JP6529098B2 - Position estimation device, position estimation method, and program - Google Patents

Description

The present invention relates to a position estimation device and a position estimating method for estimating the position of the target, further relates to a program for realizing these.

  BACKGROUND ART Conventionally, unmanned aerial vehicles called “drone” (hereinafter also referred to as “UAV (Unmanned Aerial Vehicle)”) are used in various applications such as military applications and pesticides. In particular, in recent years, small-sized unmanned airplanes that use electric motors as power sources have been developed due to the downsizing and high output of batteries (see, for example, Non-Patent Documents 1 and 2). Small unmanned aerial vehicles are rapidly spreading because of their ease of operation.

  In addition, the unmanned airplane is generally equipped with a photographing camera and a GPS (Global Positioning System) receiver, and the position (position information) of the own aircraft measured by the GPS receiver can be linked to the photographed image. For this reason, unmanned aerial vehicles are used, for example, in applications such as wildlife ecology surveys, surveys of crowded people at events, surveys of traffic congestion, surveillance of suspicious people, etc., grasp of evacuation status of humans during disasters Is expected.

“Unmanned Aerial Vehicle”, [online], May 25, 2015, Wikipedia, [Search on June 1, 2015], Internet <URL: http://en.wikipedia.org/wiki/%E7%84%A1 % E4% BA% BA% E8% 88% AA% E7% A9% BA% E6% A9% 9F> "Drone", [online], April 22, 2015, weblio dictionary, [June 1, 2015 search], Internet <URL: http://www.weblio.jp/content/%E3%83%89 % E3% 83% AD% E3% 83% BC% E3% 83% B3>

  By the way, when it is necessary to identify the position of investigation object or surveillance object when conducting investigation or surveillance by the unmanned aerial vehicle, the data outputted from the unmanned aerial vehicle is only the image data to which the position information is added. Therefore, the manager can not identify the absolute position of the survey target or the monitoring target, and can only identify the relative position with respect to the unmanned airplane, so in the conventional unmanned airplane, highly accurate survey and monitoring There is a problem that it can not be done.

An example of the object of the present invention is to provide a position estimation device, a position estimation method, and a program capable of solving the above problems and estimating an absolute position of an object from data output from a moving object.

In order to achieve the above object, a position estimation device according to one aspect of the present invention acquires surrounding situation data specifying the surrounding situation from a mobile body provided with a sensor capable of detecting the surrounding situation, and the surrounding situation A correspondence specifying unit that compares the data with map data to specify the correspondence between the two;
A coordinate calculation unit that extracts a target of position estimation from the surrounding situation data, and calculates coordinates of the extracted target on the surrounding situation data;
An absolute position estimation unit configured to estimate the position of the object on the map data from the identified correspondence relationship and the calculated coordinates;
It is characterized by having.

Further, in order to achieve the above object, a position estimation method according to one aspect of the present invention is:
(A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
It is characterized by having.

Furthermore, in order to achieve the above object, a program according to an aspect of the present invention is a computer,
(A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
Allowed to run and wherein the Turkey.

  As described above, according to the present invention, it is possible to estimate the absolute position of an object from data output from a moving object.

FIG. 1 is a block diagram showing a schematic configuration of a position estimation apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram specifically showing the configuration of the position estimation apparatus according to the embodiment of the present invention. FIG. 3 is a view showing an example of image data used in the embodiment of the present invention. FIG. 4 is a diagram showing an example of environmental map data used in the embodiment of the present invention. FIG. 5 is a view showing an example of the wide area map data used in the embodiment of the present invention. FIG. 6 is a diagram showing the correspondence between the environmental map and the wide area map used in the embodiment of the present invention. FIG. 7 is a flow chart showing the operation of the position estimation device 10 according to the embodiment of the present invention. FIG. 8 is a block diagram showing an example of a computer for realizing the position estimation device in the embodiment of the present invention.

Embodiment
Hereinafter, a position estimation device, a position estimation method, and a program according to an embodiment of the present invention will be described with reference to FIGS. 1 to 8.

[Device configuration]
First, the configuration of a position estimation apparatus according to an embodiment of the present invention will be described with reference to FIG. FIG. 1 is a block diagram showing a schematic configuration of a position estimation apparatus according to an embodiment of the present invention.

  The position estimation device 10 in the present embodiment shown in FIG. 1 is a device for estimating the position of an object such as a human or an animal using the moving body 20. As shown in FIG. 1, the position estimation device 10 includes a correspondence specifying unit 11, a coordinate calculation unit 12, and an absolute position estimation unit 13.

  The correspondence specifying unit 11 first obtains surrounding situation data specifying the surrounding situation from the mobile unit 20 provided with the sensor 22 capable of detecting the surrounding situation. Subsequently, the correspondence specifying unit 11 compares the surrounding situation data with the map data to specify the correspondence between the two.

  The coordinate calculation unit 12 extracts a target 30 for position estimation from the surrounding situation data, and calculates coordinates of the extracted target 30 on the surrounding situation data. The absolute position estimation unit 13 estimates the position of the object 30 on the map data from the identified correspondence relationship and the calculated coordinates.

  As described above, according to the present embodiment, the absolute position of the object 30 can be estimated using the surrounding situation data output from the moving body 20.

  Subsequently, in addition to FIG. 1, the configuration of the position estimation device 10 according to the present embodiment will be more specifically described using FIGS. 2 to 6. FIG. 2 is a block diagram specifically showing the configuration of the position estimation apparatus according to the embodiment of the present invention. FIG. 2 also discloses the configuration of the mobile unit.

  First, as shown in FIG. 1, the moving body 20 used in the present embodiment is a multicopter type unmanned airplane equipped with a plurality of rotors and is a so-called drone. In the following description, the "moving object" 20 is also referred to as a "unmanned airplane" 20. As shown in FIG. 2, the unmanned airplane 20 includes a data processing unit 21, a sensor 22, a GPS signal receiving unit 23, a thrust generating unit 24, and a wireless communication unit 25.

  In the unmanned airplane 20, the wireless communication unit 25 performs wireless data communication with the position estimation device 10. The wireless communication unit 25 is realized by, for example, a communication device for Wi-Fi communication.

  The GPS signal receiving unit 23 receives a GPS (Global Positioning System) signal from a satellite, and measures the current position and altitude based on the received GPS signal. The four thrust generating units 24 are provided in the example of FIG. 1 and each include a rotor that generates a thrust and an electric motor serving as a driving source of the rotor.

  When the unmanned airplane 20 is remotely operated from the outside, the data processing unit 21 adjusts the thrust of each thrust generating unit 24 according to the operation input from the outside, and the speed, altitude, and travel of the unmanned airplane 20 Control the direction.

  In addition, when the unmanned airplane 20 is automatically steered so as to fly the set route, the data processing unit 21 presets the current position and the altitude measured by the GPS signal receiving unit 23. Match flight routes. Then, the data processing unit 21 adjusts the thrust of each thrust generating unit 24 such that the unmanned airplane 20 flies along the flight route while checking the collation result.

  Further, in the unmanned airplane 20, the sensor 22 may be any sensor that can detect the situation around the unmanned airplane 20. Examples of the sensor 22 include an imaging device that outputs a pixel signal in accordance with the received light. Further, since the imaging device is usually combined with a lens or the like to construct a camera, in practice, a camera including an imaging device is used as the sensor 22. Furthermore, since the wavelength range in which the imaging device can receive light may be visible light or infrared light, the camera may be a visible light camera or an infrared camera. good.

  When a camera is used as the sensor 22, as shown in FIG. 3, the sensor 22 outputs image data created from pixel signals as surrounding situation data. FIG. 3 is a view showing an example of image data used in the embodiment of the present invention. Further, in the present embodiment, the camera as the sensor 22 is installed downward on the bottom surface of the unmanned airplane 20 (see FIG. 1). Therefore, as shown in FIG. 3, the image specified by the image data is an image from above.

  In addition, as another example of the sensor 22, a sensor in which the feature of the output signal changes in accordance with the distance to an object present in the periphery can also be mentioned. In this case, the sensor 22 includes, for example, a light source for irradiating the object 30 with light, and a light receiving element for receiving the light reflected by the object 30, and generates ambient situation data from the output signal of the light receiving element. Specifically, examples of the sensor 22 include a laser range finder using a laser beam as emission light, and a depth camera using infrared light as emission light.

  Then, when the sensor 22 outputs the surrounding situation data, the data processing unit 21 receives this. Further, the data processing unit 21 transmits the output peripheral situation identification data to the position estimation device 10 via the wireless communication unit 25.

  Further, as shown in FIG. 2, in the present embodiment, the position estimation device 10 is installed outside the unmanned airplane 20 and performs data communication with the unmanned airplane 20 by wireless communication. The position estimation apparatus 10 includes a wireless communication unit 14 and a map database 15 in addition to the correspondence specifying unit 11, the coordinate calculation unit 12, and the absolute position estimation unit 13 described above.

  The wireless communication unit 14 performs wireless data communication with the unmanned airplane 20. Specifically, the wireless communication unit 14 receives the surrounding situation identification data transmitted from the wireless communication unit 25 of the unmanned airplane 20. The wireless communication unit 13 is also realized by, for example, a communication device for Wi-Fi communication. The map database 15 also stores environmental map data to be described later and wide area map data.

  Further, in the present embodiment, the correspondence specifying unit 11 first describes the correspondence (hereinafter, “first correspondence”) between environmental map data of the surroundings specified by the surrounding situation data and the surrounding situation data. Identify).

  Specifically, the correspondence specifying unit 11 first acquires environmental map data created in advance from the map database 15. FIG. 4 is a diagram showing an example of environmental map data used in the embodiment of the present invention. In the present embodiment, environmental map data is created using, for example, SLAM (Simultaneous Localization and Mapping) technology. Specifically, environmental map data is created by flying the unmanned airplane 20 along roads, rivers, tracks, etc., and identifying the position of the unmanned airplane 20 while extracting the outlines thereof by the sensor 22. Ru.

  Subsequently, the correspondence specifying unit 11 specifies a plurality of places in the surrounding situation data, for example, a plurality of characteristic places in the image specified by the image data, and further, the environment specified by the environment map data In the map, a point corresponding to each identified place is identified. Then, the correspondence specifying unit 11 associates the coordinates of each part in the image with the coordinates of the specified point in the environment map, and sets the correspondence between the coordinates as a first correspondence.

  In addition, the correspondence specifying unit 11 extracts map data (hereinafter referred to as "wide area map data") covering a range wider than the imaging range from the map database 15, and extracts the extracted wide area map data into the surrounding situation data. Match FIG. 5 is a view showing an example of the wide area map data used in the embodiment of the present invention. Then, the correspondence specifying unit 11 specifies the correspondence between the surrounding situation data and the map data (hereinafter, referred to as “second correspondence”).

  Specifically, the correspondence specifying unit 11 extracts a plurality of portions of the wide area map specified by the wide area map data, and for each of the extracted portions, is specified by the extracted portion and the image data (peripheral situation specifying data) Calculate the amount of mutual information with the image. Then, the correspondence specifying unit 11 determines that the portion where the value of the mutual information amount is the largest is a portion corresponding to the image (hereinafter referred to as “corresponding portion”), and further, in the corresponding portion, the image A point (corresponding point) corresponding to each of a plurality of characteristic points in the area is identified. Then, the correspondence specifying unit 11 associates the coordinates of each part in the image with the coordinates of the corresponding point in the corresponding part in the wide area map, and sets the correspondence between the coordinates as a second correspondence.

  For example, when the surrounding situation data is image data and the position estimation target 30 is a human, the coordinate calculation unit 12 has local feature amounts registered for the human among images specified by the image data. The location is identified, and the identified location is detected as the target 30. Further, the coordinate calculation unit 12 calculates the coordinates in the image of the detected object 30.

  In the present embodiment, the absolute position estimation unit 12 first uses the first correspondence identified by the correspondence identification unit 11 and the coordinates calculated by the coordinate calculation unit 12 to obtain the environmental map data of the object 30. Identify the coordinates (x, y) above.

  Subsequently, the absolute position estimation unit 12 calculates an affine map of the environmental map data and the wide area map data, using the first correspondence relationship and the second correspondence relationship. Furthermore, as shown in FIG. 6, the absolute position estimation unit 12 inputs the coordinates of the object 30 on the environmental map data into the affine map, whereby the coordinates of the object 30 on the wide area map data (east longitude X °, Convert to north latitude Y °). Then, the absolute position estimation unit 12 estimates the coordinates (east longitude X °, north latitude Y °) obtained by this conversion as the position of the object 30 on the wide area map data.

  FIG. 6 is a diagram showing the correspondence between the environmental map and the wide area map used in the embodiment of the present invention. Further, as shown in FIG. 6, the position of the object 30 on the wide area map data is an absolute position, and is expressed by east longitude and north latitude.

[Device operation]
Next, the operation of the position estimation device 10 according to the embodiment of the present invention will be described with reference to FIG. FIG. 7 is a flow chart showing the operation of the position estimation device 10 according to the embodiment of the present invention. In the following description, FIGS. 1 to 6 will be referred to as appropriate. Further, in the present embodiment, by operating the position estimation device 10, the position estimation method is implemented. Therefore, the description of the estimation method in the present embodiment is replaced with the following description of the operation of the position estimation device 10.

  As shown in FIG. 7, first, in the position estimation device 10, the correspondence specifying unit 11 acquires the surrounding situation data transmitted from the unmanned airplane 20 via the wireless communication unit 14 (step A1).

  Next, the correspondence specifying unit 11 acquires environmental map data created in advance from the map database 15, and specifies the correspondence (first correspondence) between the environmental map data and the surrounding situation data (Step A2). ). Specifically, assuming that the surrounding situation data is image data, the correspondence specifying unit 11 indicates the coordinates of a plurality of locations in the image specified by the image data and the correspondence in the environment map specified by the environment map data. The coordinates of the point to be linked are associated, and the association between the coordinates is taken as a first correspondence relationship.

  Next, the correspondence specifying unit 11 extracts the wide area map data from the map database, collates the surrounding situation data with the extracted wide area map data, and correspondence between the surrounding situation data and the map data (second correspondence Relationship) is identified (step A3). Specifically, assuming that the surrounding situation data is image data, the correspondence specifying unit 11 sets coordinates of a plurality of places in the image specified by the image data and coordinates of corresponding points in the corresponding part in the wide area map. Are associated with each other, and the association between the coordinates is taken as a second correspondence relationship.

  Next, the coordinate calculation unit 12 extracts the target 30 for position estimation from the surrounding situation data, and calculates the coordinates on the surrounding situation data of the target 30 (step A4). Specifically, assuming that the surrounding situation data is image data, the coordinate calculation unit 12 detects the object 30 in the image using the local feature amount, and calculates coordinates in the image of the detected object 30.

  Next, the absolute position estimation unit 12 specifies the coordinates of the object 30 on the environmental map data, using the first correspondence specified in step A2 and the coordinates calculated in step A4 (step A5). ).

  Next, the absolute position estimation unit 12 uses the first correspondence specified in step A2 and the second positional relation specified in step A3 to generate affine maps of environmental map data and wide area map data. Is calculated (step A6).

  Next, the absolute position estimation unit 12 converts the coordinates of the object 30 into the coordinates on the wide area map data by inputting the coordinates on the environmental map data of the object 30 into the affine map, and the obtained coordinates are The absolute position of the object 30 on map data is estimated (step A7).

[Effect in the embodiment]
As described above, according to the present embodiment, the absolute position of the object 30 can be estimated by acquiring, for example, image data and the like on which the object 30 of position estimation is captured from the unmanned airplane 20. Therefore, if the position estimation device 10 according to the present embodiment is used, ecological research on wild animals, research on congestion of people at events, research on traffic congestion, monitoring of suspicious persons, etc., evacuation of humans in disasters In situations such as grasping the situation, it is possible to obtain highly accurate results.

[Modification]
Moreover, although the unmanned airplane 20 is one in the example shown in FIGS. 1-7, the number of unmanned airplanes 20 is not specifically limited in this Embodiment. In this case, the position of a different target may be estimated for each unmanned airplane 20, or the position of the same target may be estimated by two or more unmanned airplanes 20. In particular, in the latter case, even if the target can not be detected by one unmanned aerial vehicle 20, the target may be detected by another unmanned aerial vehicle 20. Thus, the latter case is particularly effective when it is necessary to track the object.

  Furthermore, in the present embodiment, the mobile unit is not limited to the unmanned airplane. Other examples of mobiles include vehicles. Also in this case, the sensor may be a camera, a laser range finder, or a depth camera.

  Moreover, although the object 30 is a human in the example shown to FIGS. 1-7, the object of position estimation is not limited to this in this Embodiment. Other examples of the target 30 of position estimation include animals, vehicles, buildings, farmland, and forestry. Also, the target 30 of position estimation may be a part of an object. Specifically, there are abnormal points and broken points such as buildings, bridges, tunnels and dams. There is a possibility that abnormal places or failure places such as buildings, bridges, tunnels and dams can not be approached by humans, and in the case of using these as targets 30, maintenance and management of infrastructure can be efficiently performed.

[program]
The program in the embodiment of the present invention may be a program which causes a computer to execute steps A1 to A7 shown in FIG. By installing this program in a computer and executing it, the position estimation device 10 and the position estimation method in the present embodiment can be realized. In this case, a central processing unit (CPU) of the computer functions as the correspondence specifying unit 11, the coordinate calculating unit 12, and the absolute position estimating unit 13 to perform processing.

  Here, a computer for realizing the position estimation apparatus 10 by executing the program according to the present embodiment will be described with reference to FIG. FIG. 8 is a block diagram showing an example of a computer for realizing the position estimation device in the embodiment of the present invention.

  As shown in FIG. 8, the computer 110 includes a CPU 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These units are communicably connected to each other via a bus 121.

  The CPU 111 develops the program (code) in the present embodiment stored in the storage device 113 in the main memory 112 and executes various operations by executing these in a predetermined order. The main memory 112 is typically a volatile storage device such as a dynamic random access memory (DRAM). In addition, the program in the present embodiment is provided in the state of being stored in computer readable recording medium 120. The program in the present embodiment may be distributed on the Internet connected via communication interface 117.

  Further, as a specific example of the storage device 113, besides a hard disk drive, a semiconductor storage device such as a flash memory may be mentioned. The input interface 114 mediates data transmission between the CPU 111 and an input device 118 such as a keyboard and a mouse. The display controller 115 is connected to the display device 119 and controls the display on the display device 119.

  The data reader / writer 116 mediates data transmission between the CPU 111 and the recording medium 120, and executes reading of a program from the recording medium 120 and writing of the processing result in the computer 110 to the recording medium 120. The communication interface 117 mediates data transmission between the CPU 111 and another computer.

  In addition, specific examples of the recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark) and SD (Secure Digital), magnetic storage media such as flexible disk (Flexible Disk), or CD- An optical storage medium such as a ROM (Compact Disk Read Only Memory) may be mentioned.

  A part or all of the embodiment described above can be expressed by (Appendix 1) to (Appendix 12) described below, but is not limited to the following description.

(Supplementary Note 1)
Ambient condition data specifying the surrounding condition is acquired from a mobile body equipped with a sensor capable of detecting the surrounding condition, and the surrounding condition data is compared with map data to identify the correspondence between the two. A correspondence specifying unit,
A coordinate calculation unit that extracts a target of position estimation from the surrounding situation data, and calculates coordinates of the extracted target on the surrounding situation data;
An absolute position estimation unit configured to estimate the position of the object on the map data from the identified correspondence relationship and the calculated coordinates;
A position estimation device characterized in that

(Supplementary Note 2)
The correspondence specifying unit specifies, as a first correspondence, the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data, and further, the surrounding situation data is captured in a photographing range. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a wider range than the map data.
The absolute position estimation unit
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
The position estimation device according to appendix 1.

(Supplementary Note 3)
The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
The correspondence specifying unit acquires image data generated from the pixel signal as the surrounding situation data.
The position estimation device according to appendix 1.

(Supplementary Note 4)
The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
The correspondence specifying unit acquires data generated from the output signal as the surrounding situation data.
The position estimation device according to appendix 1.

(Supplementary Note 5)
(A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
A position estimation method characterized in that.

(Supplementary Note 6)
In the step (a), the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data is specified as a first correspondence, and the surrounding situation data is photographed. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a range wider than the range.
In the step (c),
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
The position estimation method according to appendix 5.

(Appendix 7)
The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
In the step (a), image data generated from the pixel signal is acquired as the surrounding situation data.
The position estimation method according to appendix 5.

(Supplementary Note 8)
The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
In the step (a), data generated from the output signal is acquired as the surrounding situation data.
The position estimation method according to appendix 5.

(Appendix 9)
On the computer
(A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
Ru is the execution, program.

(Supplementary Note 10)
In the step (a), the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data is specified as a first correspondence, and the surrounding situation data is photographed. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a range wider than the range.
In the step (c),
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
The program described in Supplementary Note 9.

(Supplementary Note 11)
The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
In the step (a), image data generated from the pixel signal is acquired as the surrounding situation data.
The program described in Supplementary Note 9.

(Supplementary Note 12)
The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
In the step (a), data generated from the output signal is acquired as the surrounding situation data.
The program described in Supplementary Note 9.

  Although the present invention has been described above with reference to the embodiment, the present invention is not limited to the above embodiment. The configurations and details of the present invention can be modified in various ways that can be understood by those skilled in the art within the scope of the present invention.

  According to the present invention, it is possible to estimate the absolute position of an object from data output from a mobile. INDUSTRIAL APPLICABILITY The present invention is effective in situations such as wildlife ecology survey, survey of congestion status of people at the time of event, survey of traffic congestion, surveillance of suspicious persons etc., grasp of evacuation status of humans at the time of disaster.

DESCRIPTION OF SYMBOLS 10 Position estimation apparatus 11 Correspondence specification part 12 Coordinate calculation part 13 Absolute position estimation part 14 Wireless communication part 15 Map database 20 Unmanned airplane 21 Data processing part 22 Sensor 23 GPS signal receiving part 24 Thrust generation part 25 Wireless communication part 110 Computer 111 CPU
112 main memory 113 storage device 114 input interface 115 display controller 116 data reader / writer 117 communication interface 118 input device 119 display device 120 recording medium 121 bus

Claims (9)

Ambient condition data specifying the surrounding condition is acquired from a mobile body equipped with a sensor capable of detecting the surrounding condition, and the surrounding condition data is compared with map data to identify the correspondence between the two. A correspondence specifying unit,
A coordinate calculation unit that extracts a target of position estimation from the surrounding situation data, and calculates coordinates of the extracted target on the surrounding situation data;
An absolute position estimation unit configured to estimate the position of the object on the map data from the identified correspondence relationship and the calculated coordinates;
Equipped with
The correspondence specifying unit specifies, as a first correspondence, the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data, and further, the surrounding situation data is captured in a photographing range. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a wider range than the map data.
The absolute position estimation unit
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
A position estimation device characterized by The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
The correspondence specifying unit acquires image data generated from the pixel signal as the surrounding situation data.
The position estimation device according to claim 1 . The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
The correspondence specifying unit acquires data generated from the output signal as the surrounding situation data.
The position estimation device according to claim 1 . (A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
Equipped with
In the step (a), the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data is specified as a first correspondence, and the surrounding situation data is photographed. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a range wider than the range.
In the step (c),
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
A position estimation method characterized by The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
In the step (a), image data generated from the pixel signal is acquired as the surrounding situation data.
The position estimation method according to claim 4 . The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
In the step (a), data generated from the output signal is acquired as the surrounding situation data.
The position estimation method according to claim 4 . On the computer
(A) From a mobile body equipped with a sensor capable of detecting the surrounding situation, the surrounding situation data specifying the surrounding situation is acquired, the surrounding situation data is compared with the map data, and the correspondence relationship between the two is obtained. Identify, step, and
(B) extracting a target of position estimation from the surrounding situation data, and calculating coordinates of the extracted target on the surrounding situation data;
(C) estimating the position of the object on the map data from the identified correspondence and the calculated coordinates;
Was executed,
In the step (a), the correspondence between the surrounding environmental map data specified by the surrounding situation data and the surrounding situation data is specified as a first correspondence, and the surrounding situation data is photographed. The correspondence between the surrounding situation data and the map data is specified as a second correspondence by matching the map data covering a range wider than the range.
In the step (c),
The coordinates on the environmental map data of the target are specified from the first correspondence relationship and the coordinates on the peripheral situation data of the target,
Furthermore, an affine mapping of the environmental map data and the map data is calculated using the first correspondence relationship and the second correspondence relationship,
Then, the coordinates on the environmental map data are converted into the coordinates on the map data by inputting the coordinates on the environmental map data into the calculated affine map,
Estimating the coordinates obtained by the transformation as the position of the object on the map data,
program. The movable body includes, as the sensor, an imaging element that outputs a pixel signal according to the received light.
In the step (a), image data generated from the pixel signal is acquired as the surrounding situation data.
The program according to claim 7 . The moving body includes, as the sensor, a sensor whose characteristic of an output signal changes in accordance with the distance to an object present in the periphery;
In the step (a), data generated from the output signal is acquired as the surrounding situation data.
The program according to claim 7 .

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