JP2022180077A - Autonomous moving device - Google Patents

Abstract

To provide an autonomous moving device which correctly recognizes a landmark that has a state changing, and which correctly estimates the own location.SOLUTION: An autonomous moving device includes: a ceiling camera that images a landmark; an environmental sensor that obtains a surrounding situation; an internal sensor that detects information on the own position; and an own position estimating device. The own position estimating device includes: a landmark detection processing unit that detects the information on the landmark; a storing unit that stores the information on the landmark and environmental map data; a landmark state determining unit which determines the state of the landmark on the basis of the detected information on the landmark and of the stored information on the landmark, and which calculates the positional information on the landmark having undergone weighting in accordance with the detection precision of the information on the landmark; and an own position estimating unit based on the positional information by the internal sensor, the surrounding situation in the travelling direction obtained by the environmental sensor, the environmental map data stored by the storing unit, and the weighted positional information on the landmark calculated by the landmark state determining unit.SELECTED DRAWING: Figure 1

Description

The present invention relates to an autonomous mobile device in which a ceiling camera facing the ceiling detects landmarks and estimates its own position based on landmark information.

An autonomous mobile device, such as a robot, is being developed in which an external sensor and an internal sensor are installed in an autonomous mobile device, which uses these external and internal sensors to estimate its own position and autonomously move to a destination. .

In particular, in order to stably detect landmarks even when the autonomous mobile device is surrounded by people, an external sensor such as a ceiling camera is used to Autonomous mobile devices for estimating position have been proposed.

Background art in such a technical field includes, for example, Japanese Patent Laying-Open No. 2005-242409 (Patent Document 1) and Japanese Patent Laying-Open No. 6-4127 (Patent Document 2).

Patent Document 1 discloses a sign detecting means for detecting signs (landmarks) installed in a moving environment, a distance measuring means for acquiring distance information to objects existing in the surroundings, and a map information storing map information of the moving environment. Autonomous movement having map storage means, self-position calculation means for estimating self-position by collating acquired distance information and stored map information, and route generation means for generating a movement route to a destination A robotic system (autonomous mobile device) is described (see abstract). Patent Document 1 describes that the sign detected by the sign detection means is installed on the ceiling of the mobile environment (see 0041).

In addition, in Patent Document 2, a TV camera installed on a traveling truck shoots the ceiling above the traveling route (moving environment) including fluorescent lamps (landmarks), and the position of the fluorescent lamp in the photographed image. , an indoor moving body (autonomous mobile device) that calculates (detects) with an image processing device and calculates the position of the traveling trolley with a calculation device based on the position of the fluorescent light in the captured image and the absolute position of the fluorescent light. (see abstract).

JP-A-2005-242409 JP-A-6-4127

Patent Literature 1 and Patent Literature 2 describe an autonomous mobile device that detects landmarks (signs and fluorescent lights) installed on the ceiling of a mobile environment and estimates its own position.

However, Patent Literature 1 and Patent Literature 2 describe situations in which an installed sign cannot be detected due to deterioration of the sign over time or changes in the surrounding lighting environment, or when the installed lighting is turned off. Circumstances which cannot be detected due to the cause are not described.

Accordingly, the present invention provides an autonomous mobile device that correctly recognizes a landmark whose state changes and correctly estimates its own position.

In order to solve the above-described problems, an autonomous mobile device that moves autonomously based on a self-position estimated by a self-position estimation device according to the present invention includes a ceiling camera that captures landmarks installed on the ceiling; It has an environment sensor that acquires the surrounding conditions in the traveling direction and an internal sensor that detects its own position information.

The self-position estimation device for estimating the self-position includes a landmark detection processing unit for detecting landmark information based on the information detected by the ceiling camera, and a memory for storing the landmark information and environment map data. , landmark information detected by the landmark detection processing unit, and landmark information stored in the storage unit. a landmark state determination unit that calculates weighted landmark position information, position information detected by an internal sensor, surrounding conditions in the direction of travel acquired by an environment sensor, and environmental map data stored in a storage unit. and a self-position estimation unit for estimating the self-position based on the weighted landmark position information calculated by the landmark state determination unit.

According to the present invention, it is possible to provide an autonomous mobile device that correctly recognizes a landmark whose state changes and correctly estimates its own position.

Problems, configurations, and effects other than those described above will be clarified by the description of the embodiments below.

2 is an explanatory diagram illustrating the configuration of the autonomous mobile device 1 and the flow of processing in the autonomous mobile device 1 described in Embodiment 1. FIG. FIG. 10 is an explanatory diagram for explaining the flow of processing of the self-position estimation unit 1005 described in Embodiment 1; 4 is an explanatory diagram for explaining a self-position estimation method based on illumination information of the autonomous mobile device 1 described in Example 1. FIG. FIG. 4 is an explanatory diagram for explaining a method of determining a lighting state of the autonomous mobile device 1 described in Example 1; 4 is an explanatory diagram illustrating a user interface for controlling the autonomous mobile device 1 described in Example 1. FIG. FIG. 10 is an explanatory diagram for explaining a method of notifying a determination result of a lighting state of the autonomous mobile device 1 described in Example 1; FIG. 4 is an explanatory diagram for explaining a user interface for editing lighting information when the autonomous mobile device 1 according to the first embodiment is offline; FIG. 10 is an explanatory diagram for explaining the configuration of the autonomous mobile device 1 described in Example 2;

Embodiments of the present invention will be described below with reference to the drawings. In addition, for parts having substantially the same or similar configurations and functions, the same reference numerals are used in common between different drawings, and overlapping explanations may be omitted in some cases. be.

In addition, in the drawings, the position, size, shape, range, etc. of each component having each function may differ from the actual position, size, shape, range, etc., in order to facilitate the understanding of the invention. be. Therefore, the present invention is not necessarily limited to the positions, sizes, shapes, ranges, etc. shown in the drawings.

First, the configuration of the autonomous mobile device 1 described in the first embodiment and the flow of processing in the autonomous mobile device 1 will be described.

FIG. 1 is an explanatory diagram for explaining the configuration of the autonomous mobile device 1 and the flow of processing in the autonomous mobile device 1 described in the first embodiment.

The autonomous mobile device 1 described in the first embodiment includes a ceiling camera 101 facing the ceiling, a ceiling height measuring means 102, an environment sensor 103, wheels 104a (front wheels) and wheels 104b (rear wheels), and a rotary encoder. 105a and a rotary encoder 105b.

The ceiling camera 101 captures an image of the ceiling above (above) the autonomous mobile device 1, and captures (detects) landmarks (in the first embodiment, lighting, such as fluorescent lamps) installed on the ceiling. A plurality of ceiling cameras 101 may be installed in order to photograph a wider range.

The ceiling height measuring means 102 measures the distance (ceiling height) from the ceiling camera 101 to the ceiling where the landmark photographed by the ceiling camera 101 is installed (for example, the distance from the ceiling camera 101 to the ceiling (autonomous mobile device 1 to the ceiling)) is measured (detected). For example, the ceiling height measuring means 102 is a laser rangefinder or the like.

For the ceiling camera 101, a stereo camera that processes the parallax information of the photographed image and detects the distance to the object, a depth camera that has a depth sensor that detects depth information, or the like is used. It may have the function of the height measuring means 102 .

Information detected by the ceiling camera 101 and the ceiling height measuring means 102 is processed by a landmark detection processing unit 1001, which will be described later, in terms of landmark positions (e.g., lighting positions) and landmark shapes (e.g., lighting shapes). It is detected as information of a certain landmark (for example, lighting information).

That is, for example, the illumination position is detected from the ceiling image captured by the ceiling camera 101 and the distance to the ceiling detected by the ceiling height measuring means 102 .

The environment sensor (external (external) sensor) 103 is installed in front (front part) of the autonomous mobile device 1 and acquires (detects) the surrounding situation in the traveling direction (for example, point cloud (point group) or image in the traveling direction) )do. A plurality of environment sensors 103 may be installed in order to detect a wider range.

The environment sensor 103 is, for example, LiDAR (Laser Imaging Detection and Ranging), a stereo camera, and a depth camera that measure the scattered light of pulsed laser irradiation light and detect the distance to a distant object. and so on.

The rotary encoder 105a measures the rotation angle (rotation amount) of the wheel 104a, outputs (detects) position information, and connects to the wheel 104a. In other words, it is an inner world (internal) sensor that detects (acquires) the state of the autonomous mobile device 1 (own position information). Note that the rotary encoder 105a may be an inertial measurement device.

The rotary encoder 105b measures the rotation angle (rotation amount) of the wheel 104b, outputs (detects) position information, and connects to the wheel 104b. In other words, it is an inner world (internal) sensor that detects (acquires) the state of the autonomous mobile device 1 (own position information). Note that the rotary encoder 105b may be an inertial measurement device.

The autonomous mobile device 1 also has a self-position estimation device 1000 that estimates its own position, a control unit 1006, and communication means that communicates between the self-position estimation device 1000 and the outside (user).

The control unit 1006 determines a control amount based on the self-position estimated by the self-position estimation device 1000 (self-position estimation unit 1005 described later), controls the wheels 104a and 104b, and controls the autonomous mobile device 1. control movement (running).

That is, the self-position estimation device 1000 estimates the self-position based on the information detected by the ceiling camera 101, the ceiling height measuring means 102, the environment sensor 103, the rotary encoder 105a, and the rotary encoder 105b.

In addition, in Example 1, the self-position estimation device 1000 is installed in the autonomous mobile device 1, and the self-position estimation device 1000, the ceiling camera 101, the ceiling height measurement means 102, the environment sensor 103, the rotary encoder 105a, and the rotary encoder 105b is directly connected by wiring such as a cable, and information is transmitted between the self-position estimation device 1000, the ceiling camera 101, the ceiling height measurement means 102, the environment sensor 103, the rotary encoder 105a, and the rotary encoder 105b. communicated directly.

Self-position estimation device 1000 includes landmark detection processing unit 1001, storage unit 1002, landmark state determination unit 1003, landmark state notification unit 1004 (communication means), and self-position estimation unit 1005. have.

The landmark detection processing unit 1001 detects information detected by the ceiling camera 101 and the ceiling height measuring means 102 (the distance between the landmark imaged by the ceiling camera 101 and the ceiling measured by the ceiling height measuring means 102). Then, the position of the landmark and the shape of the landmark (landmark information: the landmark information may include landmark color information as a feature amount in order to improve detection accuracy). (Extract.

The storage unit 1002 stores environment map data (mobile environment map: map coordinate system), which is map data of the mobile environment in which the autonomous mobile device 1 moves autonomously, and preset landmark positions and landmark shapes. Information of a certain landmark (the information of the landmark may have the color information of the landmark) is stored (recorded, stored).

Note that the landmark information stored in the storage unit 1002 is lighting information when the landmark is lighting. The ON state and the lighting OFF state are preferred.

Note that in the first embodiment, the storage unit 1002 stores landmark information and environment map data in advance. However, the storage unit 1002 may be operated like SLAM (Simultaneous Localization and Mapping) in which landmark information and environment map data are stored in the storage unit 1002 while the autonomous mobile device 1 moves.

The landmark state determination unit 1003 stores position information output from the rotary encoder 105a and the rotary encoder 105b, landmark information (landmark position and landmark shape) detected by the landmark detection processing unit 1001, and a storage unit. The status of the landmark is determined based on the landmark information (location and shape of the landmark) stored in the 1002 .

It should be noted that "determining the state of a landmark" means detecting (detecting) the state of a landmark. to detect

That is, the landmark state determination unit 1003 determines that the landmark information detected by the landmark detection processing unit 1001 and the storage unit 1002 are located at positions specified based on the position information output by the rotary encoder 105a and the rotary encoder 105b. The stored landmark information is collated to detect whether or not the landmark is functioning properly.

When the landmark information detected by the landmark detection processing unit 1001 and the landmark information stored in the storage unit 1002 are collated, the landmark information detected by the landmark detection processing unit 1001 and the stored landmark information are compared. The landmark information stored by the unit 1002 is associated with the position specified based on the position information output by the rotary encoder 105a and the rotary encoder 105b, and is compared for reference.

In this case, the landmark information detected by the landmark detection processing unit 1001 and the landmark information stored by the storage unit 1002 are combined based on the position information output by the rotary encoders 105a and 105b. The landmark information is weighted according to the landmark detection state (detection accuracy of the landmark information) (weighted landmark information is calculated).

That is, the landmark state determination unit 1003 determines the state of the landmark based on the landmark information detected by the landmark detection processing unit 1001 and the landmark information stored in the storage unit 1002. The weighted landmark position information is calculated according to the detection accuracy of the landmark information.

Based on the state of the landmark detected by the landmark state determination unit 1003, the landmark state notification unit 1004, when an abnormality is detected in the state of the landmark, notifies information of the landmark in which the abnormality is detected. , to notify the user.

In this way, by immediately notifying the user of the information on the landmark in which an abnormality has been detected, the landmark (for example, lighting) can also be checked at the same time.

The self-position estimation unit 1005 uses the position information output by the rotary encoders 105a and 105b, the surrounding conditions in the traveling direction detected by the environment sensor 103, the environmental map data stored by the storage unit 1002, and the landmark state determination unit. The self-position is estimated based on the weighted landmark position information calculated by 1003 .

That is, the self-position estimation unit 1005 estimates the self-position in the first state by odometry based on the position information output by the rotary encoder 105a and the rotary encoder 105b. and the surrounding conditions in the traveling direction detected by the sensor 103 are associated with each other, and the self-position in the second state is estimated. , and based on these first, second, and third self-positions, the final self-position is estimated (Kalman filtering).

Next, the processing flow of the self-position estimation unit 1005 described in the first embodiment will be explained.

FIG. 2 is an explanatory diagram for explaining the processing flow of the self-position estimation unit 1005 described in the first embodiment.

The self-position estimation unit 1005 includes a self-position estimation unit (first self-position estimation unit) 201 based on the lighting information, a self-position estimation unit (second self-position estimation unit) 202 based on the environment sensor 103, and a self-position synthesis unit. 203, and a self-location synthesizing unit 203 that uses the self-locations estimated by the self-location estimation units 201 and 202 to estimate the final self-location.

The self-position estimation unit 201 estimates the self-position based on the weighted illumination information (position information) calculated by the landmark state determination unit 1003 .

The self-position estimation unit 202 is based on the position information output by the rotary encoders 105a and 105b, the environment map data stored by the storage unit 1002, and the surrounding conditions in the direction of travel detected by the environment sensor 103. Estimate location.

Self-position synthesis section 203 uses the self-positions estimated by self-position estimation section 201 and self-position estimation section 202 to estimate the final self-position, and outputs the estimated self-position to control section 1006. .

Note that the weighted illumination information (position information) calculated by the landmark state determination unit 1003 includes the position information output by the rotary encoders 105a and 105b and the illumination information (position information) detected by the landmark detection processing unit 1001. ) and illumination information (position information) stored in the storage unit 1002 .

In addition, between the self-position estimation unit 201 and the self-position estimation unit 202, the positions specified based on the position information output by the rotary encoders 105a and 105b are shared.

When estimating the self-position, self-position estimation section 201 and self-position estimation section 202 respectively output a variance (reciprocal of weight) in consideration of detection accuracy.

For example, the estimated self-position value r estimated by the self-position synthesis unit 203 is the estimated self-position value r1 of the self-position estimation unit 201, the variance σ^2_1, and the estimated self-position value r2 of the self-position estimation unit 202. Let the variance be σ^2_2, then
r = (1-(σ^2_2/(σ^2_1+σ^2_2)))r1+(σ^2_2/(σ^2_1+σ^2_2))r2
It is calculated by a weighted average of

That is, the self-position estimation value estimated by the self-position estimation unit 201 is calculated based on the weighted illumination information (position information) calculated by the landmark state determination unit 1003 .

Next, a self-position estimation method based on illumination information of the autonomous mobile device 1 described in the first embodiment will be described.

FIG. 3 is an explanatory diagram for explaining a self-position estimation method based on illumination information of the autonomous mobile device 1 described in the first embodiment.

The autonomous mobile device 1 uses the ceiling camera 101 to capture an image 304 of the ceiling, and detects lighting 301, lighting 302, and lighting 303 as landmarks.

At this time, the positions of the lighting 301, the lighting 302, and the lighting 303 are determined based on the position information output by the rotary encoders 105a and 105b. position of the illumination 303).

That is, the lighting positions (L1′, L2′, L3′) of the lighting 301, the lighting 302, and the lighting 303 in the environment map data stored by the storage unit 1002 and the lighting of the lighting 301, the lighting 302, and the lighting 303 detected by the ceiling camera 101 Positions (L1, L2, L3) are associated.

The lighting positions (L1, L2, L3) detected by the ceiling camera 101 are the positions of the lighting 301, the lighting 302, and the lighting 303 in the image 304 of the ceiling captured by the ceiling camera 101, and the positions of the lighting 301, the lighting 302, and the lighting 303 detected by the ceiling height measuring means 102. detected by the distance to the ceiling and

At this time, the self-position estimation value r1 of the self-position estimation unit 201 is redundantly calculated by the illumination positions L1′, L2′, and L3′ stored in the storage unit 1002 and the illumination positions L1, L2, and L3 detected by the ceiling camera 101. It is represented as a simple system of equations (with more equations than variables).

Then, the lighting 301, the lighting 302, and the lighting 303 are weighted according to the detection state by the landmark state determination unit 1003, and when the redundant simultaneous equations are solved, the weighted Self-position estimation value r1 of self-position estimating section 201 is calculated by the method of least squares.

The variance of the self-position estimation unit 201 is also calculated as the error variance of the weighted least-squares method using the weights assigned to the lighting 301, the lighting 302, and the lighting 303, respectively.

As described above, in the first embodiment, the landmark state determination unit 1003 weights each light detected by the ceiling camera 101 according to the detection state. As a result, even if the installed lighting cannot be detected due to a cause such as lighting failure, the result of estimating the self-position is not deteriorated.

By using lighting as a landmark, there is no need to install a sign in advance on the ceiling of the mobile environment of the autonomous mobile device 1 .

Further, according to the first embodiment, a plurality of landmarks (illuminations) can be handled.

Next, a method for determining the illumination state of the autonomous mobile device 1 described in the first embodiment will be described.

FIG. 4 is an explanatory diagram for explaining a method of determining the illumination state of the autonomous mobile device 1 described in the first embodiment.

In FIG. 4, an image 405 is captured by the ceiling camera 101, and lighting 401, lighting 402, lighting 403, and lighting 404 are detected as landmarks. In FIG. 4, the center line of the image 405 is indicated by a dotted line, and the vectors of illumination 401, illumination 402, illumination 403, and illumination 404 from the center of the image 405 are indicated by arrows.

In the first embodiment, the storage unit 1002 stores lighting information (for example, all lighting is ON as a normal state) as landmark information.

In FIG. 4, in the image 405, the illumination 401, the illumination 402, and the illumination 404 are in a state that matches the illumination information of the illumination ON state stored as the normal state in the storage unit 1002, and the illumination 403 is in a state where the illumination is off. This is a state in which the illumination information does not match the illumination information stored in the storage unit 1002 (a state in which detection is not possible) due to such causes. That is, the illumination 403 is in the illumination OFF state.

In this way, when illumination (illumination 403) in a different illumination state from the ambient illumination (illumination 401, illumination 402, and illumination 404) is detected, the landmark state determination unit 1003 detects this illumination (illumination 403). ) is determined to be abnormal, and the illumination information (illumination state) in which the abnormality is detected is notified to the user via the landmark state notification unit 1004 .

Note that when the storage unit 1002 stores the illumination ON state and the illumination OFF state, the illumination 401, the illumination 402, and the illumination 404 are detected as being in the illumination ON state, and the illumination 403 is detected as being in the illumination OFF state.

Then, it is determined that the lighting 403 is in a different lighting state (abnormal) from the lighting states of the surrounding lighting 401, lighting 402, and lighting 404, and the abnormality is detected via the landmark state notification unit 1004. Illumination information (illumination state) is reported to the user.

Next, a weighting method for each lighting, which is weighted according to the detection state of each lighting in the landmark state determination unit 1003, will be described.

In general, the lens used in the ceiling camera 101 has distortion, and the distortion of the lens increases with increasing distance from the center of the lens. In particular, when a wide-angle lens or the like is used, the distortion becomes conspicuous.

Even if the lens distortion is corrected, the image 405 has distortion that could not be corrected. For this reason, in the first embodiment, each illumination is weighted (0.0 to 1 .0 is accumulated).

That is, weighting is performed so that the smaller the magnitude of the vector from the center of the image 405, the greater the weight. Thus, the weighted lighting information (position information) is set based on the magnitude of the vector from the center of the image 405 captured by the ceiling camera 101 .

Also, the detection accuracy of the ceiling camera 101 may differ depending on whether the lighting is ON or the lighting is OFF. Basically, the illumination ON state has higher luminance and is more characteristic than the illumination OFF state, so the illumination ON state is weighted so as to have a greater weight than the illumination OFF state.

Also, regarding the distance to the ceiling (distance to the lighting) detected by the ceiling height measuring means 102, the greater the distance to the lighting installed on the ceiling, the worse the detection accuracy of the ceiling height measuring means 102. Sometimes. For this reason, weighting is performed so that the higher the ceiling position, the smaller the weight of the lighting.

In addition to the factors described above, for example, lighting near a window may be subject to disturbance, which may reduce the detection accuracy of the ceiling camera 101 . In such a case as well, it is preferable that the landmark state determination unit 1003 performs weighting according to the detection state (factor) of each illumination.

In other words, it is preferable to set the weighting in the landmark state determination unit 1003 according to the movement environment of the autonomous mobile device 1 . Also, this weighting may be set, for example, based on the variance of detection accuracy.

As described above, in the first embodiment, the landmark state determination unit 1003 can handle lighting information according to the lighting state. As a result, the result of estimating the self-position is not deteriorated.

In the first embodiment, the lighting to be detected is rectangular like a fluorescent lamp, but it is not limited to rectangular lighting, and may be round like a downlight.

Next, a user interface for controlling the autonomous mobile device 1 described in the first embodiment will be described.

FIG. 5 is an explanatory diagram illustrating a user interface regarding control of the autonomous mobile device 1 described in the first embodiment.

In the first embodiment, in order to control the autonomous mobile device 1, the screen (interface) 501 of the user's smartphone, tablet, PC, etc. displays the current position of the autonomous mobile device 1 and lighting based on the lighting information stored in the storage unit 1002. 503, an environment data map 502 based on the environment map data stored in the storage unit 1002 is displayed.

In the first embodiment, the environmental data map 502 is displayed with a solid line, the lighting 503 is displayed with a dotted square, and the autonomous mobile device 1 is displayed with a solid square. It can be changed as appropriate so that the user can easily see it.

Next, a method of notifying the determination result of the illumination state of the autonomous mobile device 1 described in the first embodiment will be described.

FIG. 6 is an explanatory diagram for explaining a method of notifying the determination result of the illumination state of the autonomous mobile device 1 described in the first embodiment.

In the first embodiment, when it is determined that there is an abnormality in the lighting, the user is notified of the lighting information in which the abnormality was detected.

As a result, the lighting 604 in which the abnormality is detected blinks on the screen 501 . When the user performs an operation such as clicking on the blinking lighting 604 for which an abnormality has been detected, a screen 605 displaying the content of the abnormal state is popped up on the screen 501 .

A pop-up screen 605 displaying the content of the abnormal state includes, for example, the content of the abnormal state (lighting information (lighting state) in which the abnormality was detected) such as "state abnormality detected: non-lighting error"; For example, an image captured by the ceiling camera 101 as shown in FIG. 4 is displayed.

As described above, when the landmark state determination unit 1003 detects an abnormality in the lighting, the content of the abnormal state is immediately notified to the user via the landmark state notification unit 1004 . Thereby, the lighting in the mobile environment of the autonomous mobile device 1 can be inspected.

Next, a user interface for editing lighting information when the autonomous mobile device 1 according to the first embodiment is offline will be described.

FIG. 7 is an explanatory diagram illustrating a user interface for editing lighting information when the autonomous mobile device 1 according to the first embodiment is offline.

In the first embodiment, when the autonomous mobile device 1 is not moving and offline, the user displays lighting 503 based on the lighting information stored in the storage unit 1002 and environmental data based on the environment map data stored in the storage unit 1002 on the screen 501. A map 502 is displayed.

Thereby, the user edits the lighting information about the lighting 503 . A screen 702 for editing the lighting information pops up on the screen 501 by performing an operation such as clicking on the lighting 701 to be edited.

A pop-up screen 702 for editing lighting information displays lighting information such as, for example, "lighting information: position: ..., shape: ..., color: ...".

Thus, the user edits the lighting information stored in the storage unit 1002. FIG. As a result, when there is a change in lighting information due to replacement of lighting, etc., the change in lighting information can be reflected immediately, and the result of estimating the self-position is deteriorated in the mobile environment of the autonomous mobile device 1. never

Thus, the autonomous mobile device 1 moves autonomously based on the self-position estimated by the self-position estimation device 1000, and has the following configuration.
(1) A ceiling camera 101 that captures a landmark installed on the ceiling.
(2) Ceiling height measuring means 102 for measuring the distance from the ceiling camera 101 to the ceiling.
(3) An environment sensor 103 that acquires the surrounding conditions in the traveling direction.
(4) An internal sensor (105) that detects its own location information.

Self-position estimation device 1000 for estimating the self-position has the following configuration.
(1) A landmark detection processing unit 1001 that detects landmark information based on information detected by the ceiling camera 101 and the ceiling height measuring means 102 .
(2) A storage unit 1002 that stores landmark information and environmental map data.
(3) Based on the landmark information detected by the landmark detection processing unit 1001 and the landmark information stored in the storage unit 1002, the state of the landmark is determined, and the detection accuracy of the landmark information is determined. A landmark state determination unit 1003 that calculates the weighted landmark position information according to .
(4) Positional information detected by the internal sensor (105), surrounding conditions in the direction of travel acquired by the environment sensor 103, environment map data stored by the storage unit 1002, and weighting calculated by the landmark state determination unit 1003 A self-position estimation unit 1005 for estimating the self-position based on the position information of the landmarks obtained.

Then, the autonomous mobile device 1 may be in a situation where the installed sign cannot be detected due to deterioration of the sign over time or changes in the surrounding lighting environment, or due to a cause such as the installed lighting being turned off. Even in a situation where detection is impossible, it is possible to correctly recognize a landmark whose state changes without degrading the result of estimating the self-position, and to correctly estimate the self-position.

Further, the autonomous mobile device 1, which estimates its own position based on landmark information, cannot use preset landmark information due to a lighting failure or the like, and even if the state of the landmark changes. Also, it is possible to suppress the deterioration of the estimation accuracy of the self-position.

Next, the configuration of the autonomous mobile device 1 described in Example 2 will be described.

FIG. 8 is an explanatory diagram for explaining the configuration of the autonomous mobile device 1 described in the second embodiment.

The autonomous mobile device 1 described in the second embodiment differs from the autonomous mobile device 1 described in the first embodiment in the installation position of the self-position estimation device 1000 .

In the autonomous mobile device 1 described in the first embodiment, the self-position estimation device 1000 is installed inside the autonomous mobile device 1, but in the autonomous mobile device 1 described in the second embodiment, the self-position estimation device 1000 moves autonomously. It is installed outside the device 1 .

That is, in the second embodiment, the self-position estimation device 1000 is not mounted on the autonomous mobile device 1, but is mounted on a controller (PC) for external control that estimates the self-position of the autonomous mobile device 1, or the like.

Then, the self-position estimation device 1000 transmits the detection results of the ceiling camera 101, the ceiling height measurement means 102, the environment sensor 103, the rotary encoder 105a and the rotary encoder 105b via the wireless communication means 801a and the wireless communication means 801b. be done.

As in the first embodiment, the self-position estimation device 1000 estimates the self-position based on the detection result.

Then, the estimation result of the self-position estimation device 1000 is communicated to the control unit 1006 of the autonomous mobile device 1 via the wireless communication means 801a and the wireless communication means 801b.

As a result, there is no need to estimate the self-position inside the autonomous mobile device 1, the processing capacity of the PC installed in the autonomous mobile device 1 can be reduced, and the power consumption and size of the autonomous mobile device 1 can be reduced. is achieved.

In addition, the present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiments are specifically described in order to explain the present invention in an easy-to-understand manner, and are not necessarily limited to those having all the configurations described.

Also, part of the configuration of one embodiment can be replaced with part of the configuration of another embodiment. Also, the configuration of another embodiment can be added to the configuration of one embodiment. Also, a part of the configuration of each embodiment can be deleted, a part of another configuration can be added, and a part of another configuration can be substituted.

Reference Signs List 1 Autonomous mobile device 101 Ceiling camera 102 Ceiling height measuring means 103 Environment sensors 104a, 104b Wheels 105a, 105b Rotary encoder 1000 Self-position estimation Device 1001 Landmark detection processing unit 1002 Storage unit 1003 Landmark state determination unit 1004 Landmark state notification unit 1005 Self-position estimation unit 1006 Control unit 201 Self-position estimation unit 202 based on lighting information Self-position estimation unit 203 based on environment sensors Self-position synthesis units 301, 302, 303 Lighting 304 detected as a landmark Ceiling Images 401, 402, 403, 404 captured by the cameras...Lighting 405 detected as landmarks...Image 501 captured by the ceiling camera...Screen 502...Environmental data map 503... Lighting 604 stored in the storage section Lighting 605 in which an abnormality was detected Screen 701 displaying details of the abnormal state Lighting to be edited 702 Screen 801a for editing lighting information, 801b... Wireless communication means

Claims (7)

An autonomous mobile device that moves autonomously based on the self-position estimated by the self-position estimation device,
It has a ceiling camera that captures landmarks installed on the ceiling, an environment sensor that acquires the surrounding conditions in the direction of travel, and an internal sensor that detects its own position information,
The self-position estimation device for estimating the self-position,
a landmark detection processing unit that detects landmark information based on the information detected by the ceiling camera;
a storage unit that stores the landmark information and environment map data;
Based on the landmark information detected by the landmark detection processing unit and the landmark information stored in the storage unit, the state of the landmark is determined, and detection accuracy of the landmark information is determined. a landmark state determination unit that calculates weighted landmark position information according to
Position information detected by the internal sensor, surrounding conditions in the traveling direction acquired by the environment sensor, environmental map data stored by the storage unit, and weighted landmark positions calculated by the landmark state determination unit a self-position estimation unit that estimates a self-position based on the information;
An autonomous mobile device comprising: An autonomous mobile device according to claim 1,
The autonomous mobile device, wherein the landmark is lighting installed on the ceiling. An autonomous mobile device according to claim 2,
An autonomous mobile device, wherein the self-position estimation device is mounted inside the autonomous mobile device. An autonomous mobile device according to claim 2,
An autonomous mobile device, wherein the self-position estimation device is mounted outside the autonomous mobile device. An autonomous mobile device according to claim 2,
When an abnormality is detected in the state of the landmark based on the state of the landmark detected by the landmark state determination unit, the self-position estimation device transmits information about the landmark in which the abnormality is detected. , an autonomous mobile device, comprising a landmark state notification unit for notifying a user. An autonomous mobile device according to claim 2,
The self-position estimation unit is
a first self-position estimation unit that estimates the self-position based on the weighted illumination information calculated by the landmark state determination unit;
a second self-position estimation unit that estimates the self-position based on the position information detected by the internal sensor, the environment map data stored by the storage unit, and the surrounding situation in the direction of travel detected by the environment sensor; ,
a self-location synthesizing unit that uses the self-locations estimated by the first self-location estimating unit and the second self-location estimating unit to estimate a final self-location and outputs the estimated self-location;
An autonomous mobile device comprising: An autonomous mobile device according to claim 1,
The autonomous mobile device, wherein the weighted landmark position information is set based on the size of a vector from the center of the image captured by the ceiling camera.

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