detection system according to claim 3, wherein another dot in the image is selected through a calculation unit. The feature amount matching means includes:
5. The moving body position detection system according to claim 1, wherein the detected feature amount is collated with a reference feature amount of a collation range having a predetermined size in the reference feature amount database. . The collation range is
6. The moving body position detection system according to claim 5, wherein the moving body position detection system is set to a peripheral region including a movable range of the moving body determined from a maximum moving speed of the moving body and an image acquisition time interval of the imaging means. . A fixed-side device fixed at a predetermined position, and a mobile-side device that moves with the mobile body and can communicate with the fixed-side device by wireless communication,
While the fixed side device has the reference feature amount storage means,
The mobile body position detection system according to any one of claims 1 to 6, wherein the mobile body side device includes the imaging unit, the detected feature amount calculating unit, and the feature amount collating unit.

Images