JP2023178529A - Information processing device and information processing method - Google Patents

Abstract

To provide a technology that can monitor sensors and suppress occurrence of abnormal operations.SOLUTION: An exemplary information processing device of the present invention includes a processing section that processes information. The processing section determines whether detection ranges overlap between a first sensor installed in a first device and a second sensor installed in a second device. When it is determined that the detection ranges overlap, the processing section calculates a degree of matching between a detection result of the first sensor and a detection result of the second sensor in the overlapped area. When the degree of matching is below a certain level, the one of the first device and the second device that is determined to have a lower priority based on priority determination information assigned to each device is determined to be abnormal.SELECTED DRAWING: Figure 6

Description

The present invention relates to a technique for monitoring the state of a sensor included in a device.

BACKGROUND ART Conventionally, an information processing device for estimating the self-position of a mobile body based on a map of the environment in which the mobile body moves is known (for example, see Patent Document 1). The self-position of a mobile object is estimated by, for example, aligning the position of the mobile object with respect to an environmental map prepared in advance using distance data obtained from the output of a distance sensor.

International Publication No. 2020/183659

By the way, in an autonomous mobile object that runs autonomously, such as an automatic driving vehicle or a self-driving robot, route planning and operations are executed by relying on the estimation results of its own position. An error in self-position estimation may lead to dangerous operations or accidents, so it is necessary to prevent incorrect self-position estimation. Examples of cases where an incorrect self-position is estimated include a case where a failure occurs in a sensor, a case where a sensor is interfered with by radio waves, etc.

In view of the above-mentioned points, an object of the present invention is to provide a technique that can monitor a sensor and suppress the occurrence of abnormal operation.

An exemplary information processing device of the present invention includes a processing section that processes information. The processing unit determines whether or not detection ranges overlap between a first sensor mounted on a first device and a second sensor mounted on a second device, and determines whether the detection ranges overlap. If it is determined that the detection result of the first sensor and the detection result of the second sensor in the overlapped area is determined to be the same, the degree of coincidence between the detection result of the first sensor and the detection result of the second sensor is determined, and if the degree of coincidence is below a certain level, the Among the device and the second device, the one that is determined to have a lower priority based on the priority determination information given to each device is determined to be abnormal.

According to the exemplary embodiment of the present invention, it is possible to monitor a sensor and suppress the occurrence of abnormal operation.

Diagram showing a schematic configuration of an information processing system Block diagram showing the schematic configuration of an autonomous mobile object Block diagram showing the functional configuration of a processing unit included in the information processing device Schematic diagram showing a state where the detection ranges of the first sensor and the second sensor do not overlap Schematic diagram showing a state where the detection ranges of the first sensor and the second sensor overlap Flowchart illustrating the flow of information processing method A diagram showing a schematic configuration of an information processing system of a first modification example A diagram showing a schematic configuration of an information processing system according to a second modification example.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the drawings.

<1. Overview of information processing system>
FIG. 1 is a diagram showing a schematic configuration of an information processing system 100 according to an embodiment of the present invention. As shown in FIG. 1, the information processing system 100 includes a plurality of devices 1 and 2 that are provided so as to be able to communicate with each other. Note that although FIG. 1 shows only two devices, the first device 1 and the second device 2, the number of devices included in the information processing system 100 may be three or more.

In this embodiment, the plurality of devices 1 and 2 are, for example, autonomously movable (also referred to as autonomously movable) moving objects such as robots and self-driving vehicles. Hereinafter, a mobile body capable of autonomous movement will be simply referred to as an autonomous mobile body. In this embodiment, both the first device 1 and the second device 2 are autonomous mobile bodies. According to the present embodiment, it is possible to provide a mechanism for monitoring and comparing the states of each other's sensors between autonomous mobile bodies and suppressing the occurrence of abnormal operations.

In addition, in this embodiment, the first device 1 may be expressed as the first autonomous mobile body 1, and the second device 2 may be expressed as the second autonomous mobile body 2.

The plurality of autonomous mobile bodies 1 and 2 that constitute the information processing system 100 may communicate with each other directly or indirectly. When the plurality of autonomous mobile bodies 1 and 2 communicate indirectly, for example, they may be configured to communicate via a base station or a server.

<2. Schematic configuration of autonomous mobile body>
FIG. 2 is a block diagram showing a schematic configuration of the autonomous mobile bodies 1 and 2 according to the embodiment of the present invention. Note that in FIG. 2, constituent elements necessary for explaining the features of the embodiment are shown, and descriptions of general constituent elements are omitted. Further, in this embodiment, the plurality of autonomous mobile bodies 1 and 2 included in the information processing system 100 have the same general configuration. Hereinafter, the configuration of an autonomous mobile body included in the information processing system 100 will be described using the first autonomous mobile body 1 as a representative example.

As shown in FIG. 2, the first autonomous mobile body 1 includes an information processing device 11, a sensor 12, and a communication device 13.

The information processing device 11 includes a processing unit 111 that processes information. The information processing device 11 further includes a storage unit 112. The information processing device 11 may be a so-called computer device.

The processing unit 111 includes a processor that performs arithmetic processing and the like. The processor may be configured to include, for example, a CPU (Central Processing Unit). The processing unit 111 may be composed of one processor or may be composed of a plurality of processors. When configured with a plurality of processors, those processors may be connected to each other so as to be able to communicate with each other.

The storage unit 112 includes volatile memory and nonvolatile memory. The volatile memory may include RAM (Random Access Memory) and the like. Nonvolatile memory may include ROM (Read Only Memory), flash memory, hard disk drive, and the like. Non-volatile memory stores computer readable programs and data. In this embodiment, priority determination information 112a, the details of which will be described later, is stored in the nonvolatile memory.

The sensor 12 detects information that enables estimation of the self-position of the first autonomous mobile body 1 (hereinafter sometimes simply expressed as self-position estimation). The sensor 12 outputs the acquired information to the information processing device 11. Specifically, the information acquired by the sensor 12 is input to the processing unit 111. The sensor 12 may be, for example, LiDAR (Light Detection And Ranging), radar, or a camera. In this embodiment, sensor 12 is LiDAR. The LiDAR can detect the presence or absence of an object by irradiating a beam around the first autonomous mobile body 1. Detection information is input to the processing unit 111 every time a beam is periodically irradiated from LiDAR.

The communication device 13 enables wireless communication with another autonomous mobile body (for example, the second autonomous mobile body 2). The communication device 13 may be configured to directly communicate with a communication device included in another autonomous mobile body, or may be configured to communicate indirectly via a base station. Further, the communication device 13 may be configured to be able to perform multiple types of communication, such as cellular communication such as 4G and 5G, Bluetooth (registered trademark), Wi-Fi (registered trademark), and reception of GNSS signals. Note that GNSS is an abbreviation for Global Navigation Satellite System, and refers to a satellite positioning system.

<3. Information processing equipment>
Next, details of the information processing device 11 will be explained. As described above, the information processing device 11 is provided in each of the plurality of autonomous mobile bodies 1 and 2. However, the general configuration of the information processing device 11 provided in each of the autonomous mobile bodies 1 and 2 is the same. For this reason, the information processing device 11 will be explained using a case where the information processing device 11 is included in the first autonomous mobile body 1 as a representative example.

FIG. 3 is a block diagram showing the functional configuration of the processing unit 111 included in the information processing device 11 according to the embodiment of the present invention. In this embodiment, the functions of the processing unit 111 are realized by a processor executing arithmetic processing according to a program stored in the storage unit 112. As shown in FIG. 3, the processing unit 111 includes, as its functions, a self-position estimation unit 1111, a detection range determination unit 1112, a degree of coincidence calculation unit 1113, an abnormality determination unit 1114, and an abnormality notification unit 1115. .

Note that the scope of the present disclosure may include a computer program that causes a processor (computer) to implement at least some of the functions of the information processing device 11. The scope of the present disclosure may also include computer-readable non-volatile storage media that record such computer programs. The nonvolatile recording medium may include, for example, in addition to the above-mentioned nonvolatile memory, an optical recording medium (for example, an optical disk), a magneto-optical recording medium (for example, a magneto-optical disk), a USB memory, an SD card, or the like.

Further, each of the units 1111 to 1115 may be realized by having a processor execute a program, that is, by software, as described above, but may also be realized by other methods. Each of the units 1111 to 1115 may be realized using, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). That is, each of the units 1111 to 1115 described above may be realized by hardware using a dedicated IC or the like. Further, each of the units 1111 to 1115 described above may be realized using a combination of software and hardware. Further, each of the units 1111 to 1115 described above is a conceptual component. A function performed by one component may be distributed among multiple components. Further, functions possessed by a plurality of components may be integrated into one component. Further, in a configuration in which each of the units 1111 to 1115 is implemented by software, the number of programs may be one or more. For example, a program may be provided corresponding to each of the units 1111 to 1115.

The self-position estimating unit 1111 estimates the self-position of the first autonomous mobile body 1 on which the information processing device 11 is mounted. That is, the processing unit 111 estimates the self-position of the first device 1 in which the own device 11 is mounted. In detail, self-position estimation includes a process of recognizing where the moving object is currently located and which direction it is facing. The self-position estimating unit 1111 performs self-position estimation at regular time intervals. That is, the first autonomous mobile body 1 grasps its own position at regular time intervals.

Self-position estimation may be performed using various known techniques. Self-position estimation is a configuration in which, for example, distance information obtained by the sensor 12 is used to align the first autonomous mobile body 1 with respect to an environmental map (existing map) prepared in advance to estimate the self-position. It's fine. Note that as a method for positioning the first autonomous mobile body 1, for example, a known method called ICP (Iterative Closest Point) may be used. Furthermore, the self-position estimation may be performed using, for example, a known technique called SLAM (Simultaneous Localization and Mapping). In SLAM, a current environmental map is sequentially created using information obtained by the sensor 12, and self-position estimation is performed based on the created current map.

Note that LiDAR that constitutes the sensor 12 measures the distance to an object by irradiating the surrounding area with laser light such as an infrared laser. The LiDAR measures the distance to the object and the direction of the object using its own position, the center of the sensor, as a reference position. The LiDAR acquires environmental information around the first autonomous mobile body 1, for example, with one rotation around the sensor center as one cycle. Self-position estimation may be performed every cycle or every time the cycle is repeated a predetermined number of times.

The detection range determination unit 1112 determines whether the detection ranges of the sensors 12 mounted on the two autonomous mobile bodies 1 and 2 overlap. That is, the processing unit 111 performs detection between the first sensor 12a mounted on the first device 1 and the second sensor 12b mounted on the second device 2 (see FIG. 4 and FIG. 5 described later). Determine whether the ranges overlap.

Note that the first sensor 12a and the second sensor 12b refer to the same sensor 12 described above. The expressions "first sensor 12a" and "second sensor 12b" are expressions used for convenience in order to distinguish which of the first autonomous mobile body 1 and the second autonomous mobile body 2 has the sensor 12. be. That is, in this embodiment, the first sensor 12a and the second sensor 12b are LiDAR. However, the first sensor 12a and the second sensor 12b may be other than LiDAR. The first sensor 12a and the second sensor 12b may each be a sensor used for self-position estimation of the devices 1 and 2 in which the sensor is mounted. The first sensor 12a and the second sensor 12b may be, for example, a camera, a radar, or the like. Furthermore, the first sensor 12a and the second sensor 12b may be of different types.

In this embodiment, information regarding the detection range of the first sensor 12a is stored in advance in the storage unit 112 of the information processing device 11 mounted on the first autonomous mobile body 1. For this reason, the detection range determination unit 1112 can acquire the detection range of the first sensor 12a. Furthermore, information regarding the detection range of the second sensor 12b is stored in advance in the storage unit 112 of the information processing device 11 mounted on the second autonomous mobile body 2. For this purpose, the detection range determination unit 1112 determines the detection range of the second sensor 12b from the second autonomous mobile body on the premise that communication between the first autonomous mobile body 1 and the second autonomous mobile body 2 is possible. It can be obtained from body 2.

Note that the information regarding the detection range of the second sensor 12b may be stored in advance in the storage unit 112 of the information processing device 11 mounted on the first autonomous mobile body 1. For example, when the detection range determination unit 1112 recognizes the second autonomous mobile body 2 using identification information obtained from a camera, wireless, etc. , the detection range of the second sensor 12b may be acquired.

The detection range determination unit 1112 uses the detection range information of the first sensor 12a and the second sensor 12b and the information indicating the relative positional relationship between the first sensor 12a and the second sensor 12b. It is determined whether the detection ranges of the second sensor 12b and the second sensor 12b overlap. The information indicating the relative positional relationship between the first sensor 12a and the second sensor 12b can be obtained, for example, by the result of self-position estimation obtained by the first autonomous mobile body 1 using SLAM technology and the creation of an environmental map. It may be determined from the obtained position information of the second autonomous mobile body 2. As another example, if the self-positions of the autonomous mobile bodies 1 and 2 can be estimated by odometry, which is a known method, the results of the self-position estimation obtained thereby may be used. That is, information indicating the relative positional relationship between the first sensor 12a and the second sensor 12b may be obtained from the result of self-position estimation obtained by odometry. Note that in self-position estimation using odometry, the amount of movement is calculated using the rotation angle of the wheels, and the self-position is estimated based on the amount of movement.

FIG. 4 is a schematic diagram showing a state in which the detection ranges of the first sensor 12a and the second sensor 12b do not overlap. FIG. 5 is a schematic diagram showing a state in which the detection ranges of the first sensor 12a and the second sensor 12b overlap. In FIGS. 4 and 5, a broken line L1 indicates the outer edge of the detection range of the first sensor 12a mounted on the first autonomous mobile body 1. That is, the inside of the broken line (outer edge) L1 is the detection range of the first sensor 12a. Further, a dashed-dotted line L2 indicates the outer edge of the detection range of the second sensor 12b mounted on the second autonomous mobile body 2. That is, the inside of the dashed-dotted line (outer edge) L2 is the detection range of the second sensor 12b.

As shown in FIGS. 4 and 5, whether the detection ranges of the sensors 12 overlap may be determined by comparing the detection ranges in plan view. For example, when the detection ranges of the first sensor 12a and the second sensor 12b in plan view overlap by a predetermined area or more, the detection range determination unit 1112 determines that the detection ranges of both sensors 1 and 2 overlap. good. The predetermined area may be determined, for example, by experiment. Further, for example, the outer edge L1 of the detection range of the first sensor 12a and the outer edge L2 of the detection range of the second sensor 12b have an intersection, and the distance between the first autonomous mobile body 1 and the second autonomous mobile body 2 is If it is within a predetermined value, it may be determined that the detection ranges of both 1 and 2 overlap. The predetermined value may be determined, for example, by experiment.

The matching degree calculation unit 1113 calculates the matching degree between the detection result of the first sensor 12a and the detection result of the second sensor 12b in the region OR (see FIG. 5) where the detection ranges overlap. That is, when it is determined that the detection ranges of the first sensor 12a and the second sensor 12b overlap, the processing unit 111 combines the detection result of the first sensor 12a and the second sensor 12b in the overlapped region OR. Find the degree of agreement with the detection results. Note that the detection result of the second sensor 12b is acquired from the second autonomous mobile body 2 through communication using the communication device 13.

The degree of coincidence is determined, for example, by comparing the detection result of the obstacle 3 (see FIG. 5) by the first sensor 12a and the detection result of the obstacle 3 by the second sensor 12b. The obstacles 3 include not only stationary objects but also moving objects. For example, if the obstacle 3 is detected by one sensor 12 but not by the other sensor 12, the degree of coincidence may be set to 0%. Conversely, when the obstacle 3 is detected at the same position by both sensors 12, the degree of coincidence may be set to 100%. If the obstacle 3 is detected by both sensors 12 and there is a deviation in the position of the detected obstacle 3, the positions (areas) will match depending on the degree of overlap. It is good to have a degree. The greater the overlap of locations, the greater the degree of matching given as a percentage may be. Further, the degree of coincidence may be simply expressed by the magnitude of the positional shift (distance difference) of the obstacle 3. In this case, the smaller the distance difference, the higher the degree of matching.

Note that the obstacle 3 may include other autonomous moving bodies. That is, the degree of coincidence is determined by comparing the position of the second autonomous mobile body 2 obtained using the first sensor 12a and the self-position of the second autonomous mobile body 2 obtained using the second sensor 12b. Good too.

When the matching degree is below a certain level, the abnormality determination unit 1114 prioritizes the first autonomous mobile body 1 and the second autonomous mobile body 2 based on the priority determination information 112a (see FIG. 2) assigned to each of them. The one that is determined to have a lower degree is determined to be abnormal. That is, when the matching degree is below a certain level, the processing unit 111 selects one of the first device 1 and the second device 2 that is determined to have a lower priority according to the priority determination information 112a assigned to each. is determined to be abnormal. According to this configuration, if there is a difference in the detection results of the sensor 12 between the two devices 1 and 2, it can be determined that one of the devices is abnormal. That is, according to this configuration, it is possible to monitor and compare the states of the sensors 12 of the two devices 1 and 2, and to prevent the devices 1 and 2 from performing abnormal operations.

For example, when the degree of coincidence is expressed as a percentage, the abnormality determination unit 1114 determines that the degree of coincidence is below a certain level when the degree of coincidence is less than or equal to a predetermined percentage value. The predetermined percentage value may be determined, for example, experimentally, and is, for example, 80%. Further, for example, when the degree of coincidence is expressed as a distance difference, the abnormality determination unit 1114 determines that the degree of coincidence is below a certain value when the distance difference is greater than or equal to a predetermined value. The predetermined value may be determined by experiment, for example, and is, for example, 1 m.

The priority determination information 112a is information that allows the reliability of the self-position estimation result to be determined. Thereby, the devices (autonomous mobile bodies) 1 and 2 that are likely to be able to estimate their own positions more accurately can be determined to be normal. Specifically, the priority determination information 112a includes at least one of the performance of the sensor 12, the usage time of the sensor 12, the performance of the calculation unit that estimates the self-position, and the remaining amount of the battery. It is preferable. Thereby, priority can be determined appropriately.

For example, an autonomous mobile body having a sensor 12 with low performance is determined to have a lower priority than an autonomous mobile body having a sensor 12 with high performance. This is because the sensor 12 with lower performance is likely to have lower position estimation accuracy. Further, for example, an autonomous mobile body having a sensor 12 that has been used for a long time is determined to have a lower priority than an autonomous mobile body that has a sensor 12 that has a long usage time. This is because the sensor 12 that has been used for a long time has a high possibility of failure and low reliability of position estimation.

Further, for example, an autonomous mobile body having a processing unit 111 whose calculation unit has a low performance has a lower priority than an autonomous mobile body which has a processing unit 111 whose calculation unit has a high performance for estimating its own position. It is determined that This is because the processing unit 111 with a lower performance arithmetic unit is likely to have lower accuracy in position estimation. The performance of the arithmetic unit may include, for example, the reliability and accuracy of the self-position estimation algorithm executed using the processor, in addition to the performance of the processor itself that constitutes the arithmetic unit.

Also, for example, an autonomous mobile object with a low remaining battery level is determined to have a lower priority than an autonomous mobile object with a higher remaining battery level (not shown) that serves as a driving source for the autonomous mobile objects 1 and 2. be done. This is because an autonomous mobile body with a low battery level may operate unstable, and the reliability of position estimation is likely to be low.

Note that it is preferable that the priority determination information 112a used for determining the priority between the first autonomous mobile body 1 and the second autonomous mobile body 2 has a plurality of types rather than a single type. By determining the priority by combining multiple types of priority determination information 112a, the accuracy of determining which of the first autonomous mobile body 1 and the second autonomous mobile body 2 is abnormal is improved. can do.

Further, the priority determination information 112a given to each of the autonomous mobile bodies 1 and 2 may be stored separately in the storage unit 112 of the information processing device 11 included in each of the autonomous mobile bodies 1 and 2. In such a configuration, for example, when the first autonomous mobile body 1 performs a priority determination using the priority determination information 112a, the priority determination information is transmitted from the second autonomous mobile body 2 through communication using the communication device 13. 112a may be obtained to determine the priority. Note that in addition to the priority determination information given to the first autonomous mobile body 1, the storage unit 112 of the information processing device 11 included in the first autonomous mobile body 1 is stored in the storage unit 112 of the information processing device 11 provided in the first autonomous mobile body 1. etc.) may be stored. In such a configuration, the processing unit 111 transmits the priority determination information of the target autonomous mobile body to the own device according to the identification information of the other autonomous mobile body acquired using a camera, wireless, etc. It may be read out from the storage unit 112 of No. 11 and used.

Further, the priority determination information 112a given to each of the autonomous mobile bodies 1 and 2 may be fixed information stored in advance in the storage unit 112, but may be updated as appropriate by the information processing device 11. For example, the usage time of the sensor 12 described above, the remaining amount of battery, etc. may be updated as appropriate.

The abnormality notification unit 1115 performs notification processing to notify abnormalities of the autonomous mobile bodies 1 and 2. That is, the processing unit 111 performs notification processing to notify of an abnormality. By reporting an abnormality, for example, a device or person managing the information processing system 100 can quickly take appropriate measures.

The notification of abnormality may be, for example, notification using notification means provided in the autonomous mobile bodies 1 and 2. The notification means may be, for example, an audio output device, a light emitting device, a display device, or the like. For example, when it is determined that the first autonomous moving body 1 on which the own device 1 is mounted is abnormal, the abnormality notification unit 1115 operates the notification means of the first autonomous moving body 1 on which the own device 11 is mounted. It's fine. Further, for example, when it is determined that the second autonomous mobile body 2, not the first autonomous mobile body 1 on which the own device 1 is mounted, is abnormal, the abnormality notification unit 1115 may notify the second autonomous mobile body 2 Communication may be performed to operate the notification means of the second autonomous mobile body 2. However, in the second autonomous mobile body 2 as well, since an abnormality in the self-mobile body is detected using the information processing No. 11 provided in the second autonomous mobile body 2, the process of notifying abnormalities in other than the own mobile body is It doesn't have to be done.

Further, as another example, the notification of the abnormality may be, for example, a notification to a server (not shown) connected through a communication network such as the Internet, or an e-mail transmission to the administrator of the information processing system 100. When a server is notified of an abnormality or an email is sent, information about an autonomous mobile object that was determined to have no abnormality at the time of the abnormality determination is reported together with information about an autonomous mobile object that was determined to have an abnormality. It's fine.

Note that notification of an abnormality does not necessarily have to be performed. That is, the abnormality notification section 1115 may not be provided. For example, instead of or in addition to reporting the abnormality, the autonomous mobile bodies 1 and 2 determined to be abnormal may automatically stop operating. Also, for example, instead of automatic stopping or after automatic stopping, the autonomous mobile body that has been determined to be abnormal may be temporarily operated by making corrections using the information of the autonomous mobile body that has been determined to be normal. Good too.

In the above description of the information processing device 11, it is assumed that the information processing device 11 is mounted on the first autonomous mobile body 1. For this purpose, the information processing device 11 is configured to be mounted on the first autonomous mobile body 1 . However, as described above, the information processing device 11 is also installed in the second autonomous mobile body 2, and its functional configuration is the same as that of the information processing device 11 installed in the first autonomous mobile body 1. When the information processing device 11 mounted on the second autonomous mobile body 2 is used as a reference, the information processing device 11 has a configuration in which the information processing device 11 itself is mounted on the second autonomous mobile body 2 . That is, in the information processing device 11 of this embodiment, it can be said that the own device is installed in either the first device 1 or the second device 2 that can communicate with each other. By configuring the information processing device 11 to be installed in the same device as the sensor 12 that enables self-position estimation as in this embodiment, even in an environment where communication networks such as the Internet are not available, each device 1 , 2 can be monitored between the devices 1 and 2.

<4. Information processing method>
Next, an information processing method executed by the information processing device 11 described above will be described. FIG. 6 is a flowchart illustrating the flow of the information processing method according to the embodiment of the present invention. It is assumed that the information processing device 11 that executes the information processing method in FIG. 6 is mounted on the first autonomous mobile body 1.

Note that a computer program that causes a computer device to implement at least part of the information processing method of the present disclosure is included in the scope of the present disclosure. Also, a computer-readable non-volatile recording medium that records such a computer program is within the scope of the present disclosure.

In step S1, the self-position estimating unit 1111 performs self-position estimation. That is, the information processing method of this embodiment includes the step of estimating the self-position. Self-position estimation is performed at regular time intervals. Note that, as described later, the information processing device 11 does not need to be mounted on the autonomous mobile body. For this reason, the information processing method performed by the information processing device 11 does not necessarily have to include the step of estimating the self-position. Once the self-position is estimated, the process proceeds to the next step S2.

In step S2, the detection range determination unit 1112 determines whether the detection ranges of the first sensor 12a and the second sensor 12b overlap. That is, the information processing method of the present embodiment determines whether the detection ranges of the first sensor 12a mounted on the first device 1 and the second sensor 12b mounted on the second device 2 overlap. The method includes a step of determining (determination step). Note that, in this embodiment, the second sensor 12b is a sensor 12 provided in an unspecified autonomous mobile body (this is expressed as a second autonomous mobile body 2) that exists near the first autonomous mobile body 1. If no autonomous mobile body exists near the first autonomous mobile body 1, information from the second sensor 12b cannot be obtained in the first place, and it may not be possible to determine whether the detection ranges overlap. In such a case where determination is impossible, it is determined that the detection ranges do not overlap. If it is determined that the detection ranges overlap (Yes in step S2), the process proceeds to the next step S3. If it is determined that the detection ranges do not overlap (No in step S2), the process shown in FIG. 6 ends once. When the next self-position is estimated, the process shown in FIG. 6 starts again.

In step S3, the matching degree calculation unit 1113 calculates the matching degree between the detection result of the first sensor 12a and the detection result of the second sensor 12b in the area where the detection ranges overlap. That is, in the information processing method of the present embodiment, when it is determined that the detection ranges overlap, the degree of coincidence between the detection results of the first sensor 12a and the detection results of the second sensor 12b in the overlapped area is determined. The step of determining the degree of matching (degree of matching calculation step) is provided. Once the degree of matching is determined, the process proceeds to the next step S4.

In step S4, the abnormality determining unit 1114 determines whether the degree of matching is below a certain level. That is, the information processing method of this embodiment includes the step of determining whether the degree of matching is below a certain level. If the degree of matching is below a certain level (Yes in step S4), the process proceeds to the next step S5. If the matching degree is not below a certain level (No in step S4), similar results are obtained between the first sensor 12a and the second sensor 12b and no abnormality is recognized in both, so the process shown in FIG. It will end once. When the next self-position is estimated, the process shown in FIG. 6 starts again.

In step S5, the abnormality determination unit 1114 selects one of the first autonomous mobile body 1 and the second autonomous mobile body 2 that is determined to have a lower priority by comparing the priority determination information 112a assigned to each of the first autonomous mobile body 1 and the second autonomous mobile body 2. Determined as abnormal. That is, in the information processing method of the present embodiment, when the degree of matching is below a certain level, it is determined that the priority is lower depending on the priority determination information 112a assigned to each of the first device 1 and the second device 2. A step of determining the determined one as abnormal (an abnormality determination step) is provided. According to this embodiment, if there is a difference in the detection results of the sensor 12 between the two devices 1 and 2, it can be determined that one of the devices is abnormal. That is, according to this configuration, it is possible to monitor and compare the states of the sensors 12 of the two devices 1 and 2, and to prevent the devices 1 and 2 from performing abnormal operations. Once the abnormality determination is made, the process proceeds to the next step S6.

In step S6, the abnormality notification unit 1115 performs notification processing to notify of an abnormality. That is, the information processing method of this embodiment includes a step (notification processing step) of performing notification processing for notifying an abnormality. As described above, it is preferable that, in addition to reporting the abnormality, processing for stopping the autonomous mobile body determined to be abnormal and operation processing using a correction value are performed. Upon completion of step S6, the process shown in FIG. 6 is temporarily ended. When the next self-position is estimated, the process shown in FIG. 6 starts again.

In addition, in this embodiment, if it is determined in step S2 that the detection ranges overlap, not only the information processing device 11 installed in the first autonomous mobile object 1 but also the information processing device installed in the second autonomous mobile object 2 The apparatus 11 also performs the processing from step S3 onwards. However, the processing after step S3 may be configured to be performed by only one of the first autonomous mobile body 1 and the second autonomous mobile body 2.

<5. Modified example>
[5-1. 1st modification]
In the embodiment described above, the first device 1 and the second device 2, which mutually monitor the states of the sensors 12, are both autonomous mobile bodies, but this is just an example. FIG. 7 is a diagram showing a schematic configuration of an information processing system 100A of a first modification. As shown in FIG. 7, one of the first device and the second device may be an autonomous mobile body 1A, and the other may be a fixing device 2A fixed at a fixed position. The configurations of the autonomous mobile body 1A and the fixing device 2A may be similar to the configuration of the autonomous mobile body 1 shown in FIG. 2. Note that, since the fixing device 2A is a device that is fixedly arranged, for example, on a wall of a building, it does not include transportation means such as wheels included in the autonomous mobile body 1A. The fixing device 2A of this modification performs self-position estimation at regular time intervals.

In the configuration that uses the sensor 12 of the fixing device 2A, the position of the fixing device 2A and the detection range of the sensor 12 are predetermined positions, so processes such as determining whether the detection range overlaps can be easily performed. Furthermore, the sensor 12 placed on the fixed device 2A is less susceptible to deterioration than the sensor 12 placed on the moving object, and furthermore, it is easier to stably estimate the position. For this reason, for example, when the performance of the sensor 12 of the autonomous mobile body 1A and the sensor 12 of the fixing device 2A is the same, it is assumed that the sensor 12 of the fixing device 2A has higher detection accuracy. For this reason, the priority determination information may be set so that the fixed device 2A has a higher priority than the autonomous mobile body 1A.

Further, the number of fixing devices 2A may be plural. The plurality of fixing devices 2A may be arranged so that a part of the detection range of the sensor 12 overlaps with each other. With this configuration, the state of the sensor 12 of the autonomous mobile body 1A can be easily monitored using the sensor 12 of the fixing device 2A.

[5-2. Second modification]
In the embodiment described above, the information processing device 11 itself is installed in the first device 1 and the second device 2. However, such a configuration is merely an example. FIG. 8 is a diagram showing a schematic configuration of an information processing system 100B of a second modification. As shown in FIG. 8, the information processing device 11B itself may be included in a server device 4 that is provided to be able to communicate with the first device 1B and the second device 2B. With such a configuration, the server device 4 can determine whether there is an abnormality in the devices 1B, 2B, and the processing load on each device 1B, 2B can be reduced. In addition, in this modification, the first device 1B and the second device 2B are autonomous mobile bodies, as an example.

In the second modification, the communication device 41 of the server device 4 can communicate with the communication device 13 (see FIG. 2) provided in each device 1B, 2B via a communication network 5 such as the Internet. In the second modification, self-position estimation is performed in each device 1B, 2B. The information processing device 11B of the second modification does not perform self-position estimation, but obtains the results of self-position estimation from each device 1B and 2B. The information processing device 11B has the same configuration as the information processing device 11 of the above-described embodiment, except that it does not perform self-position estimation. The server device 4 may be a stationary device, or may be a cloud server. Further, the CPU included in the server device 4 may be a virtual CPU.

Note that in this modification, the information processing device 11B acquires the detection results of the first sensor 12a and the second sensor 12b from each device 1B and 2B via the communication network 5. Further, the information regarding the sensor 12 of each device 1B, 2B may be stored in advance in the storage unit of the information processing device 11B, or may be acquired from each device 1B, 2B through communication. Furthermore, the priority determination information 112a given to each device 1B, 2B may be stored in advance in the storage unit of the information processing device 11B, or may be acquired from each device 1B, 2B through communication.

<6. Things to keep in mind>
Various changes can be made to the various technical features disclosed in the detailed description of this specification without departing from the gist of the technical creation. Further, the plurality of embodiments and modifications disclosed in the detailed description of this specification may be implemented in combination to the extent possible.

1... First device, first autonomous moving body 1A, 1B... First device, autonomous moving body 2... Second device, second autonomous moving body 2A... Second device, fixing device 2B ...Second device, autonomous mobile body 4...Server device 11, 11B...Information processing device 12...Sensor 12a...First sensor 12b...Second sensor 111...Processing unit 112a...Priority determination information

Claims (9)

An information processing device including a processing unit that processes information,
The processing unit includes:
Determining whether the detection ranges overlap between a first sensor installed in the first device and a second sensor installed in the second device,
If it is determined that the detection ranges overlap, find the degree of coincidence between the detection results of the first sensor and the detection results of the second sensor in the overlapped areas,
Information that, when the degree of matching is below a certain level, the one of the first device and the second device that is determined to have a lower priority based on priority determination information assigned to each device is determined to be abnormal. Processing equipment. The first sensor and the second sensor are sensors used for estimating the self-position of the device in which the sensor is installed,
The information processing device according to claim 1, wherein the priority determination information is information that allows reliability of the self-position estimation result to be determined. 3. The priority determination information includes at least one of the performance of the sensor, the usage time of the sensor, the performance of the calculation unit that estimates the self-position, and the remaining amount of the battery. The information processing device described. The information processing device according to claim 1, wherein the processing unit performs notification processing to notify the abnormality. The information processing device according to any one of claims 1 to 4, wherein the first device and the second device are both autonomous mobile bodies. The information processing according to any one of claims 1 to 4, wherein one of the first device and the second device is an autonomous moving body and the other is a fixed device fixed at a fixed position. Device. The information processing device according to any one of claims 1 to 4, wherein the information processing device is installed in one of the first device and the second device that can communicate with each other. The information processing device according to any one of claims 1 to 4, wherein the information processing device is included in a server device provided to be able to communicate with the first device and the second device. An information processing method executed by an information processing device, the method comprising:
determining whether the detection ranges of a first sensor mounted on the first device and a second sensor mounted on the second device overlap;
If it is determined that the detection ranges overlap, determining the degree of coincidence between the detection results of the first sensor and the detection results of the second sensor in the overlapped areas;
a step of determining, when the degree of coincidence is below a certain level, one of the first device and the second device that is determined to have a lower priority based on priority determination information assigned to each device to be abnormal; ,
An information processing method comprising:

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