JP3735675B2 - Object arrangement drawing creation method, program thereof, storage medium, and object arrangement drawing creation system - Google Patents

Description

  The invention of this application is a computer readable recording object layout map creation method, object layout map creation program, and object layout map creation program useful for grasping a rough layout relationship between objects scattered indoors and outdoors. The present invention relates to a storage medium and an object layout drawing creation system.

People often forget where they put things, and often use things such as glasses and keys, as well as things that are not normally used, such as bags and stamps. Sometimes I can't remember. In particular, forgetfulness becomes more prominent as the age increases, and it is difficult to keep track of the position of the object.
JP 2003-23385 A JP-A-10-83454 JP 2001-188880 A

  In this way, in order to recall the memory and remind you of the place or place where you have forgotten things, it is effective to show a layout that shows the location of each object. At present, no technology that can be created automatically has been realized.

  For example, in Patent Documents 1 to 3 described above, although a technique for attaching a tag to an object and acquiring its position is disclosed, no technical idea of creating a layout drawing has been proposed.

  In Patent Document 1, a communication tag is attached to an object, a signal radio wave corresponding to the identification number of the object to be searched for is transmitted by a portable wireless device, and the communication tag that senses the radio wave matches the recognition number Discloses a system that emits sound and light, and it is said that people can discover things with the sound and light. However, radio waves must be transmitted from the portable radio device every time an object is searched, and since different objects cannot be searched at once, they must be set once and transmitted again.

  In contrast, layouts can continue to be used as long as the object is not moved significantly from the position shown, and can be created even if it is moved, and multiple objects can be created at once. Therefore, it can be said that it is much more useful to present a layout diagram than in the case of using sound and light as described in Patent Document 1 above.

  Also, if the purpose of this effective layout is to evoke memory and help find things, it is not necessary to indicate exact positions, and if rough positions can be taught It is considered good.

  Although the above-mentioned patent document 2 does not clearly indicate that a layout drawing is to be created, it discloses a system for accurately positioning an infrared tag attached to an object from a camera image, and spatial localization for the positioning. Since the processing is performed by the computer, it can be estimated that some kind of diagram can be created using the computer. However, there is no disclosure of the technical idea of creating a layout diagram showing a rough positional relationship in order to realize the purpose of recalling memory and helping to search for an object.

  On the other hand, the above-mentioned patent document 3 discloses a system for determining the position of a tagged object, and clearly shows that low-accuracy spatial positioning is performed using a computer. However, similarly to the above-mentioned Patent Document 2, there is no technical idea of creating a rough layout diagram that is effective for helping to find an object.

  Therefore, in view of the circumstances as described above, the invention of this application creates a rough layout of objects, teaches the approximate positional relationship of multiple objects at a time, and remembers where they are placed and where they have been placed. It is an object of the present invention to provide an object arrangement drawing creation method, an object arrangement drawing creation program, a computer-readable storage medium storing the object arrangement drawing creation program, and an object arrangement drawing creation system.

  In order to solve the above-mentioned problems, the invention of this application is a method for creating an object layout diagram, in which a processing unit includes an ID tag attached to an object and a receiver. Storing the communication history data in a storage unit; a processing unit calculating a spatial distance estimate between two objects using the communication history data read from the storage unit; and the processing unit There is provided an object arrangement drawing creation method including a step of creating an arrangement drawing using a spatial distance estimation value.

  Second, the processing unit stores the tag data received by the receiver and the reception time in the storage unit as the communication history data, or the tag data received by the receiver in the order of the reception time. The communication unit stores the communication history data in the storage unit, and the processing unit calculates the temporal proximity between the two objects using the communication history data read from the storage unit. The object arrangement drawing creation method is characterized in that the spatial distance estimation value between objects is calculated.

Third, the processing unit counts n _ij how many times any two ID tags i and j appear in the communication history data, and how many times each of the ID tags i and j is The occurrence of n _i and n _j is counted, and the temporal proximity between the two objects corresponding to the ID tag i and j is determined by the correlation coefficient using these count values n _ij , n _i and n _j. The object arrangement drawing creation method is characterized by calculating.

Fourth, the processing unit collects the communication history data within a predetermined time into one, counts n _ij how many times any two ID tags i and j appear at the same time, and the ID tag i, or j appeared many times each n _i, counts n _j, corresponding to the ID tag i, j by a correlation coefficient using these count values n _ij, n _i, n _j The object arrangement drawing creation method is characterized in that the temporal proximity between two objects is calculated.

Fifth, the processing unit collects the communication history data of a predetermined continuous number into one, counts n _ij how many times any two ID tags i and j appear at the same time, and the ID tag i, or j appeared many times each n _i, counts n _j, corresponding to the ID tag i, j by a correlation coefficient using these count values n _ij, n _i, n _j The object arrangement drawing creation method is characterized in that the temporal proximity between two objects is calculated.

Sixth, the processing unit calculates an average time or an average data interval T _i → _j until another ID tag j first appears after the ID tag i appears in the communication history data, The object arrangement drawing creation method, wherein the temporal proximity between two objects corresponding to the ID tag i, j is calculated by a correlation coefficient using the average time or average data interval T _i → _j . I will provide a.

  Seventhly, the object placement map creating method is characterized in that the processing unit calculates the spatial distance estimation value between two objects by a non-negative monotonic decreasing function using the temporal proximity. .

  Eighth, the processing unit stores the movement distance between two objects of the receiver in the storage unit as the communication history data, and the processing unit reads the communication history data read from the storage unit as the communication history data. An object layout drawing creation method comprising: calculating an average moving distance as the estimated spatial distance between two objects using the moving distance, and creating the layout map using the average moving distance. provide.

  Ninth, the processing unit calculates a coordinate value of an object by a multidimensional scaling method using the matrix of spatial distance estimation values, and creates the layout using the coordinate values. The object layout drawing creation method is provided.

  Tenth, the processing unit stores tag data and coordinate values of one or more objects in advance in the storage unit as anchor data, and the anchor read out from the storage unit by the processing unit The object layout drawing creation method further includes the step of correcting the layout map using data.

  In addition, according to an eleventh aspect of the present invention, there is provided an object arrangement drawing creation program for causing a computer to execute the object arrangement drawing creation method according to any one of claims 1 to 10.

  Further, according to a twelfth aspect of the present invention, there is provided a computer-readable recording medium in which the object layout drawing creation program is recorded.

  Furthermore, the invention of this application is, in the thirteenth aspect, a system for creating a layout drawing of an object, an ID tag attached to the object, a receiver that communicates with the ID tag and receives tag data, and an ID tag And a receiver for creating a layout map based on communication history data between the receiver and the receiver, and the layout map generating apparatus uses the communication history data to calculate a spatial distance estimate between two objects And a means for creating a layout map using the calculated spatial distance estimation value.

  14thly, the said layout drawing creation apparatus receives the tag data received by the receiver as the communication history data and its reception time, or the tag data in the reception time series order received by the receiver as the communication history data. The object location map creation system is characterized in that the temporal proximity between two objects is calculated using the temporal proximity and the estimated spatial distance between the two objects is calculated using the temporal proximity. .

  15thly, the said layout drawing preparation apparatus calculates the average moving distance as said spatial distance estimated value between two objects using the moving distance between two objects of the receiver as communication history data. The object arrangement drawing creation system is provided.

  Sixteenthly, the layout drawing creation apparatus further includes means for correcting the layout chart using anchor data including tag data and coordinate values of one or a plurality of objects. An object layout drawing creation system is provided.

  According to the first object layout drawing creation method, an ID tag is attached to each object, communication history data between the tag and the receiver is accumulated, and a spatial distance estimation value between the two objects is based on the accumulated data. And a layout map is created using the estimated spatial distance. This is based on an empirical rule by the inventors of the invention of this application that objects closer to each other have a higher frequency of simultaneous observation, and by executing each processing based on this, a house, its room, etc. You can easily create a layout that shows the rough position of each object scattered indoors, and by presenting it, you can teach the positional relationship of multiple objects at the same time, reminding you where to place it Helps to find things easily and effectively.

  Needless to say, the present invention can be applied not only to indoor object arrangements but also to the creation of approximate arrangements of objects existing outdoors. In other words, the same effect as described above can be realized both indoors and outdoors if an object has an ID tag attached to an object, a receiver that can communicate with the ID tag, and the communication history data can be acquired.

  According to the second object layout drawing creation method, the same effect as the first method can be obtained, and tag data and tag data in the order of reception time and reception time are accumulated as communication history data. After calculating the temporal proximity between the two objects based on the above, the spatial distance estimation value is calculated using the temporal proximity. In addition to the above-mentioned experience side, the inventors of the invention of this application have found that the temporal proximity represents the average temporal proximity of two objects appearing in a series of communication history data. A new concept is used, and by using this, it is possible to calculate the spatial distance estimation value along the above empirical rule more accurately, and to create a more useful layout diagram.

  According to the third to fifth object layout drawing creation methods, the same effect as the second creation method is obtained, and the temporal proximity is calculated by the correlation coefficient using the count value as described above. By doing so, calculation of the spatial distance estimated value according to the above empirical rule can be executed with higher accuracy.

  According to the sixth object arrangement drawing creation method, the same effect as the second creation method can be obtained, and the temporal proximity can be determined by the correlation coefficient using the average time or the average data interval as described above. By calculating the spatial distance estimated value according to the above empirical rule, the calculation can be performed with higher accuracy.

  According to the seventh object layout drawing creation method, the same effects as in the second to sixth creation methods can be obtained, and the spatial distance estimation value and the non-negative monotonic phenomenon function calculated as described above can be obtained. By using it, it is possible to accurately calculate the estimated spatial distance according to the above rule of thumb.

  According to the eighth object arrangement drawing creation method, the same effect as in the first creation method can be obtained, and the movement distance between two objects of the receiver is acquired and stored as communication history data. The spatial distance estimate is directly calculated based on the above. According to this, for example, when the reception time of the tag data by the receiver cannot be obtained, the spatial distance estimation value according to the above empirical rule is temporally calculated by using the moving distance of the receiver instead of the reception time. It is possible to calculate accurately without performing proximity calculation. Of course, it is needless to say that the layout map may be created by combining the spatial distance estimation based on the moving distance and the spatial distance estimation based on the reception time.

  According to the ninth object layout drawing creation method, the same effects as in the first to eighth creation methods can be obtained, and the spatial distance estimation matrix and multidimensional scale calculated as described above can be obtained. By using the construction method, the approximate coordinate value of each object can be accurately obtained, and then a rough layout can be created with high accuracy.

  According to the tenth object layout drawing creation method, the same effects as in the first to ninth creation methods can be obtained, and an object that is rarely carried around or moved in the room is an anchor object. By considering the ID tag as an anchor tag and setting the tag data and coordinate values as anchor data in advance, the arrangement map is corrected by correcting the coordinate values of each object based on the anchor data. Thereby, a rough layout can be completed with higher accuracy.

  According to the eleventh object arrangement drawing creation program and the computer-readable recording medium storing the twelfth program, a computer program that can obtain the same effects as the first to tenth object arrangement drawing creation methods In addition, a recording medium such as a flexible disk, a CD, or a DVD on which it is recorded is realized.

  According to the thirteenth to sixteenth object layout drawing creation systems, a system that achieves the same effects as the first to tenth object layout drawing creation methods is realized.

[First Embodiment]
Hereinafter, an embodiment of the invention of this application will be described in detail for each process with reference to FIGS. 1 and 2 as appropriate. FIG. 1 is a flowchart of object arrangement drawing creation processing, and FIG. 2 is a system configuration diagram.

  The system configuration shown in FIG. 2 includes a display unit (1), an input unit (2), a processing unit (CPU) (3), a main storage unit (4), a communication history database (5), and a bus (6). The layout drawing creation device (10), the receiver (7), and the ID tag (8).

  In the layout drawing creation apparatus (10), the main storage unit (4) stores various data such as an object layout drawing creation program, initial settings, parameters, and the like. Communication history data is accumulated in the communication history database (5). The processing unit (3) connected to the main storage unit (4) and the communication history database (5) by the bus (6) receives an instruction of the object arrangement drawing preparation program and executes the object arrangement drawing preparation processing. . The processing unit (3) is also connected to a display unit (1) such as a display device for displaying a layout diagram and the like and an input unit (2) such as a keyboard and a mouse through a bus (6), and input / output processing of various data. Is also executed. The input unit (2) may be a device for inputting tag data, reception time data, and the like from the receiver (7) that communicates with the ID tag (8) of the object. The input data is mainly input by the processing unit (3). It is stored in the storage unit (4) and the communication history database (5).

  Of course, the layout drawing creation device (10) and the receiver (7) may be integrally formed. For example, the receiver (7) has the function of the layout drawing creation device (10). Small devices can be considered.

<Acquisition / Acquisition of Communication History Data (Step S1)>
First, FIG. 3 shows an example of how various objects are scattered in the room. In this example, insurance cards, televisions, books A, documents, stamps, mugs, glasses, books B, scissors, passbooks, and books C are scattered in the room. 8) is attached in advance. As the ID tag (8), a non-contact type tag such as an RFID tag, an ultrasonic tag, or a barcode can be used.

  On the other hand, a person who is the owner of these objects wears or carries a receiver (7) capable of wirelessly communicating with the ID tag (8) and receiving the data, and moves around the room. As the receiver, a wireless receiver such as a tag reader or a non-contact type such as an optical receiver / receiver in the case of a barcode can be used.

  When a person having the receiver (7) moves in the room, the ID tag (8) in the vicinity, more specifically, the ID tag (8) and the receiver (7) present in the communicable range, Automatically communicates, and the communication data is sequentially stored in the communication history database (5) or the like to create communication history data.

  Therefore, the communication history data with each object in the room is automatically accumulated without any consciousness just by wearing a receiver (7) and carrying out daily life. Further, when searching for a certain object, the communication history data is automatically created simply by walking around the room with the receiver (7). What is important here is that there is no need to measure the position of the moving receiver (7) or the person holding the receiver (7), and the receiver (7) and the ID tag (8). It is also unnecessary to measure the relative position of the receiver, that is, the distance and direction from the receiver (7) to the ID tag (8). As described below, “when the communication with the tag was performed” and “what Since it is only necessary to use simple information that “communication with the tag was performed in time order”, the system cost is excellent.

  In addition, even if a person does not move around the room with the receiver (7), it is sufficient that the receiver (7) can move. For example, the receiver (7) itself may be a self-propelled type indoors, Moreover, you may use moving apparatuses, such as a robot provided with a receiver (7) and an indoor airship.

  Of course, as illustrated in FIG. 4, for example, even in a situation where a plurality of receivers (7) move in the same room and communicate with the ID tag (8), each receiver ( It goes without saying that the communication history data between 7) and the ID tag (8) can be accumulated and used for the calculation process described below.

  As for the communication history data, the tag data received by the indoor receiver (7) and the time when it was received, or the tag data received by the receiver (7) are stored in chronological order, that is, What is stored in the order received is considered.

  For example, FIGS. 5A to 5D show an example of the communication history data. The communication history data in FIG. 5A is for storing ID tag data and its reception time, and a set of tag data measured at the same time becomes one communication history data together with the reception time. Are stored in chronological order. At 19:20:35, three data, tag 2, tag 11, and tag 17, are received and recognized. At 19:20:38, three data, tag 11, tag 17, and tag 25, are received and recognized. , 19:21:45, the data format represents that the two data of the tag 11 and the tag 25 are received and recognized. The communication history data in FIG. 5 (b) is also for storing ID tag data and its reception time, but here is a single communication history with a single tag data measured at a certain time. Data is accumulated in chronological order. Tag 2 was received and recognized at 19: 20: 35.217 seconds, Tag 11 was received and recognized at 19: 20: 35.224 seconds, and Tag 17 was received and recognized at 19: 20: 35,231 seconds. It is a data format that represents this. In the example of FIG. 5 (a), the data is collected in the same second by recognizing the data in units of one second, whereas in the example of FIG. 5 (b), it is finely distinguished to 1 / 100th of a second. It is single data.

  In addition, the communication history data in FIG. 5 (c) is a case where the exact reception time is not stored and the ID tag data is stored in the order of reception time series, and only one set of tag data measured simultaneously is one. Communication history data is accumulated in chronological order. That is, the data format does not have the time shown in FIG. The communication history data in FIG. 5 (d) is also for storing ID tag data in the order of reception time series, but only a single tag data becomes one communication history data, which is in time series order. Accumulated. That is, the data format does not have the time shown in FIG.

  Since these various data formats can be used depending on the specifications and performance of the tag system including the ID tag (8) and the receiver (7), they may be selected according to the system.

  As for the ID tag (8), not only those of radio wave communication and optical communication but also those capable of recognizing an image from the outside can be considered. In this case, for example, it is attached to a place visible from the outside of the object. Then, an image is picked up by an image pickup device as a receiver (7) installed indoors, and the ID tag (8) is recognized. The reception time is the imaging time. As described above, various types can be used as the ID tag (8) as long as they are non-contact types, and the receiver (7) is also adapted to that.

<Calculation of Temporal Proximity Between Objects (Step S2)>
Subsequently, the temporal proximity between two objects existing in the room is calculated using the communication history data as described above. This temporal proximity represents the average temporal proximity of two objects appearing in a series of communication history data, and is calculated so as to increase as the two objects are closer. For example, if the ID tag i and the ID tag j are often recognized at the same time or in a very short time, the temporal proximity is considered large. More specifically, the following four calculation methods can be considered.

First, as illustrated in FIGS. 6A and 6B, for example, n _ij is counted how many times any two ID tags i and j appear simultaneously in the communication history data, In addition, n _i and n _j are counted as to how many times the ID tags i and j appear, respectively, and correspond to the ID tags i and j by the correlation coefficient using these count values n _ij , n _i and n _j. The temporal proximity between two objects is calculated.

In the example of FIG. _6A , since the tag 11 and the tag 25 appear simultaneously at _{19:20:38 and 19:21:45, the} number of simultaneous appearances is n _11,25 = 2. The number of appearances of the tag 25 is n ₂₅ = 2. However, since the tag 11 also appears at 19:20:35, n ₁₁ = 3. Similarly, the number of subsequent appearances continues to be counted, and other pairs such as n _2,11 are also counted.

The correlation coefficient using these count values n _ij , n _i , and n _j is such that the temporal proximity p _ij, which is the average temporal proximity, becomes larger as two objects are closer. For example, p _ij = n _ij / (n _i + n _j −n _ij ) equivalent to the Jaccard coefficient, Braun, Blankue coefficient n _ij / max {n _i , n _j }, Kulczynski coefficient n _ij Various factors such as / (n _i + n _j −2n _ij ) can be taken into consideration, and these are defined and calculated using various correlation coefficients.

  This first method is useful in the case of the data format shown in FIG. 5A as illustrated in FIG. Further, as illustrated in FIG. 6B, the present invention can also be applied to the data format shown in FIG. This is because even if the exact time is not known, it can be counted as long as the data sets are measured simultaneously. That is, this method is a useful calculation method when a plurality of tag data can be acquired simultaneously.

Second, for example, as illustrated in FIG. 7, the above communication history data within a predetermined time is collected into one, and n _ij indicates how many times any two ID tags i and j appear at the same time. counted, and ID tag i, or n _i j appeared several times each, also counts n _j, these count values n _ij, n _i, ID tag i by the correlation coefficient with n _j, j The temporal proximity between two objects corresponding to is calculated.

In the example of FIG. 7, the predetermined time is set to 5 seconds, the tag 2 at 19:20:35, the tag 11 at 19:20:37, and the tag 17 at 19:20:37 are one data. The tag 15 at 19:20:42, the tag 4 at 19:20:43, and the tag 8 at 19:20:44 are entered into the next 5 seconds. The data will continue to be integrated as well. After data integration, n _ij , n _i , n _j are counted and p _ij is calculated as in the first method.

  This second method is useful in the case of the data format shown in FIG. 5B, and is pre-processed for pseudo conversion of the data format into the data format shown in FIG. 5A.

Thirdly, as illustrated in FIG. 8, for example, a predetermined continuous number of communication history data are collected into one, and n _ij is counted how many times any two ID tags i and j appear at the same time. In addition, n _i and n _j are counted as to how many times each of the ID tags i and j appears, and the ID tags i and j are assigned to the ID tags i and j by the correlation coefficient using these count values n _ij , n _i and n _j. The temporal proximity between the two corresponding objects is calculated.

In the example of FIG. 8, two continuous data are integrated into one, tag 2 and tag 11 are integrated, then tag 11 and tag 17 are integrated, and the subsequent data is also integrated in the same manner. Is done. Of course, the number of continuous data is not limited to two, and three or more continuous data can be integrated and used. After data integration, n _ij , n _i , n _j are counted and p _ij is calculated as in the first method.

  This third method is useful in the case of the data format shown in FIG. 5D, and performs preprocessing for pseudo-converting the data format into the data format shown in FIG. There is an advantage that an accurate time is unnecessary and a data processing load is light.

And fourth, for example, as illustrated in FIG. 9, the average time or average data interval T _i → _j until another ID tag j first appears after the ID tag i appears in the communication history data. And the temporal proximity between the two objects corresponding to the ID tags i and j is calculated by the correlation coefficient using the average time or the average data interval T _i → _j .

As in the first to fourth methods, the correlation coefficient is defined such that the temporal proximity p _ij , which is an average temporal proximity, becomes larger as two objects are closer. Therefore, for example, p _ij = 1 / (T _i → _j + T _j → _i ) can be considered. Of course, other correlation coefficients can be applied.

  This fourth method can be applied to any of the formats shown in FIGS.

<Calculation of Spatial Distance between Objects (Step S3)>
Subsequently, an estimated spatial distance between the two objects is calculated from the temporal proximity calculated as described above. This estimated spatial distance is based on an empirical rule that objects closer to each other have a higher frequency of simultaneous observations, and is calculated so that two objects having a larger temporal proximity p _ij have a smaller value. For example, the estimated spatial distance is considered to be smaller as the temporal proximity p _ij between the ID tag i and the ID tag j is larger.

More specifically, the spatial distance estimated value d _ij (with a hat) can be calculated using a non-negative monotone decreasing function. This non-negative monotonic decreasing function refers to a monotonic decreasing function that is non-negative in the domain of temporal proximity p _ij , as shown in FIG. 10, for example, and does not become negative. Various functions can be considered.

FIGS. 11 (a) to 11 (c) each show an example. FIG. 11 (a) shows y = a · e ^−bx , (a> 0, b> 0), and FIG. y = a · (1−x) ^b , (a> 0, b> 0) and FIG. 11C are step-like functions. Regarding these various non-negative monotonic decreasing functions, it is possible to consider processing such as selecting an appropriate combination based on prior knowledge or automatically determining parameters (see below).

<Creation of Object Layout (Step S4)>
Then, an object arrangement map is created from the estimated spatial distance calculated as described above.

  More specifically, for example, as illustrated in FIG. 12, a two-dimensional or three-dimensional coordinate value of an object is calculated from a matrix of spatial distance estimation values by a multidimensional scaling method, and a layout diagram is calculated from the coordinate values. create.

  In the example of FIG. 12, the ID tags of the objects are set vertically and horizontally in order from 1, and the distance estimated value matrix in which the spatial distance estimated values between the two objects are associated with each other is formed. For example, the estimated spatial distance between the tag 1 and the tag 2 is 0.5, the estimated spatial distance between the tag 1 and the tag 3 is 2.2, and thereafter the spatial distance estimated values of all two objects are matrixes. It corresponds to the shape.

  Coordinate values are calculated from this matrix by a multidimensional scaling method. There are various methods such as classical scaling and SMACOF (Scaling by MAjorizing a COnvex Function) in Multi-Dimensional Scaling (MDS), and any of them can be used.

  The layout based on the coordinate values calculated in this way does not indicate the exact position of each object in the room, but only represents the overall rough layout. This is the most important point in the invention of this application. That is, according to the invention of this application, it presents a rough position in the whole room rather than a numerically precise position of an object, and arouses a person's memory and helps to remember where it is placed or where it is placed. It can be done.

<Automatic determination of parameters of non-negative monotone decreasing function>
Here, the parameter automatic determination process of the non-negative monotone decreasing function for calculating the spatial distance estimation value described above will be described.

  In this processing, for example, as illustrated in FIG. 13, by using a multidimensional scaling method and a function approximation method such as a least square method repeatedly (corresponding to the flow of the loop dotted line in FIG. 1), non-negative monotonicity The parameter value in the decreasing function is optimally estimated.

  More specifically, first, a spatial distance estimation value is calculated by a non-negative monotone decreasing function using an initial value of a parameter to create a matrix, and a coordinate value by a multidimensional scaling method is calculated. The parameter value is updated by function approximation by the least square method with respect to the obtained coordinate value, the spatial distance estimation value is calculated again using the updated value, and the coordinate value is calculated. The parameter value can be optimized by repeating this until the error falls within an allowable range.

<Correction of Object Layout (Step S5)>
The layout created as described above can be modified as follows.

  First, ID tags of one or more objects among the objects scattered in the room are set as anchor tags, and the position of each object is corrected using the tag data and coordinate values as anchor data.

  Unlike reading books and frequently used glasses, the room is almost fixed, with rarely moving objects such as pillars and walls (which can be called fixed objects), TVs, furniture, etc. Often there are still objects (called semi-fixed objects). Therefore, these fixed objects or quasi-fixed objects are used as objects that serve as anchors in the arrangement relationship, and their ID tags and accurate coordinate values are used as anchor data in advance as main memory (4) or communication history database (5) (see FIG. 3) ) Or the like. And, for example, as illustrated in FIG. 14, after the layout drawing is created, the coordinate values (solid circles in the drawing) of the object having the same ID tag as the anchor tag are stored in the accurate anchor coordinates. Each tag position is corrected by performing a primary transformation such as an affine transformation that completely matches the values (dotted circles in the figure) or minimizes the average coordinate error.

  In the example of FIG. 14, since the tags 1, 6, and 7 are anchor tags, the coordinate values (solid line circles) of the tags 1, 6, and 7 obtained by the multidimensional scale construction method are the anchor coordinate values (dotted line circles). In addition, by moving and correcting the coordinate values of the other tags 2, 3, 4, and 5 in accordance with the estimated spatial distance from the tags 1, 6, and 7, the rough but more accurate layout diagram, In other words, a more accurate and rough layout can be obtained.

[Second Embodiment]
By the way, in 1st Embodiment mentioned above, the tag reception time (it can also call tag recognition time) by a receiver (7) is used as communication history data with an ID tag, and the temporal proximity between objects based on this, The spatial distance estimation value is calculated in order. In the invention of this application, instead of the above time, the moving distance of the receiver (7) between the objects is used, and the spatial distance estimation value is calculated from now on. May be directly calculated. More specifically, it is as follows, FIG. 15 shows the processing flow diagram, and FIG. 16 shows one specific example.

<Spatial distance estimation based on moving distance>
Consider spatial distance estimation between an ID tag A attached to an object and an ID tag B attached to another object.

First, the moving distance of the receiver (7) between these two objects is acquired (step S11). More specifically, when the receiver (7) receives the tag data of the ID tag A and recognizes it, and subsequently receives the tag data of the ID tag B and recognizes it, it recognizes the ID tag A. Then, the distance traveled by the receiver (7) from when the ID tag B is recognized is acquired (step S11). In the example of FIG. 16, for example, the moving distance M ₂ → ₁₁ from the glasses / tag 2 to the stamp / tag 11.

  For this moving distance, for example, when the receiver (7) is worn or carried by a person, a separate measuring device (not shown) such as an accelerometer or a pedometer (registered trademark) is prepared and received. Measurement data is acquired by executing measurement in synchronization with ID tag recognition by the machine (7), and a moving distance is calculated based on the measurement data. The measuring device may be worn or carried by a person as a separate body from the receiver (7), or may be integrated into the receiver (7). Further, when the receiver (7) is provided in a moving device such as a robot, a configuration in which a measuring device such as an encoder is incorporated in the moving device can be considered, and the moving distance is acquired from the measurement data.

  The movement distance acquired in this way is stored in the internal storage unit such as the main storage unit (4) (see FIG. 4) or the communication history database (5) (see FIG. 4), and several movements between A → B are performed. After the distance is accumulated, the average moving distance is calculated from the communication history data (step S12). This average moving distance is the estimated spatial distance between objects.

Of course, even when tags are recognized in the order of B → A, the movement distance between AB is the same, so it goes without saying that the average movement distance may be calculated from the communication history data including B → A. In the example of FIG. 16, for example, the movement distance M ₂ → ₁₁ and the movement distance M ₁₁ → ₂ are calculated, and the average movement distance as exemplified in FIG. 17 is calculated from these. In the example of FIG. 17, the distance between the tag 2 and the tag 11 is 1.2 m, and the distance between the tag 11 and the tag 8 is 0.7 m.

  In addition, it is preferable to increase the calculation accuracy by combining a statistical test method such as outlier removal for the average movement distance calculation.

  After that, from the average moving distance as the estimated spatial distance, an object layout is created using the multidimensional scale construction method as in the first embodiment (step S13), and the layout is made as necessary. The figure may be corrected (step S14).

[Third Embodiment]
Of course, as illustrated in FIGS. 18 and 19, it is also possible to execute layout drawing creation by combining the first embodiment and the second embodiment.

  More specifically, when both the reception time and the movement distance can be obtained as the communication history data, the spatial distance estimation based on the reception time (step S21 → step S22 → step S23) and the spatial distance based on the movement distance The estimation (step S21 → step S23) is executed, and a layout map is created by combining the obtained spatial distance estimation values (step S24, step S25). As a result, it is possible to improve the map accuracy, that is, to obtain a more accurate rough layout than when only one piece of information is used.

  Various combinations of spatial distance estimation values can be considered. For example, the following formula is given as an example.

The weight parameter w is determined by how reliable each information is. After that, coordinate values are calculated from the obtained D _AB values by a multidimensional scale construction method or the like, and an arrangement diagram is created.

  In the present embodiment, not only the time and distance can be acquired by one receiver (7), but in an environment using a plurality of receivers (7), one can acquire only time and the other can acquire only distance. It can be applied to such cases.

  It goes without saying that the invention of this application is not limited to the above-described embodiments, and various aspects are possible in detail. For example, although the above embodiment has been described mainly for indoor spaces, it is also possible to create a layout drawing of an object existing in an outdoor space in the same way, and receive an ID tag (8) attached to the object and reception If the communication history data can be acquired by communicating with the machine (7), the spatial distance may be estimated based on the reception time and the moving distance.

  As explained in detail above, the invention of this application makes it easy and effective to create a rough layout of objects existing indoors and outdoors to teach rough positional relationships and to remember where they are placed and where they are placed. There are provided an object arrangement drawing creation method, an object arrangement drawing creation program, a computer-readable storage medium storing the object arrangement drawing creation program, and an object arrangement drawing creation system.

It is a processing flow figure of invention of this application. It is a system configuration | structure figure of invention of this application. It is a figure for demonstrating a mode that the object was scattered in the room. It is another system block diagram of invention of this application. (A)-(d) is a figure for demonstrating an example of a communication log | history data format, respectively. (A) and (b) are the figures for demonstrating one calculation method of temporal proximity, respectively. It is a figure for demonstrating another calculation method of another time proximity. It is a figure for demonstrating another one calculation method of temporal proximity. It is a figure for demonstrating another one calculation method of temporal proximity. It is a figure for demonstrating the non-negative monotone decreasing function used for calculation of a spatial distance estimated value. (A)-(c) is a figure for demonstrating an example of a non-negative monotone decreasing function, respectively. It is a figure for demonstrating an example of a layout drawing creation process. It is a figure for demonstrating an example of the parameter update process of a non-negative monotone decreasing function. It is a figure for demonstrating an example of a layout map correction process. It is another process flow figure of invention of this application. It is a figure for demonstrating a mode that a receiver moves. It is a figure for demonstrating an example of the movement distance as communication log | history data. It is another process flowchart of invention of this application. It is a figure for demonstrating an example of the reception time and moving distance as communication log | history data.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Display part 2 Input part 3 Processing part (CPU)
4 main memory 5 communication history database 6 bus 7 receiver 8 ID tag 10 object layout drawing creation device

Claims (16)

A method for creating an object layout, comprising:
A step of storing, in a storage unit, communication history data between an ID tag attached to an object and a receiver in advance,
A processing unit calculates a spatial distance estimated value between two objects based on the communication history data read from the storage unit, and a processing unit uses the calculated spatial distance estimated value to display a layout diagram. A method for creating an object layout diagram, comprising the step of creating. The processing unit stores the tag data received by the receiver and its reception time in the storage unit as the communication history data, or the tag data received by the receiver as the communication history data in the order of the reception time series. Memorize it in the memory,
The processing unit calculates a temporal proximity between two objects using the communication history data read from the storage unit, and calculates the estimated spatial distance between the two objects using the temporal proximity. The object layout drawing creation method according to claim 1, wherein: Wherein the processing unit is, any two ID tags i in the communication history data, j counts whether n _ij appeared many times at the same time, and the ID tag i, or j appeared many times each n _i , N _j are counted, and the temporal proximity between the two objects corresponding to the ID tag i, j is calculated by a correlation coefficient using these count values n _ij , n _i , n _j. The object layout drawing creation method according to claim 2. The processing unit combines the communication history data within a predetermined time into one, counts n _ij how many times any two ID tags i and j appear at the same time, and the ID tag i, n _i and n _j are counted as to how many times j appears, and the correlation between the two objects corresponding to the ID tags i and j is determined by the correlation coefficient using these count values n _ij , n _i and n _j. 3. The object layout drawing creation method according to claim 2, wherein temporal proximity is calculated. The processing unit collects a predetermined number of continuous communication history data into one, counts n _ij how many times any two ID tags i and j appear at the same time, and the ID tag i, n _i and n _j are counted as to how many times j appears, and the correlation between the two objects corresponding to the ID tags i and j is determined by the correlation coefficient using these count values n _ij , n _i and n _j. 3. The object layout drawing creation method according to claim 2, wherein temporal proximity is calculated. The processing unit calculates an average time or an average data interval T _i → _j until another ID tag j first appears after the ID tag i appears in the communication history data, and this average time or average 3. The object arrangement drawing creation method according to claim 2, wherein the temporal proximity between two objects corresponding to the ID tag i, j is calculated by a correlation coefficient using a data interval T _i → _j . 7. The object arrangement diagram according to claim 2, wherein the processing unit calculates the spatial distance estimation value between two objects using a non-negative monotone decreasing function using the temporal proximity. 8. How to make. The processing unit stores the movement distance between two objects of the receiver in the storage unit as the communication history data,
The processing unit calculates an average moving distance as the estimated spatial distance between two objects using the moving distance as the communication history data read from the storage unit, and uses the average moving distance to calculate the average moving distance. 2. The object layout drawing creation method according to claim 1, wherein the layout drawing is created. 2. The processing unit calculates a coordinate value of an object by a multi-dimensional scale construction method using the matrix of estimated spatial distance values, and creates the arrangement map using the coordinate value. 9. The object layout drawing creation method according to any one of claims 8 to 8. A step in which the processing unit previously stores tag data and coordinate values of one or more objects in the storage unit as anchor data, and the processing unit uses the anchor data read from the storage unit, The object layout drawing creation method according to claim 1, further comprising a step of correcting the layout map.   An object arrangement drawing creation program for causing a computer to execute the object arrangement drawing creation method according to claim 1.   A computer-readable recording medium on which the object layout drawing creating program according to claim 11 is recorded. A system for creating a layout drawing of an object,
An ID tag attached to an object, a receiver that communicates with the ID tag and receives tag data, and a layout drawing creation device that creates a layout map based on communication history data between the ID tag and the receiver,
The layout drawing creation device has means for calculating a spatial distance estimation value between two objects using communication history data, and means for creating a layout map using the calculated spatial distance estimation value. A featured object layout drawing system. The arrangement drawing creation device uses the tag data received by the receiver as the communication history data and the reception time, or the tag data in the reception time series order received by the receiver as the communication history data. 14. The object arrangement drawing creation system according to claim 13, wherein the temporal proximity degree is calculated, and the estimated spatial distance between the two objects is calculated using the temporal proximity degree. 14. The arrangement drawing creation apparatus calculates an average moving distance as the estimated spatial distance between two objects using a moving distance between two objects of the receiver as communication history data. The object arrangement drawing creation system described. 16. The layout drawing creation device further includes means for correcting the layout map using anchor data including tag data and coordinate values of one or a plurality of objects. The object arrangement drawing creation system according to any one of the above.