Information processing method, information processing device, and program

Abstract

[Problem] To provide an information processing method, an information processing device, and a program that make it possible to prevent a decline in processing accuracy of obstacle detection and host vehicle position estimation even if light is illuminated through a transparent object. [Solution] In order to solve the problem, the present disclosure provides an information processing method comprising: a measurement step for generating values related to return times of reflected light pulse signals corresponding to a plurality of light emission pulse signals repeatedly emitted at predetermined time intervals; a generation step for generating a histogram representing the number of measurements of the reflected light pulse signals for each of the values related to the return times; and a signal processing step for, when the histogram includes two peaks, determining the presence of an obstacle relative to a host vehicle using a distance value based on one of the peaks and estimating the position of the host vehicle using a distance value based on the other peak.

Description

Information processing method, information processing device, and program

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

[0002] In autonomously driven mobile vehicles, distance information is acquired. Based on this distance information, obstacle detection, self-location estimation, etc. are performed. In this case, light is irradiated onto the subject, and the time it takes for the reflected light from the subject to be received is converted into distance information.

[0003] Japanese Patent Application Laid-Open No. 2021-47208

[0004] However, if there is a transparent object in front of the subject, the accuracy of measuring the distance information to the subject may decrease.

[0005] Therefore, the present disclosure provides an information processing method, an information processing device, and a program that can suppress a decrease in the processing accuracy of obstacle detection and self-position estimation even when light is irradiated through a transparent object.

[0006] In order to solve the above problems, according to the present disclosure, there is provided an information processing method comprising: a measurement process for generating values ​​relating to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals repeatedly emitted at predetermined time intervals; a generation process for generating a histogram of the measured number of reflected light pulse signals relative to the values ​​relating to the return time; and a signal processing process for, when two peaks are present in the histogram, determining whether there is an obstacle for the own aircraft using a distance value based on one of the peaks, and estimating the own position of the own aircraft using a distance value based on the other peak.

[0007] In the signal processing step, if two peaks exist in the histogram, a distance value based on the peak on the near side may be used for obstacle determination.

[0008] In the signal processing step, if two peaks exist in the histogram, a distance value based on the peak on the far side may be used to estimate the self-position.

[0009] In the signal processing step, when three or more peaks exist in the histogram, a distance value based on the peak closest to the object may be used for obstacle determination.

[0010] In the signal processing step, when three or more peaks exist in the histogram, a distance value based on the peak on the farthest side may be used to estimate the self-position.

[0011] In the signal processing step, if only one peak exists in the histogram, a distance value based on the peak may be used for obstacle determination and self-position estimation.

[0012] In the measurement process, the plurality of light emission pulse signals are emitted in a plurality of irradiation directions; in the generation process, the histogram is generated for each of the plurality of irradiation directions; and in the signal processing process, if two peaks exist in the histogram for each of the plurality of irradiation directions, an obstacle determination is made using a first distance value based on the peak on the closest side, and the self-position is estimated using a second distance value based on the peak on the farthest side.

[0013] The obstacle determination may be based on the first distance value and an illumination direction from the own aircraft corresponding to the first distance value.

[0014] The estimation of the self-location may be based on the second distance value and an illumination direction from the own device corresponding to the second distance value.

[0015] The method may further include a determining step of determining whether or not two or more peaks exist in the histogram, and the signal processing step may be performed based on the determination in the determining step.

[0016] In the determining step, it may be determined that a transparent object is present when two or more peaks exist in the histogram.

[0017] When it is determined in the determination step that two or more peaks exist, the obstacle determination may determine that the transparent object exists in the irradiation direction in which it is determined that two or more peaks exist.

[0018] The first distance value and the illumination direction from the own aircraft corresponding to the first distance value may be generated as second point cloud data, and if the transparent object exists, the distance value to the transparent object may be included in the second point cloud data.

[0019] The second distance value and the illumination direction from the own aircraft corresponding to the second distance value may be generated as first point cloud data, and when the transparent object is present, the distance value to a subject farther away than the transparent object may be included in the first point cloud data.

[0020] If it is determined in the determination step that two or more peaks exist, the emission in the irradiation direction in which it was determined in the measurement step that two or more peaks exist may be performed again with a different emission intensity.

[0021] In order to solve the above problems, according to the present disclosure, there is provided an information processing device comprising: a time measurement unit that generates a value relating to the return time of a reflected light pulse signal corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a histogram generation unit that generates a histogram of the measured number of the reflected light pulse signal relative to the value relating to the return time; and a signal processing unit that, when two peaks exist in the histogram, determines whether there is an obstacle relative to the own device using a distance value based on one of the peaks, and estimates the own position relative to the own device using a distance value based on the other peak.

[0022] The vehicle may further include a discrimination unit that determines whether or not two or more peaks exist in the histogram, and the obstacle determination and the self-location estimation may be performed based on the determination by the discrimination unit.

[0023] The identification unit may determine that a transparent object is present when two or more peaks exist in the histogram.

[0024] When the identification unit determines that the transparent object is present, the obstacle determination may determine that the transparent object is present in an illumination direction in which it is determined that two or more peaks are present.

[0025] In order to solve the above problem, according to the present disclosure, there is provided a program that causes an information processing device to execute the following steps: a measurement step of generating values ​​related to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a generation step of generating a histogram of the measured number of reflected light pulse signals relative to the values ​​related to the return time; and a signal processing step of, when two peaks exist in the histogram, determining whether there is an obstacle for the vehicle using a distance value based on one of the peaks, and estimating the vehicle's own position using a distance value based on the other peak.

[0026] 1 is a block diagram showing a schematic configuration of a distance measuring device according to an embodiment. FIG. 1 is a block diagram showing the configurations of a light receiving device, an information processing device, and a driving control device. FIG. 2 is a diagram showing a schematic diagram of a scanning range of a light scanning unit. FIG. 3 is a diagram showing a schematic diagram of an example of the configuration inside a light emitting unit and a light receiving range of a light receiving unit. FIG. 4 is a diagram showing a relationship between a projection pattern of a light emitting element and a focus of a light emitting optical system. FIG. 5 is a diagram showing a relationship between a projection pattern of a light emitting element and an irradiation angle of a near projection pattern NFP. FIG. 6 is a diagram showing a far projection pattern FFP received via a light receiving optical system. FIG. 7 is a diagram showing a projection view of each light emitting element projected in a second direction. FIG. 8 is a diagram showing a projection pattern of light emitting elements arranged in a first direction. FIG. 9 is a block diagram showing an example of a schematic configuration of a vehicle control system. FIG. 10 is an explanatory diagram showing an example of the installation positions of an outside vehicle information detection unit and an imaging unit.

[0027] Hereinafter, embodiments of an information processing method, an information processing device, and a program will be described with reference to the drawings. The following description will focus on the main components of the information processing method, the information processing device, and the program, but the information processing method, the information processing device, and the program may include components and functions that are not shown or described. The following description does not exclude components and functions that are not shown or described.

[0028] First Embodiment FIG. 1 is a block diagram illustrating a schematic configuration of an autonomously driven mobile body 100 according to this embodiment. As illustrated in FIG. 1 , the mobile body 100 may be, for example, an autonomous mobile robot such as an autonomous mobile vacuum cleaner that moves indoors, an autonomous food delivery machine, an autonomously flying drone, an autonomously traveling vehicle that moves on land, or an autonomously navigating ship that moves on or underwater. The mobile body 100 includes a light-emitting device 1, a light-receiving device 2, an information processing device 3, an operation control device 4, and a drive device 5. In other words, the technology disclosed herein can be applied to an autonomous mobile robot such as an autonomous mobile vacuum cleaner that moves indoors, an autonomously flying drone, an autonomously traveling vehicle that moves on land, or an autonomously navigating ship that moves on or underwater. Below, an example in which the technology disclosed herein is applied to an autonomous mobile robot will be described.

[0029] The light-emitting device 1 is a device that irradiates an optical pulse signal onto a subject 6. The light-emitting device 1 irradiates an optical pulse signal (TX pulse signal) within a two-dimensional measurement range around the device itself. The light-receiving device 2 detects a reflected optical pulse signal (RX pulse signal) that is the optical pulse signal reflected by the subject 6. The light-receiving device 2 detects the returning light from the two-dimensional measurement range as a reflected optical pulse signal. The subject 6 includes objects, buildings, etc. in the surrounding environment of the device itself (mobile body 100).

[0030] The information processing device 3 can generate point cloud data having two-dimensional distance information around the vehicle, based on the reflected light pulse signal received by the light receiving device 2. Furthermore, the information processing device 3 can estimate the position of the vehicle and detect obstacles with which it may collide, based on this point cloud data.

[0031] The driving control device 4 controls the autonomous driving of the mobile body 100 so as to avoid collision with an obstacle, based on the estimated position of the mobile body generated by the information processing device 3 and the position of the detected obstacle. For example, it controls the driving of the mobile body 100 along a target route.

[0032] The drive unit 5 is a mechanism for moving the mobile body 100, and includes a running mechanism, a propulsion mechanism, a flight mechanism, etc. In this example, the mobile body 100 is configured as an autonomous mobile robot, and the drive unit 5 is configured as a motor, wheels, etc. of the autonomous mobile robot. Furthermore, if the mobile body 100 is configured as an autonomously sailing ship, the drive unit 5 is configured as a screw propeller, etc. of the propulsion mechanism. Furthermore, if the mobile body 100 is configured as a drone, the drive unit 5 is configured as a motor, propellers, etc. of the flight mechanism. The drive unit 5 is driven under the control of the operation control device 4 to move the mobile body 100.

[0033] 2 and 3, the configurations of the light-emitting device 1, the light-receiving device 2, the information processing device 3, and the operation control device 4 will be described in more detail. Fig. 2 is a block diagram showing the configurations of the light-receiving device 2, the information processing device 3, and the operation control device 4. Fig. 3 is a block diagram showing the configurations of the light-emitting device 1, the light-receiving device 2, and the information processing device 3 according to this embodiment in more detail.

[0034] The moving object 100 shown in FIGS. 2 and 3 performs distance measurement processing using, for example, a dToF (direct time of flight) system. As shown in FIGS. 2 and 3, the light emitting device 1 includes a laser emitter 10, a measurement pulse generator 11, and a light emission optical system (TX optical system) 12. As shown in FIG. 3, the laser emitter 10 includes a plurality of light emitting elements 10a. The plurality of light emitting elements 10a are arranged in multiple rows along a predetermined direction (first direction Y). For convenience, in this specification, the first direction Y is defined as the vertical direction and the second direction X is defined as the horizontal direction. Alternatively, the first direction Y may be defined as the horizontal direction and the second direction X may be defined as the vertical direction. In other words, the plurality of light emitting elements 10a may be arranged in the second direction X (horizontal direction). Alternatively, the plurality of light emitting elements 10a may be arranged in both the first direction Y and the second direction X.

[0035] The plurality of light-emitting elements 10a repeatedly emit light-emitting pulse signals (TX pulse signals) at predetermined time intervals. The light-emitting unit 2 can also scan the optical signals emitted by the plurality of light-emitting elements 10a in the first direction X. The specific method for scanning the optical signals is not limited.

[0036] The light-emitting elements 10a are, for example, edge-emitting lasers (EELs) or vertical cavity surface-emitting lasers (VCSELs), and the number of light-emitting elements 10a included in the light-emitting unit 2 is arbitrary. In the following, an example will be described in which the light-emitting unit 2 includes a plurality of light-emitting elements 10a, and the plurality of light-emitting elements 10a are arranged in the first direction Y.

[0037] The plurality of light-emitting elements 10a emit light one by one in sequence with a time lag. Alternatively, among the plurality of light-emitting elements 10a, each group of light-emitting elements 10a including two or more light-emitting elements 10a may emit light with a time lag. Alternatively, the plurality of light-emitting elements 10a may emit light at the same timing. Each light-emitting element 10a repeatedly emits an optical pulse signal thousands to tens of thousands of times in one measurement.

[0038] The measurement pulse generating unit 11 controls the emission timing of the optical pulse signal. That is, the measurement pulse generating unit 11 has a drive circuit 13, a clock generating unit 14, and an emission control unit 15. The drive circuit 13 drives the plurality of light-emitting elements 10a based on a control signal from the emission control unit 15. For example, the drive circuit 13 controls the emission timing of the optical pulse signal based on the control signal from the emission control unit 15.

[0039] The clock generating unit 14 generates a clock signal synchronized with a reference clock signal, which may be input from the operation control device 4, for example.

[0040] The light-emission control unit 15 is composed of a CPU (Central Processing Unit), memory, etc., and controls the drive circuit 13 and the clock generation unit 14 by executing a predetermined program, as described above. That is, the light-emission control unit 15 generates a control signal for controlling the light-emission timing of each light-emitting element 10a in synchronization with a clock signal. The drive circuit 13 drives the plurality of light-emitting elements 10a based on the control signal output from the light-emission control unit 15.

[0041] The light emitting optical system (TX optical system) 12 irradiates or scans the light pulse signal emitted from the light emitting unit 2 within a predetermined angular range. The light emitting optical system 12 may have a mechanical scanning mechanism such as a polygon mirror or a MEMS mirror. The light emitting optical system 12 can change the angular range of irradiation in synchronization with a control signal from the light emission control unit 15. A central processing unit 40 (see FIG. 4 ) of the operation control device 4 controls the light emitting device 1, the light receiving device 2, and the information processing device 3.

[0042] 2 and 3, the light receiving device 2 has a light detection unit 20 and a light receiving optical system (RX optical system) 21. As shown in Fig. 3, the light receiving optical system (RX optical system) 21 focuses a reflected light signal from the subject 6 onto the light detection unit 20. The light detection unit (SPAD sensor light detection unit) 20 has a pixel array unit 22, a timing control unit 23, and a drive circuit 24.

[0043] The timing control unit 23 is composed of a CPU (Central Processing Unit), memory, etc., and executes a predetermined program to control the pixel array unit 22 and the drive circuit 24 at timing synchronized with the measurement pulse generation unit 11. The pixel array unit 22 has a plurality of ranging pixels 22a arranged in a two-dimensional direction. The ranging pixels 22a receive reflected light signals from the subject 6. The ranging pixels 22a output electrical signals corresponding to the light intensity of the received reflected light signals.

[0044] Each of the multiple ranging pixels 22a includes a light-receiving element. The light-receiving element is, for example, a single photon avalanche photodiode (SPAD). Each ranging pixel 22a may include a quench circuit (not shown). In an initial state, the quench circuit supplies a reverse bias voltage between the anode and cathode of the SPAD, with a potential difference exceeding the breakdown voltage. After the SPAD detects a photon, the drive circuit 24 supplies the reverse bias voltage to the SPAD via the corresponding quench circuit to prepare for detection of the next reflected light pulse signal (RX pulse signal). As described above, to obtain two-dimensional distance information, for example, each light-emitting element 10a repeatedly emits a light pulse signal thousands to tens of thousands of times, and each corresponding ranging pixel 22a converts the light pulse signal into an electrical signal thousands to tens of thousands of times.

[0045] 2 and 3, the information processing device 3 includes a signal processing control unit 30a, a storage unit 30b, a time measurement unit (TDC) 31, a histogram generation unit 32, and a signal processing unit 33. Also, as shown in FIG. 3, the signal processing unit 33 includes an echo identification unit 34, a distance generation unit 35, a self-position estimation unit 36, and an obstacle determination unit 37. The signal processing control unit 30a is composed of a CPU (Central Processing Unit), a storage unit 30b, and the like, and controls the time measurement unit (TDC) 31, the histogram generation unit 32, and the signal processing unit 33 by executing a predetermined program. The storage unit 30b stores data generated by the time measurement unit (TDC) 31, the histogram generation unit 32, and the signal processing unit 33. The echo identification unit 34 according to this embodiment corresponds to the identification unit.

[0046] The TDC 31 generates a time digital signal corresponding to the light reception time of the reflected light pulse signal received by the SPAD with a predetermined time resolution. For example, the TDC 31 generates a time digital signal for each ranging pixel 22 a by repeating the process several thousand to several tens of thousands of times with the predetermined time resolution in synchronization with the light emission timing of several thousand to several tens of thousands of light emission pulse signals.

[0047] The histogram generator 32, the echo discriminator 34, and the distance generator 35 will now be described with reference to FIGS. 4 to 7. FIG. 4 is a diagram showing an example of measuring distance values ​​in a surrounding environment including a subject 6a. This shows an example in which a polygon mirror 53 is used as the optical system 12. As shown in FIG. 4, the optical system 12 is composed of an exit lens 51, a dichroic mirror 52, and a polygon mirror 53. An optical pulse signal is irradiated onto a scanning range 12r of the polygon mirror 52 via the exit lens 51, the dichroic mirror 52, and the polygon mirror 53.

[0048] The polygon mirror 51 is rotated around its axis of rotation by a motor under the control of the light emission control unit 15. When the light pulse signal scanned by the polygon mirror 53 is irradiated onto the subject 6a, a reflected light pulse signal having a light intensity corresponding to the reflectance of the subject 6a is reflected from the subject 6a. This reflected light pulse signal is reflected by the polygon mirror 53 and the dichroic mirror 52, and is measured in order by the ranging pixels 22a of the pixel array unit 22 and converted into a distance value. Note that in FIG. 4, the distance value corresponding to the subject 6a is schematically illustrated as subject d6a.

[0049] At this time, the light emitting position of the laser emitting unit 10, the light emitting time, the rotation angle of the polygon mirror 51, and the ranging pixels 22a of the pixel array unit 22 are associated with each other and stored in the storage unit 30b. As can be seen from these, the irradiation direction of the light emitting pulse can be calculated from the light emitting position of the laser emitting unit 10 and the rotation angle of the polygon mirror 51.

[0050] Fig. 5 is a diagram showing an example of first point cloud data in the measurement of Fig. 4. Fig. 5(a) is a diagram showing a schematic diagram of the first point cloud data g10. The first point cloud data g10 is used for self-position estimation by the self-position estimation unit 36, which will be described later. The first point cloud data g10 is data associated with each ranging pixel 22a, and includes information on distance values ​​and irradiation directions.

[0051] 5B is a diagram showing an example of a histogram used to generate element p20 of the first point cloud data g20. The vertical axis represents the time digital signal generated by the TDC 31, and the vertical axis represents the number of measurements within the bin width. For example, if a light emission pulse signal is emitted several thousand times corresponding to the ranging pixel 22a and all measurements are taken, the sum of the numbers of measurements within all bins will be several thousand measurements.

[0052] 5B, the histogram generator 32 generates a histogram for each ranging pixel 22a with a bin width according to the time resolution of the TDC 31 based on the time digital signals generated by the TDC 31 several thousand to several tens of thousands of times, and stores the generated histogram in the memory 30b. Here, the bin width is the width of each frequency unit constituting the histogram. The higher the time resolution of the TDC 31, the narrower the bin width can be, and the more accurately a histogram can be obtained that reflects the time frequency of receiving the RX pulse signal.

[0053] That is, the histogram generator 32 adds up the number of time digital signals within a bin width to obtain the number of measurements (photon count) within the bin width. In this way, the histogram generator 32 generates a histogram by arranging the number of measurements within each bin width for each bin width. The histogram generator 32 also generates a histogram corresponding to each ranging pixel 22a.

[0054] Fig. 6 is a diagram showing an example of measurement of the surrounding environment including a subject 6b via a transparent object A20. In Fig. 6, a transparent object A10 is placed in the scanning range 12r of the polygon mirror 53. Furthermore, a subject 6b is located on the far side of the transparent object A10. Note that in Fig. 6, the distance value corresponding to the subject 6b is schematically shown as a subject d6b.

[0055] 6, when the light pulse signal scanned by the polygon mirror 53 is irradiated onto a transparent object A10, a first reflected light pulse signal having a light intensity according to the reflectance of the transparent object A10 is reflected from the transparent object A10. Furthermore, the light pulse signal transmitted through the transparent object A10 is emitted from the subject 6b as a second reflected light pulse signal having a light intensity according to the reflectance of the subject 6b. As can be seen from this, when a transparent object A10 is placed, the first reflected light pulse signal and the second reflected light pulse signal are reflected at different times from the same irradiation direction.

[0056] Fig. 7 is a diagram showing an example of the first point cloud data g10a and the second point cloud data g20 in the measurement of Fig. 6. Fig. 7(a) is a diagram showing a schematic diagram of the second point cloud data g20. The second point cloud data g20 is used for obstacle determination by the obstacle determination unit 37, which will be described later. The second point cloud data g20 is data associated with each ranging pixel 22a, and includes information on distance values ​​and irradiation directions.

[0057] 7B is a diagram schematically illustrating the first point cloud data g10a. As described above, the first point cloud data g10a is used for self-position estimation by the self-position estimation unit 36, which will be described later. FIG. 7C is a diagram illustrating an example of the first point cloud data g10a and a histogram used to generate the element p20 of the second point cloud data g20. The vertical axis represents the time digital signal generated by the TDC 31, and the vertical axis represents the number of measurements within the bin width.

[0058] 7C, the first reflected light pulse signal having a light intensity corresponding to the reflectance of the transparent object A10 is measured as a peak h20. Meanwhile, the second reflected light pulse signal having a light intensity corresponding to the reflectance of the subject 6b is measured as a peak h10a. Thus, the histogram when the transparent object A10 is used is generally measured as two or more peaks h20 and h10a.

[0059] As shown in FIG. 7A, the second point cloud data g20 is distance value data based on the position of the peak h20 on the short distance side. In the second point cloud data g20, the distance value of the transparent object A10 is used. On the other hand, as shown in FIG. 7B, the first point cloud data g10a is distance value data based on the position of the second peak h10a on the long distance side. In the first point cloud data g10a, instead of the distance value of the transparent object A10, the distance value based on the position of the second peak h10a on the far side of the transparent object A10 is used. In this embodiment, the distance values ​​of the area other than the transparent object A10 are the same in the first point cloud data g10a and the second point cloud data g20.

[0060] Furthermore, when there are three or more peaks, distance value data is generated in the first point cloud data g10a based on the position of the peak h10a on the farthest side. In this way, when there are three or more peaks, distance values ​​based on the position of the peak h10a on the farthest side from the transparent object A10 are used in the first point cloud data g10a instead of the distance values ​​of the transparent object A10. Even when there are three or more peaks, in this embodiment, the distance values ​​of areas other than the transparent object A10 are the same in the first point cloud data g10a and the second point cloud data g20.

[0061] The echo discrimination unit 34 of the signal processing unit 33 determines the number of peaks in the histogram for each ranging pixel 22a. If there are two or more peaks, the echo discrimination unit 34 determines that measurement was performed through a transparent object. In other words, if there are two or more peaks in the histogram, the echo discrimination unit 34 determines that a transparent object is present.

[0062] The echo discrimination unit 34 outputs information on the first peak of the histogram, which corresponds to the second peak on the long distance side, to the distance generation unit 35. When the echo discrimination unit 34 determines that there are two peaks in the histogram, it outputs information on the second peak of the histogram, which corresponds to the shortest distance side, in addition to information on the first peak, to the distance generation unit 35. That is, when there are two peaks in the histogram, the echo discrimination unit 34 can determine that measurement was performed through a transparent object. When the echo discrimination unit 34 determines that there are two peaks in the histogram, it outputs information on the second peak of the second histogram, which corresponds to the shortest distance side, in addition to information on the first histogram, to the distance generation unit 35. That is, when there are two peaks in the histogram, the echo discrimination unit 34 can determine that measurement was performed through a transparent object.

[0063] When the histogram has three or more peaks, the echo discrimination unit 34 sets the histogram corresponding to the farthest distance as the first histogram and outputs information about the first peak of the first histogram to the distance generation unit 35. When the echo discrimination unit 34 determines that the histogram has three or more peaks, it outputs information about the second peak of the second histogram corresponding to the shortest distance to the distance generation unit 35 in addition to the information about the first histogram. That is, when the histogram has two or more peaks, the echo discrimination unit 34 can determine that measurement was performed through a transparent object. When the echo discrimination unit 34 determines that the histogram has three or more peaks, it sets the histogram corresponding to the farthest distance as the first histogram and outputs information about the second peak of the second histogram corresponding to the shortest distance to the distance generation unit 35 in addition to the information about the first histogram. That is, when the histogram has two or more peaks, the echo discrimination unit 34 can determine that measurement was performed through a transparent object.

[0064] The distance generation unit 35 calculates first distance information to the subject 6 for each ranging pixel 22a by, for example, calculating the center of gravity of the RX pulse signal in the first histogram based on the information of the first peak, and outputs the first distance information to the obstacle determination unit 37. The distance generation unit 35 generates first point cloud data, which is information on the first distance and the irradiation direction from the aircraft at the first distance, based on the information in the storage unit 30b, and supplies the first point cloud data to the self-position estimation unit 36. The irradiation direction from the aircraft corresponds to, for example, the irradiation direction from the aircraft centered on the irradiation point of the optical system 12.

[0065] On the other hand, when only information about the first peak is available, the distance generation unit 35 calculates the first distance to the subject 6 by, for example, calculating the center of gravity of the RX pulse signal in the first histogram based on the information about the first peak, and when information about the second peak is available, the distance generation unit 35 calculates the second distance to the subject 6 for each ranging pixel 22a by, for example, calculating the center of gravity of the RX pulse signal in the second histogram based on the information about the second peak.

[0066] Then, the distance generation unit 35 generates information on the first distance and information on the irradiation direction from the own aircraft at the first distance as first point cloud data based on the information in the storage unit 30b, and supplies this to the self-position estimation unit 36. Furthermore, if there is information on the first distance, information on the irradiation direction from the own aircraft at the first distance, and information on the second distance, the distance generation unit 35 generates information on the second distance and information on the irradiation direction from the own aircraft at the second distance as second point cloud data based on the information in the storage unit 30b, and supplies this to the obstacle determination unit 37.

[0067] The self-location estimation unit 36 ​​generates map information of the self-location and the surrounding environment of the self-device based on the first distance and the irradiation direction from the self-device. That is, the self-location estimation unit 36 ​​can create the shape of surrounding objects using the first point cloud data. It is known that detecting objects that are as far away as possible is effective in improving the self-location accuracy.

[0068] On the other hand, to avoid obstacles, it is necessary to detect objects that are as close as possible. Therefore, the obstacle determination unit 37 detects obstacles in the direction of the vehicle's path based on the second distance and the illumination direction from the vehicle. That is, the obstacle determination unit 37 can create the shapes and positions of surrounding obstacles using the second point cloud data. The self-position estimation unit 36 ​​and the obstacle determination unit 37 will be described in detail later.

[0069] 2 , the driving control device 4 has a central processing unit 40, a motion sensor 41, an encoder 42, and a main memory device 43. The central processing unit 40 is configured by a CPU (Central Processing Unit) and executes a predetermined program to control the driving device 5 and cause the moving object 100 to move. That is, the central processing unit 40 controls the movement of the moving object 100 based on control information generated by the self-position estimation unit 36 ​​and the obstacle determination unit 37.

[0070] The motion sensor 41 measures the angular velocity and angular acceleration of the wheels of the moving body 100, and supplies a velocity information signal including information on the angular velocity and angular acceleration to the self-position estimation unit 36. The encoder 42 is an encoder for the wheels of the moving body 100, measures the rotation angle of the wheels, and supplies a direction information signal including information on the rotation angle to the self-position estimation unit 36.

[0071] Here, the self-position estimation unit 36 ​​will be described in detail. The self-position estimation unit 36 ​​calculates the self-position, velocity vector, and acceleration vector of the vehicle (mobile body 100). The self-position estimation unit 36 ​​calculates the velocity vector and acceleration vector of the vehicle based on the angular velocity, angular acceleration, and rotation angle of the wheels supplied from the motion sensor 41 and the encoder 42.

[0072] The self-position estimation unit 36 ​​calculates the relative position of the vehicle from the point where it started moving by accumulating the wheel angular velocity and the trajectory of the wheel rotation angle. The self-position estimation unit 36 ​​also uses the relative position of the vehicle at the time the first point cloud data was acquired as a reference coordinate. The self-position estimation unit 36 ​​then uses the acquired first point cloud data to generate a first map indicating distance values ​​to subjects (objects) 6 in the surrounding environment, while estimating the vehicle's position. If a second map of the driving environment exists, the self-position estimation unit 36 ​​can also match the position information of the second map with the position information of the generated first map to generate the vehicle's absolute position.

[0073] Here, details of the obstacle determination unit 37 will be described. When the echo identification unit 34 determines that two or more peaks exist in the histogram and that a transparent object exists, the obstacle determination unit 37 determines that a transparent object exists in the irradiation direction in which it has been determined that two or more peaks exist, and at a distance corresponding to the peak on the short-distance side.

[0074] For example, the obstacle determination unit 37 determines the possibility of collision of the mobile object 100 with an obstacle based on the second point cloud data and the velocity vector and acceleration vector at the mobile object's own position determined by the self-position estimation unit 36. The obstacle determination unit 37 divides the spatial region in the traveling direction of the mobile object 100 into small regions that are continuous in the traveling direction based on the velocity vector. For each divided small region, the obstacle determination unit 37 configures the moving obstacle with a distance value based on the second point cloud data.

[0075] The obstacle determination unit 37 also calculates the risk of collision with an obstacle based on the velocity vector and acceleration vector. The obstacle determination unit 37 sets an obstacle area where an obstacle may exist based on the collision risk for each small area. The obstacle determination unit 37 then outputs obstacle control information for controlling the movement of the vehicle (mobile body 100) to the central processing unit 40 based on the distance from the vehicle to the obstacle area.

[0076] The central processing unit 40 calculates the angular velocity, angular acceleration, and rotation angle of the wheels based on the first map information and the vehicle's own position, and controls the drive unit 5 to travel to the next destination. At this time, the vehicle's travel path is changed based on the obstacle control information from the obstacle determination unit 37. Alternatively, the vehicle's speed can be reduced. In this way, even when a transparent object is positioned as an obstacle, it is possible to avoid a collision and control driving based on the position information of the first map.

[0077] 8 is a flowchart showing an example of processing by the information processing device 3. Here, an example of generating point cloud data after the histogram generation unit 32 generates a histogram will be described. Also, an example will be described in which the pixel array unit 22 has a two-dimensional array of ranging pixels 22a with 0 to 56 pixels vertically (Y) and 0 to 192 pixels horizontally (X).

[0078] First, the echo discriminator 34 acquires 57 × 193 histograms corresponding to each ranging pixel 22a from the storage unit 30b (step S10). Next, the echo discriminator 34 sequentially discriminates the 57 × 193 histograms, detects the number of peaks and their positions (bin positions) in the histograms, and stores them in the storage unit 30b in association with coordinates (X, Y) (X = 0 to 56, Y = 0 to 192) (step S12).

[0079] The distance generating unit 35 initializes X=0 and Y=0 (step S14). Then, the distance generating unit 35 acquires information on the histogram associated with (X, Y), the number of peaks n in the histogram, and the peak positions from the storage unit 30b (steps S16 and S17).

[0080] Next, the distance generation unit 35 determines whether the number of peaks n associated with (X, Y) is 1 (step S18). If the distance generation unit 35 determines that n is 1 (Yes in step S18), it performs depth conversion (calculates distance) based on the peak position (step S20). Then, the distance value, the illuminated target direction, and the (X, Y) coordinates are associated with each other and supplied to the obstacle determination unit 37 as part of the second point cloud data (step S22). Subsequently, the distance value, the illuminated target direction, and the (X, Y) coordinates are associated with each other and supplied to the self-position estimation unit 36 ​​as part of the first point cloud data (step S24).

[0081] Next, the distance generation unit 35 sets the (X, Y) coordinates corresponding to the next pixel (step S26). If the set pixel is the last pixel (X=56, Y=192) (Yes in step S28), the process proceeds to the next frame (step S30). On the other hand, if the set pixel is not the last pixel (X=56, Y=192) (No in step S28), the process repeats from step S16.

[0082] On the other hand, if the distance generation unit 35 determines that n is not 1 (No in step S18), it performs depth conversion (calculates distance) based on the peak position on the closest side (step S32), associates the distance value, the illuminated target direction, and the (X, Y) coordinates, and supplies the resulting data to the obstacle determination unit 37 as part of the second point cloud data (step S34). Then, the process from step S26 is repeated. Similarly, if the distance generation unit 35 determines that n is not 1 (No in step S18), it performs depth conversion (calculates distance) based on the second closest peak position (step S36), associates the distance value, the illuminated target direction, and the (X, Y) coordinates, and supplies the resulting data to the self-position estimation unit 36 ​​as part of the first point cloud data (step S38). Then, the process from step S26 is repeated. If it is determined that n is not 1 (No in step S18), and if n is 3 or more, the distance generation unit 35 performs depth conversion (calculates the distance) based on the peak position on the farthest side (step S36), associates the distance value, the target direction, and the (X, Y) coordinates, and supplies them to the self-position estimation unit 36 ​​as part of the first point cloud data (step S38).

[0083] Through such processing, first point cloud data and second point cloud data are generated according to the number of peaks in the histogram.

[0084] As described above, according to this embodiment, the echo discrimination unit 34 determines the number of peaks in the histogram generated by the histogram generation unit 32, and when there are multiple peaks, the distance generation unit 35 supplies the obstacle determination unit 37 with a distance value based on the short-distance peak and supplies the self-position estimation unit 36 ​​with a distance value based on the long-distance peak. This allows the obstacle determination unit 37 to perform obstacle determination based on the short-distance distance value, and the self-position estimation unit 36 ​​to perform self-position estimation based on the long-distance distance value, even when distance values ​​of the surrounding environment are generated through a transparent object. Therefore, even when a transparent object is present, it is possible to suppress a decrease in the processing accuracy of the obstacle determination unit 37 and the self-position estimation unit 36.

[0085] (Modification of First Embodiment) The moving body 100 according to the modification of the first embodiment differs from the moving body 100 according to the first embodiment in that, when there are two or more peaks in the histogram, the light emission intensity is changed to enable false shadow detection. The differences from the moving body 100 according to the first embodiment will be described below.

[0086] 9 is a diagram showing an example of a histogram when a false shadow occurs. The vertical axis indicates the time digital signal generated by the TDC 31, and the vertical axis indicates the number of measurements within the bin width. Peak h30a is a peak caused by lens flare / ghosting. Peak h30b is a peak caused by reflection from the subject 6.

[0087] If the echo discrimination unit 34 determines that there are two or more peaks, the central processing unit 40 reduces the emission intensity of the laser emitter 10 and causes it to emit light again. The echo discrimination unit 34 compares, for example, a first ratio of the heights of peaks h30a and h30b in the initially generated histogram with a second ratio of the heights of peaks h30a and h30b in the regenerated histogram, and determines that there is no artifact if the ratio is within a predetermined range. On the other hand, the echo discrimination unit 34 compares the first ratio with the second ratio, and determines that there is an artifact if the ratio is outside the predetermined range. If there is an artifact, the information on the histogram associated with that ranging pixel 22a can be invalidated. Alternatively, the emission intensity can be changed and measured again. This prevents unnecessary obstacle avoidance operations from being performed.

[0088] <Application to a Mobile Body> The technology according to the present disclosure (the present technology) can be applied to various products. For example, the technology according to the present disclosure may be realized as a device mounted on any type of mobile body, such as an automobile, an electric vehicle, a hybrid electric vehicle, a motorcycle, a bicycle, personal mobility, an airplane, a drone, a ship, or a robot.

[0089] FIG. 10 is a block diagram showing a schematic configuration example of a vehicle control system, which is an example of a mobile object control system to which the technology according to the present disclosure can be applied.

[0090] The vehicle control system 12000 includes a plurality of electronic control units connected via a communication network 12001. In the example shown in Fig. 10, the vehicle control system 12000 includes a drive system control unit 12010, a body system control unit 12020, an outside-vehicle information detection unit 12030, an inside-vehicle information detection unit 12040, and an integrated control unit 12050. Also shown as functional components of the integrated control unit 12050 are a microcomputer 12051, an audio / video output unit 12052, and an in-vehicle network I / F (Interface) 12053.

[0091] The drivetrain control unit 12010 controls the operation of devices related to the drivetrain of the vehicle in accordance with various programs. For example, the drivetrain control unit 12010 functions as a control device for a drive force generating device for generating a drive force of the vehicle, such as an internal combustion engine or a drive motor, a drive force transmission mechanism for transmitting the drive force to the wheels, a steering mechanism for adjusting the steering angle of the vehicle, and a braking device for generating a braking force of the vehicle.

[0092] The body system control unit 12020 controls the operation of various devices equipped in the vehicle body according to various programs. For example, the body system control unit 12020 functions as a control device for a keyless entry system, a smart key system, a power window device, or various lamps such as headlamps, backup lamps, brake lamps, turn signals, and fog lamps. In this case, radio waves transmitted from a portable device that serves as a key or signals from various switches can be input to the body system control unit 12020. The body system control unit 12020 receives these radio waves or signals and controls the vehicle's door lock device, power window device, lamps, etc.

[0093] The outside-vehicle information detection unit 12030 detects information outside the vehicle equipped with the vehicle control system 12000. For example, an imaging unit 12031 is connected to the outside-vehicle information detection unit 12030. The outside-vehicle information detection unit 12030 causes the imaging unit 12031 to capture images outside the vehicle and receives the captured images. The outside-vehicle information detection unit 12030 may perform object detection processing or distance detection processing for people, cars, obstacles, signs, characters on the road surface, etc. based on the received images.

[0094] The imaging unit 12031 is an optical sensor that receives light and outputs an electrical signal corresponding to the amount of light received. The imaging unit 12031 can output the electrical signal as an image or as distance measurement information. The light received by the imaging unit 12031 may be visible light or invisible light such as infrared light.

[0095] The in-vehicle information detection unit 12040 detects information inside the vehicle. For example, a driver state detection unit 12041 that detects the state of the driver is connected to the in-vehicle information detection unit 12040. The driver state detection unit 12041 includes, for example, a camera that captures an image of the driver, and the in-vehicle information detection unit 12040 may calculate the degree of fatigue or concentration of the driver based on the detection information input from the driver state detection unit 12041, or may determine whether the driver is dozing off.

[0096] The microcomputer 12051 can calculate control target values ​​for the driving force generating device, steering mechanism, or braking device based on the information inside and outside the vehicle acquired by the outside-vehicle information detection unit 12030 or the inside-vehicle information detection unit 12040, and output control commands to the drive system control unit 12010. For example, the microcomputer 12051 can perform cooperative control aimed at realizing the functions of an ADAS (Advanced Driver Assistance System), including vehicle collision avoidance or impact mitigation, following driving based on the inter-vehicle distance, vehicle speed maintenance driving, vehicle collision warning, vehicle lane departure warning, etc.

[0097] In addition, the microcomputer 12051 can perform cooperative control for the purpose of autonomous driving, which allows the vehicle to travel autonomously without relying on driver operation, by controlling the driving force generating device, steering mechanism, braking device, etc. based on information about the surroundings of the vehicle obtained by the outside vehicle information detection unit 12030 or the inside vehicle information detection unit 12040.

[0098] Furthermore, the microcomputer 12051 can output a control command to the body system control unit 12020 based on the information outside the vehicle acquired by the outside information detection unit 12030. For example, the microcomputer 12051 can control the headlamps according to the position of a preceding vehicle or an oncoming vehicle detected by the outside information detection unit 12030, and perform cooperative control aimed at preventing glare, such as switching from high beams to low beams.

[0099] The audio / video output unit 12052 transmits at least one of audio and video output signals to an output device capable of visually or audibly notifying the passengers of the vehicle or the outside of the vehicle of information. In the example of Fig. 10, the output devices are exemplified by an audio speaker 12061, a display unit 12062, and an instrument panel 12063. The display unit 12062 may include, for example, at least one of an on-board display and a head-up display.

[0100] FIG. 11 is a diagram showing an example of the installation position of the imaging unit 12031.

[0101] In FIG. 11, the imaging unit 12031 includes imaging units 12101, 12102, 12103, 12104, and 12105.

[0102] The imaging units 12101, 12102, 12103, 12104, and 12105 are provided, for example, at positions such as the front nose, side mirrors, rear bumper, back door, and the top of the windshield inside the vehicle cabin of the vehicle 12100. The imaging unit 12101 provided on the front nose and the imaging unit 12105 provided on the top of the windshield inside the vehicle cabin mainly acquire images of the front of the vehicle 12100. The imaging units 12102 and 12103 provided on the side mirrors mainly acquire images of the sides of the vehicle 12100. The imaging unit 12104 provided on the rear bumper or back door mainly acquires images of the rear of the vehicle 12100. The imaging unit 12105 provided on the top of the windshield inside the vehicle cabin is mainly used to detect preceding vehicles, pedestrians, obstacles, traffic lights, traffic signs, lanes, etc.

[0103] 11 shows an example of the imaging ranges of the imaging units 12101 to 12104. Imaging range 12111 indicates the imaging range of the imaging unit 12101 provided on the front nose, imaging ranges 12112 and 12113 indicate the imaging ranges of the imaging units 12102 and 12103 provided on the side mirrors, respectively, and imaging range 12114 indicates the imaging range of the imaging unit 12104 provided on the rear bumper or back door. For example, by overlaying the image data captured by the imaging units 12101 to 12104, an overhead image of the vehicle 12100 viewed from above can be obtained.

[0104] At least one of the image capturing units 12101 to 12104 may have a function of acquiring distance information. For example, at least one of the image capturing units 12101 to 12104 may be a stereo camera made up of multiple image capturing elements, or may be an image capturing element having pixels for phase difference detection.

[0105] For example, based on the distance information obtained from the imaging units 12101 to 12104, the microcomputer 12051 can calculate the distance to each three-dimensional object within the imaging ranges 12111 to 12114 and the change in this distance over time (relative speed with respect to the vehicle 12100), thereby extracting as a preceding vehicle, in particular, the three-dimensional object that is the closest three-dimensional object on the path of the vehicle 12100 and traveling in approximately the same direction as the vehicle 12100 at a predetermined speed (e.g., 0 km / h or higher). Furthermore, the microcomputer 12051 can set a vehicle-to-vehicle distance to be maintained in advance in front of the preceding vehicle, and perform automatic braking control (including follow-up stop control), automatic acceleration control (including follow-up start control), etc. In this way, cooperative control can be performed for the purpose of autonomous driving, which runs autonomously without relying on driver operation.

[0106] For example, the microcomputer 12051 classifies and extracts three-dimensional object data regarding three-dimensional objects into two-wheeled vehicles, ordinary vehicles, large vehicles, pedestrians, utility poles, and other three-dimensional objects based on distance information obtained from the imaging units 12101 to 12104, and can use the data for automatic obstacle avoidance. For example, the microcomputer 12051 distinguishes obstacles around the vehicle 12100 into obstacles that are visible to the driver of the vehicle 12100 and obstacles that are difficult to see. The microcomputer 12051 then determines a collision risk that indicates the risk of collision with each obstacle, and when the collision risk is equal to or greater than a set value and a collision is possible, the microcomputer 12051 can provide driving assistance for collision avoidance by outputting an alarm to the driver via the audio speaker 12061 or the display unit 12062, or by performing forced deceleration or avoidance steering via the drive system control unit 12010.

[0107] At least one of the image capturing units 12101 to 12104 may be an infrared camera that detects infrared rays. For example, the microcomputer 12051 can recognize a pedestrian by determining whether a pedestrian is present in the images captured by the image capturing units 12101 to 12104. Such pedestrian recognition is performed, for example, by extracting feature points from the images captured by the image capturing units 12101 to 12104 as infrared cameras and performing pattern matching on a series of feature points that indicate the outline of an object to determine whether the object is a pedestrian. When the microcomputer 12051 determines that a pedestrian is present in the images captured by the image capturing units 12101 to 12104 and recognizes the pedestrian, the audio / image output unit 12052 controls the display unit 12062 to superimpose a rectangular outline on the recognized pedestrian for emphasis. The audio / image output unit 12052 may also control the display unit 12062 to display an icon or the like indicating the pedestrian at a desired position.

[0108] The above describes an example of a vehicle control system to which the technology according to the present disclosure can be applied. The technology according to the present disclosure can be applied to the outside vehicle information detection unit 12030 and the image capture unit 12031 among the above-described configurations. Since more accurate distance images can be obtained, it becomes possible to further improve the accuracy of cooperative control for the purpose of autonomous driving and the like.

[0109] The present technology can be configured as follows:

[0110] (1) An information processing method comprising: a measurement step of generating values ​​relating to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals repeatedly emitted at predetermined time intervals; a generation step of generating a histogram of the number of measurements of the reflected light pulse signals relative to the values ​​relating to the return time; and a signal processing step of, when two peaks exist in the histogram, determining whether there is an obstacle for the aircraft itself using a distance value based on one of the peaks, and estimating the aircraft's own position using a distance value based on the other peak.

[0111] (2) The information processing method according to (1), wherein, in the signal processing step, when two peaks exist in the histogram, the distance value based on the peak on the closer distance side is used for obstacle determination.

[0112] (3) The information processing method according to (2), wherein, in the signal processing step, when two peaks exist in the histogram, the distance value based on the peak on the far side is used to estimate the self-position.

[0113] (4) The information processing method according to (1), wherein, in the signal processing step, when three or more peaks exist in the histogram, the distance value based on the peak on the shortest distance side is used for obstacle determination.

[0114] (5) The information processing method according to (4), wherein, in the signal processing step, when three or more peaks exist in the histogram, a distance value based on the peak on the farthest side is used to estimate the self-position.

[0115] (6) The information processing method according to (1), wherein, in the signal processing step, if only one peak exists in the histogram, a distance value based on the peak is used for obstacle determination and self-position estimation.

[0116] (7) The information processing method described in (1), wherein in the measurement step, the plurality of light emission pulse signals are emitted in a plurality of irradiation directions; in the generation step, the histogram is generated for each of the plurality of irradiation directions; and in the signal processing step, when two peaks exist in the histogram for each of the plurality of irradiation directions, an obstacle is determined using a first distance value based on the peak on the closest side, and a self-position is estimated using a second distance value based on the peak on the farthest side.

[0117] (8) The information processing method according to (7), wherein the obstacle determination determines an obstacle based on the first distance value and an illumination direction from the own aircraft corresponding to the first distance value.

[0118] (9) The information processing method according to (8), wherein the estimation of the self-position is based on the second distance value and an illumination direction from the own device corresponding to the second distance value.

[0119] (10) The information processing method according to (9), further comprising a determining step of determining whether or not two or more peaks exist in the histogram, and the signal processing step is executed based on the determination in the determining step.

[0120] (11) The information processing method according to (10), wherein the determining step determines that a transparent object is present when two or more peaks exist in the histogram.

[0121] (12) The information processing method according to (11), wherein, when it is determined in the determination step that two or more peaks exist, the obstacle determination determines that the transparent object exists in the irradiation direction in which it is determined that two or more peaks exist.

[0122] (13) The information processing method according to (11), wherein the first distance value and the illumination direction from the own device corresponding to the first distance value are generated as second point cloud data, and when the transparent object exists, the distance value to the transparent object is included in the second point cloud data.

[0123] (14) The information processing method according to (13), wherein the second distance value and the illumination direction from the own device corresponding to the second distance value are generated as first point cloud data, and when the transparent object is present, a distance value to a subject that is farther away than the transparent object is included in the first point cloud data.

[0124] (15) The information processing method according to (10), wherein, when it is determined in the determination step that two or more peaks exist, the light emission in the irradiation direction in which it is determined in the measurement step that two or more peaks exist is performed again with a different light emission intensity.

[0125] (16) An information processing device comprising: a time measurement unit that generates values ​​relating to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a histogram generation unit that generates a histogram of the measured number of reflected light pulse signals relative to the values ​​relating to the return time; and a signal processing unit that, when two peaks exist in the histogram, determines whether there is an obstacle relative to the device using a distance value based on one of the peaks, and estimates the device's own position relative to the device using a distance value based on the other peak.

[0126] (17) The information processing device according to (16), further comprising a discrimination unit that determines whether or not two or more peaks exist in the histogram, and the obstacle determination and the estimation of the self-position are performed based on the determination of the discrimination unit.

[0127] (18) The information processing device according to (17), wherein the identification unit determines that a transparent object is present when two or more peaks exist in the histogram.

[0128] (19) The information processing device according to (18), wherein, when the identification unit determines that the transparent object exists, the obstacle determination determines that the transparent object exists in an illumination direction in which two or more peaks are determined to exist.

[0129] (20) A program that causes an information processing device to execute the following steps: a measurement step of generating values ​​relating to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a generation step of generating a histogram of the number of measurements of the reflected light pulse signals relative to the values ​​relating to the return time; and a signal processing step of, when two peaks exist in the histogram, determining whether there is an obstacle for the vehicle using a distance value based on one of the peaks, and estimating the vehicle's own position using a distance value based on the other peak.

[0130] The aspects of the present disclosure are not limited to the individual embodiments described above, but include various modifications that may be conceived by those skilled in the art, and the effects of the present disclosure are not limited to the above-described contents. In other words, various additions, modifications, and partial deletions are possible within the scope of the conceptual idea and spirit of the present disclosure, which is derived from the contents defined in the claims and their equivalents.

[0131] 1: Light emitting device, 2: Light receiving device, 3: Information processing device, 4: Operation control device, 5: Mobile device, 6: Subject (object), 31: Time measurement unit (TDC), 32: Histogram generation unit, 33: Signal processing unit, 34: Echo identification unit, 35: Distance generation unit, 36: Self-position estimation unit, 37: Obstacle determination unit, 100: Mobile body.

Claims

1. An information processing method comprising: a measurement step of generating values ​​relating to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals repeatedly emitted at predetermined time intervals; a generation step of generating a histogram of the number of measurements of the reflected light pulse signals relative to the values ​​relating to the return time; and a signal processing step of, when two peaks exist in the histogram, determining whether there is an obstacle for the aircraft using a distance value based on one of the peaks, and estimating the aircraft's own position using a distance value based on the other peak.

2. The information processing method according to claim 1, wherein, in the signal processing step, if two peaks exist in the histogram, the distance value based on the peak on the near side is used for obstacle determination.

3. The information processing method according to claim 2, wherein, in the signal processing step, if two peaks exist in the histogram, the distance value based on the peak on the far side is used to estimate the self-position.

4. The information processing method according to claim 1, wherein in the signal processing step, when three or more peaks exist in the histogram, the distance value based on the peak on the shortest distance side is used for obstacle determination.

5. The information processing method according to claim 4, wherein, in the signal processing step, if three or more peaks exist in the histogram, the distance value based on the farthest peak is used to estimate the self-position.

6. The information processing method according to claim 1, wherein, in the signal processing step, if only one peak exists in the histogram, a distance value based on the peak is used for obstacle determination and self-position estimation.

7. An information processing method as described in claim 1, wherein in the measuring step, the plurality of light emission pulse signals are emitted in a plurality of irradiation directions; in the generating step, the histogram is generated for each of the plurality of irradiation directions; and in the signal processing step, when two peaks exist in the histogram for each of the plurality of irradiation directions, an obstacle is determined using a first distance value based on the peak on the shortest side, and the self-position is estimated using a second distance value based on the peak on the farthest side.

8. The information processing method according to claim 7, wherein the obstacle determination is based on the first distance value and an illumination direction from the own aircraft corresponding to the first distance value.

9. An information processing method according to claim 8, wherein the estimation of the self-position is based on the second distance value and an illumination direction from the own aircraft corresponding to the second distance value.

10. The information processing method according to claim 9, further comprising a determination step of determining whether or not two or more peaks exist in the histogram, and the signal processing step is performed based on the determination in the determination step.

11. The information processing method according to claim 10, wherein said determining step determines that a transparent object is present when two or more peaks exist in said histogram.

12. The information processing method according to claim 11, wherein, if it is determined in the determination step that two or more peaks exist, the obstacle determination determines that the transparent object exists in the irradiation direction in which it is determined that two or more peaks exist.

13. An information processing method as described in claim 11, wherein the first distance value and the illumination direction from the own aircraft corresponding to the first distance value are generated as second point cloud data, and when the transparent object exists, the distance value to the transparent object is included in the second point cloud data.

14. An information processing method as described in claim 13, wherein the second distance value and the illumination direction from the own aircraft corresponding to the second distance value are generated as first point cloud data, and when the transparent object is present, the distance value to a subject farther away than the transparent object is included in the first point cloud data.

15. An information processing method according to claim 10, wherein, if it is determined in the determination step that two or more peaks exist, the emission intensity is changed and light is emitted again in the irradiation direction in which it was determined in the measurement step that two or more peaks exist.

16. An information processing device comprising: a time measurement unit that generates values ​​related to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a histogram generation unit that generates a histogram of the measured number of reflected light pulse signals relative to the values ​​related to the return time; and a signal processing unit that, when two peaks exist in the histogram, determines whether there is an obstacle relative to the device using a distance value based on one of the peaks, and estimates the device's own position relative to the device using a distance value based on the other peak.

17. An information processing device according to claim 16, further comprising an identification unit that determines whether or not two or more peaks exist in the histogram, and the obstacle determination and the estimation of the self-position are performed based on the determination of the identification unit.

18. The information processing device according to claim 17, wherein the identification unit determines that a transparent object is present when two or more peaks exist in the histogram.

19. The information processing device according to claim 18, wherein, when the identification unit determines that the transparent object exists, the obstacle determination determines that the transparent object exists in an illumination direction in which two or more peaks are determined to exist.

20. A program that causes an information processing device to execute the following steps: a measurement step of generating values ​​related to the return time of reflected light pulse signals corresponding to a plurality of light emission pulse signals that are repeatedly emitted at predetermined time intervals; a generation step of generating a histogram of the number of measurements of the reflected light pulse signals relative to the values ​​related to the return time; and a signal processing step of, when two peaks exist in the histogram, determining whether there is an obstacle for the aircraft using a distance value based on one of the peaks, and estimating the aircraft's own position using a distance value based on the other peak.

Images