JP2022135351A - Information processor, method for processing information, program, and storage medium - Google Patents

Abstract

To accurately calculate the distance of a stationary object by a method that fits the condition at the time of a measurement.SOLUTION: In an information processor, acquisition means receives reflected light of emitted light and acquires measurement data including a measurement distance of an object for each measurement point, bin width determination means determines the bin width of a histogram on the basis of the measurement data, histogram creation means creates a histogram of the measurement distance of the object for each measurement point by using the determined bin width, and distance estimation means estimates the distance to the stationary object at each measurement point on the basis of the histogram.SELECTED DRAWING: Figure 7

Description

TECHNICAL FIELD The present invention relates to a technology for acquiring surrounding information.

Conventionally, the measurement object is irradiated with light and the reflected light from the measurement object is detected, and measurement is performed by measuring the time difference between the timing of irradiating the measurement object with light and the timing of detecting the reflected light from the measurement object. A distance measuring device that calculates the distance to an object is known. Japanese Patent Application Laid-Open No. 2002-201001 discloses a forward vehicle recognition device that detects the distance and inclination of a forward vehicle by changing a lighting pattern for projecting a light projection pattern according to the detection state of the light projection pattern.

JP 2008-082750 A

A background map can be created using a ranging device such as that described above. A background map is a map that indicates the distance of a stationary object. Specifically, a distance measuring device is fixedly installed at a predetermined place such as the side of a road, and the distance to a stationary object within the measurement range is measured over a predetermined period of time. For each measurement point, the distance to the stationary object corresponding to that measurement point is calculated, and a background map showing the distance to the stationary object for each measurement point is created. By using measurement data over a predetermined period of time, even if a moving object such as a vehicle or a person enters the measurement range, it is possible to exclude the moving object and create a distance map of the stationary object.

Measurement data of a distance measuring device such as a lidar includes an error, and this error has the characteristic of changing according to the measurement conditions of the distance measuring device. Therefore, it is necessary to calculate the distance to the stationary object by a method suitable for the measurement conditions.

Examples of the problems to be solved by the present invention include the above. A main object of the present invention is to calculate the distance of a stationary object with high accuracy by a method suitable for measurement conditions.

A claimed invention is an information processing apparatus comprising an acquisition means for receiving reflected light corresponding to emitted light and acquiring measurement data including a measured distance of an object for each measurement point; bin width determination means for determining the bin width of the histogram; histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width; and based on the histogram, each measurement point distance estimating means for estimating the distance of a stationary object in

According to another aspect of the invention, there is provided an information processing method executed by an information processing apparatus, which receives reflected light corresponding to emitted light, and acquires measurement data including the measured distance of an object for each measurement point. an acquisition step, a bin width determination step of determining the bin width of the histogram based on the measurement data, and a histogram creation step of creating a histogram of the measured distance of the object for each measurement point using the determined bin width. and a distance estimation step of estimating the distance of the stationary object at each measurement point based on the histogram.

According to another aspect of the present invention, there is provided a program comprising: acquisition means for receiving reflected light corresponding to emitted light and acquiring measurement data including a measured distance of an object for each measurement point; bin width determination means for determining the bin width of the histogram; histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width; and based on the histogram, each measurement point The computer functions as distance estimating means for estimating the distance of a stationary object in .

1 shows an apparatus configuration for creating a background map; Here is an example of a background map. 2 is a block diagram showing a schematic configuration of a lidar; FIG. An example of a histogram of measured distances is shown. 3 is a block diagram showing the hardware configuration of the background map creation device; FIG. 2 is a block diagram showing the functional configuration of a background map creation device; FIG. 9 is a flowchart of background map creation processing;

In a preferred embodiment of the present invention, an information processing apparatus includes an acquisition unit that receives reflected light corresponding to emitted light and acquires measurement data including a measured distance of an object for each measurement point, and based on the measurement data: , bin width determination means for determining the bin width of the histogram, histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width, and based on the histogram, at each measurement point distance estimating means for estimating the distance of a stationary object.

In the above information processing apparatus, the acquisition means receives reflected light corresponding to the emitted light, and acquires measurement data including the measured distance of the object for each measurement point. The bin width determining means determines the bin width of the histogram based on the measurement data. The histogram creation means creates a histogram of the measured distances of the object for each measurement point using the determined bin widths. The distance estimation means estimates the distance of the stationary object at each measurement point based on the histogram. As a result, the distance of a stationary object can be accurately estimated using a histogram of bin widths according to the measurement conditions of the object.

In one aspect of the information processing apparatus, the bin width determining means determines the bin width for each measurement point based on the measured distance of the object. In this aspect, the bin width is determined using the measured distance of the object as the measurement condition.

In another aspect of the information processing apparatus, the measurement data includes the reflection intensity of an object, and the bin width determining means determines the bin width for each measurement point based on the reflection intensity. In this aspect, the bin width is determined using the reflection intensity of the object as the measurement condition.

In another aspect of the information processing apparatus, the measurement data includes the reflectance of an object, and the bin width determination means determines the bin width for each measurement point based on the reflectance. In this aspect, the bin width is determined using the reflectance of the object as a measurement condition.

In another aspect of the information processing apparatus, the measurement data includes the amount of received external light, and the bin width determining means determines the bin width for each measurement point based on the amount of received external light. decide. In this aspect, the bin width is determined using the amount of reflected light received as the measurement condition.

Another aspect of the above information processing apparatus includes map creation means for creating a background map corresponding to a plurality of measurement points based on the distance of the stationary object estimated at each measurement point. In this aspect, a background map is created using the estimated distances of stationary objects.

In another embodiment of the present invention, an information processing method executed by an information processing apparatus includes an acquisition step of receiving reflected light corresponding to emitted light and acquiring measurement data including a measured distance of an object for each measurement point. a bin width determination step of determining a bin width of the histogram based on the measurement data; a histogram creation step of creating a histogram of the measured distance of the object for each measurement point using the determined bin width; and a distance estimation step of estimating the distance of the stationary object at each measurement point based on. As a result, the distance of a stationary object can be accurately estimated using a histogram of bin widths according to the measurement conditions of the object.

In another embodiment of the present invention, a program includes an acquisition means for receiving reflected light corresponding to emitted light and acquiring measurement data including a measured distance of an object for each measurement point, and a histogram based on the measurement data. Bin width determination means for determining the bin width of , histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width, and stationary object at each measurement point based on the histogram The computer functions as distance estimating means for estimating the distance of . By executing this program on a computer, the above information processing apparatus can be realized. This program can be handled by being stored in a storage medium.

Preferred embodiments of the present invention will be described below with reference to the drawings.
[overall structure]
FIG. 1 shows an apparatus configuration for creating a background map. In this embodiment, the background map is created using the lidar 100 and the background map creation device 200 . The rider 100 generates measurement data D<b>1 for each of a plurality of measurement points, and outputs the measurement data D<b>1 to the background map creation device 200 . The background map creation device 200 creates a background map corresponding to the measurement range of the rider 100 using the measurement data D1 input from the rider 100 .

As described above, the background map is a map that indicates the distance of a stationary object within the measurement range of the lidar 100 . FIG. 2 shows an example of a background map. FIG. 2(A) shows an image 40 captured by a camera fixedly installed at a certain point on the side of the road. An image 40 shows a one-lane road, and in addition to the road, left and right fences 41 and 42 and a traffic light 43 are shown.

FIG. 2(B) shows an example of a background map created for the same range as the image 40 of FIG. 2(A). The background map 45 indicates the distance of a stationary object for each measurement point by the lidar 100 in grayscale brightness. In the example of FIG. 2B, the closer the distance to the stationary object is, the brighter the measurement point is, and the longer the distance to the stationary object is, the darker the measurement point is. In the example of FIG. 2B, the area of the traffic light 43 is shown with brightness corresponding to the distance of the traffic light 43 . In addition, the fences 41 and 42 and the ground area are basically indicated by a gradation that changes from light color to dark color from the front area to the back area. Specifically, since the road near the installation position of the rider 100 is measured as a stationary object at the measurement points on the near side, the lower area of the background map 45 is shown in a bright color. On the other hand, since the distant road and sky are measured as stationary objects at the measurement points on the far side, the upper area of the background map 45 is shown in a dark color.

[Rider configuration]
FIG. 3 is a block diagram showing a schematic configuration of the lidar 100. As shown in FIG. In this embodiment, the rider 100 is fixedly installed on the side of a road or the like. The lidar 100 irradiates laser light (also referred to as “irradiation light”) to a predetermined angle range in the horizontal and vertical directions, and emits light (also referred to as “reflected light”) returned by the irradiation light reflected by an object. ) is received, the distance from the lidar 100 to the object is discretely measured, and point cloud information indicating the three-dimensional position of the object is generated. The lidar 100 is installed so that the area for which the background map is to be created is included in the measurement range.

As shown in FIG. 3 , the lidar 100 mainly has a transmitter 1 , a receiver 2 , a beam splitter 3 , a scanner 5 , a piezo sensor 6 , a controller 7 and a memory 8 .

The transmitter 1 is a light source that emits pulsed irradiation light toward the beam splitter 3 . The transmitter 1 includes, for example, an infrared laser emitting element. The transmission unit 1 is driven based on the driving signal Sg1 supplied from the control unit 7. FIG.

The receiver 2 is, for example, an avalanche photodiode, generates a detection signal Sg2 corresponding to the amount of received light, and supplies the generated detection signal Sg2 to the controller 7 .

The beam splitter 3 transmits the pulsed irradiation light emitted from the transmitter 1 . The beam splitter 3 also reflects the reflected light incident through the scanner 5 toward the receiver 2 .

The scanner 5 is, for example, an electrostatically driven mirror (MEMS mirror), and its tilt (that is, the optical scanning angle) changes within a predetermined range based on the drive signal Sg3 supplied from the controller 7 . The scanner 5 reflects the irradiation light transmitted through the beam splitter 3 toward the outside of the lidar 100 , and emits the reflected light incident from the outside of the lidar 100 toward the beam splitter 3 . A point irradiated with irradiation light within the measurement range of the lidar 100 is also called a “measurement point”.

The scanner 5 is provided with a piezo sensor 6 . The piezo sensor 6 detects strain caused by the stress of the torsion bar that supports the mirror portion of the scanner 5 . The piezo sensor 6 supplies the generated detection signal Sg4 to the controller 7 . The detection signal Sg4 is used for detecting the orientation of the scanner 5. FIG.

The memory 8 is composed of various volatile and nonvolatile memories such as RAM (Random Access Memory), ROM (Read Only Memory), and flash memory. The memory 8 stores programs necessary for the control unit 7 to execute predetermined processing. The memory 8 also stores various parameters referred to by the control unit 7 . The memory 8 stores the latest point group information for a predetermined number of frames generated by the control unit 7 .

The control unit 7 includes various processors such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The control unit 7 executes a predetermined process by executing a program stored in the memory 8 . Note that the control unit 7 is not limited to being realized by software programs, and may be realized by any combination of hardware, firmware, and software. Further, the control unit 7 may be a user-programmable integrated circuit such as FPGA (field-programmable gate array) or microcontroller, ASSP (Application Specific Standard Produce), ASIC (Application Specific Integrated Circuit), etc. may be

The control unit 7 functionally includes a transmission drive block 70 , a scanner drive block 71 , a point cloud information generation block 72 and a point cloud information processing block 73 .

The transmission drive block 70 outputs a drive signal Sg1 for driving the transmission section 1. FIG. The drive signal Sg1 includes information for controlling the light emission time of the laser light emitting element included in the transmitter 1 and the light emission intensity of the laser light emitting element. The transmission drive block 70 controls the emission intensity of the laser light emitting element included in the transmission section 1 using the drive signal Sg1.

A scanner drive block 71 outputs a drive signal Sg3 for driving the scanner 5 . The drive signal Sg3 includes a horizontal drive signal corresponding to the resonance frequency of the scanner 5 and a vertical drive signal for vertical scanning. Further, the scanner drive block 71 monitors the detection signal Sg4 output from the piezo sensor 6 to detect the scanning angle of the scanner 5 (that is, the emission direction of the irradiation light).

Based on the detection signal Sg2 supplied from the receiving unit 2, the point cloud information generation block 72 generates point cloud information indicating the distance and direction to the object irradiated with the irradiation light for each measurement point, with the lidar 100 as a reference point. to generate In this case, the point cloud information generation block 72 calculates the time from when the irradiation light is emitted until the receiving unit 2 detects the reflected light as the time of flight of the light. Light received by the receiver 2 other than the reflected light of the irradiation light from the object is called external light. For example, after irradiation with irradiation light, the receiving unit 2 detects the light as reflected light at the time when the amount of received light reaches a peak. Here, the light received by the receiver 2 other than the peak (other than the light forming the peak) is external light.

Then, the point cloud information generation block 72 generates point cloud information indicating the distance corresponding to the calculated flight time and the irradiation direction of the irradiation light corresponding to the reflected light received by the reception unit 2 for each measurement point, The generated point cloud information is supplied to the point cloud information processing block 73 . Hereinafter, the point group information obtained by scanning all the measurement points once will be referred to as point group information for one frame. Point cloud information is an example of measurement data.

Here, the point group information can be regarded as an image in which the measurement points are pixels and the distance indicated by each measurement point is the pixel value. The point group information includes reflection intensity information for each measurement point. The point group information may also include the amount of external light received (average value/variance value) for each measurement point.

The point cloud information processing block 73 generates measurement data D1 for each measurement point in the measurement range (scanning range) of the rider 100 based on the point cloud information supplied from the point cloud information generation block 72, and outputs the data to the outside. The measurement data D1 includes, for each measurement point included in the measurement range of the lidar, the distance to the measured object (hereinafter also referred to as "measurement distance"), the reflection intensity, the received amount of reflected light, and the like. The measurement data D1 is output to the background map creation device 200. FIG.

[Background map creation device]
(Explanation of principle)
First, the principle of creating a background map will be explained. The background map creation device 200 estimates the distance of a stationary object at each measurement point based on the measurement data D1 obtained by the lidar 100 and creates a background map. At this time, the background map creation device 200 creates a histogram of distances measured by the rider 100 for each measurement point to estimate the distance of each measurement point.

FIG. 4A shows an example of a histogram of measured distances obtained at a certain measurement point X. FIG. At this measurement point X, it is assumed that there is a stationary object at a position about 15 m from the position where the lidar 100 is installed. Rider 100 acquires a plurality of (N) pieces of measurement data for each measurement point by performing measurement for a predetermined period of time. FIG. 4A is a histogram of N measurement distances included in N measurement data obtained at a certain measurement point X. FIG. Note that the bin width of the histogram in FIG. 4A is 0.1 m. Since there is an error in the measurement by the rider 100, the N measured distances contain some errors. The distance is estimated to be the distance of a stationary object at that measurement point X. As a result, even if the measured distance obtained at each measurement point contains some error, the distance to the stationary object at that measurement point can be correctly estimated.

However, the presence or absence and magnitude of errors in the distance measured by the rider 100 change according to the measurement conditions of the rider 100 . Specifically, the measurement error varies depending on the distance to the object, the reflectance of the object, the ambient environment such as the amount of external light, and the like. Since the lidar 100 performs measurement by receiving the reflected light of the irradiation light reflected by the object, the error increases as the distance to the object increases. Also, the smaller the reflectance of the object, the larger the error. Furthermore, as the surrounding environment, the error is small in an environment such as nighttime with little outside light (background light), but the error becomes large in an environment with much outside light such as daytime. Therefore, when a histogram with a constant bin width is used, if the error increases due to changes in the measurement conditions as described above, there is a problem that the distance to the stationary object cannot be accurately estimated.

Let us elaborate on this issue. FIG. 4B shows an example of a histogram of measured distances obtained at a certain measurement point Y. FIG. FIG. 4B is a histogram of N measurement distances included in N measurement data obtained at a certain measurement point Y. In FIG. At the measurement point Y, it is assumed that there is a stationary object in the vicinity of 30 m from the installation position of the rider 100 . Note that the bin width of the histogram in FIG. 4B is 0.1 m as in FIG. 4A. As can be seen from a comparison with FIG. 4A, at measurement point Y, as the distance from rider 100 increases, the error (variation) in the distance measured by the rider increases. For this reason, if a histogram is created at measurement point Y with the same bin width of 0.1 m as at measurement point X, each measurement distance will be dispersed over multiple bins, making it impossible to find a peak with a sufficiently large frequency. , unable to get an accurate distance estimate.

Therefore, in this embodiment, the bin width of the histogram is changed according to the measurement conditions of the lidar 100 . That is, under conditions where the error in the distance measured by the rider is large, the bin width of the histogram is made larger than under conditions where the error is small. FIG. 4C is a histogram of the N measurement distances obtained at the measurement point Y with a bin width of 1 m. As can be seen from a comparison with FIG. 4B, even when the same N measurement distances are used, a clear peak appears in the histogram by increasing the bin width. In this way, even if the error in the measured distance changes due to the measurement conditions, it is possible to correctly estimate the distance to the stationary object. Specifically, the background map creation device 200 changes the bin width for each measurement condition as follows.

(A) Distance from Lidar The measurement error of the lidar is smaller as the distance from the lidar to the object is shorter, and larger as the distance is longer. Therefore, the background map creation device 200 reduces the bin width as the measurement points are closer, and increases the bin width as the measurement points are farther. For example, the background map creation device 200 may calculate the average value of N measured distances at each measurement point, and the smaller the average value, the smaller the bin width, and the larger the average value, the larger the bin width.

(B) Reflection intensity The measurement error of the lidar is smaller when the reflection intensity of the object is higher, and is larger when the reflection intensity is lower. Therefore, the background map creation device 200 reduces the bin width as the reflection intensity at the measurement point increases, and increases the bin width as the reflection intensity decreases. For example, the background map creation device 200 may calculate the average value of N reflection intensities at each measurement point, and the larger the average value, the smaller the bin width, and the smaller the average value, the smaller the bin width. With this method, the bin width is changed according to the reflection intensity of the object itself. Therefore, even if the object at the measurement point is close to the lidar, the bin width is set large when the reflection intensity of the object is small. Also, even if the object at the measurement point is far from the lidar, the bin width is set small if the reflection intensity of the object is high.

Note that the bin width may be determined using both the distance from the lidar and the reflection intensity of the object. For example, when the distance from the lidar at a certain measurement point is "x", the distance coefficient is "a", the reflection intensity at the measurement point is "y", and the reflection intensity coefficient is "b", the bin width W is You can also ask for:
W = ax + by

(C) Amount of outside light (background light) In an environment with little outside light (background light), such as at night, the average and variance of the amount of outside light received becomes small. The average and variance of the amount of light received by Therefore, the intensity of outside light and the magnitude of the error can be estimated from the average and variance of the received amount of outside light. Therefore, the background map creation device 200 reduces the bin width as the average and variance of the outside light are smaller, and increases the bin width as the average and variance of the outside light is larger. For example, the background map creation device 200 calculates the average value and variance value of the N received light amounts at each measurement point, and the smaller the average value, the smaller the bin width, and the larger the average value, the larger the bin width, The smaller the variance value, the smaller the bin width, and the larger the variance value, the larger the bin width. Only one of the average value and the variance value may be used instead of both. Also, the control of the bin width based on the received amount of reflected light may be combined with the control of the bin width based on one or both of (A) the distance from the lidar and (B) the reflection intensity of the object.

(Hardware configuration)
FIG. 5 is a block diagram showing the hardware configuration of the background map creation device 200. As shown in FIG. The background map creation device 200 includes a communication section 201 , a control section 202 , a memory 203 , an input section 204 and a display section 205 .

A communication unit 201 communicates with an external device by wire or wirelessly. Specifically, the communication unit 201 receives measurement data D1 from the rider 100 .

The control unit 202 includes, for example, various processors such as CPU and GPU. The control unit 7 executes a predetermined process by executing a program stored in the memory 8 . The control unit 7 is an example of a computer that executes programs. Note that the control unit 7 is not limited to being realized by software programs, and may be realized by any combination of hardware, firmware, and software.

The memory 203 is composed of various volatile memories and nonvolatile memories such as RAM, ROM, and flash memory. The memory 203 stores various parameters referred to by the control unit 202 . The memory 203 also stores the measurement data D1 received from the rider. Furthermore, the memory 203 stores programs necessary for the control unit 7 to execute predetermined processing. In this case, the memory 203 may include a disk-shaped storage medium storing programs.

The input unit 204 is used by the operator to make necessary settings and instructions. The display unit 205 is, for example, a liquid crystal display, and is used to display a background map as illustrated in FIG. 2B as necessary.

(Functional configuration)
FIG. 6 is a block diagram showing the functional configuration of the background map creation device 200. As shown in FIG. The background map creation device 200 functionally includes a bin width determination unit 211 , a histogram creation unit 212 , a distance estimation unit 213 , and a map creation unit 214 .

The measurement data D1 output from the rider 100 is input to the bin width determination section 211 and the histogram creation section 212 . The bin width determination unit 211 determines the bin width of the histogram for each measurement point of the measurement data D1. Specifically, as described above, the bin width determining unit 211 determines the bin width of the histogram based on one or more of the distance from the lidar, the reflection intensity, and the amount of external light (background light) received. decide. Bin width determination section 211 outputs the determined bin widths to histogram creation section 212 .

The histogram creation unit 212 creates a histogram of measured distances for each measurement point of the measurement data D1. At this time, the histogram creation unit 212 creates a histogram having the bin width determined by the bin width determination unit 211 . Then, histogram creating section 212 outputs the created histogram to distance estimating section 213 .

The distance estimation unit 213 estimates the distance of the stationary object based on the histogram for each measurement point. Specifically, the distance estimation unit 213 estimates the measured distance corresponding to the peak of the frequency in the histogram created by the histogram creation unit 212 as the distance of the stationary object at that measurement point. Distance estimation section 213 outputs the distance estimated for each measurement point to map generation section 214 .

The map creating unit 214 creates a background map based on the distance for each measurement point estimated by the distance estimating unit 213 . Specifically, the map creating unit 214 creates, as a background map, a map in which each measurement point belonging to the measurement range (scanning range) of the lidar 100 is associated with the distance of the stationary object estimated for that measurement point. do. The background map is an image in which each measurement point is associated with one pixel, and the distance of a stationary object at each measurement point is associated with the brightness or color of the pixel, as illustrated in FIG. 2B, for example. can be displayed.

(background map creation process)
FIG. 7 is a flowchart of background map creation processing. This processing is realized by executing a program prepared in advance by the control unit 202 shown in FIG. 5 and operating as each element shown in FIG.

First, the control unit 202 acquires measurement data D1 of one measurement point acquired from the rider 100 (step S11). Next, the bin width determination unit 211 determines the bin width of the histogram for that measurement point based on the measurement data of that measurement point (step S12). Specifically, as described above, the bin width determining unit 211 determines the bin width of the histogram based on one or more combinations of the distance from the lidar, the reflection intensity, and the amount of external light (background light) received. Determine width.

Next, the histogram creation unit 212 creates a histogram of the bin widths determined in step S12 using the measurement data of the measurement points (step S13). Next, the distance estimation unit 213 estimates the distance corresponding to the peak of the frequency in the created histogram as the distance of the stationary object at the measurement point (step S14). Thus, the distance to the stationary object is obtained for one measurement point selected in step S11.

Next, the control unit 202 determines whether or not the processing is completed for the measurement data D1 of all the measurement points acquired from the rider 100 (step S15). If the processing has not been completed for all measurement points (step S15: No), the control unit 202 returns to step S11, acquires measurement data D1 of another measurement point, and performs the processing of steps S12 to S14. Run. In this way, steps S11 to S14 are repeated until the distance to the stationary object is estimated for the measurement data D1 of all the measurement points acquired from the rider 100. FIG. When the distances to the stationary object are estimated for all measurement points (step S15: Yes), the map creation unit 214 creates a background map using the distances for all measurement points (step S16). Then the process ends.

[Modification]
Although the lidar 100 described above outputs the reflection intensity of the object as measurement data, there is also known a type of lidar that calculates and outputs the reflectance of the object instead of the reflection intensity of the object. For example, the Velodyne lidar estimates the reflectance of an object based on the intensity of the reflected light and the distance of the object, and outputs a reflectance value. This embodiment can also be applied to such type of lidar. In this case, the measurement error of the lidar is considered to decrease as the reflectance of the object increases and increase as the reflectance of the object decreases. Therefore, the bin width determining unit 211 calculates the average value of the reflectance values of the target measurement points, and decreases the bin width as the reflectance increases, and increases the bin width as the reflectance decreases. .

Although the present invention has been described with reference to the embodiments, the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. That is, the present invention naturally includes various variations and modifications that a person skilled in the art can make according to the entire disclosure including the scope of claims and technical ideas. In addition, the disclosures of the cited patent documents and the like are incorporated herein by reference.

1 transmitter 2 receiver 3 beam splitter 5 scanner 6 piezo sensor 7 controller 8 memory 100 lidar 200 background map generator 202 controller 211 bin width determiner 212 histogram generator 213 distance estimator 214 map generator

Claims (9)

Acquisition means for receiving reflected light corresponding to the emitted light and acquiring measurement data including the measured distance of the object for each measurement point;
Bin width determination means for determining the bin width of the histogram based on the measurement data;
histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width;
distance estimation means for estimating the distance of a stationary object at each measurement point based on the histogram;
Information processing device. 2. The information processing apparatus according to claim 1, wherein said bin width determining means determines said bin width for each measurement point based on the measured distance of said object. The measurement data includes the reflection intensity of the object,
3. The information processing apparatus according to claim 1, wherein said bin width determining means determines said bin width for each measurement point based on said reflection intensity. The measurement data includes the reflectance of the object,
2. The information processing apparatus according to claim 1, wherein said bin width determination means determines said bin width for each measurement point based on said reflectance. The measurement data includes the amount of external light received,
5. The information processing apparatus according to any one of claims 1 to 4, wherein the bin width determination means determines the bin width for each measurement point based on the received amount of the external light. 6. The information processing apparatus according to any one of claims 1 to 5, further comprising map creation means for creating a background map corresponding to a plurality of measurement points based on the distance of the stationary object estimated at each measurement point. An information processing method executed by an information processing device,
an acquisition step of receiving reflected light corresponding to the emitted light and acquiring measurement data including the measured distance of the object for each measurement point;
A bin width determination step of determining the bin width of the histogram based on the measurement data;
A histogram creation step of creating a histogram of the measured distance of the object for each measurement point using the determined bin width;
a distance estimation step of estimating the distance of a stationary object at each measurement point based on the histogram;
An information processing method comprising: Acquisition means for receiving reflected light corresponding to the emitted light and acquiring measurement data including the measured distance of the object for each measurement point;
Bin width determination means for determining the bin width of the histogram based on the measurement data;
histogram creation means for creating a histogram of the measured distance of the object for each measurement point using the determined bin width;
Distance estimating means for estimating the distance of a stationary object at each measurement point based on the histogram;
A program that makes a computer function as a A storage medium storing the program according to claim 8 .

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