JP2013160566A - Positioning device and positioning program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a positioning device, a memory device, and a positioning program which are capable of precisely estimating a position of a mobile without arranging a device in a space in which the mobile moves.SOLUTION: A positioning device 100a includes a dead reckoning unit 120 which estimates a position of a user 200 on a map on the basis of a sensing result by a sensor device 110 for estimating a position of a user 200, a database unit 130 which associates the sensing result with the position on the map and stores the sensing result in advance, and a correction unit 140 which corrects the position of the user 200 estimated by the dead reckoning unit 120 so as to match the position on the map associated with the sensing result.

Description

  The present invention relates to a positioning device and a positioning program for estimating the position of a moving object.

  There is a technique for estimating the position of a person using a sensor arranged in a space where the person moves. Patent Documents 1 and 2 disclose a technique for positioning while switching a plurality of frequency bands in a positioning system using a high-frequency signal, and a means for estimating a position and a direction using a plurality of environment-installed active tags. Has been.

International Publication No. 1999/060338 JP 2000-549909 A

  In the positioning system (positioning device) disclosed in Patent Documents 1 and 2, a global positioning system (GPS), an RFID (Radio Frequency IDentification) tag, and a Wi- It is assumed that the position of a person is estimated using a Fi (registered trademark) device, a Bluetooth (registered trademark) device, or the like.

  However, there are many spaces where these devices cannot be arranged. For example, GPS cannot receive radio waves from satellites in the basement and indoors and cannot be used. In addition, for example, there are many indoor spaces in which RFID tags, Wi-Fi (registered trademark) devices, Bluetooth (registered trademark) devices, and the like are not arranged. As described above, the positioning devices disclosed in Patent Documents 1 and 2 have a problem that the position of the moving body cannot be estimated unless the device is arranged in a space in which the moving body moves.

  The present invention has been made in view of the above points, and provides a positioning device and a positioning program capable of estimating the position of a moving body with high accuracy without arranging the apparatus in a space in which the moving body moves. The purpose is to provide.

  The present invention has been made to solve the above problem, and based on a sensing result by a sensor device for estimating the position of the moving body, a dead reckoning unit that estimates the position of the moving body, A storage unit that stores a sensing result in advance in association with a position on a map, and a position on the map that is associated with the sensing result, the position of the moving body on the map estimated by the dead reckoning unit. And a correction unit that corrects the signal so as to coincide with the positioning device.

  Further, the present invention provides the correction unit on the map so that the correction unit matches the position on the map associated with the sensing result having a high probability of being taken, based on the probability that the sensing result can be taken. It is a positioning device characterized by correcting the position of a moving body.

  Further, the present invention is the positioning device, wherein the storage unit stores the sensing result in advance in association with a position on the map of a target that affects the position of the moving body.

  Further, in the present invention, the storage unit stores in advance, as the map, a network type map, a polygon type map, and the sensing result corresponding to the position of the moving body. Device.

  Further, the present invention is the positioning device, wherein the storage unit stores in advance the network type map including shape information of the geometric structure of the network.

  In the present invention, the storage unit stores in advance the network type map including a point to which an identifier is assigned and a point to which no identifier is assigned as points constituting the geometric structure of the network. This is a characteristic positioning device.

  In the present invention, the sensor device senses at least one of acceleration, velocity, angular velocity, temperature, humidity, image, pressure, magnetic field strength, electric field strength, direction, air vibration, posture, light quantity, and luminance. This is a positioning device.

  Further, the present invention provides an integration unit that integrates the first position of the moving object estimated by the dead reckoning unit and the second position of the moving object estimated by the positioning unit that positions the moving object. And the correction unit corrects the position of the moving body on the map integrated by the integration unit so as to coincide with the position on the map associated with the sensing result. It is.

  Further, the present invention provides a computer with a procedure for estimating the position of the moving object based on a sensing result by a sensor device for estimating the position of the moving object, and the estimated position of the moving object on a map. And a procedure for correcting the position so as to match the position on the map associated with the sensing result.

  According to the present invention, the correction unit corrects the estimated position of the moving body on the map to the position on the map associated with the sensing result. Thereby, the positioning apparatus can estimate the position of the moving body with high accuracy without arranging the apparatus in the space in which the moving body moves.

It is a block diagram which shows the structural example of the positioning apparatus in 1st Embodiment of this invention. It is an example of the map by which the node and link in 1st Embodiment of this invention are arrange | positioned. It is an example of the map by which the node, link, and arc in 1st Embodiment of this invention are arrange | positioned. It is an example of the map in which the spatial polygon is arrange | positioned in 1st Embodiment of this invention. It is an example of the map in which the walking space polygon and the barrier polygon are arrange | positioned in 1st Embodiment of this invention. It is an example of the map in which the walking space polygon, the barrier polygon, and the object polygon are arrange | positioned in 1st Embodiment of this invention. It is a block diagram which shows the structural example of the positioning apparatus in 2nd Embodiment of this invention.

[First Embodiment]
A first embodiment of the present invention will be described in detail with reference to the drawings. Hereinafter, a mobile body (for example, a pedestrian, a wheelchair, a vehicle) will be described as an example of a pedestrian. In addition, hereinafter, the pedestrian state (for example, the position, posture, behavior, speed, direction) of the pedestrian and the surrounding environment (for example, current time, stairs) that affects the position of the pedestrian are referred to as “pedestrian. Context.

  Hereinafter, estimating the position of the moving object is referred to as “positioning”. Hereinafter, a positioning method for estimating the position of the moving object using the current state of the moving object and its history is referred to as “dead reckoning”. Hereinafter, a value output from the sensor device according to the sensing result is referred to as a “sensor value”. Hereinafter, an index (sensor value accuracy information) indicating how reliable the sensor value output by the sensor device is referred to as “sensor reliability”. Hereinafter, an index of how reliable the positioning result is (positioning result accuracy information) is referred to as “positioning reliability”. Hereinafter, the error information of the sensor value is referred to as “sensor accuracy”. Hereinafter, the position error information as the positioning result is referred to as “positioning accuracy”.

  Hereinafter, a value used for position estimation (position recognition) such as dead reckoning is referred to as a “parameter”. Hereinafter, correction of a value (correction of a positioning result or a parameter used for position estimation, or correction of a position using a high positioning accuracy method such as an active tag) is referred to as “calibration”.

  Hereinafter, the positioning method using the sensor device held by the moving body is referred to as “autonomous navigation type positioning (autonomous navigation, dead reckoning navigation)”. Here, the autonomous navigation type positioning includes a positioning method using both a sensor device held by the moving body and a device (for example, an active tag) arranged in a space in which the moving body moves.

First, a configuration example of the positioning device will be described.
FIG. 1 is a block diagram showing a configuration example of a positioning device. The positioning device 100a moves with the user 200 by being held by the user 200 as a pedestrian. The positioning device 100a matches the position estimation result of its own device with dead reckoning (autonomous navigation type positioning) and map information even when no other positioning device is arranged in the space in which the user 200 moves. The position of 200 can be estimated with high accuracy.

  The positioning system includes a positioning device 100a and an information presentation device 300. The positioning device 100a includes a sensor device 110, a dead reckoning unit 120, a database unit 130, a correction unit 140, and an application unit 150. The dead reckoning unit 120, the correction unit 140, and the application unit 150 are arithmetic units that operate based on a program developed in a memory (not shown), for example.

  The sensor device 110 and the database unit 130 may be provided outside the positioning device 100a by being connected to the positioning device 100a via an interface unit (not shown). In this case, the positioning device 100a may further include a memory that stores data (cache data) similar to the data stored in the database unit 130 (server device).

  The sensor device 110 detects the pedestrian context of the user 200 by sensing, and outputs a sensor value corresponding to the detection result to the dead reckoning unit 120 for each type of sensor device. Here, the sensor value includes, for example, a value indicating acceleration, a value indicating velocity, a value indicating angular velocity, a value indicating temperature, a value indicating humidity, and an image (icon image, character / symbol image). A value indicating light intensity and brightness, a value indicating pressure (atmospheric pressure, etc.), a value indicating magnetic field strength, a value indicating electric field strength, a value indicating direction, and a value indicating air vibration, There is a value indicating the posture. The sensor device 110 is, for example, an acceleration sensor, a velocity sensor, an angular velocity sensor, a temperature sensor, a humidity sensor, an image sensor, a pressure sensor, a magnetic field sensor, an air vibration sensor, and a gyro sensor.

  The pedestrian context includes, for example, actions (walking on a flat ground, running on a flat ground, sitting, moving on an escalator, walking on an escalator, walking on an escalator, walking on a escalator, rising or falling on an elevator, etc. Pedestrian behavior), environment (stairs, elevator, indoor, outdoor, roadway, subway platform, subway car, etc.) , Expressed in altitude, relative coordinate system, expressed by semantic information indicating the location, etc. There are various representation methods, speed (moving speed of pedestrians), and movement history (pedestrians) ), The current time, the posture (the pedestrian's posture and direction), the direction (the pedestrian's moving direction), the positioning device 100a, and the sensor device 1. 0 and a place where the positioning device 100a and the sensor device 110 are held by a pedestrian (including the sensor device 110 in a pedestrian's breast pocket, a pants pocket, a shoe, a bag, etc. And a place where the positioning device 100a is held.

  Sensor values detected according to the pedestrian context of the user 200 are input from the sensor device 110 to the dead reckoning unit 120 for each type of sensor device. The dead reckoning unit 120 performs positioning by dead reckoning (first positioning method) based on the input sensor values (for example, the user's 200 step cycle, number of steps, stride, posture, and orientation) and a predetermined reference position. The positioning result (for example, three-dimensional coordinates) is output to the correction unit 140. In addition, the dead reckoning unit 120 transfers the sensor value detected according to the pedestrian context of the user 200 to the correction unit 140 for each type of sensor device.

  The database unit 130 (storage unit) stores map information in advance. This map information includes network-type map information, polygon-type map information, and pedestrian context (context information). The network type and the polygon type are examples of map information types, and the map information need not be limited to these types. The database unit 130 is a recording medium such as a silicon memory, an optical recording disk, or a magnetic recording disk.

  Network type map information and polygon type map information include objects (objects) existing in the real space shown on the map, such as passages, stairs, escalators, moving walkways, elevators, walls, obstacles, furniture. , Posters and signs (signage) etc., their width, length, height and angle shape, their colors and materials, the speed of elevators, escalators and moving walkways, elevators, escalators and moving Information indicating an operation sound peculiar to a sidewalk, information indicating an announcement sound, and information indicating a warning sound are included.

  The database unit 130 stores in advance, as the probability that the pedestrian context can take, what action the user 200 can take when the user 200 uses an object (target) that affects the position of the user 200. Yes. Here, the probability that the pedestrian context can take is, for example, the probability that the user 200 uses a passage, stairs, escalator, moving sidewalk, and elevator as objects. In addition, for example, the probability that the pedestrian context can take is the probability that the user 200 remains facing the direction of the wall at the same position in order to use a signage (signage) as an object attached to the wall. Good.

  In addition, the database unit 130 stores in advance, as a probability that a pedestrian context can take, what state the environment of the space in which the user 200 moves when the user 200 uses the object. Here, the probability that the pedestrian context can take is, for example, the probability that the user 200 located in a predetermined range from the object can hear a specific sound (for example, announcement sound, warning sound, operation sound) from the object. is there.

  The database unit 130 stores a pedestrian context and an object polygon (described later with reference to FIG. 6) in association with each other. In addition, the database unit 130 stores in advance the sensor pattern information unique to the object, which is assumed to be detected by the sensor device 110 when the user 200 uses the object, and the pedestrian context. .

  That is, the sensor pattern information associated with the pedestrian context and the object polygon are associated in advance. Since the object polygon is arranged on the map (described later with reference to FIG. 6), the sensor pattern information unique to the object is associated with the position of the object polygon on the map.

  More specifically, the context type ID, context ID and context name relating to the pedestrian context, the sensor type ID and sensor pattern relating to the sensor pattern information, and the polygon ID and position accuracy relating to the object polygon are associated with each other. It has been.

  Here, the context type ID is an ID for identifying the type of the pedestrian context. The context ID is an ID for identifying a pedestrian context. The context name is the name of the pedestrian context. The sensor type ID is an ID for identifying the type of the sensor device for estimating the pedestrian context. The sensor pattern is a sensor pattern for estimating a pedestrian context. The polygon ID is an ID for identifying an object polygon (described later). The position accuracy is the position estimation accuracy. The position accuracy is expressed as, for example, the accuracy of three-dimensional coordinates (longitude, latitude, altitude).

  A positioning result by dead reckoning (first positioning method) and a sensor value for each type of sensor device are input from the dead reckoning unit 120 to the correction unit 140. Further, the correction unit 140 acquires map information (network type map information, polygon type map information, pedestrian context) from the database unit 130.

  When the user 200 uses an object that is within a predetermined range from the position indicated by the estimated pedestrian context, the correction unit 140 provides information on what action the user 200 can take on the object. The correctness in the estimation of the pedestrian context is determined based on the included map information. In addition, when the user 200 uses an object that is within a predetermined range from the position indicated by the estimated pedestrian context, the correction unit 140 can assume what state the environment of the space in which the user 200 moves can take. The correctness in the estimation of the pedestrian context is determined based on the map information including the information.

  More specifically, the correction unit 140 determines the correctness in the estimation of the pedestrian context by the dead reckoning unit 120 by using a sensor pattern (map) unique to an object within a predetermined range from the position indicated by the estimated pedestrian context. Information) and the sensor pattern of the sensor value input for each type of sensor device.

  Here, the correction unit 140 reestimates the probabilities that each of the estimated plurality of pedestrian contexts can take (re-evaluates the reliability), thereby enabling the pedestrian context having the highest possible probability (reliability). Is estimated to be the most correct pedestrian context. Note that the correction unit 140 may reestimate the probability that the pedestrian context can take based on the information indicating the sensor reliability, the sensor accuracy, and the positioning accuracy.

  When the pedestrian context estimated based on the sensor value is different from the most correct pedestrian context, the correction unit 140 corrects the pedestrian context estimated based on the sensor value to the most correct pedestrian context (pedestrian Context correction). That is, the correcting unit 140 employs the most correct pedestrian context among a plurality of pedestrian contexts estimated based on the sensor value.

  For example, when the user 200 is located within a predetermined range from an elevator as an object and the sensor value of the atmospheric pressure is reduced, the correction unit 140 displays a pedestrian context in a state where the user 200 has climbed on the elevator. Adopt as the most correct pedestrian context. Further, for example, when the user 200 is located within a predetermined range from the posting as an object and an announcement sound from the posting is detected by the sensor device 110, the correction unit 140 causes the user 200 to display the posting. The pedestrian context in the state of watching is adopted as the most correct pedestrian context.

  As a result, the correction unit 140 can correct (calibrate) the position (parameter) of the user 200 on the map to the position indicated by the most correct pedestrian context as necessary, such as ensuring positioning accuracy. it can. For example, the correction | amendment part 140 correct | amends the position of the user 200 on a map to the position of the elevator which is rising, when the user 200 employ | adopts the pedestrian context in the state where it climbs on the elevator. Further, for example, when the pedestrian context in which the user 200 is looking at the posting material is adopted, the correction unit 140 changes the position and orientation of the user 200 on the map to a predetermined relative position and relative direction with respect to the posting material. To correct.

  The correction unit 140 may adopt the most correct pedestrian context based on a predetermined criterion. Here, for example, when the object is an elevator, the determination criterion is a criterion for adopting a pedestrian context in which the sensor value of the atmospheric pressure changes according to the elevator rising or falling (conditional branch). As described above, the determination criterion may be expressed in the form of conditional branching.

  The correction unit 140 outputs information indicating the position of the user 200 on the map (or the corrected position when corrected) to the application unit 150. Further, the correction unit 140 outputs information indicating the direction of the user 200 on the map (or the corrected direction when corrected) to the application unit 150.

  The application unit 150 performs predetermined application processing on the information indicating the position of the user 200 on the map and the information indicating the direction of the user 200 on the map, and outputs the processing result to the information presentation device 300. Here, the predetermined application process is, for example, a process of generating a map image to which a mark image indicating the position of the user 200 (corrected position when corrected) is pasted.

  A processing result of application processing (for example, a map image with a mark image pasted) is input from the application unit 150 to the information presentation device 300. The information presentation device 300 presents the input processing result to the user 200. The information presentation device 300 is, for example, a display device or a speaker.

Next, details of the network type map information will be described.
Network-type map information (hereinafter referred to as “spatial network”) includes a node and a link as geometric structure information. Here, the node is point information on the route, and is information indicating a point where traffic is possible. Further, an identifier is assigned to the node. This identifier is a number that is managed and operated by the Ubiquitous ID Center (Shinagawa-ku, Tokyo) for individually identifying a real-world article and place, and may be a ucode that is a 128-bit unique number. The link is connection information that connects nodes that can pass, and is information that indicates a path that can be passed. The geometric structure of the link is defined by a start node and an end node.

  The spatial network may include an arc as the geometric structure information. Here, the arc is shape information connecting the links, and is information indicating a more detailed route shape as compared with the links. An arc is represented by a sequence of points having position information. Note that an identifier may not be given to each point of the arc.

  As described above, the spatial network is a database including points (nodes) and routes (links) as information indicating the geometric structure of routes that can be passed by pedestrians. Here, the minimum unit of the spatial network is a link structure including a node as a starting point of one link, a node as an end point of the link, and an arc as a shape of the route. A spatial network is represented by a table in which a large number of link structures are connected. The spatial network may be expressed in the form of a directed graph.

  The spatial network includes information indicating the type (category) of the route in addition to information indicating the geometric structure. Here, the type of route is information indicating a type (category) for each static geometric structure (for example, a passage, an elevator, and an escalator) that is assumed not to be changed in a short time.

  In addition, unlike the walking space network data (Ministry of Land, Infrastructure, Transport and Tourism “Walking space network data maintenance specification draft”, September 2010 version), the type of route may include an arc that is the shape information of the route.

  FIG. 2 is an example of a map in which nodes and links are arranged. In FIG. 2, nodes and links are arranged on a map representing a certain underground shopping area. The nodes are arranged at points where the route is branched and points where the type of the route is changed on a route that the pedestrian can pass (hereinafter referred to as “traffic route”).

  The points where the passage route branches include, for example, a point where the corridor is bent, a point where the slope angle changes, a branch point to the entrance / exit of the underground shopping street, and a branch point to the side road. In addition, the points where the route type (for example, stairs and rooms) changes include, for example, a stair landing and a point that passes when moving from one room to another. Here, the reason why the node is arranged at the point where the route type changes is that the route type is associated with the link. That is, the route is identified for each link.

  The link is connection information (route connection information) that connects nodes that can pass, and is information that indicates a route that can pass. The link can be operated as long as the branch structure and type of the route do not change. The link expresses a semantic relationship of the connection relationship between the nodes, and does not indicate the shape of the route in the real space.

  FIG. 3 is an example of a map in which nodes, links, and arcs are arranged. In FIG. 3, nodes, links, and arcs are arranged on a map representing a certain underground shopping street. The arc is path shape information and can be densely arranged according to the shape of the path. Details of the geometric structure of the path are expressed by line segments connecting the points of the point sequence constituting the arc.

  Here, when a route search from a node is executed in a spatial network in which identifiers are assigned to nodes that are arranged too densely, multiple identifier resolution is required, so the processing efficiency deteriorates. End up. Therefore, there is an advantage in distinguishing the link (route connection information) managed by the identifier from the arc (route shape information) not managed by the identifier.

  On the other hand, there is also an advantage in managing the link point sequence and the arc point sequence using identifiers. In this case, for example, position information, traffic information, content information, and the like can be associated with each other without executing a large-scale geometric calculation. Nodes, links and arcs will be placed taking into account the tradeoffs of these benefits.

Next, details of polygon (polygon) map information will be described.
The polygon-type map information is a database that expresses a free space with a space polygon that cannot be expressed by a spatial network. The space polygon is data that expresses a space through which a pedestrian can pass with a polygon. The spatial polygon includes a row of vertices, a side connecting the vertices along the row (hereinafter referred to as “edge”), and attribute information (Polygon property) indicating the type of the polygon.

  The vertex (vertex) includes the three-dimensional position information (three-dimensional coordinates). The attribute information indicating the type of polygon includes a space polygon ID, a space polygon type, and an area ID (space ID). Here, the spatial polygon ID is an identifier for identifying a polygon. Also, the spatial polygon type is a type indicating whether it is a spatial polygon indicating an object that can pass even if it is somewhat difficult to pass, or whether it is a spatial polygon indicating an object (barrier) that cannot be passed at all. is there. The area ID is an identifier indicating the partial space to which the space polygon belongs.

  FIG. 4 is an example of a map in which spatial polygons are arranged. In FIG. 4, each space polygon is arranged on the same plane as a plane polygon. Polygon type map information includes a walking space polygon, a barrier polygon, and an object polygon.

  Here, the walking space polygon is a planar polygon that can be partially and freely arranged at a necessary portion of the space polygon indicating the floor space that can be passed. In the following, it is assumed that the walking space polygon is partially and freely arranged at a necessary portion of the space polygon.

  FIG. 5 is an example of a map in which walking space polygons and barrier polygons are arranged. Since the walking space polygon is a polygon that expresses a space in which a pedestrian can pass, it is necessary to make the walking space polygon distinguish between an edge that can pass and an edge that cannot pass. The barrier polygon is used in combination with a walking space polygon as a polygon representing an impassable barrier. More specifically, the barrier polygon is arranged at the edge of the walking space polygon as an inaccessible edge in the space where the walking space polygon is arranged.

  In FIG. 5, the barrier polygon is arranged at the edge of the walking space polygon. In FIG. 5, a part of the barrier polygon and the edge of the walking space polygon overlap. An edge in which the coordinate values overlap in the same space indicates that the pedestrian on the map cannot enter or exit the walking space polygon. That is, from this overlapping edge, a pedestrian on the map cannot enter or exit the walking space polygon. Here, the walking space polygon and the barrier polygon are associated with the walking space polygon so that it can be identified whether they belong to the same walking space polygon.

  FIG. 6 is an example of a map in which a walking space polygon, a barrier polygon, and an object polygon are arranged. The object polygon is a general-purpose polygon for showing details of the position, size, and shape of an obstacle (for example, a foliage plant, a dust box, and an ornament). The object polygon is a general-purpose polygon for describing a more dynamic and detailed object as compared with the walking space polygon and the barrier polygon.

  The object polygon is a spatial polygon including information indicating a local space (for example, a step position, a store shelf position, a dust box position, an automatic ticket gate position, and a houseplant position). The object polygon includes a column of vertices, an edge, and attribute information indicating the type of the polygon. Here, information indicating the local space is included as attribute information indicating the type of polygon.

  The object polygon is arranged when it is desired to express the fine position of the obstacle arranged on the pedestrian's path with a wide polygon instead of a point and a line. Note that the local space in which the obstacle indicated by the object polygon is arranged is a space that can be passed if, for example, a pedestrian straddles the obstacle even if the passage is somewhat difficult. The information indicating the local space may include information indicating the degree of difficulty in passing.

  As described above, the positioning device 100a includes the dead reckoning unit 120 that estimates the position of the user 200 based on the sensing result by the sensor device 110 for estimating the position of the user 200, and the sensing result on the map. The position of the user 200 on the map estimated by the dead reckoning unit 120 and the database unit 130 stored in advance in association with the position matches the position on the map associated with the sensing result (pedestrian context). And a correction unit 140 that corrects the correction.

  With this configuration, the correction unit 140 corrects the position of the user 200 on the map estimated by the dead reckoning unit 120 so as to match the position on the map associated with the sensing result. Thereby, the positioning apparatus 100a can estimate the position of the moving body with high accuracy without arranging the apparatus in the space in which the moving body moves. Further, the positioning device 100a can perform efficient and robust pedestrian position estimation.

  Further, the correction unit 140 is configured to map the map associated with the sensing result (the most correct pedestrian context) having the highest probability based on the probability that the sensing result can be taken (the probability that the pedestrian context can take). The position of the user 200 on the map is corrected so as to coincide with the upper position (the position indicated by the object polygon arranged on the polygon type map).

  In addition, the database unit 130 stores the sensing result in advance in association with the position on the map of an object (object) that affects the position of the user 200.

  In addition, the database unit 130 stores in advance a network type map, a polygon type map, and the sensing result corresponding to the position of the moving body as the map.

  Further, the database unit 130 stores in advance the network type map including shape information (arc) of the geometric structure of the network.

  In addition, the database unit 130 includes a point where an identifier is given (a node constituting a link) and a point where no identifier is given (a point constituting an arc) as points constituting the geometric structure of the network. A map of the type is stored in advance.

  The sensor device 110 senses at least one of acceleration, velocity, angular velocity, temperature, humidity, image, pressure, magnetic field strength, electric field strength, direction, air vibration, posture, light amount, and luminance.

[Second Embodiment]
The second embodiment is different from the first embodiment in that the integration result of the positioning result by dead reckoning (first positioning method) and the positioning result by the second positioning method is corrected. Only the differences from the first embodiment will be described below.

  FIG. 7 is a block diagram illustrating a configuration example of the positioning device. The positioning device 100b further includes a positioning unit 121 and an integration unit 122, as compared with the positioning device 100a of the first embodiment.

  The positioning unit 121 measures the user 200 by the second positioning method, and outputs the positioning result to the integration unit 122. As the second positioning method, for example, there is a positioning method using a high-frequency signal (a signal from an RFID tag, a Wi-Fi (registered trademark) device, or a Bluetooth (registered trademark) device).

  A positioning result by dead reckoning is input from the dead reckoning unit 120 to the integration unit 122. In addition, the positioning unit 121 receives a positioning result by the second positioning method from the positioning unit 121. The integration unit 122 integrates the positioning result by dead reckoning and the positioning result by the second positioning method, and outputs the integrated positioning result (for example, three-dimensional coordinates) to the correction unit 140.

  As described above, the integration unit 122 that integrates the first position of the user 200 estimated by the dead reckoning unit 120 and the second position of the user 200 estimated by the positioning unit 121 that positions the user 200 is provided. The correction unit 140 corrects the position of the user 200 on the map integrated by the integration unit 122 so as to coincide with the position on the map associated with the sensing result.

  With this configuration, the correction unit 140 corrects the position of the user 200 on the map integrated by the integration unit 122 so as to match the position on the map associated with the sensing result (pedestrian context). Thereby, when the apparatus for positioning is arrange | positioned in the space where a mobile body moves, the positioning apparatus 100b can estimate the position of the mobile body with higher precision.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes designs and the like that do not depart from the gist of the present invention.

  For example, the moving body may be a moving body (for example, a wheelchair or a vehicle) that moves by wheels. The positioning device may estimate the position of the moving body based on the wheel diameter and the wheel rotation angle instead of the stride.

  For example, the correctness in estimating the pedestrian context may be expressed by a plurality of step levels.

  Note that a program for realizing the positioning device described above may be recorded on a computer-readable recording medium, and the program may be read into a computer system and executed. The “computer system” here includes an OS and hardware such as peripheral devices. The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Further, the “computer-readable recording medium” refers to a volatile memory (RAM) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, those holding programs for a certain period of time are also included. The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, what is called a difference file (difference program) may be sufficient.

DESCRIPTION OF SYMBOLS 100a and 100b ... Positioning apparatus, 110 ... Sensor device, 120 ... Dead reckoning part, 121 ... Positioning part, 122 ... Integration part, 130 ... Database part (memory | storage part), 140 ... Correction | amendment part, 150 ... Application part, 200 ... User , 300 ... Information presentation device

Claims (9)

A dead reckoning unit for estimating the position of the moving body based on a sensing result by the sensor device for estimating the position of the moving body;
A storage unit for storing the sensing result in advance in association with a position on a map;
A correction unit that corrects the position of the moving body on the map estimated by the dead reckoning unit to match the position on the map associated with the sensing result;
A positioning device comprising:   The correction unit corrects the position of the moving body on the map so as to coincide with the position on the map associated with the sensing result having a high probability of being taken, based on the probability that the sensing result can be taken. The positioning device according to claim 1, wherein:   The positioning device according to claim 1, wherein the storage unit stores the sensing result in advance in association with a position on the map of a target that affects the position of the moving body.   The storage unit stores in advance a network-type map, a polygon-type map, and the sensing result corresponding to the position of the moving body as the map. The positioning device according to any one of the above.   The positioning device according to claim 4, wherein the storage unit stores in advance the network type map including shape information of a geometric structure of the network.   5. The storage unit stores in advance the network type map including a point to which an identifier is assigned and a point to which no identifier is assigned as points constituting the geometric structure of the network. Or the positioning apparatus of Claim 5.   The sensor device senses at least one of acceleration, velocity, angular velocity, temperature, humidity, image, pressure, magnetic field strength, electric field strength, direction, air vibration, posture, light quantity, and luminance. The positioning device according to any one of claims 1 to 6. An integration unit that integrates the first position of the moving body estimated by the dead reckoning unit and the second position of the moving body estimated by the positioning unit that positions the moving body;
The correction unit corrects the position of the moving body on the map integrated by the integration unit so as to coincide with the position on the map associated with the sensing result. The positioning device according to claim 7. On the computer,
A procedure for estimating the position of the moving body based on a sensing result by the sensor device for estimating the position of the moving body;
Correcting the estimated position of the moving body on the map to match the position on the map associated with the sensing result;
Positioning program to execute.

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