JP2016080460A - Moving body - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a moving body which detects its current position using information on positioning by GPS and that accurately finds the current position even if a reception state of radio waves from GPS satellites is inferior.SOLUTION: A moving body 1 according to the present invention comprises: a storage part 14 which stores map information 14a including body information representing positions of a plurality of fixed bodies; a body recognition part 15 which recognizes the bodies; a relative position calculation part 10a which calculates current relative positions of the moving body 1 with respect to the bodies based upon the body information and recognition results by the body recognition part 15; a position estimation part 10b which retrieves and estimates positions of the bodies on a map that map information represents, and finds a current estimated position of the moving body 1 on the map that the relative positions indicate; and a position estimation part 10c which weights the current estimated position found by the position estimation part 10b and a current positioning position that GPS positioning information indicates according to a likelihood of estimation by the position estimation part 10b, and determines a current position of the moving body 1.SELECTED DRAWING: Figure 1A

Description

  The present invention relates to a mobile object, and more particularly to a mobile object equipped with a positioning function using GPS (Global Positioning System).

  Conventionally, various types of mobile objects for carrying people and things have been distributed. In addition, an autonomous traveling type moving body has also been proposed as a moving body, so that it can be used not only for transportation purposes but also for surrounding monitoring (security). Regardless of whether it is a transportation purpose or a monitoring purpose, and whether it is an autonomous traveling type, there is a mobile body equipped with a GPS positioning function for grasping its current position. On the other hand, the moving body can move even in a place where GPS radio waves do not reach, and various position detection techniques have been proposed assuming such a situation.

  For example, Patent Document 1 discloses a self-position detection device that calculates an inertial movement amount of a moving body from detection signals of an acceleration sensor and an angular velocity sensor, and detects the position of the moving body from the inertial movement amount. In this apparatus, the camera relative movement amount of the moving object is calculated based on image information captured by a camera mounted on the moving object so that the front of the moving object is a field of view, and is represented by the inertial movement amount. The position of the moving body is corrected by the position of the moving body represented by the camera relative movement amount. As a result, the self-position can be detected with high accuracy even in a place where absolute position detection using radio waves such as GPS is difficult or even when the speed of the moving body is slow.

  Patent Document 2 discloses a current position estimation device that estimates a user's current position without using GPS at the time of route guidance. The current position estimation device includes a positional relationship input unit that inputs a result visually recognized by a user regarding a relative positional relationship between a plurality of features, a map database reference unit that refers to a map database that records the positions of each feature, An estimation engine that estimates a user's current position by specifying a range that can be visually recognized with respect to a plurality of features in a relative positional relationship with reference to a map database.

  Patent Document 3 discloses a vehicle movement determination device that can detect the movement of a vehicle even if the parked vehicle has been moved to a position where GPS satellites do not reach. In this apparatus, when the vehicle is parked, the camera is used to shoot a part of the periphery of the vehicle, and at the time of starting the vehicle, the camera is used to shoot the part of the periphery of the vehicle, and the images of both are compared. It is determined whether or not the vehicle has been moved while the vehicle is parked.

  Patent Document 4 discloses a navigation system that displays a user's estimated position on a predetermined route and provides route guidance with little error even when GPS radio waves cannot be used. This navigation system is an autonomous navigation system that calculates an estimated position based on a GPS mode that calculates an estimated position based on GPS positioning information, a user's travel distance information acquired from a pedometer, and azimuth information acquired from a geomagnetic sensor. Mode, and a pedometer mode that calculates an estimated position based only on travel distance information. When GPS positioning information can be acquired at the time of calculating the estimated position, it is in GPS mode, and autonomous when GPS positioning information cannot be acquired. The navigation mode is switched to the pedometer mode when GPS positioning information cannot be acquired and the operation of the geomagnetic sensor is abnormal.

JP 2005-315709 A JP 2007-205948 A JP 2009-280046 A JP 2012-230092 A

  However, the technique described in Patent Document 4 switches the mode depending on whether radio waves from a GPS satellite can be received or not, and in other modes than the GPS mode, the moving object is positioned regardless of the surrounding environment such as the position of the building. Since it is used to acquire information and the actual reception status of radio waves is not uniquely categorized as usable / unusable, it uses GPS positioning information to respond to changes over time in the surrounding environment. It cannot be said that the current position can be detected accurately.

  Note that the technique described in Patent Document 3 is not a technique that can only determine whether or not the vehicle has moved, and can detect the position of the vehicle. In addition, the techniques described in Patent Documents 1 and 2 are techniques that do not use a positioning result by GPS. Even if the technology described in Patent Documents 1 and 2 is used only when GPS positioning results are used and radio waves from GPS satellites cannot be received, the reception status of radio waves is unambiguous. Therefore, it is not possible to divide the information into available / unusable, so it is not known which position should be used for which scene and the optimum use is not possible.

  The technique described in Patent Document 1 corrects the amount of inertial movement at the position of a moving body represented by the amount of relative movement of the camera. For correction, the same object is added to two captured images. Since there is a need to include it, there is a problem that the speed of a moving body that can cope with correction is limited if the photographing interval with the camera is long. In addition, the technique described in Patent Document 2 requires a user to input a visual recognition result, cannot be applied to an autonomous traveling device, and cannot be used while traveling on a moving body that requires a driver such as an automobile. is there.

  The present invention has been made in view of the above-described situation, and the purpose of the present invention is to determine whether the reception state of a radio wave from a GPS satellite in a mobile body that detects its current position using information measured by GPS. The goal is to be able to accurately determine the current position even in bad situations.

  In order to solve the above-described problem, the first technical means of the present invention is a mobile body including a positioning information acquisition unit that acquires GPS positioning information indicating a positioning position measured by GPS (Global Positioning System), A storage unit that stores map information including object information indicating positions of a plurality of fixed objects, an object recognition unit that recognizes the object, and the object based on the object information and a recognition result of the object recognition unit A relative position calculation unit that calculates a current relative position of the moving body with respect to the map, and searches and estimates the position of the object on the map indicated by the map information, and on the map of the moving body indicated by the relative position A position estimation unit for obtaining a current estimated position of the current position, a current estimation position obtained by the position estimation unit, and a current positioning position indicated by the GPS positioning information. According to the degree A position determining unit that performs weighting and determines the current position of the moving body.

  According to a second technical means, in the first technical means, the position determination unit performs weighting so as to reduce the weight of the positioning position as the likelihood increases.

  According to a third technical means, in the first technical means, when the likelihood is greater than or equal to a predetermined value, the position determination unit eliminates the weight of the positioning position and the likelihood is less than the predetermined value. The weight of the estimated position is eliminated.

  According to a fourth technical means, in any one of the first to third technical means, when the position estimation unit searches for the position of the object, the position is determined at the current position determined by the position determination unit immediately before. The search start range and / or the search range is determined based on this.

  According to a fifth technical means, in any one of the first to fourth technical means, the object information includes information indicating a position of the object recognized in advance by the object recognition unit. It is a thing.

  A sixth technical means is any one of the first to fifth technical means, wherein the object information includes information indicating a height of the object, and the position estimation unit estimates the estimated position. The likelihood increases as the height of the used object increases.

  A seventh technical means is the technical means according to any one of the first to sixth technical means, wherein the object recognizing unit detects an area of the field of view in the upward direction of the moving body, and the position estimating unit comprises the object The likelihood is increased as the field of view detected by the recognition unit is narrower.

  The eighth technical means is any one of the first to seventh technical means, wherein the position determination unit is a GPS satellite used for positioning included in the GPS positioning information or calculated from the GPS positioning information. The weighting coefficient is determined on the basis of information indicating the number and arrangement.

  A ninth technical means is the accuracy of any one of the first to eighth technical means, wherein the map information indicates an area in which the accuracy of the GPS positioning information that can be acquired by the positioning information acquisition unit is worse than a predetermined accuracy. Including the information, the position estimating unit is characterized in that the position determining unit determines the weighting coefficient based on the accuracy information.

  In a tenth technical means according to any one of the first to ninth technical means, the storage unit stores a scheduled travel route of the moving body as a part of the map information, The autonomous traveling device includes a drive control unit that performs autonomous traveling along the planned traveling route based on the current position determined by the position determining unit.

  The eleventh technical means includes any one of the first to ninth technical means on the map based on the operation unit that receives a driving operation by the driver and the current position determined by the position determination unit. And a navigation unit for performing the navigation.

  ADVANTAGE OF THE INVENTION According to this invention, in the mobile body which detects the own present position using the information measured by GPS, a present position can be calculated | required correctly also in the scene where the receiving condition of the electromagnetic wave from a GPS satellite is bad.

It is a block diagram which shows the example of 1 structure of the moving body which concerns on the 1st Embodiment of this invention. It is an external view which shows an example of the mobile body of FIG. 1A. It is a block diagram for demonstrating the detail of the position determination part in the mobile body of FIG. 1A. It is a figure which shows an example of the driving | running route of the mobile body of FIG. 1A. It is a figure which shows an example of the sky image which the mobile body image | photographed in the driving | running route of FIG. It is a block diagram which shows the structural example of a part of moving body which concerns on the 4th Embodiment of this invention. It is a block diagram which shows the example of 1 structure of the moving body which concerns on the 8th Embodiment of this invention.

  The moving body according to the present invention is a moving body that moves within a facility such as a factory or a public facility, or a site such as a facility or a parking lot, or a moving body such as an automobile or a motorcycle traveling on a public road. In particular, some moving bodies that automatically move within a site or facility have an autonomous traveling type control mechanism. A moving body based on driving by a driver such as an automobile also has autonomous driving control so that autonomous driving or autonomous driving as driving assistance for the driver becomes possible. Moreover, the mobile body according to the present invention can be used not only for the purpose of transporting people and objects, but also for monitoring the surroundings while moving, and the mobile body in that case can also be called a monitoring robot. Hereinafter, various embodiments of the present invention will be described with reference to the drawings.

(First embodiment)
A first embodiment of the present invention will be described with reference to FIGS. 1A to 3. First, a configuration example of the moving body according to the present embodiment will be described with reference to the block diagram of FIG. 1A and the external view of FIG. 1B.

  The moving body 1 is a machine having a moving mechanism for moving, and can also be called a moving device. In the example of FIG. 1A and FIG. 1B, this moving mechanism includes a drive control unit 11 and a drive unit 12 including a wheel 12 a controlled by the drive control unit 11. The drive unit 12 includes, for example, an engine and / or a motor (not shown).

  Furthermore, the moving body 1 includes a positioning information acquisition unit 13, a storage unit 14, and an object recognition unit 15, and includes a relative position calculation unit 10a, a position estimation unit 10b, and a position determination unit 10c. In FIG. 1A, an example in which the main control unit 10 that controls the moving body 1 includes the respective units 10 a to 10 c is given, but the configuration is not limited thereto.

  The main control unit 10 may be configured to control the drive control unit 11 and read / write to / from the storage unit 14, and also perform acquisition control by the positioning information acquisition unit 13 and recognition control by the object recognition unit 15. it can. For example, the main control unit 10 includes a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), a RAM (Random Access Memory) as a work area, and a control device such as a storage device. It can also be mounted as an integrated circuit / IC chip set. This storage device stores a control program (including a program for executing processing to be described later in each unit 10a to 10c), and various setting contents. As this storage device, various devices such as an HDD (Hard Disk Drive) and an SSD (Solid State Drive) can be applied.

  The positioning information acquisition unit 13 is a part that acquires GPS positioning information indicating a positioning position measured by GPS. The positioning information (latitude and longitude) is obtained by analyzing an antenna that receives radio waves from a GPS satellite and a received GPS signal. It consists of the analysis part etc. which ask for. The antenna may be arranged at an appropriate position of the main body 16 of the moving body 1 like the position of the positioning information acquisition unit 13 illustrated in FIG. 1B. However, the antenna is not limited to the illustrated arrangement, and the antenna may be provided at a position where the sensitivity is improved. In addition, the positioning information acquisition part 13 corrects a position from providing the function of DGPS (Differential GPS) or the function of RTK-GPS (Real Time Kinematic GPS), and the positional relationship with a radio | wireless communication part and a radio | wireless communication base station. By providing the function, the cost increases, but the accuracy can be increased.

  The memory | storage part 14 is a site | part which memorize | stores the map information 14a. The map information 14a also includes object information indicating the positions of a plurality of fixed objects. The map information 14a also includes information indicating the position of a passable area (such as a road or a non-parking area in a parking lot). When the moving body 1 is a monitoring robot, the map information 14a can be said to be information indicating an environmental map. Here, the fixed object (hereinafter simply referred to as an object) may include not only a real estate such as a building but also other structures such as railroad tracks, planted trees, street trees, walls, and pillars. It can be said that the object is a concept that is actually present and excludes an area (such as a road) that is actually present among concepts that are generally called features.

  The object recognition unit 15 is a part that recognizes an object. The object recognition unit 15 may basically recognize the position of the object with respect to the moving body 1 (distance and direction from the moving body 1 to the object). Therefore, as the object recognition unit 15, an obstacle detection sensor for detecting the position of the obstacle with respect to the moving body 1, a camera for taking a still image or a moving image, or the like can be used. Note that a camera that captures a still image can cope with the movement of the moving body 1 by shortening the shooting interval.

  The obstacle detection sensor is a sensor for detecting them in advance in order to avoid collision with other moving objects and obstacles, and actively transmits light, infrared rays, other electromagnetic waves, ultrasonic waves, etc. The active sensor detects the position of the obstacle by receiving the reflected wave of the transmitted wave. As the obstacle detection sensor, for example, various types of sensors such as LIDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging), laser range finder, radio wave radar (millimeter wave radar, etc.), and ultrasonic sensor can be applied. In addition, the obstacle detection sensor performs reception using a mechanical scan system that moves left and right by a motor or multiple channels as necessary, and calculates the detection angle using the phase difference that occurs between the reception channels. The obstacle may be detected by adopting an electronic scanning method. The laser range finder is a distance measuring sensor that employs a time of flight (TOF) time-of-flight method. By providing one or two scanning axes, two-dimensional measurement and three-dimensional measurement are possible. Measurement is possible. LIDAR can also be said to be a kind of laser range finder.

  Further, the object recognition unit 15 is preferably provided in front of the moving body 1 as illustrated in FIG. 1B, but it is only necessary to recognize an object in the traveling direction even if it is provided in another part. In addition, by providing a plurality of object recognition units 15 at different positions and / or by providing a plurality of types of object recognition units 15, the position of the object can be recognized more accurately.

  The relative position calculation unit 10 a calculates the current relative position of the moving body 1 with respect to the recognized object based on the object information and the recognition result in the object recognition unit 15. Some obstacle detection sensors incorporate the function of the relative position calculation unit 10a. Since the recognition of the object means the recognition of the surrounding environment (surrounding situation) of the mobile body 1, it can be said that the object recognition unit 15 and the relative position calculation unit 10a constitute a surrounding environment information acquisition unit.

  The position estimation unit 10b refers to the map information 14a to obtain the current estimated position on the map of the mobile body 1. More specifically, the position estimation unit 10b searches and collates the position of the recognized object on the map indicated by the map information 14a and estimates the position on the map of the moving object 1 indicated by the relative position. Find the current estimated position of. For this search, an image matching (also referred to as map matching) technique can be applied. In the following description, this search is also called image matching. The image matching method is not limited, but it is preferable to perform pattern matching that extracts the position of the object or a point on the surface of the object as a feature point and matches the pattern.

  At this time, even if only one object can be recognized, image matching is possible because, for example, the angle of a line segment connecting two horizontal points on the surface of the object can be recognized. Therefore, if there is even one object, it is possible to estimate not only the distance of the object to the moving body 1 but also the direction. It is also possible to employ a procedure in which the relative position calculation unit 10a calculates the relative position of the moving body 1 after the position estimation unit 10b searches for the position of the object, and the position estimation unit 10b obtains the estimated position from the result. Good.

  Since the position estimation unit 10b performs estimation by image matching, the degree of coincidence (coincidence rate) is one index that represents the likelihood of the estimation. When the likelihood is high, it means that the estimation result of the self-position in the position estimation unit 10b is reliable. Conversely, when the likelihood is low, it means that the estimation result is not reliable. The degree of coincidence or likelihood is the amount of information used for estimation, such as the accuracy of the map information 14a used for recognition (particularly the accuracy in the region where the recognized object exists) and the number of recognized objects. Will depend.

  For example, in a situation where the environment does not change over 360 degrees, such as a vast desert or a plaza, the feature point for estimating the self-position cannot be found (the amount of information is insufficient) (ie, the estimation accuracy is degraded) The likelihood is reduced). However, under such circumstances, since there is no obstacle from the GPS satellite to the moving body 1, the accuracy of the GPS positioning information is high. On the contrary, in the situation where there are high buildings around, the accuracy of the estimation increases (that is, the likelihood increases). Under such circumstances, the GPS positioning information deteriorates its accuracy because it may receive radio waves reflected on the building or the satellite may become invisible. Considering these points, the position determination unit 10c determines the current position as follows.

  That is, the position determination unit 10c weights the current estimated position obtained by the position estimation unit 10b and the current positioning position indicated by the GPS positioning information according to the likelihood of estimation by the position estimation unit 10b. The current position of the moving body 1 is determined (determined). The current position determined in this way is an accurate position even in a situation where the reception state of the radio wave from the GPS satellite is poor.

  Next, a more specific example of the position determination unit 10c in the present embodiment will be described with reference to FIGS. FIG. 2 is a block diagram for explaining details of the position determining unit in the moving body in FIG. 1A, and FIG. 3 is a diagram showing an example of a travel route of the moving body in FIG. 1A.

  The above-mentioned weighting according to likelihood means weighting with a weighting coefficient according to likelihood. Therefore, the position determination unit 10c receives the likelihood as shown in FIG. 2, inputs the weighting coefficient calculation unit 21 that calculates the weighting coefficient, and the GPS positioning information and the estimated position together with the weighting coefficient, and calculates the current position. A weighting execution unit 22.

  For example, the likelihood K (0 <K ≦ 1) is directly used as the weighting coefficient for the estimated position, and the remaining position (1-K) is used as the weighting coefficient on the positioning position side to obtain the current position. This calculation may be executed for each latitude and longitude as in the following equation. The reason why (1-K) is used as the weighting coefficient on the positioning position side is that the likelihood K is large so that there are many objects around the moving body 1 (the reliability of the estimated position is high), which prevents the reception of GPS signals, This is because the reliability of the GPS positioning information may be reduced.

(Latitude of current position) = (1-K) × (Latitude of GPS positioning position) + K × (Latitude of estimated position)
(Longitude of current position) = (1-K) × (longitude of GPS positioning position) + K × (longitude of estimated position)

These equations mean the following equations when the reliability of the GPS positioning information is α (0 <α ≦ 1).
(Latitude of current position) = α × (Latitude of GPS positioning position) + (1−α) × (Latitude of estimated position)
(Longitude of current position) = α × (longitude of GPS positioning position) + (1−α) × (longitude of estimated position)

  As in this example, it is preferable that the position determination unit 10c performs weighting that reduces the weight of the positioning position as the likelihood increases (that is, decreases the reliability of the positioning position). Therefore, if the matching rate (collation rate) of image matching, which can be said to be an index of likelihood, is k (%), the reliability α of the GPS positioning position may be set to 1-k / 100, for example. However, the method of obtaining the likelihood K and α is not limited to this. Of course, the reliability β on the estimated position side according to the likelihood K may be defined, the weighting coefficient on the estimated position side may be β, and the weighting coefficient on the positioning position side may be 1−β.

  A map 30 illustrated in FIG. 3 shows a map of an area where objects (buildings or other obstacles) 31 a to 31 d and objects (street trees or planted trees) 31 e exist along the road 32. Such a map is included in the map information 14a. A description will be given assuming a scene in which the moving body 1 actually moves on the road 32 from the position of the moving body 1a to the position of the moving body 1b and the position of the moving body 1c in time series.

  First, in a scene where the moving body 1 is present at the position of the moving body 1a, since the object does not exist in the surroundings, the matching rate corresponding to the likelihood is 0% or several percent, while the GPS positioning information indicates Will overlap with the actual position of the mobile body 1a. Of course, it is assumed here that the object recognition unit 15 does not have the capability of recognizing the objects 31a, 31c and the like. In this case, the reliability α of the GPS positioning information is 1, and the current position is determined as the GPS positioning position.

  In a scene where the moving body 1 is present at the position of the moving body 1b, since there are many objects in the vicinity, the matching rate corresponding to the likelihood is 100% (or a value close thereto), while the GPS positioning information indicates The latitude / longitude 33b on the map is considerably different from the actual position of the moving body 1b. In this case, the reliability α of the GPS positioning information is 0 (or a value close to 0), and the current position is determined as the estimated position (or the vicinity thereof) in the position estimation unit 10b.

  In a scene where the moving body 1 exists at the position of the moving body 1c, since there are a small number of objects in the vicinity, the matching rate corresponding to the likelihood is, for example, 50%, and the latitude and longitude 33c on the map indicated by the GPS positioning information moves. It will slightly deviate from the actual position of the body 1c. In this case, the reliability α of the GPS positioning information is 0.5, for example, and the current position is determined to be an intermediate position between the position estimated by the position estimation unit 10b and the position indicated by the GPS positioning information.

  Further, when the likelihood K is greater than or equal to a predetermined value, the position determination unit 10c eliminates the weight of the positioning position (determines the current position as the estimated position), and when the likelihood K is less than the predetermined value, Weighting may be performed so as to eliminate the weight of the estimated position (determine the current position as a positioning position). The predetermined value may be a predetermined higher value such as 70%.

Next, other application examples will be described.
When executing the image matching, the position estimation unit 10b preferably determines the search start range and / or the search range on the basis of the current position determined by the position determination unit 10c immediately before. This not only increases the speed of image matching, but also preferentially extracts search results that are close to the determined search start range, or searches within the determined search range for image matching. (That is, estimation accuracy) can be improved. In particular, not only the determined current position but also the speed of the moving body 1 (and the traveling direction of the moving body 1 obtained from other sensors such as a magnetic sensor) are taken into account, and these ranges are determined, so that more images can be obtained. Matching accuracy can be increased.

  As can be seen from this example, the moving body 1 includes a magnetic sensor that measures the geomagnetism, and detects the traveling direction of the moving body 1 by detecting the direction in which the magnetic sensor is facing. It can also be configured to output to the main control unit 10 and be used for correction of the traveling direction.

  The object information of the map information 14a used for image matching preferably includes information indicating the position of the object recognized in advance by the object recognition unit 15. That is, in order to use it for image matching during actual traveling, object recognition by the object recognition unit 15 (which is preferably mounted on the moving body 1 but may be non-mounted) is performed on the route planned to travel, The object recognition result and the recognized position are stored in association with each other. Thereby, the coincidence rate in image matching is increased, and the accuracy is improved.

  For example, when the moving body 1 is used for monitoring in a specific area such as a parking lot or a site, it is very useful because a planned travel route is determined. That is, the mobile body 1 stores the planned travel route of the mobile body 1 as part of the map information 14a in the storage unit 14, and based on the current position (current position on the map) determined by the position determination unit 10c, This is particularly beneficial when the autonomous traveling device includes the drive control unit 11 that performs autonomous traveling along the planned traveling route. Of course, the example of performing autonomous traveling along such a planned traveling route can also be applied to an example not including information indicating the position of an object recognized in advance as object information.

  Further, such prior object recognition is not limited to the above-described example. The mobile body 1 performs object recognition by the object recognition unit 15 during actual travel, associates the current position determined by the position determination unit 10c with the object, and registers it as object information. You may give it. In recent years, the development of SLAM (Simultaneous Localization and Mapping) technology that simultaneously performs self-position estimation and map creation based on object recognition results such as cameras and laser range finders has been actively conducted. You may make it produce the map information 14a containing object information.

(Second Embodiment)
A second embodiment of the present invention will be described mainly with reference to FIG. In the present embodiment, description of the overlapping parts with the first embodiment is basically omitted, but various application examples described in the first embodiment can be applied, for example.

  In the present embodiment, the object information in the map information 14a includes information indicating the height of the object (for example, the heights Ha to He in FIG. 3), that is, the map information 14a is information on a three-dimensional map. preferable. Here, the height information represents the small surface area of the object that can be recognized from the moving body 1. In particular, the information is more preferably information indicating the height of an object recognized in advance by the object recognition unit 15.

  And the position estimation part 10b in this embodiment raises the said likelihood K, so that the height of the object used for estimation of the said estimated position is high. More specifically, first, when an object such as a high building exists around the moving body 1, the accuracy of GPS deteriorates due to the influence of the reflected wave on the object. However, in the present embodiment, the higher the height of the object used for estimation based on the height information held as part of the map information 14a, the lighter the positioning position and the higher the estimated position weight. To confirm the current position. Therefore, for example, even when the moving body 1 is traveling in a position surrounded by objects (buildings) 31a to 31c such as the moving body 1b in FIG. It can be determined with high accuracy.

(Third embodiment)
A third embodiment of the present invention will be described mainly with reference to FIGS. FIG. 4 is a diagram showing an example of the sky image taken by the moving body 1b in the travel route of FIG. In the present embodiment, description of the overlapping parts with the first embodiment is basically omitted, but various application examples described in the first embodiment can be applied, for example.

  The object recognition unit 15 in the present embodiment detects the size of the field of view in the upward direction of the moving body 1. Here, the width of the field of view in the sky direction represents the small surface area of the object that can be recognized from the moving body 1, similarly to the height described in the second embodiment. In this embodiment, it is preferable to provide the object recognition unit 15 on the upper surface side of the moving body 1, and therefore it can be said that it is preferable to provide a plurality of object recognition units 15 together with the object recognition unit 15 for the traveling direction.

  And the position estimation part 10b in this embodiment raises the likelihood K, so that the said visual field detected by the object recognition part 15 is narrow. More specifically, first, for example, when a camera is used as the object recognition unit 15, it is understood that the sky field of view is opened when the proportion of the sky (not an artifact) is large by image recognition. For example, when LIDAR is used If the percentage of the distance data in the upward direction is infinite (there is no object), it can be understood that the sky field of view has been developed.

  Therefore, for example, an object recognized by the moving body 1 at the position of the moving body 1b in FIG. 3 (for example, a photographed image or a two-dimensional representation image (depth image) of the detected distance) is an image 40 illustrated in FIG. become. Of these, the sky region 41 is wider than when no object is present, and the moving body 1 is located in a situation where the sky field of view of itself is blocked (a situation where the degree of opening up the sky field of view is low). . In this situation, the accuracy of GPS deteriorates due to the influence of the reflected wave on the object.

  Therefore, in the present embodiment, as the field of view is narrower, the likelihood K is increased, thereby reducing the weighting to the positioning position and increasing the weighting to the estimated position to determine the current position. By such processing, for example, even when the moving body 1 is traveling in a position surrounded by objects (buildings) 31a to 31c such as the moving body 1b in FIG. 3, there is an accurate estimation result based on object recognition. The current position can be determined with high accuracy.

  In addition, this embodiment can be used in combination with the second embodiment. In this case, the likelihood K is obtained based on a predetermined function having the height and the field of view as variables, or the weighting coefficient is directly set. You just have to ask for it.

(Fourth embodiment)
A fourth embodiment of the present invention will be described with reference to FIG. FIG. 5 is a block diagram illustrating a configuration example of a part of the moving body according to the fourth embodiment of the present invention. In this embodiment, the description of the overlapping part with the first embodiment is basically omitted, but for example, various application examples described in the first embodiment can be applied, and the second and third examples can be applied. Combination with the embodiment is also possible.

  The position determination unit 10c in the present embodiment determines the weighting coefficient based on information indicating the number and arrangement of GPS satellites used for positioning (hereinafter referred to as satellite arrangement information). An example of such a configuration will be described. FIG. 5 illustrates a part of the moving body 1, but the positioning information acquisition unit 13 includes a GPS signal reception unit 51, a GPS coordinate calculation unit 52, and a DOP (Dilution Of Precision) value calculation unit 53. The position estimation unit 10 b includes a position coordinate estimation unit 54 and a likelihood calculation unit 55. The position determination unit 10c includes a weighting coefficient calculation unit 21 and a weighting execution unit (multiplication unit) 22 as illustrated in FIG.

  In the position estimation unit 10b, the position coordinate estimation unit 54 calculates an estimated position (coordinates of the estimated position) by image matching, and the likelihood calculation unit 55 calculates the likelihood K from the calculation process.

  On the other hand, in the positioning information acquisition unit 13, the GPS signal receiving unit 51 receives radio waves from GPS satellites, and the GPS coordinate calculation unit (analysis unit) 52 analyzes the received signal to calculate GPS positioning coordinates. Further, the DOP value calculation unit 53 analyzes the received signal or calculates the DOP value from the calculation process of the GPS positioning coordinates.

  Thus, the satellite arrangement information is information included in the GPS positioning information acquired by the positioning information acquisition unit 13 or information that can be calculated from the GPS positioning information. For example, an index value indicating the degree of deterioration of the GPS satellite arrangement, That is, it is possible to use a DOP value that is an index value indicating the degree of degradation of GPS accuracy. The greater the DOP value, the lower the GPS accuracy. A value of 0 to 1 may be used as the DOP value, but is not limited to this. Further, the DOP value has many index values such as a geometric accuracy reduction rate, a horizontal accuracy reduction rate, and a vertical degree reduction rate, and any value or a plurality of values may be adopted. Good.

  The satellite arrangement information such as the DOP value can be said to be an index representing the breadth of the field of view above the moving body 1, and is related to the number and height of objects around the moving body 1. There is a relationship. In general, when the DOP value is high, the reliability of the positioning position is low and the reliability of the estimated position is high because the positioning of the satellite is bad, for example, the satellite is fixed.

  Therefore, it can be said that determining the weighting coefficient based on the satellite arrangement information as in this embodiment is beneficial for improving the accuracy of the current position. In the position determination unit 10c, the weighting coefficient calculation unit 21 inputs the likelihood K from the likelihood calculation unit 55 and the DOP value from the DOP value calculation unit 53, and calculates the weighting coefficient from these values. For example, a K × DOP value may be used as the weighting coefficient γ on the estimated position side, and the weighting coefficient on the GPS positioning position side may be 1−γ. In addition, although the example using the value between 0 and 1 was given as a K and DOP value, it is not restricted to this, In that case, what is necessary is just to normalize (normalize).

  As illustrated here, the position determination unit 10c may perform weighting that reduces the weight of the positioning position as the DOP value increases (that is, decreases the reliability of the positioning position). Alternatively, when the DOP value is equal to or greater than a predetermined value (for example, 50% of the maximum value), the position determining unit 10c eliminates the weight of the positioning position (determines the current position as the estimated position), and the DOP value is the predetermined value. If it is less than the weight, weighting may be performed so as to eliminate the weight of the estimated position (determine the current position as a positioning position).

  In addition, it can be said that the satellite arrangement information is a determination condition to be added to the weighting coefficient determination conditions as described in the first to third embodiments. However, the determination procedure is not limited. For example, after the weighting coefficient is determined according to the determination condition described in the first to third embodiments, it may be corrected based on the satellite arrangement information.

  After the weighting coefficient is determined, the weighting execution unit (multiplication unit) 22 uses the weighting coefficient to determine the positioning coordinate input from the GPS coordinate (positioning coordinate) calculation unit 52 and the estimated position coordinate input from the position coordinate estimation unit 54. On the other hand, for example, weighting is performed according to the following equation to calculate (determine) the coordinates of the current position.

(Latitude of current position) = (1−γ) × (Latitude of GPS positioning position) + γ × (Latitude of estimated position)
(Longitude of current position) = (1-γ) × (longitude of GPS positioning position) + γ × (longitude of estimated position)

(Fifth embodiment)
The weighting method using the satellite arrangement information described in the fourth embodiment can be applied even when the likelihood is not used. Such a configuration example will be briefly described as a fifth embodiment.

  The mobile body according to the present embodiment is the same as the mobile body 1 described in the first embodiment and the like, the positioning information acquisition unit 13, the storage unit 14, the object recognition unit 15, the relative position calculation unit 10a, and the position estimation unit. 10b, but the processing of the position determination unit 10c is slightly different.

  The position determination unit 10c in the present embodiment weights the current estimated position obtained by the position estimation unit 10b and the current positioning position indicated by the GPS positioning information according to the satellite arrangement information (calculation of a weighting coefficient). To determine the current position of the moving object. For example, when the DOP value is low, the weighting coefficient on the positioning position side is increased and the weighting coefficient on the estimated position side is decreased. Conversely, when the DOP value is high, the weighting coefficient on the positioning position side is lowered and the weighting coefficient on the estimated position side is increased. It can be said that performing weighting based on satellite arrangement information as in the present embodiment is beneficial for improving the accuracy of the current position.

(Sixth embodiment)
A sixth embodiment of the present invention will be described. In this embodiment, the description of the overlapping part with the first embodiment is basically omitted, but for example, various application examples described in the first embodiment can be applied, and the second to fifth examples are applicable. It can be used in combination with any embodiment.

  In the present embodiment, the map information 14a includes accuracy information indicating a region where the accuracy of the GPS positioning information that can be acquired by the positioning information acquisition unit 13 is worse than a predetermined accuracy. The timing for embedding the accuracy information in the map information 14a may be, for example, the same timing as the prior object recognition in the object recognition unit 15 described in the first embodiment. Therefore, when the map information 14a is first created (map) At the time of construction) or a learning function for accuracy information. When the accuracy information learning function is provided, for example, the difference between the current position determined by the position determination unit 10c and the positioning position indicated by the GPS positioning information used at that time is regarded as an error, and the accuracy information at the current position is used. That's fine.

  This accuracy information can be used as information indicating the reliability of the current GPS positioning information acquired by the positioning information acquisition unit 13 and is an index indicating the breadth of the field of view above the moving body 1. It is related to the number and height of surrounding objects, and therefore also related to the ease of estimation. Therefore, the position determination unit 10c in the present embodiment determines the weighting coefficient based on the accuracy information. And it can be said that determining the weighting coefficient based on the accuracy information in this way is useful for improving the accuracy of the current position.

  When determining the weighting coefficient, the position determination unit 10c performs weighting that increases the weight of the positioning position (that is, increases the reliability of the positioning position) as the accuracy indicated by the accuracy information increases. Alternatively, when the accuracy indicated by the accuracy information is greater than or equal to a predetermined value (for example, 50% of the maximum value), the position determination unit 10c eliminates the weight of the estimated position (determines the current position as the positioning position), and the accuracy is If it is less than the predetermined value, weighting may be performed so as to eliminate the weight of the positioning position (determine the current position as the estimated position). Further, as accuracy information, only two values of “0” indicating that the accuracy is low and “1” indicating that the accuracy is high are adopted, and in the case of the former, the estimated position is determined, and in the case of the latter, You may make it fix to a positioning position.

  It can be said that the accuracy information is a determination condition to be added to the weighting coefficient determination conditions as described in the first to fourth embodiments. However, the determination procedure is not limited. For example, after the weighting coefficient is determined according to the determination conditions described in the first to fourth embodiments, it may be corrected based on the accuracy information.

(Seventh embodiment)
The weighting method using the accuracy information described in the sixth embodiment can be applied even when the likelihood is not used. Such a configuration example will be briefly described as a seventh embodiment.

  The mobile body according to the present embodiment is the same as the mobile body 1 described in the first embodiment and the like, the positioning information acquisition unit 13, the storage unit 14, the object recognition unit 15, the relative position calculation unit 10a, and the position estimation unit. 10b, but the processing of the position determination unit 10c is slightly different.

  The position determination unit 10c according to the present embodiment performs weighting (calculation of a weighting coefficient) according to accuracy information for the current estimated position obtained by the position estimation unit 10b and the current positioning position indicated by the GPS positioning information. Determine the current position of the moving object. For example, when the accuracy information indicates that the GPS accuracy is high, the weighting coefficient on the positioning position side is increased and the weighting coefficient on the estimated position side is decreased. Conversely, when the accuracy information indicates that the GPS accuracy is low, the weighting coefficient on the positioning position side is decreased and the weighting coefficient on the estimated position side is increased. It can be said that performing weighting based on accuracy information as in this embodiment is beneficial for improving the accuracy of the current position.

(Eighth embodiment)
An eighth embodiment of the present invention will be described with reference to FIG. FIG. 6 is a block diagram illustrating a configuration example of a moving object according to the eighth embodiment of the present invention. In the present embodiment, the description of the overlapping part with the first embodiment is basically omitted, but various application examples described in the first embodiment can be applied, and the second to seventh examples can be applied. It can be used in combination with any embodiment.

  In 1st Embodiment, the mobile body 1 demonstrated and demonstrated the example which is an autonomous traveling apparatus. The moving body 6 according to the present embodiment illustrated in FIG. 6 is based on the operation unit 61 that receives a driving operation by the driver and the current position determined by the position determination unit 10c in addition to the units 11 to 15 in FIG. A navigation unit 62 that performs navigation on the map indicated by the map information 14a. The operation unit 61 includes a handle, an accelerator, a brake, and the like.

  The navigation unit 62 displays, for example, a map such as the map 30 illustrated in FIG. 3 (however, the position of the moving body is one location of the current position), for example, a destination registered in advance by a driver or a passenger It may be guided by voice and a route display so as to go to (to be along a planned travel route to the destination). Therefore, the navigation unit 62 includes an image display unit and / or an audio output unit. In the present embodiment, an autonomous traveling function may be provided. In that case, autonomous traveling may be supplemented by driving of the driver, or deficiencies of driving by the driver may be supplemented by autonomous traveling.

DESCRIPTION OF SYMBOLS 1, 1a, 1b, 1c, 6 ... Mobile body, 10 ... Main control part, 10a ... Relative position calculation part, 10b ... Position estimation part, 10c ... Position determination part, 11 ... Drive control part, 12 ... Drive part, 12a DESCRIPTION OF SYMBOLS ... Wheel, 13 ... Positioning information acquisition part, 14 ... Memory | storage part, 14a ... Map information, 15 ... Object recognition part, 16 ... Main body, 21 ... Weighting coefficient calculation part, 22 ... Weighting execution part, 30 ... Map, 31a, 31b , 31c, 31d, 31e ... object, 32 ... road, 33a, 33b, 33c ... latitude and longitude, 40 ... image, 41 ... sky region, 51 ... GPS signal receiver, 52 ... GPS coordinate calculator, 52 ... GPS coordinate calculator 53, DOP value calculation unit, 54 ... Position coordinate estimation unit, 55 ... Likelihood calculation unit, 61 ... Operation unit, 62 ... Navigation unit.

Claims (11)

A mobile body including a positioning information acquisition unit that acquires GPS positioning information indicating a positioning position measured by GPS (Global Positioning System),
A storage unit for storing map information including object information indicating positions of a plurality of fixed objects;
An object recognition unit for recognizing the object;
A relative position calculation unit that calculates a current relative position of the moving body with respect to the object based on the object information and a recognition result in the object recognition unit;
A position estimation unit that searches and estimates the position of the object on the map indicated by the map information, and obtains a current estimated position on the map of the moving object indicated by the relative position;
The current estimated position obtained by the position estimating unit and the current positioning position indicated by the GPS positioning information are weighted according to the likelihood of estimation by the position estimating unit, and A position determination unit for determining the current position;
A moving object comprising:   The mobile unit according to claim 1, wherein the position determination unit performs weighting so as to reduce a weight of the positioning position as the likelihood increases.   The position determination unit eliminates the weight of the positioning position when the likelihood is equal to or greater than a predetermined value, and eliminates the weight of the estimated position when the likelihood is less than the predetermined value. Item 4. The moving body according to Item 1.   The position estimation unit, when searching for the position of the object, determines a search start range and / or a search range based on the current position determined by the position determination unit immediately before. 4. The moving body according to any one of 3 above.   The mobile object according to claim 1, wherein the object information includes information indicating a position of the object recognized in advance by the object recognition unit. The object information includes information indicating the height of the object,
The mobile object according to claim 1, wherein the position estimation unit increases the likelihood as the height of the object used for estimating the estimated position is higher. The object recognizing unit detects a field of view in the sky direction of the moving body,
The mobile object according to claim 1, wherein the position estimation unit increases the likelihood as the field of view detected by the object recognition unit is narrower.   The position determining unit determines the weighting coefficient based on information indicating the number and arrangement of GPS satellites used for positioning included in the GPS positioning information or calculated from the GPS positioning information. The moving body according to any one of claims 1 to 7. The map information includes accuracy information indicating an area in which the accuracy of the GPS positioning information that can be acquired by the positioning information acquisition unit is worse than a predetermined accuracy,
The mobile unit according to claim 1, wherein the position determination unit determines the weighting coefficient based on the accuracy information. The storage unit stores a planned travel route of the moving body as a part of the map information,
The said mobile body is an autonomous traveling apparatus provided with the drive control part which performs autonomous traveling along the said scheduled traveling route based on the said current position determined by the said position determination part. The moving body according to any one of 9. An operation unit for receiving a driving operation by the driver;
A navigation unit for performing navigation on the map based on the current position determined by the position determination unit;
The moving body according to any one of claims 1 to 9, further comprising:

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