Information processing device, information processing method, and program

Abstract

To stably move a mobile body.SOLUTION: An information processor for controlling a mobile body including measurement means for measuring a position of the mobile body includes: first acquisition means for acquiring environment information on a surrounding environment in which the mobile body moves; estimation means for estimating first position information indicating a position at which measurement accuracy of the measurement means changes on the basis of the environment information; and determination means for determining contents of the control on the basis of the first position information.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Technologies have been proposed for automatically moving a mobile object such as a transport vehicle (e.g., an AGV; Automated Guided Vehicle) within an environment such as a factory or a logistics warehouse. When moving automatically, a map of the real space may be created and the vehicle's own position and orientation within the real space may be measured. A known method for this is the SLAM (Simultaneous Localization and Mapping) method. Non-Patent Document 1 describes a method for estimating the vehicle's own position and orientation (the camera's shooting position and orientation) by comparing a video frame captured by a camera with feature points on map information. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Jakob Engel,et.al.LSD-SLAM:Large-Scale Direct Monocular SLAM,Technical University Munich Summary of the Invention [Problem to be solved by the invention]

[0004] However, as described in Non-Patent Document 1, when position and orientation measurement is performed using images captured by a camera, the accuracy of position measurement may decrease due to changes in the imaging environment, which poses a problem in that the moving object cannot be made to travel stably.

[0005] SUMMARY OF THE INVENTION An object of the present invention is to move a moving body stably. [Means for solving the problem]

[0006] The present invention provides an information processing device for controlling a moving body, the information processing device comprising: a measurement means for measuring the position of the moving body; a first acquisition means for acquiring environmental information about the surroundings of the moving body; an estimation means for estimating, based on the environmental information, first position information indicating a position where the measurement accuracy of the measurement means changes; and a determination means for determining the content of the control based on the first position information. a display control means for displaying positions where the measurement accuracy changes in a different display format from other positions on a map showing the layout of objects in the environment; The present invention is characterized by having the following. [Effects of the Invention]

[0007] According to the present invention, it is possible to move a moving body stably. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a mobile system. [Figure 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of an information processing device. [Figure 4] 10 is a flowchart illustrating a process executed by the information processing device. [Figure 5] FIG. 10 is a diagram illustrating an example of a GUI screen. [Figure 6] FIG. 10 is a diagram illustrating an example of a GUI screen. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0010] <Embodiment 1> In this embodiment, an example will be described in which the present invention is applied to the control of a mobile object that transports luggage in a logistics warehouse. In this embodiment, a camera is mounted on the mobile object, and the mobile object measures its own position and orientation based on feature points extracted from an image captured by the camera. In this embodiment, it is assumed that multiple mobile objects or people are working in the logistics warehouse. Therefore, the brightness of the aisles and walls changes when lights are turned on and off or when the arrangement of items on shelves is changed, which changes the number and distribution of extracted feature points.

[0011] Therefore, an overhead camera is installed in a position and orientation that allows it to capture changes in brightness in the environment surrounding the moving object. The information processing device according to this embodiment uses images from the overhead camera to detect changes in brightness in the environment surrounding the moving object while measuring its own position and orientation. Based on the change in brightness, the amount of change in measurement accuracy of the position and orientation is calculated, and control is performed to adjust the speed of the moving object before it reaches a point or area where the measurement accuracy decreases. This allows the moving object to continue operating stably.

[0012] Fig. 1 shows an example of the configuration of a mobile body system according to this embodiment. The mobile body system shown in Fig. 1 is a system that automatically drives (moves) a mobile body 100 in a logistics warehouse, and is composed of the mobile body 100, multiple overhead cameras 111a, 111b installed at various locations in the logistics warehouse, and an information processing device 104 (Fig. 2) that is wirelessly connected to these cameras. Note that the information processing device 104 may be mounted on the mobile body 100. The overhead cameras 111a and 111b are cameras that function as sensors for detecting environmental information within a logistics warehouse. Because the overhead cameras 111a and 111b have the same configuration, they will be described below as the overhead camera 111. The environmental information is information related to the measurement accuracy of the position measurement device 102 (described later), and in this embodiment, it is information related to the light source environment (brightness) along the route traveled by the mobile object 100. The mobile object 100 includes an imaging device 101, a position measurement device 102 that measures the position information of the mobile object 100 based on images captured by the imaging device 101, and a control device 103 that controls the driving units of the mobile object 100, such as the motor.

[0013] The imaging device 101 captures images of the surrounding environment of the moving object 100. In this embodiment, the imaging device 101 is mounted on the moving object 100 and moves as the moving object 100 moves, but it may also be configured to be fixed in a position and orientation that allows the position and orientation of the moving object 100 to be measured. The position measurement device 102 measures its own position and orientation from an image captured by the imaging device 101. In this embodiment, the position measurement device 102 measures its own position and orientation by comparing feature points on map information registered when the system was constructed with feature points extracted from a currently captured image. The control device 103 controls the drive units and various devices provided in the moving object 100 in accordance with control content received from the information processing device 104.

[0014] FIG. 2 shows an example of the hardware configuration of an information processing device according to this embodiment. As shown in FIG. 2, the information processing device 104 includes a CPU 201, a ROM 202, a RAM 203, an external memory 204, an input unit 205, a display unit 206, and a network I / F 207. These units are connected to each other via a bus 208. The CPU 201 controls the entire information processing device 104. The CPU 201 loads a program stored in the external memory 204 into the RAM 203 and executes it, thereby realizing the processing of the flowcharts described below. The ROM 202 stores data such as various setting values ​​and parameters. The RAM 203 is a memory that temporarily stores data and control information, and serves as a work area used by the CPU 201 when executing various processes. The external memory 204 stores not only the program executed by the CPU 201 but also a coordinate conversion data table described below.

[0015] The input unit 205 is a keyboard, mouse, or robot controller, and accepts input operations such as information. The display unit 206 outputs processing results under the control of the CPU 201. The display unit 206 may be of any type, such as a liquid crystal display device, a projector, or an LED indicator. The network I / F (interface) 207 is an interface for communicating with the outside world via a network. The information processing device 104 transmits and receives various data to and from external devices such as the moving object 100 and the overhead camera 111 via the network I / F 207. The CPU 201 receives captured images from the overhead camera 111 via the network I / F 207. The CPU 201 also receives measurement results from the position measurement device 102 from the moving object 100 via the network I / F 207, and transmits control details of the control device 103 to the moving object 100.

[0016] 3 shows an example of the functional configuration of the information processing device according to this embodiment. The information processing device 104 functions as an environmental information acquisition unit 311, a calculation unit 312, an estimation unit 313, a position acquisition unit 314, a control determination unit 315, and a presentation unit 316 by the CPU 201 executing a program stored in the external memory 204 or the like.

[0017] The environmental information acquisition unit 311 acquires environmental information about the environment in which the mobile object 100 moves. In this embodiment, the environmental information acquisition unit 311 receives captured images from the overhead camera 111 while the mobile object 100 is moving and acquires brightness values ​​of floor and wall surfaces from the captured images. The environmental information acquisition unit 311 also reads, from the external memory 204 or the like, a coordinate conversion data table for converting pixel positions in the captured images of the overhead camera 111 into three-dimensional coordinates representing three-dimensional positions within the logistics warehouse. Here, the three-dimensional coordinates are expressed in a coordinate system representing positions within the logistics warehouse with the starting position of the mobile object 100 as the origin. The environmental information acquisition unit 311 uses the coordinate conversion data table to generate data indicating the correspondence between the positions of each pixel in the captured images of the overhead camera 111 and three-dimensional positions within the logistics warehouse, and provides the data to the estimation unit 313. The environmental information acquisition unit 311 also provides the captured images of the overhead camera 111 to the calculation unit 312.

[0018] The calculation unit 312 calculates the amount of change in measurement accuracy of the position measurement device 102 based on changes in environmental information. In this embodiment, the calculation unit 312 compares an image (hereinafter referred to as a reference image) taken when creating a map (S401 in FIG. 4) with the captured image provided by the environmental information acquisition unit 311, and calculates the amount of change in luminance value for each pixel. Then, based on the calculated amount of change in luminance value, the calculation unit 312 calculates the amount of change in measurement accuracy of the position measurement device 102 caused by changes in brightness in the driving environment of the mobile object 100. The calculation result is provided to the estimation unit 313. Note that the calculation unit 312 may divide the image captured by the overhead camera 111 into multiple regions, and calculate the amount of change in measurement accuracy for each region based on the proportion of pixels in each region whose luminance value has changed.

[0019] The estimation unit 313 estimates a point or area where the measurement accuracy of the position measurement device 102 changes. In this embodiment, the estimation unit 313 estimates a position where the measurement accuracy changes on a three-dimensional coordinate system with the starting position of the mobile object 100 as the origin, based on data provided by the environmental information acquisition unit 311 and the pixel position where the change in measurement accuracy is detected by the calculation unit 312. The estimation unit 313 provides the estimated position information to the control determination unit 315. Note that the estimation unit 313 may obtain a polygon that circumscribes the points where the measurement accuracy of the position measurement device 102 changes, and estimate the internal area of ​​the polygon as the area where the measurement accuracy of the position measurement device 102 changes. Furthermore, the estimation unit 313 may identify the point or area where the measurement accuracy of the position measurement device 102 changes in two-dimensional space or three-dimensional space.

[0020] The position acquisition unit 314 acquires the position information of the moving object 100 measured by the position measurement device 102 from the moving object 100. The position acquisition unit 314 provides the acquired position information to the control determination unit 315. The control determination unit 315 determines the control details for the moving body 100 and the peripheral devices of the moving body 100 based on the positional relationship between the position information provided by the estimation unit 313 and the position information provided by the position acquisition unit 314. Here, the control determination unit 315 determines the control details for stably moving (traveling) the moving body 100 even if the measurement accuracy of the position measurement device 102 changes. The control determination unit 315 transmits the determined control details to the moving body 100 and the peripheral devices of the moving body 100.

[0021] In this embodiment, when the point or area estimated by the estimation unit 313 is located within a portion of the path along which the mobile object 100 moves, the control determination unit 315 determines to perform control to decelerate the mobile object 100 at a predetermined acceleration. Specifically, the control determination unit 315 transmits the determined control content to the mobile object 100 immediately before the mobile object 100 enters the area estimated by the estimation unit 313. When the mobile object 100 receives the control content, the control device 103 reduces the rotation speed of the motor, thereby enabling the mobile object 100 to stably move (travel) in an area where the measurement accuracy of the position measurement device 102 decreases. Note that when the mobile object 100 is located within the area estimated by the estimation unit 313, the information processing device 104 may immediately transmit the determined control content to the mobile object 100. The presentation unit 316 displays the control content determined by the control determination unit 315 on the display unit 206 .

[0022] Next, the processing executed by the information processing device 104 according to this embodiment will be described. Fig. 4 is a flowchart showing the processing executed by the information processing device 104. The flowchart in Fig. 4 is realized by the CPU 201 expanding a program stored in the external memory 204 or the like into the RAM 203 and executing it. The flowchart in Fig. 4 is executed when a map showing the route along which the moving object 100 will travel is created. Each process (step) in the flowchart will be described below with the prefix S (step) of each code.

[0023] As an initialization step, first, in S401, the CPU 201 stores various setting values, such as map-related information about the driving environment of the mobile object 100 (environmental information indicating the brightness at the time of map creation, the starting position of the mobile object, etc.) and the driving speed of the mobile object, in the ROM 202, etc. The CPU 201 also reads, from the external memory 204, etc., the coordinate conversion data table described above, the driving speed when decelerating the mobile object 100, and predetermined parameters used in S403 to convert the amount of change in luminance value into the amount of change in position measurement accuracy. The position measurement device 102 also acquires camera parameters necessary for self-position measurement. Here, the CPU 201 also performs processing to capture an image using the overhead camera 111 at least once and set a threshold value for the amount of change in luminance value to detect a change in the measurement accuracy of the position measurement device 102 using the captured image (reference image).

[0024] When the moving object 100 starts moving, the CPU 201 starts receiving the captured images being captured by the overhead camera 111 and the position and orientation being measured by the position measurement device 102, and repeatedly executes the processes of S402 to S406 at predetermined intervals. The intervals may be predetermined time intervals, or may be intervals corresponding to the predetermined distance traveled by the moving object 100. Alternatively, the processes may be executed repeatedly at all times. In S402, CPU 201 acquires environmental information about the driving environment of moving body 100. Specifically, CPU 201 acquires brightness values ​​from the image captured by overhead camera 111 at the current time. Note that, if there are multiple overhead cameras 111, CPU 201 may generate environmental information by integrating brightness value information of the images captured by the multiple overhead cameras 111. Next, in S403, the CPU 201 compares the currently captured image with an image captured previously, and detects a change in the measurement accuracy of the position measurement device 102 due to a change in brightness in the driving environment of the mobile object 100, based on information about the luminance values ​​of the floor and wall surfaces. Specifically, the CPU 201 compares the luminance value acquired in S402 with the luminance value of the reference image captured in S401 for each corresponding pixel, and calculates the absolute value of the difference in luminance values ​​as the amount of change. If the amount of change is equal to or greater than the threshold set in S401, the degree of accuracy degradation for that pixel is set to 1, and if it is less than the threshold, the degree of accuracy degradation for that pixel is set to 0, thereby identifying the position of the pixel where the position measurement accuracy has decreased.

[0025] Next, in S404, the CPU 201 estimates a point where the position measurement accuracy changes within the space in which the moving object 100 moves. Specifically, the CPU 201 identifies the point where the position measurement accuracy has decreased based on the image area including the position of the pixel whose accuracy decrease degree became 1 in S403 and the coordinate conversion data table read in S401. Next, in S405, the CPU 201 acquires the position coordinates of the moving body 100 in the spatial coordinate system in which the moving body 100 moves. Next, in S406, the CPU 201 calculates the distance between each point estimated in S404 and the position of the moving body 100, and if any of the distances is less than a predetermined threshold, it determines that the moving body 100 is approaching a point where the position measurement accuracy decreases, and determines to perform control to decelerate the moving body 100. On the other hand, if both distances are equal to or greater than the predetermined threshold, the moving body 100 is not decelerated. Note that the distance between each point estimated in S404 and the position of the moving body 100 may be the distance on the route along which the moving body 100 moves, or may be the distance in a spatial coordinate system along which the moving body 100 moves. The CPU 201 transmits the determined control content to the moving body 100 via the network I / F 207. Next, in S407, CPU 201 repeats the processes of S402 to S406 until it determines that an end instruction has been input from input unit 205, and if it determines that an end instruction has been input, it ends the series of processes shown in the flowchart of FIG.

[0026] In this embodiment, the CPU 201 displays on the display unit 206 a GUI (Graphical User Interface) screen reflecting the control content determined in S406. FIG. 5 shows an example of the GUI screen. The user uses the GUI screen to check and edit the control content of the moving object 100. FIG. 5 displays a horizontal plane 505 when the spatial coordinates in which the moving object 100 moves are viewed from above. An icon 510 indicates the position and orientation of the moving object 100 on the horizontal plane 505. The horizontal plane 505 also shows the position and size of an obstacle 506 in the space in which the moving object 100 moves, and a route A for the moving object 100 to move that has been planned by the user. The moving object 100 continues to move, turning 90 degrees clockwise from the upper right end of the horizontal plane 505.

[0027] Area 500 is displayed with a gray background in an area where it is estimated that the measurement accuracy of the position measurement device 102 will decrease. A dashed line portion 501 within area 500 indicates a route where control of the moving body 100 is reflected in the area where the measurement accuracy decreases. In the example shown in FIG. 5, the moving body 100 enters an area where the measurement accuracy decreases from an area where there is no change in the measurement accuracy. In this embodiment, control is performed to decelerate the moving body 100 in the area where the measurement accuracy of the position measurement device 102 decreases, so in the dashed line portion 501, the moving body 100 moves (travels) at a speed slower than the normal moving speed on route A.

[0028] As shown in FIG. 5, an object list 502 and a control result 503 are displayed on the right side of the GUI screen. The object list 502 displays a selectable list of objects indicating control details on a horizontal plane 505. The control result 503 displays a list of detailed control parameters of the object selected in the object list 502. The control parameters relate to the control details (length of the path traveled by the mobile object 100, traveling speed) determined in S406. The accuracy change color map 504 shows the correspondence between the background color on the horizontal plane 505 and whether or not there is a decrease in position measurement accuracy. In this embodiment, the background color of areas where the position measurement accuracy decreases is gray to distinguish them from areas where the position measurement accuracy does not change.

[0029] According to the first embodiment described above, the moving body 100 having a self-position and orientation measurement function can move (travel) stably even in an environment where the position measurement accuracy is reduced. This makes it possible to prevent rear-end collisions of the moving body 100, which are likely to occur in dark areas inside a logistics warehouse.

[0030] As a first modification of this embodiment, the method by which the CPU 201 acquires environmental information in S402 of FIG. 4 is not limited to the method of acquiring environmental information from images captured by the overhead camera 111, as long as the method can acquire the brightness in the driving environment of the mobile object 100 and the location of the brightness. For example, the CPU 201 may acquire information on the lighting status of lighting fixtures in a logistics warehouse and the illumination range of the lighting fixtures in the spatial coordinates through which the mobile object 100 moves. Furthermore, information on the frequency and color of the lighting fixtures may be acquired. Alternatively, the CPU 201 may acquire output values ​​of multiple illuminometers installed near the route of the mobile object 100 and the measurement range of the illuminometers. Furthermore, the CPU 201 may acquire the environmental information from images captured by the imaging device 101 mounted on the mobile object 100 and information on the position, imaging direction, and angle of view of the mobile object 100.

[0031] As a second modification of this embodiment, the method of converting the image coordinates of the overhead camera 111 into three-dimensional coordinates is not limited to the method using a coordinate conversion data table, as long as it is a method that can uniquely convert the coordinates. For example, a method may be used in which an overhead camera as a stereo camera is used to calculate three-dimensional coordinates in the space in which the moving object 100 moves from pixel positions on the captured image using a known distance measurement method. Alternatively, a method may be used in which a camera that can measure luminance values ​​with known positional relationships between pixels is combined with a camera that can capture distance images to calculate three-dimensional coordinates.

[0032] As a third modification of this embodiment, the method for measuring the self-position and orientation is not limited to the method using the captured image of the imaging device 101, as long as the method can measure the position information of the mobile object 100 in the world coordinate system in the driving environment of the mobile object 100. For example, a method may be used in which the position information of the mobile object 100 is measured by image measurement or image recognition from an image captured by a camera not mounted on the mobile object 100. Alternatively, a method may be used in which the position information is measured from the output value of a position sensor such as a GPS (Global Positioning System) sensor attached to the mobile object 100. Alternatively, a method in which the user specifies the position of the mobile object 100 on a map representing the driving environment of the mobile object 100 may be used. Furthermore, a method may be used in which the edge arrangement and distance information obtained from a depth image are used as indices for position measurement.

[0033] In a fourth modification of the present embodiment, the control content determined by the CPU 201 in S406 of FIG. 4 is not limited to deceleration of the moving object 100. For example, the CPU 201 may control an audio output device (not shown) mounted on the moving object 100 to output a warning sound. The CPU 201 may also control the volume and range of the warning sound to be changed depending on the magnitude of a change in measurement accuracy. The CPU 201 may also control a change in image processing parameters used when extracting feature points from images captured by the imaging device 101. The CPU 201 may also control a change in feature points in map information when performing position and orientation measurement, or a change in map information. The CPU 201 may also control a change in the path of the moving object 100 to bypass the point or area estimated in S404 of FIG. 4. If the moving object 100 is equipped with an obstacle sensor, the CPU 201 may control the obstacle sensor to increase a distance threshold for detecting the presence or absence of an obstacle. Furthermore, the CPU 201 may perform control to accelerate the moving body 100 when the distance between each point estimated in S404 and the position of the moving body 100 becomes equal to or greater than a threshold value.

[0034] Hereinafter, as a fifth modification of the present embodiment, a method for dynamically changing control content based on the amount of change in measurement accuracy of the position measurement device 102 within a point or area where the measurement accuracy changes will be described. In S403 of FIG. 4, a decrease in measurement accuracy is detected by determining the amount of change in luminance value based on a threshold. In this modification, however, the amount of change in luminance value is used as the amount of decrease in measurement accuracy. The CPU 201 may calculate the amount of decrease in measurement accuracy using a stepwise threshold. The CPU 201 may also convert the amount of change in luminance value into the amount of change in measurement accuracy using a predetermined parameter. In this modification, in S406 of FIG. 4, the CPU 201 changes the control parameter depending on the amount of decrease calculated in S403. Specifically, the CPU 201 controls the moving object 100 to decelerate in stages. Here, even when the moving object 100 is moving within an area where the measurement accuracy decreases, the CPU 201 also controls the moving object 100 to decelerate in stages depending on the amount of decrease in measurement accuracy.

[0035] FIG. 6 shows an example of a GUI screen according to this modification. Differences from FIG. 5 will be mainly described below. Region 600 displays the background of a region where the measurement accuracy of the position measurement device 102 is estimated to decrease in gray. Region 600 is displayed in a darker gray than region 500, indicating that the control content is different from that of region 500. Region 600 is a region where the amount of decrease in measurement accuracy is greater than that of region 500. The background color on the horizontal plane 505 is color-coded according to the calculation result of the calculation unit 312. An accuracy change color map 601 indicates the correspondence relationship between the background color on the map and the amount of decrease in measurement accuracy of the position measurement device 102. In this modification, because the amount of decrease in measurement accuracy is greater in region 600 than in region 500, the position measurement device 102 is controlled to move at a slower speed in region 600 than in region 500.

[0036] <Embodiment 2> In the first embodiment, a method for detecting a change in the measurement accuracy of the position measurement device 102 was described based on the brightness values ​​acquired from the image captured by the overhead camera 111. In the present embodiment, a method for detecting a change in the measurement accuracy of the position measurement device 102 will be described based on feature points extracted from the image captured by the overhead camera 111. Below, a description of the same parts as in the first embodiment will be omitted, and the description will focus on the differences.

[0037] In this embodiment, the processes in S402 to S404 in the flowchart of FIG. 4 are different from those in the first embodiment. First, as a premise, in S401 , the CPU 201 performs processing for setting a threshold value for the amount of change in the feature points for detecting a change in the measurement accuracy of the position measurement device 102 . In this embodiment, in S402, the CPU 201 acquires the positions of feature points (distribution of feature points) from the image captured by the overhead camera 111 at the current time. In this embodiment, in S403, the CPU 201 detects a change in the measurement accuracy of the position measurement device 102 based on the distribution of feature points in the currently captured image and the captured image captured before the currently captured image. Specifically, the CPU 201 calculates the absolute value of the difference in the number of feature points between the currently captured image and the captured image captured before the currently captured image as the amount of change, and sets the degree of accuracy degradation to 1 if the amount of change is equal to or greater than a threshold, and sets the degree of accuracy degradation to 0 if the amount of change is less than the threshold. In this embodiment, in S404, if the degree of accuracy degradation is 1, the CPU 201 estimates points or areas in the space in which the moving object 100 moves where the position measurement accuracy is degraded, from the distribution of feature points whose number has changed. Specifically, the CPU 201 divides the image captured by the overhead camera 111 into multiple image areas, and identifies image areas that include the number of changed feature points equal to or greater than the threshold set in S401. The CPU 201 then estimates areas where the measurement accuracy is degraded, based on the identified image areas and the coordinate conversion data table read in S401.

[0038] According to the second embodiment described above, the moving body 100 having a self-position and orientation measurement function can move (travel) stably even in an environment where the position measurement accuracy is reduced. This makes it possible to prevent rear-end collisions of the moving body 100, which are likely to occur in dark areas inside a logistics warehouse.

[0039] In this embodiment, the CPU 201 detects a decrease in measurement accuracy based on a change in the number of feature points extracted from the image captured by the overhead camera 111. However, the method of detecting a decrease in measurement accuracy based on a change in feature points is not limited to this. For example, the CPU 201 may divide the captured image into multiple regions and calculate the degree of accuracy decrease by threshold processing based on the change in the number of feature points included in each region. Alternatively, the CPU 201 may calculate the variance of the coordinates of the feature points and perform threshold processing based on the variance in each axial direction of the captured image coordinates to calculate the degree of accuracy decrease. Furthermore, the CPU 201 may determine the number of changed feature points included in the captured image as the degree of accuracy decrease. Furthermore, the CPU 201 may calculate the degree of accuracy decrease from a combination of the number and distribution of any of the feature points.

[0040] Furthermore, in this embodiment, CPU 201 estimates an area where position measurement accuracy will decrease based on the number of feature points extracted from the image captured by overhead camera 111, but the method for identifying an area where position measurement accuracy will decrease is not limited to this. For example, CPU 201 may estimate an area where position measurement accuracy will decrease by comparing areas divided from the image captured by overhead camera 111. Furthermore, in this embodiment, the moving body 100 is controlled based on the two-dimensional arrangement of feature points, but the moving body 100 may also be controlled based on the three-dimensional arrangement of feature points. For example, the CPU 201 may calculate the spatial positions of a group of feature points in a captured image based on output information from a sensor such as the image capture device 101 mounted on the moving body 100. Then, the CPU 201 may identify a position (area) in space where the position measurement accuracy decreases based on the calculated number and distribution of the three-dimensionally arranged feature points.

[0041] <Embodiment 3> In the first embodiment, a method for changing the speed of the moving body 100 was described when a point or area where the measurement accuracy of the position measurement device 102 changes is located in part of the path along which the moving body 100 moves. In this embodiment, instead of a method for changing the speed of the moving body 100, a method for changing the exposure parameters of the imaging device 101 mounted on the moving body 100 will be described. In the following, a description of the same parts as in the first embodiment will be omitted, and the description will focus on the differences.

[0042] In this embodiment, the process of S406 in the flowchart of FIG. 4 is different from that of the first embodiment. First, in S402, the CPU 201 calculates the amount of decrease in luminance value using the luminance value in the image captured by the overhead camera 111 acquired in S402. If there is a pixel for which the amount of decrease in luminance value is equal to or greater than a predetermined threshold, the amount of decrease in the position and orientation measurement accuracy for that pixel is set to 1, and the amount of decrease in the position and orientation measurement accuracy for other pixels is set to 0. In this embodiment, in S406, the CPU 201 performs processing to increase the exposure parameters of the image capture device 101 at points corresponding to pixels determined in S402 to have reduced position and orientation measurement accuracy. This makes it easier to extract feature points from the image captured by the image capture device 101 even in dark areas within a logistics warehouse, thereby suppressing a reduction in measurement accuracy.

[0043] According to the third embodiment described above, the moving body 100 having a self-position and orientation measurement function can move (travel) stably even in an environment where the position measurement accuracy is reduced. This makes it possible to prevent rear-end collisions of the moving body 100, which are likely to occur in dark areas inside a logistics warehouse.

[0044] In this embodiment, when the brightness value of the image captured by the overhead camera 111 decreases, the exposure parameter of the imaging device 101 of the moving object 100 is increased. On the other hand, when the brightness value of the image captured by the overhead camera 111 increases, the exposure parameter of the imaging device 101 of the moving object 100 may be decreased. Note that the parameters to be controlled are not limited to the exposure parameters of the imaging device 101, but may also be other camera parameters of the imaging device 101, parameters of various devices that affect the measurement accuracy of the position measurement device 102, and the like. For example, parameters related to the shutter speed, aperture, or frame rate of the imaging device 101 may be controlled.

[0045] Although the present invention has been described above with reference to the embodiments, the above embodiments are merely illustrative of specific examples of how the present invention can be implemented, and the technical scope of the present invention should not be construed as being limited by these embodiments. In other words, the present invention can be implemented in various forms without departing from its technical concept or main features.

[0046] (Other embodiments) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program.The present invention can also be realized by a circuit (e.g., ASIC) that realizes one or more functions. [Explanation of symbols]

[0047] 100: moving body, 101: imaging device, 102: position measurement device, 103: control device, 104: information processing device, 111: overhead camera

Claims

1. An information processing device for controlling a moving object, the information processing device comprising a measuring means for measuring a position of the moving object, a first acquisition means for acquiring environmental information of an environment in which the mobile object moves; an estimation means for estimating first position information indicating a position where the measurement accuracy of the measurement means changes based on the environmental information; a determination means for determining the content of the control based on the first position information; a display control means for displaying positions where the measurement accuracy changes in a different display format from other positions on a map showing the layout of objects in the environment; An information processing device comprising:

2. The apparatus further includes a second acquisition means for acquiring second position information indicating the position of the moving object measured by the measurement means, 2. The information processing apparatus according to claim 1, wherein the determining means determines the content of the control based on a positional relationship between the first position information and the second position information.

3. The estimation means calculates the amount of change in the measurement accuracy based on the environmental information, 3. The information processing apparatus according to claim 1, wherein the determining means changes the content of the control depending on the amount of change.

4. 4. The information processing apparatus according to claim 1, wherein the environmental information is information indicating a lighting environment along a route traveled by a mobile object.

5. 5. The information processing apparatus according to claim 1, wherein the first acquisition means acquires the environmental information from an overhead camera that captures an image of a space in which the mobile object moves.

6. the first acquisition means acquires a luminance value from an image captured by the overhead camera; 6. The information processing apparatus according to claim 5, wherein the estimation means estimates the first position information based on a change in the luminance value.

7. the first acquisition means extracts feature points from the image captured by the overhead camera; 6. The information processing apparatus according to claim 5, wherein the estimation means estimates the first position information based on a change in the feature point.

8. 8. The information processing device according to claim 5, wherein the estimation means estimates the first position information using a data table for converting pixel positions in the image captured by the overhead camera into a coordinate system representing the space in which the moving object moves.

9. 9. The information processing apparatus according to claim 1, wherein the content of the control is to change the speed of the moving object.

10. 3. The information processing apparatus according to claim 2, wherein the determining means performs control to reduce the speed of the moving object when the distance between the first position information and the second position information is less than a predetermined threshold value.

11. 11. The information processing apparatus according to claim 1, wherein the measuring means measures the position of the mobile object from a captured image of the surrounding environment of the mobile object.

12. 12. The information processing apparatus according to claim 11, wherein the content of the control is to change camera parameters of the measuring means.

13. 13. The information processing device according to claim 1, wherein the estimation means detects a change in the measurement accuracy when a difference between the environmental information acquired at the current time and the environmental information acquired before the current time is equal to or greater than a predetermined threshold.

14. An information processing device described in any one of claims 1 to 13, characterized in that the display form is a display form that can be distinguished depending on the measurement accuracy.

15. 1. An information processing method for controlling a moving object, the method comprising: a first acquisition step of acquiring environmental information of an environment in which the mobile object moves; an estimation step of estimating first position information indicating a position where the measurement accuracy of the measurement means changes based on the environmental information; a determination step of determining the content of the control based on the first position information; a display control step of displaying the positions where the measurement accuracy changes in a different display format from other positions on a map showing a layout of objects in the environment; An information processing method comprising:

16. A program for causing a computer to function as each of the means of the information processing apparatus according to any one of claims 1 to 14.

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