Information acquisition device, information acquisition method, and program

Abstract

To provide a technology with which information on an object can be optically obtained.SOLUTION: An information obtaining device according to an embodiment includes an irradiating unit, a light receiving unit, an obtaining unit, and a generation unit. The irradiating unit emits light. The light receiving unit receives the light which bounces back off an object. The obtaining unit obtains multiple distance indices based on time differences between the emissions and the receptions of the light. The generation unit generates distance information regarding the distance to the object according to the frequency distribution of the multiple distance indices or statistics calculated from the frequency distribution.SELECTED DRAWING: Figure 6

Description

Technical Field

[0001] Embodiments of the present invention relate to an information acquisition device, an information acquisition method, and a program.

Background Art

[0002] Techniques for optically obtaining information about an object, such as the distance to the object, have been researched and developed.

[0003] For example, with the development of automatic driving and production automation in factories, the use of ranging sensors for distance measurement to recognize people and objects has been expanding. Distance measurement techniques are roughly classified into two types: passive imaging that performs distance measurement based on the features of an RGB image, and active imaging that performs distance measurement based on the response characteristics to light such as laser light. Active imaging is being put into practical use because it enables robust measurement against ambient light. Among them, ranging sensors that perform distance measurement based on the time-of-flight (ToF) of light have attracted attention in recent years because they are excellent in terms of measurement time and distance measurement range. In ranging sensors based on the time-of-flight of light, a ranging sensor for short distances is called an LRF (Laser Range Finder), and a ranging sensor for long distances is called a LiDAR (Light Detection and Ranging).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The problem to be solved by the present invention is to provide a technique capable of optically obtaining information about an object.

Means for Solving the Problems

[0006] An information acquisition device according to an embodiment includes an irradiation unit, a light reception unit, an acquisition unit, and a generation unit. The irradiation unit irradiates light. The light reception unit receives the light reflected by an object. The acquisition unit acquires a plurality of distance indicators based on a time difference between the irradiation and reception of the light. The generation unit generates distance information regarding the distance to the object based on a frequency distribution of the plurality of acquired distance indicators or a statistic calculated from the frequency distribution.

Brief Description of the Drawings

[0007]

Figure 1

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Embodiments for Carrying Out the Invention

[0008] Hereinafter, embodiments will be described with reference to the drawings. The embodiments relate to an information acquisition device that obtains object information, which is information about an object based on the time of flight (ToF) of light. In one embodiment, the object information includes at least one of distance information regarding the distance to the object and attribute information indicating the attributes of the object.

[0009] First, with reference to FIGS. 1 to 4, optical distance measurement for measuring distance based on the time of flight of light will be described. In distance measurement, a distance measurement sensor 101 including a laser 102 and a photodetector 103 as shown in FIG. 1 can be used. In distance measurement, a light pulse from the laser 102 is irradiated onto the object 105, the light pulse reflected by the object 105 is received by the photodetector 103, and the distance between the distance measurement sensor 101 and the object 105 is calculated from the time difference between the irradiation time of the light pulse and the reception time of the reflected light pulse according to the following formula (1). d = tc / 2 ···(1) Here, d is the distance between the distance measurement sensor 101 and the object 105, t is the time difference between the irradiation time and the reception time, and c is the speed of light.

[0010] As shown in FIG. 2, the laser 102 irradiates a rectangular light pulse with a time width of several nanoseconds. The light pulse deforms when reflected by the object 105. A method of calculating the time difference by treating the time when photons are first detected by the photodetector 103 as the reception time is generally used. Since the detection of photons is a probabilistic process following the shape (distribution) of the reflected light, the reception time varies by the width of the distribution, resulting in variation in the measured distance (repetition error). There are also methods of setting the time when photons with a light amount exceeding a threshold are detected as the reception time, or the time when two or more photons are detected and the cumulative light amount or average light amount exceeds the threshold as the reception time. However, in all cases, the measured distance varies for the same reason. There is also a method of calculating the time difference after obtaining the shape of the reflected light, but the circuit logic becomes complicated.

[0011] The shape of the reflected light depends on the attributes of the object, such as the material and color. Therefore, even when the actual distance from the distance measuring sensor to the object is the same, a deviation (bias error) in the measured distance occurs for each object.

[0012] Figure 3 schematically shows the bias error for each object. In Figure 3, the horizontal axis represents the actual distance, and the vertical axis represents the bias error. The bias error represents the value obtained by subtracting the actual distance from the measured distance. As shown in Figure 3, when the actual distance is about 1 m, a bias error of ± several centimeters occurs. Plastic A, Plastic B, and Plastic C are different types of plastics, and the bias error is about 2 cm. The bias error of the black paper is about 2 cm, while the bias errors of the yellow, brown, and red papers are relatively small.

[0013] The repeat error can be reduced by averaging the measurement results of multiple times. However, since the bias error corresponds to the deviation of the average distance, it cannot be dealt with by averaging.

[0014] Figure 4 schematically shows the histogram of the measured distance obtained by the above-described optical distance measurement. In each graph of Figure 4, the horizontal axis represents the measured distance, the vertical axis represents the frequency (number of occurrences), and the dashed line represents the actual distance. The measured distance is obtained by the distance measuring sensor 101 with the object placed at a distance equal to the actual distance from the distance measuring sensor 101. As shown in Figure 4, the frequency distribution of the measured distance depends on the attributes of the object. Specifically, the relationship between the frequency distribution of the measured distance and the actual distance depends on the attributes of the object.

[0015] The optical distance measurement according to an embodiment irradiates light pulses one after another, obtains the time difference for each of the light pulses, calculates the distance from the time difference according to the above formula (1), and obtains the measured distance based on the frequency distribution of the calculated distance and the information indicating the relationship between the frequency distribution prepared in advance and the distance. As a result, it becomes possible to reduce the bias error. As a result, more accurate distance measurement becomes possible.

[0016] FIG. 5 schematically shows an example of the hardware configuration of an information acquisition device 500 according to an embodiment. As shown in FIG. 5, the information acquisition device 500 includes an optical sensor 510 and an information processing device 520.

[0017] The optical sensor 510 includes a light source 511 and a photodetector 512. The light source 511 generates and irradiates optical pulses. For example, a pulsed laser diode can be used as the light source 511. The photodetector 512 detects the optical pulses irradiated by the light source 511 and reflected by the object. For example, a photodiode can be used as the photodetector 512.

[0018] The information processing device 520 includes a processor 521, a RAM (Random Access Memory) 522, an auxiliary storage device 523, a program memory 524, an input / output interface 525, and a bus 526. The processor 521 is connected to the RAM 522, the auxiliary storage device 523, the program memory 524, and the input / output interface 525 via the bus 526, and exchanges signals with these components.

[0019] The processor 521 includes a general-purpose circuit such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The RAM 522 is used by the processor 521 as a working memory. The RAM 522 includes a volatile memory such as SDRAM (Synchronous Dynamic RAM). The auxiliary storage device 523 stores data. The auxiliary storage device 523 includes a non-volatile memory such as a flash memory. The program memory 524 stores programs executed by the processor 521 such as an information acquisition program. Each program includes computer-executable instructions. The program memory 524 may be a ROM (Read Only Memory). Alternatively, a part of the auxiliary storage device 523 may be used as the program memory 524.

[0020] The processor 521 expands the program stored in the program memory 524 to the RAM 522 and interprets and executes the program. When the information acquisition program is executed by the processor 521, it causes the processor 521 to perform the processes described later in each of the first to third embodiments.

[0021] The program may be provided to the information processing apparatus 520 in a state stored in a computer-readable recording medium. In this case, the information processing apparatus 520 includes a drive for reading data from the recording medium and acquires the program from the recording medium. Examples of the recording medium include magnetic disks, optical disks (such as CD-ROM, CD-R, DVD-ROM, DVD-R), magneto-optical disks (such as MO), and semiconductor memories. Also, the program may be distributed through a network. Specifically, the program may be stored in a server on the network and the information processing apparatus 520 may download the program from the server.

[0022] The input / output interface 525 includes an interface for connecting the optical sensor 510. The processor 521 communicates with the optical sensor 510 via the input / output interface 525. The processor 521 transmits a control signal to the optical sensor 510 via the input / output interface 525, and the optical sensor 510 operates according to the control signal from the processor 521. The processor 521 receives, via the input / output interface 525, from the optical sensor 510 a time difference signal indicating the time difference between the irradiation and reception of the light pulse, that is, the difference between the irradiation time of the light pulse and the reception time of the reflected light pulse. The irradiation time indicates the time when the light source 511 irradiates the light pulse, and the reception time indicates the time when the light receiving unit 612 receives the light pulse reflected by the object. Alternatively, the processor 521 may receive, via the input / output interface 525, from the optical sensor 510 time signals indicating the irradiation time of the light pulse and the reception time of the reflected light pulse, and calculate the time difference between the irradiation and reception of the light pulse from the time signals.

[0023] The information processing apparatus 520 may include a dedicated circuit instead of or in addition to a general-purpose circuit. Examples of dedicated circuits include ASICs (Application Specific Integrated Circuits) and FPGAs (Field Programmable Gate Arrays).

[0024] [First Embodiment] In the first embodiment, the object information includes distance information of the object.

[0025] FIG. 6 schematically shows a distance measurement apparatus 600 according to the first embodiment. As shown in FIG. 6, the distance measurement apparatus 600 includes a sensor unit 610 and an information processing unit 620.

[0026] The sensor unit 610 includes an irradiation unit 611 that irradiates an optical pulse, and a light receiving unit 612 that receives the optical pulse irradiated by the irradiation unit 611 and reflected by the object. The irradiation unit 611 is realized by the light source 511 shown in FIG. 5, and the light receiving unit 612 is realized by the photodetector 512 shown in FIG. 5. The sensor unit 610 sends a time difference signal indicating the time difference between the irradiation and reception of the optical pulse to the information processing unit 620. The time difference represents the time from when the irradiation unit 611 irradiates the optical pulse until the light receiving unit 612 receives the optical pulse reflected by the object. The sensor unit 610 irradiates optical pulses one after another, and thereby the information processing unit 620 receives time difference signals for individual optical pulses.

[0027] The information processing unit 620 includes an acquisition unit 621, a distance information generation unit 622, and a storage unit 623. The acquisition unit 621 and the distance information generation unit 622 are realized by the processor 521 shown in FIG. 5, and the storage unit 623 is realized by the auxiliary storage device 523 or the program memory 524 shown in FIG. 5.

[0028] The acquisition unit 621 receives a plurality of time difference signals from the sensor unit 610, and acquires a plurality of distances calculated based on the plurality of time differences indicated by the received plurality of time difference signals. The acquisition unit 621 performs a calculation for calculating the distance from the time difference for each time difference signal. The distance can be calculated, for example, according to the above formula (1).

[0029] The distance information generation unit 622 generates and outputs distance information of the object based on the frequency distribution of the plurality of distances acquired by the acquisition unit 621 or a statistic calculated from the frequency distribution. The distance information indicates the distance to the object. Specifically, the distance information indicates the measurement result of the distance between the object and the distance measurement device 600 (specifically, the sensor unit 610).

[0030] When the distance information generation unit 622 generates distance information based on the frequency distribution, the storage unit 623 may store reference information (for example, a look-up table) associating the plurality of distances with the plurality of frequency distributions. The reference information is generated in advance using an optical sensor of the same type as the optical sensor 510. For example, the reference information is generated by performing, for a plurality of distances, a process of obtaining the frequency distribution of the measurement results by performing distance measurement a plurality of times with the optical sensor in a state where the object is arranged at a specific distance from the optical sensor. The storage unit 623 includes reference information regarding one or more types of objects. As shown in FIG. 4, the frequency distributions of plastic A and plastic B show similar tendencies. Therefore, when the storage unit 623 stores the reference information regarding plastic A, the reference information regarding plastic B may not be stored in the storage unit 623. In other words, it is not necessary to have reference information for all objects that can be measurement targets. Hereinafter, the frequency distribution of the plurality of distances acquired by the acquisition unit 621 is also referred to as the target frequency distribution, and the frequency distribution included in the reference information is also referred to as the reference frequency distribution.

[0031] The distance information generation unit 622 obtains, as distance information, a distance corresponding to the target frequency distribution from the reference information stored in the storage unit 623. Specifically, the distance information generation unit 622 selects at least one reference frequency distribution similar to the target frequency distribution from among the reference frequency distributions, and generates distance information based on at least one distance associated with the selected at least one reference frequency distribution. For example, the distance information generation unit 622 may calculate the similarity between the target frequency distribution and the reference frequency distribution by regression using the k-nearest neighbor method, select the reference frequency distribution with the highest similarity, and obtain the distance associated with the selected reference frequency distribution as the distance information. Also, the distance information generation unit 622 may select a predetermined number of reference frequency distributions in descending order of similarity, and obtain the weighted average of the distances associated with the selected reference frequency distributions as the distance information.

[0032] When the distance information generation unit 622 generates distance information based on a statistic, the storage unit 623 may store reference information associating a plurality of distances with a plurality of statistics. The reference information is generated in advance using an optical sensor of the same type as the optical sensor 510. For example, the reference information is generated by performing, for a plurality of distances, a process of calculating a statistic from the frequency distribution of measurement results by performing distance measurement a plurality of times with an optical sensor in a state where an object is placed at a specific distance from the optical sensor. The storage unit 623 includes reference information regarding one or more types of objects. The statistic includes at least one of an average, a variance, a standard deviation, a median, a minimum value, a maximum value, a mode, a skewness, and a kurtosis. Preferably, the statistic includes at least one of an average, a median, and a mode, and at least one of a variance, a standard deviation, a skewness, and a kurtosis. Hereinafter, the statistic calculated from the target frequency distribution is also referred to as a target statistic, and the statistic included in the reference information is also referred to as a reference statistic.

[0033] The distance information generation unit 622 obtains, as distance information, a distance corresponding to the target statistic from the reference information stored in the storage unit 623. Since the method of obtaining the distance corresponding to the target statistic is the same as the method of obtaining the distance corresponding to the target frequency distribution described above, a detailed description thereof is omitted.

[0034] The distance information generation unit 622 may obtain a correction value based on the target frequency distribution, and generate distance information based on the plurality of distances acquired by the acquisition unit 621 and the obtained correction value. In this case, the storage unit 623 may store reference information associating a plurality of correction values with a plurality of reference frequency distributions. The reference information is generated in advance using an optical sensor of the same type as the optical sensor 510. For example, the reference information is obtained by performing distance measurement a plurality of times with an optical sensor in a state where an object is arranged at a specific distance from the optical sensor to obtain a frequency distribution of measurement results, and performing a process of calculating a correction value based on the specific distance and the measurement results for a plurality of distances. The correction value may be defined as a correction amount. For example, the correction value may be the difference between the representative distance calculated from the measurement results and the specific distance. The representative distance may be any of the average, median, and mode of the frequency distribution of the measurement results. Also, the correction value may be defined as a coefficient. For example, the correction value may be a value obtained by dividing the representative distance by the specific distance or a value obtained by dividing the specific distance by the representative distance.

[0035] The distance information generation unit 622 may obtain a correction value corresponding to the target frequency distribution from the reference information stored in the storage unit 623, and generate distance information based on the plurality of distances acquired by the acquisition unit 621 and the correction value. Since the method of obtaining the correction value corresponding to the target frequency distribution is the same as the method of obtaining the distance corresponding to the target frequency distribution described above, detailed description thereof is omitted. When the correction value is a correction amount, the distance information generation unit 622 generates distance information, for example, by calculating a representative distance from the plurality of distances acquired by the acquisition unit 621 and adding or subtracting the correction value to or from the calculated representative distance. When the correction value is a coefficient, the distance information generation unit 622 generates distance information, for example, by calculating a representative distance from the plurality of distances acquired by the acquisition unit 621 and multiplying the calculated representative distance by the correction value or dividing the representative distance by the correction value.

[0036] The distance information generation unit 622 may obtain a correction value based on the target statistic, and generate distance information based on the plurality of distances acquired by the acquisition unit 621 and the correction value. In this case, the storage unit 623 may store reference information associating a plurality of correction values with a plurality of reference statistics. The reference information is generated in advance using an optical sensor of the same type as the optical sensor 510. For example, the reference information is generated by calculating a statistic from the frequency distribution of measurement results by performing distance measurement a plurality of times with an optical sensor while placing an object at a specific distance from the optical sensor, and calculating a correction value based on the specific distance and the measurement result for a plurality of distances.

[0037] The distance information generation unit 622 may obtain a correction value corresponding to the target statistic from the reference information stored in the storage unit 623, and generate distance information based on the plurality of distances acquired by the acquisition unit 621 and the correction value. Since the method of obtaining the correction value corresponding to the target statistic is the same as the method of obtaining the distance corresponding to the target frequency distribution described above, detailed description thereof is omitted.

[0038] Instead of reference information such as a lookup table, the distance information generation unit 622 may generate distance information using a model obtained by machine learning. In this case, the storage unit 623 stores one or more parameters included in the learned model. As the machine learning algorithm, for example, a neural network, SVM (Support Vector Machine), or random forest can be used.

[0039] The model is configured to output a distance when a frequency distribution is input, and may be learned using, as learning data, reference information associating the plurality of distances and the plurality of frequency distributions described above. The distance information generation unit 622 inputs the target frequency distribution into the learned model, and obtains, as distance information, the distance output from the learned model.

[0040] Alternatively, the model may be configured to output a correction value when a frequency distribution is input, and may be trained using, as learning data, reference information associating the plurality of correction values and the plurality of frequency distributions described above with each other. The distance information generation unit 622 may input the target frequency distribution into the trained model, obtain the correction value output from the trained model, and generate distance information based on the plurality of distances and the correction value obtained by the acquisition unit 621.

[0041] Alternatively, the model may be configured to output a distance when a statistic is input, and may be trained using, as learning data, reference information associating the plurality of distances and the plurality of statistics described above with each other. The distance information generation unit 622 may input the target statistic into the trained model and obtain the distance output from the trained model as the distance information.

[0042] Alternatively, the model may be configured to output a correction value when a statistic is input, and may be trained using, as learning data, reference information associating the plurality of correction values and the plurality of statistics described above with each other. The distance information generation unit 622 may input the target statistic into the trained model, obtain the correction value output from the trained model, and generate distance information based on the plurality of distances and the correction value obtained by the acquisition unit 621.

[0043] Note that the distance information generation unit 622 may generate distance information of the target object based on both the target frequency distribution and the target statistic.

[0044] Next, the operation of the distance measurement device 600 will be described.

[0045] FIG. 7 schematically shows an example of the procedure of the process executed by the distance measuring device 600. In step S701 of FIG. 7, the acquisition unit 621 acquires the distance calculated based on the time difference between the irradiation and reception of the optical pulse. For example, the irradiation unit 611 of the sensor unit 610 irradiates the object with an optical pulse, and the light receiving unit 612 of the sensor unit 610 receives the optical pulse reflected by the object. The sensor unit 610 sends a time difference signal indicating the time difference between the irradiation time of the optical pulse and the reception time of the reflected optical pulse to the acquisition unit 621. The acquisition unit 621 calculates the distance from the time difference indicated by the time difference signal according to the above formula (1).

[0046] In step S702, it is determined whether or not the number of executions of the process shown in step S701 has reached a predetermined number of repetitions (for example, 100 times). If the number of executions has not reached the number of repetitions (step S702; No), the process returns to step S701, and the acquisition unit 621 acquires the distance.

[0047] If the number of executions has reached the number of repetitions (step S702; Yes), the process proceeds to step S703. At this time, the distances for the number of repetitions (for example, 100 distances) are acquired.

[0048] In step S703, the distance information generation unit 622 generates distance information of the target object based on the target frequency distribution, which is the frequency distribution of a plurality of distances acquired by the acquisition unit 621, or the target statistic, which is a statistic calculated from the target frequency distribution. In an example where the storage unit 623 stores reference information associating a plurality of distances with a plurality of reference frequency distributions, the distance information generation unit 622 may specify the reference frequency distribution most similar to the target frequency distribution from among the reference frequency distributions, and obtain the distance associated with the specified reference frequency distribution as the distance information of the target object. In an example where the storage unit 623 stores reference information associating a plurality of distances with a plurality of reference statistics, the distance information generation unit 622 may specify the reference statistic most similar to the target statistic from among the reference statistics, and obtain the distance associated with the specified reference statistic as the distance information of the target object. In an example where the storage unit 623 stores reference information associating a plurality of correction values with a plurality of reference frequency distributions, the distance information generation unit 622 may specify the reference frequency distribution most similar to the target frequency distribution from among the reference frequency distributions, obtain the correction value associated with the specified reference frequency distribution, and generate the distance information of the target object based on the plurality of distances acquired by the acquisition unit 621 and the obtained correction value. In an example where the storage unit 623 stores reference information associating a plurality of correction values with a plurality of reference statistics, the distance information generation unit 622 may specify the reference statistic most similar to the target statistic from among the reference statistics, obtain the correction value associated with the specified reference statistic, and generate the distance information of the target object based on the plurality of distances acquired by the acquisition unit 621 and the obtained correction value. Further, the distance information generation unit 622 may input input data including the target frequency distribution or the target statistic to a learned model, and obtain the distance output from the learned model as the distance information of the target object. Further, the distance information generation unit 622 may input input data including the target frequency distribution or the target statistic to a learned model, obtain the correction value output from the learned model, and generate the distance information of the target object based on the plurality of distances acquired by the acquisition unit 621 and the obtained correction value.

[0049] As described above, the distance measurement device 600 includes an irradiation unit 611 that irradiates light, a light receiving unit 612 that receives the light irradiated by the irradiation unit 611 and reflected by the object, an acquisition unit 621 that acquires a plurality of distances calculated based on the time difference between the irradiation and reception of the light, and a distance information generation unit 622 that generates distance information of the object based on the frequency distribution of the plurality of distances or a statistic calculated from the frequency distribution. As a result, it is possible to reduce the bias error. As a result, distance measurement can be performed more accurately.

[0050] [Second Embodiment] In the second embodiment, the object information includes the distance information and the attribute information of the object.

[0051] FIG. 8 schematically shows a distance measurement device 800 according to the second embodiment. In FIG. 8, elements similar to those shown in FIG. 6 are denoted by the same reference numerals, and redundant descriptions are omitted as appropriate.

[0052] As shown in FIG. 8, the distance measurement device 800 includes a sensor unit 610 and an information processing unit 820. The information processing unit 820 includes an acquisition unit 621, a distance information generation unit 622, a storage unit 623, an attribute information generation unit 821, and a storage unit 822. The information processing unit 820 is obtained by adding an attribute information generation unit 821 and a storage unit 822 to the information processing unit 620 shown in FIG. 6. The attribute information generation unit 821 is realized by the processor 521 shown in FIG. 5, and the storage unit 822 is realized by the auxiliary storage device 523 or the program memory 524 shown in FIG. 5.

[0053] The attribute information generation unit 821 generates and outputs attribute information of an object based on the target frequency distribution or the target statistic. The attribute information is information indicating the attributes of the object. The attributes may include materials. Examples of materials include plastic and paper. Plastic may refer to types of plastic such as plastic A, plastic B, and plastic C described above with reference to FIGS. 3 and 4. Also, the attributes may include characteristics related to light reflection. Examples of characteristics related to light reflection include reflectance, refractive index, transmittance, attenuation coefficient, absorption coefficient, and scattering cross section. The attributes may include at least one of reflectance, refractive index, transmittance, attenuation coefficient, absorption coefficient, and scattering cross section.

[0054] When the attribute information generation unit 821 generates the attribute information of the object based on the target frequency distribution, the storage unit 822 may store reference information associating the attribute information with a plurality of reference frequency distributions. The reference information is generated in advance using an optical sensor of the same type as the optical sensor 510. For example, the reference information is generated by performing, for a plurality of objects having different attributes, a process of obtaining a frequency distribution of measurement results by performing distance measurement a plurality of times with an optical sensor while placing the object at a specific distance from the optical sensor.

[0055] The attribute information generation unit 821 may select at least one reference frequency distribution similar to the target frequency distribution from among the reference frequency distributions included in the reference information, and generate the attribute information of the object based on the attribute information associated with the selected at least one reference frequency distribution. For example, the attribute information generation unit 821 calculates the similarity between the target frequency distribution and the reference frequency distribution by regression using the k-nearest neighbor method, selects the reference frequency distribution with the highest similarity, and obtains the attribute information associated with the selected reference frequency distribution as the attribute information of the object. Also, the attribute information generation unit 821 may select a predetermined number of reference frequency distributions in descending order of similarity, and generate the attribute information of the object based on the attribute information associated with the selected reference frequency distributions. For example, the attribute information output by the attribute information generation unit 821 may include a set of the attribute information associated with the selected reference frequency distribution and the similarity.

[0056] When the attribute information generation unit 821 generates the attribute information of the object based on the target statistic, the storage unit 822 may store reference information in which the attribute information and a plurality of reference statistics are associated with each other. Since the generation of the reference information and the generation of the attribute information of the object are the same as those described above, detailed description thereof is omitted.

[0057] Instead of the reference information, the attribute information generation unit 821 may generate the attribute information of the object using a model obtained by machine learning. In this case, the storage unit 822 stores one or more parameters included in the learned model. As the machine learning algorithm, for example, a neural network, SVM, or random forest can be used.

[0058] For example, the model may be configured to output attribute information when a frequency distribution is input, and may be learned using, as learning data, reference information in which the above-described attribute information and a plurality of reference frequency distributions are associated with each other. The attribute information generation unit 821 inputs the target frequency distribution into the learned model, and obtains, as the attribute information of the object, the attribute information output from the learned model.

[0059] Alternatively, the model may be configured to output attribute information when a statistic is input, and may be learned using, as learning data, reference information in which the above-described attribute information and a plurality of reference statistics are associated with each other. The distance information generation unit 622 inputs the target statistic into the learned model, and obtains, as the attribute information of the object, the attribute information output from the learned model.

[0060] Note that the attribute information generation unit 821 may generate the attribute information of the object based on both the target frequency distribution and the target statistic.

[0061] Next, the operation of the distance measurement device 800 will be described.

[0062] FIG. 9 schematically shows an example of the procedure of the process executed by the distance measurement device 800. Since the processes of steps S901, S902, and S903 shown in FIG. 9 are the same as the processes of steps S701, S702, and S703 shown in FIG. 7, detailed descriptions thereof are omitted.

[0063] In step S901 of FIG. 9, the acquisition unit 621 acquires a distance calculated based on the time difference between light irradiation and light reception. In step S902, it is determined whether or not the number of executions of the process shown in step S901 has reached the number of repetitions. If the number of executions has not reached the number of repetitions (step S902; No), the process returns to step S901, and the acquisition unit 621 acquires the distance.

[0064] If the number of executions has reached the number of repetitions (step S902; Yes), the process proceeds to step S903. In step S903, the distance information generation unit 622 generates distance information of the object based on the target frequency distribution that is the frequency distribution of a plurality of distances acquired by the acquisition unit 621 or the target statistic that is a statistic calculated from the target frequency distribution.

[0065] In step S904, the attribute information generation unit 821 generates attribute information of the object based on the target frequency distribution or the target statistic. In an example where the storage unit 822 stores reference information in which the attribute information is associated with a plurality of reference frequency distributions, the attribute information generation unit 821 may specify the reference frequency distribution that is most similar to the target frequency distribution from among the reference frequency distributions, and obtain the attribute information associated with the specified reference frequency distribution as the attribute information of the object. In an example where the storage unit 822 stores reference information in which the attribute information is associated with a plurality of reference statistics, the attribute information generation unit 821 may specify the reference statistic that is most similar to the target statistic from among the reference statistics, and obtain the attribute information associated with the specified reference statistic as the attribute information of the object. Further, the attribute information generation unit 821 may input the input data including the target frequency distribution or the target statistic into the learned model, and obtain the attribute information output from the learned model as the attribute information of the object.

[0066] As described above, the distance measurement device 800 includes an irradiation unit 611 that irradiates light, a light receiving unit 612 that receives the light irradiated by the irradiation unit 611 and reflected by the object, an acquisition unit 621 that acquires a plurality of distances calculated based on the time difference between the irradiation and reception of the light, a distance information generation unit 622 that generates distance information of the object based on the frequency distribution of the plurality of distances or a statistic calculated from the frequency distribution, and an attribute information generation unit 821 that generates attribute information of the object based on the frequency distribution of the plurality of distances or a statistic calculated from the frequency distribution. Thereby, in addition to being able to perform more accurate distance measurement, the attribute of the object can be estimated.

[0067] [Third Embodiment] In the third embodiment, the object information includes the attribute information of the object.

[0068] FIG. 10 schematically shows an attribute estimation device 1000 according to the third embodiment. In FIG. 10, the same elements as those shown in FIG. 6 or FIG. 8 are denoted by the same reference numerals, and redundant descriptions are omitted as appropriate.

[0069] As shown in FIG. 10, the attribute estimation device 1000 includes a sensor unit 610 and an information processing unit 1020. The information processing unit 1020 includes an acquisition unit 621, an attribute information generation unit 821, and a storage unit 822. The information processing unit 1020 is obtained by deleting the distance information generation unit 622 and the storage unit 623 from the information processing unit 820 shown in FIG. 6.

[0070] FIG. 11 schematically shows an example of the procedure of the process executed by the attribute estimation device 1000. Since the processes in steps S1101, S1102, and S1103 shown in FIG. 11 are the same as the processes in steps S701, S702, and S904 shown in FIG. 7, detailed descriptions are omitted.

[0071] In step S1101 of FIG. 11, the acquisition unit 621 acquires a distance calculated based on the time difference between light irradiation and light reception. In step S1102, it is determined whether the number of executions of the process shown in step S1101 has reached the number of repetitions. If the number of executions has not reached the number of repetitions (step S1102; No), the process returns to step S1101, and the acquisition unit 621 acquires the distance.

[0072] If the number of executions has reached the number of repetitions (step S1102; Yes), the process proceeds to step S1103. In step S1103, the attribute information generation unit 821 generates attribute information of the object based on the target frequency distribution that is the frequency distribution of the plurality of distances acquired by the acquisition unit 621 or the target statistic that is a statistic calculated from the target frequency distribution.

[0073] As described above, the attribute estimation device 1000 includes an irradiation unit 611 that irradiates light, a light reception unit 612 that receives the light irradiated by the irradiation unit 611 and reflected by the object, an acquisition unit 621 that acquires a plurality of distances calculated based on the time difference between light irradiation and light reception, and an attribute information generation unit 821 that generates attribute information of the object based on the frequency distribution of the plurality of distances or a statistic calculated from the frequency distribution. Thereby, the attribute of the object can be estimated.

[0074] In each of the above-described embodiments, the acquisition unit 621 acquires a distance calculated based on the time difference between light irradiation and light reception. The distance is an example of a distance index based on the time difference. The distance index refers to the distance itself or any index that can derive the distance. For example, the distance index based on the time difference may be the time difference itself. In this case, the distance information generation unit 622 obtains a time difference based on the frequency distribution of a plurality of time differences acquired by the acquisition unit 621 or a statistic calculated from the frequency distribution. For example, the storage unit 623 stores reference information associating a plurality of time differences with a plurality of reference frequency distributions, and the distance information generation unit 622 obtains a time difference corresponding to the frequency distribution of the plurality of time differences acquired by the acquisition unit 621 from the reference information stored in the storage unit 623. The distance information output by the distance information generation unit 622 may indicate the obtained time difference. Alternatively, the distance information generation unit 622 may calculate a distance from the obtained time difference according to the above formula (1) and output distance information indicating the calculated distance.

[0075] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and its equivalent scope.

Explanation of Reference Numerals

[0076] 101... Distance measurement sensor, 102... Laser, 103... Photodetector, 105... Object, 500... Information acquisition device, 510... Optical sensor, 511... Light source, 512... Photodetector, 520... Information processing device, 521... Processor, 522... RAM, 523... Auxiliary storage device, 524... Program memory, 525... Input / output interface, 526... Bus, 600... Distance measurement device, 610... Sensor unit, 611... Irradiation unit, 612... Light receiving unit, 620... Information processing unit, 621... Acquisition unit, 622... Distance information generation unit, 623... Memory unit, 800... Distance measurement device, 820... Information processing unit, 821... Attribute information generation unit, 822... Memory unit, 1000... Attribute estimation device, 1020... Information processing unit.

Claims

1. An irradiation unit that irradiates light; A light receiving unit that receives the light reflected by the object; An acquisition unit that acquires a plurality of distance indicators based on a time difference between irradiation and reception of the light; From reference information associating a plurality of correction values with a plurality of reference frequency distributions related to the distance indicators or a plurality of reference statistics calculated from the plurality of reference frequency distributions, a reference frequency distribution or a reference statistic similar to the frequency distribution of the plurality of distance indicators or the statistic calculated from the frequency distribution is selected, a correction value associated with the selected reference frequency distribution or reference statistic is obtained, a representative distance is calculated from the plurality of acquired distance indicators, and the calculated representative distance is corrected with the obtained correction value, thereby generating distance information representing the distance to the object. A first generation unit; comprising; The reference information is information acquired device that is generated in advance by performing distance measurement on an object having the same attribute as the object.

2. An irradiation unit that irradiates light; A light receiving unit that receives the light reflected by the object; An acquisition unit that acquires a plurality of distance indicators based on a time difference between irradiation and reception of the light; The frequency distribution of the plurality of distance indicators or the statistic calculated from the frequency distribution is input to a learned model configured to output a correction value when the frequency distribution related to the distance indicator or the statistic calculated from the frequency distribution related to the distance indicator is input, a correction value output from the learned model is obtained, a representative distance is calculated from the plurality of acquired distance indicators, and the calculated representative distance is corrected with the obtained correction value, thereby generating distance information representing the distance to the object. A first generation unit; comprising; The learned model is a information acquisition device that is pre-learned using information obtained by performing distance measurement on an object having the same attribute as the object.

3. The first generation unit generates the distance information based on the statistic calculated from the frequency distribution. The statistic calculated from the frequency distribution includes at least one of the mean, variance, standard deviation, median, minimum value, maximum value, mode, skewness, and kurtosis of the frequency distribution. The information acquisition device according to claim 1 or 2.

4. The statistic calculated from the frequency distribution includes at least one of the mean, the median, and the mode, and at least one of the variance, the standard deviation, the skewness, and the kurtosis. The information acquisition device according to claim 3.

5. The information acquisition device further includes a second generation unit that generates attribute information indicating an attribute of the object based on the frequency distribution of the plurality of distance metrics or the statistic calculated from the frequency distribution. The information acquisition device according to any one of claims 1 to 4.

6. The second generation unit obtains, as the attribute information of the object, the attribute information corresponding to the frequency distribution of the plurality of acquired distance metrics or the statistic calculated from the frequency distribution from reference information associating the attribute information with a plurality of frequency distributions or a plurality of statistics. The information acquisition device according to claim 5.

7. The attribute includes a material. The information acquisition device according to claim 5 or 6.

8. The attribute includes at least one of reflectance, refractive index, transmittance, attenuation coefficient, absorption coefficient, and scattering cross section. The information acquisition device according to claim 5 or 6.

9. Obtaining a plurality of distance metrics based on a time difference between irradiation of light and reception of the light reflected by the object. From reference information associating a plurality of correction values with a plurality of reference frequency distributions related to distance metrics or a plurality of reference statistics calculated from the plurality of reference frequency distributions, select a reference frequency distribution or reference statistic similar to the frequency distribution of the plurality of distance metrics or the statistic calculated from the frequency distribution, obtain the correction value associated with the selected reference frequency distribution or reference statistic, calculate a representative distance from the plurality of obtained distance metrics, and correct the calculated representative distance with the obtained correction value, thereby generating distance information representing the distance to the object. comprising The reference information is information acquisition method that is pre-generated by performing distance measurement on an object having the same attribute as the object.

10. Obtain a plurality of distance metrics based on the time difference between the irradiation of light and the reception of the light reflected by the object, Input the frequency distribution of the distance metrics or the statistic calculated from the frequency distribution of the distance metrics into a learned model configured to output a correction value when the frequency distribution or the statistic related to the distance metrics is input, obtain the correction value output from the learned model, calculate a representative distance from the plurality of obtained distance metrics, and correct the calculated representative distance with the obtained correction value, thereby generating distance information representing the distance to the object. comprising The learned model is pre-learned using information obtained by performing distance measurement on an object having the same attribute as the object.

11. Means for obtaining a plurality of distance metrics based on the time difference between the irradiation of light and the reception of the light reflected by the object, and Means for generating distance information representing the distance to the object by selecting a reference frequency distribution or a reference statistic similar to the frequency distribution of the plurality of distance metrics or a statistic calculated from the frequency distribution from reference information associating a plurality of correction values with a plurality of reference frequency distributions or a plurality of reference statistics regarding the plurality of distance metrics, obtaining the correction value associated with the selected reference frequency distribution or reference statistic, calculating a representative distance from the plurality of obtained distance metrics, and correcting the calculated representative distance with the obtained correction value causing a computer to function as The reference information is a program that is generated in advance by performing distance measurement on an object having the same attribute as the object.

12. Means for obtaining a plurality of distance metrics based on the time difference between the irradiation of light and the reception of the light reflected by the object, and inputting the frequency distribution of the distance metrics or a statistic calculated from the frequency distribution of the distance metrics into a learned model configured to output a correction value when the frequency distribution of the distance metrics or a statistic calculated from the frequency distribution of the distance metrics is input, obtaining the correction value output from the learned model, calculating a representative distance from the plurality of obtained distance metrics, and correcting the calculated representative distance with the obtained correction value to generate distance information representing the distance to the object causing a computer to function as The learned model is a program that is pre-learned using information obtained by performing distance measurement on an object having the same attribute as the object.

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