Distortion correction device, distortion correction method, and distortion correction program

Abstract

To correct a distortion of point cloud data in the time of mis-Fix during the low speed movement or during the satellite viewing.SOLUTION: A distortion correction device 100 corrects a distortion of point cloud data calculated based on measurement data obtained by a measurement system mounted on a mobile body. A distortion detection unit 110 detects the distortion of a mobile body position posture 41 which represents the self-position posture of the mobile body used for the calculation of the point cloud data. The distortion of the mobile body position posture 41 becomes a factor of the distortion of the point cloud data. A correction unit 120 corrects the distortion of the mobile body position posture 41 and outputs the self-position posture of the mobile body obtained by correcting the distortion of the mobile body position posture 41 as a corrected position posture 53.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a distortion correction device, a distortion correction method, and a distortion correction program. In particular, it relates to a distortion correction device, a distortion correction method, and a distortion correction program for correcting the distortion of the self-position and orientation of a moving object that causes the distortion of point cloud data calculated by mobile measurement.

Background Art

[0002] In recent years, with the generalization of MMS, point clouds have become the delivery target, and the distortion of point clouds has been regarded as a problem. MMS is an abbreviation for Mobile Mapping System. Also, the measurement personnel when drawing point clouds are no longer professionals, and relaxation of measurement rules is required. In addition, in order to acquire a large amount of data, it has become necessary to perform measurements without considering driving environments such as traffic jams. Due to such factors, for example, it is desirable to output smooth point clouds even in severe environments such as being caught in a traffic jam under a highway and repeatedly driving at a very low speed and stopping under satellite unavailability, or driving in a building area in the city center.

[0003] Patent Document 1 discloses a technique for generating a three-dimensional model using three-dimensional point clouds.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] With the technique of Patent Document 1, an accurate three-dimensional model cannot be generated if there is distortion in the three-dimensional point cloud. In MMS, post-processing distortion of the self-position is a cause of point cloud data distortion. Most instances of slight post-processing shifts in the self-position occur when stationary. However, slight shifts in self-position and point cloud data distortion can also occur during slow movement or when the satellite is visible. Slight shifts in self-position when the satellite is visible occur due to misfixes caused by distance or elevation difference from the reference point, or multipath. This phenomenon, like that occurring when stationary under satellite visibility, stems from errors in forward and backward position and attitude calculations. As long as the current IMU is used, this phenomenon is likely to occur. While using a high-performance IMU could reduce the degree of occurrence, it would incur significant costs and is not practical. IMU stands for Inertial Measurement Device. It is an abbreviation for Unit.

[0006] This disclosure aims to correct distortion of point cloud data during slow-speed movement or misfixes under satellite visibility. [Means for solving the problem]

[0007] The distortion correction device relating to this disclosure is In a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile body, A distortion detection unit that detects the distortion of the mobile body's position and orientation, which represents the self-position and orientation of the mobile body used in calculating the point cloud data, and which is a factor in the distortion of the point cloud data; A correction unit for correcting the distortion of the position and orientation of the moving body, It is equipped with. [Effects of the Invention]

[0008] The distortion correction device described herein corrects the distortion of point cloud data by correcting the self-position and orientation of a moving object during slow-speed movement or when misfixes occur under satellite visibility. [Brief explanation of the drawing]

[0009] [Figure 1] A diagram showing an example configuration of the distortion correction device according to Embodiment 1. [Figure 2] A diagram showing the conditions for the occurrence of distortion in point cloud data according to Embodiment 1. [Figure 3] A figure showing an example of distortion caused by misfix according to Embodiment 1. [Figure 4] A diagram illustrating the factors causing distortion due to misfix according to Embodiment 1. [Figure 5] A figure showing an example of distortion in point cloud data according to Embodiment 1. [Figure 6] A diagram showing an example of the processing flow of the distortion correction device according to Embodiment 1. [Figure 7] This figure shows an example of detecting strain from the relationship between position and yaw angle, which is part of the detection method 1 in the first strain detection process according to Embodiment 1. [Figure 8] This figure shows an example of detecting distortion from the relationship between height and pitch angle, which is one of the detection methods 1 in the first distortion detection process according to Embodiment 1. [Figure 9] This figure shows an example of detecting distortion from the relationship between height and pitch angle, which is one of the detection methods 1 in the first distortion detection process according to Embodiment 1. [Figure 10] A diagram showing the second strain detection process according to Embodiment 1. [Figure 11] A figure showing an example of a modification process according to Embodiment 1. [Figure 12] A figure showing example 2 of the modification process according to Embodiment 1. [Figure 13] A diagram showing a processing example common to Method Example 1 and Method Example 2 of the modification process according to Embodiment 1. [Figure 14] A diagram showing the processing flow of a distortion correction device according to a modified example 1 of Embodiment 1. [Figure 15] This figure shows an example of the configuration of a distortion correction device 100 according to a modified example 2 of Embodiment 1. [Figure 16] This figure shows an example of the configuration of the strain processing status display screen according to modification 3 of Embodiment 1. [Figure 17]A diagram showing an example of correcting distortion of point cloud data according to Embodiment 1. [Figure 18] A diagram showing an example of correcting distortion of point cloud data according to Embodiment 1. [Figure 19] A diagram showing an example of correcting distortion of point cloud data according to Embodiment 1. [Figure 20] A diagram showing an example of correcting distortion of point cloud data according to Embodiment 1. **Embodiments for Carrying Out the Invention**

[0010] Hereinafter, this embodiment will be described with reference to the drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals. In the description of the embodiment, the description of the same or corresponding parts will be omitted or simplified as appropriate. The arrows in the drawings mainly indicate the data flow or the processing flow. Also, in the following drawings, the relationship of the sizes of the respective components may be different from the actual ones. Also, in the description of the embodiment, directions or positions such as up, down, left, right, front, back, front side, and back side may be indicated. These notations are for convenience of explanation and do not limit the arrangement, direction, and orientation of devices, instruments, or parts.

[0011] Embodiment 1. ***Description of the Configuration*** FIG. 1 is a diagram showing a configuration example of a distortion correction device 100 according to this embodiment. The distortion correction device 100 is a device used for MMS. The distortion correction device 100 corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a moving body. The point cloud data is data in which the periphery of the moving body is represented by a point cloud. The moving body is, for example, a measurement vehicle equipped with a measurement system and acquiring measurement data while moving.

[0012] Here, an example of the measurement vehicle will be described. The measurement vehicle includes measurement devices such as a receiver, a laser scanner, an IMU, a camera, and an odometer. Measuring instruments (excluding odometers) are mounted on the cargo bed, which is, for example, installed on the roof of the measuring vehicle. Odometers are mounted on the tires, for example. However, the installation location of measuring instruments is not limited. The receiver is a receiver for a satellite positioning system and performs satellite positioning. Specifically, the receiver receives positioning signals from each of four or more positioning satellites and determines its own position. A concrete example of a satellite positioning system is the Global Positioning System (GPS). A laser scanner performs laser measurements. Specifically, the laser scanner emits a laser beam and receives the laser beam reflected from the point where the beam was emitted (the measurement point). The laser scanner then calculates the distance to the measurement point (relative distance) based on the time from when the laser beam was emitted until when it was received. The laser scanner also determines the direction from which the laser beam was emitted as the direction (relative bearing) to the measurement point. An IMU (Inertial Measurement Unit) is an inertial measurement device that performs inertial measurements. Specifically, an IMU measures angular velocity and acceleration in three dimensions. The camera takes a picture and generates an image. The odometer measures the distance traveled. The measurement vehicle travels through the measurement area, and the measurement equipment performs various measurements. The data obtained by the measuring instruments of a measurement vehicle is called measurement data.

[0013] MMS is a system that assumes post-processing of measurement data. The post-processing computer 200 is also called a point cloud generator. The post-processing computer 200 generates point cloud data using the measurement data. The point cloud data includes three-dimensional point data for each measurement location. The three-dimensional point data indicates the three-dimensional coordinate values ​​of the measurement location. The following is an example of a post-processing procedure for measurement data. (1) Copy the measurement data to the post-processing computer 200. (2) The self-position and orientation of the moving object in forward time is calculated, i.e., a forward process is performed, and the forward position and orientation 42 of the moving object obtained by the forward process is obtained. (3) The self-position and orientation of the moving object in reverse time is calculated, i.e., a backward process is performed, and the backward position and orientation 43 of the moving object obtained by the backward process is obtained. (4) The processing results of the forward position and attitude 42 and the backward position and attitude 43 are combined to calculate the mobile body position and attitude 41, which represents the mobile body's own position and attitude. (5) Using the position and orientation of the moving object 41 as a calculation element, calculations are performed on other sensors such as a laser scanner and a camera to generate point cloud data.

[0014] Thus, the mobile object's position and orientation 41 is calculated using the forward position and orientation 42, which is the mobile object's own position and orientation obtained by the forward processing, and the backward position and orientation 43, which is the mobile object's own position and orientation obtained by the backward processing. Furthermore, the point cloud data is calculated based on the mobile object's position and orientation 41. Therefore, distortion of the mobile object's position and orientation 41 is a factor in the distortion of the point cloud data. Distortion of the moving object's position and orientation 41 refers to phenomena such as inconsistencies in the self-position and orientation of the moving object calculated by the post-processing computer 200, unnatural changes in its self-position, or impossible movements.

[0015] In this embodiment, the post-processing computer 200 and the distortion correction device 100 are described as separate computers. However, the functions of the post-processing computer 200 and the distortion correction device 100 may be implemented in a single computer. Alternatively, the functions of the post-processing computer 200 and the distortion correction device 100 may be distributed across multiple computers. As long as the computer system can realize the functions of the post-processing computer 200 and the distortion correction device 100, the configuration of the computer system in this embodiment can be any configuration.

[0016] The distortion correction device 100 is a computer. The distortion correction device 100 includes a processor 910, as well as other hardware such as memory 921, auxiliary storage device 922, input interface 930, output interface 940, and communication device 950. The processor 910 is connected to the other hardware via signal lines and controls this other hardware. The distortion correction device 100 includes, as functional elements, a distortion detection unit 110, a correction unit 120, a correction confirmation unit 130, a display unit 140, and a storage unit 150. The distortion detection unit 110 includes a first distortion detection unit 111 and a second distortion detection unit 112. The storage unit 150 stores the section 50, the corrected position and attitude 53, and the satellite mask 54. The section 50 stores the first section 51 and the second section 52.

[0017] The functions of the distortion detection unit 110, the correction unit 120, the correction confirmation unit 130, and the display unit 140 are implemented by software. The storage unit 150 is provided in the memory 921. The storage unit 150 may also be provided in the auxiliary storage device 922, or it may be distributed between the memory 921 and the auxiliary storage device 922.

[0018] The processor 910 is a device that executes a distortion correction program. The distortion correction program is a program that implements the functions of the distortion detection unit 110, the correction unit 120, the correction confirmation unit 130, and the display unit 140. The processor 910 is an integrated circuit (IC) that performs arithmetic processing. Specific examples of the processor 910 include CPUs, DSPs, and GPUs. IC stands for Integrated Circuit. CPU stands for Central Processing Unit. DSP stands for Digital Signal Processor. GPU stands for Graphics Processing Unit.

[0019] Memory 921 is a storage device that temporarily stores data. Specific examples of memory 921 are SRAM or DRAM. SRAM is an abbreviation for Static Random Access Memory. DRAM is an abbreviation for Dynamic Random Access Memory. The auxiliary storage device 922 is a storage device for storing data. A specific example of the auxiliary storage device 922 is an HDD. Alternatively, the auxiliary storage device 922 may be a portable storage medium such as an SD® memory card, CF, NAND flash, flexible disk, optical disk, compact disk, Blu-ray® disc, or DVD. HDD is an abbreviation for Hard Disk Drive. SD® is an abbreviation for Secure Digital. CF is an abbreviation for CompactFlash®. DVD is an abbreviation for Digital Versatile Disk.

[0020] The input interface 930 is a port to which input devices such as a mouse, keyboard, or touch panel are connected. Specifically, the input interface 930 is a USB terminal. The input interface 930 may also be a port connected to a LAN. USB stands for Universal Serial Bus. LAN stands for Local Area Network. Figure 1 shows one input interface 930, but multiple input interfaces 930 may exist.

[0021] The output interface 940 is a port to which the cable of an output device, such as a display, is connected. Specifically, the output interface 940 is a USB terminal or an HDMI® terminal. Specifically, the display is an LCD. The output interface 940 is also called the display interface. HDMI® is an abbreviation for High Definition Multimedia Interface. LCD is an abbreviation for Liquid Crystal Display. Figure 1 shows one output interface 940, but multiple output interfaces 940 may exist.

[0022] The communication device 950 has a receiver and a transmitter. The communication device 950 is connected to a communication network such as a LAN, the Internet, a telephone line, or Wi-Fi (registered trademark). Specifically, the communication device 950 is a communication chip or NIC. NIC is an abbreviation for Network Interface Card.

[0023] The distortion correction program is executed in the distortion correction device 100. The distortion correction program is loaded into the processor 910 and executed by the processor 910. Memory 921 stores not only the distortion correction program but also the OS. OS is an abbreviation for Operating System. The processor 910 executes the distortion correction program while executing the OS. The distortion correction program and OS may also be stored in auxiliary storage device 922. The distortion correction program and OS stored in auxiliary storage device 922 are loaded into memory 921 and executed by the processor 910. Note that part or all of the distortion correction program may be incorporated into the OS.

[0024] The distortion correction device 100 may have multiple processors that replace the processor 910. These multiple processors share the task of executing the distortion correction program. Each processor is a device that executes the distortion correction program in the same way as the processor 910.

[0025] The data, information, signal values, and variable values ​​used, processed, or output by the distortion correction program are stored in memory 921, auxiliary storage device 922, or registers or cache memory within the processor 910.

[0026] The "parts" in the distortion detection unit 110, correction unit 120, correction confirmation unit 130, and display unit 140 may be read as "circuit," "process," "procedure," "process," or "circuitry." The distortion correction program causes a computer to execute the distortion detection process, correction process, correction confirmation process, and display process. The "processes" in the distortion detection process, correction process, correction confirmation process, and display process may be read as "program," "program product," "computer-readable storage medium storing the program," or "computer-readable recording medium recording the program." Furthermore, the distortion correction method is performed by the distortion correction device 100 executing the distortion correction program. The distortion correction program may be provided on a computer-readable recording medium. Alternatively, the distortion correction program may be provided as a program product.

[0027] Figure 2 shows the conditions for the occurrence of distortion in point cloud data according to this embodiment. The conditions under which distortion occurs in point cloud data are classified into categories A through F, as shown in Figure 2. In this embodiment, distortion of point cloud data caused by the following classifications C, D, and F is corrected. • Classification C: Measurement in environments with a large distance or elevation difference from the reference point, or in environments where multipath, i.e., diffracted waves are generated (MisFix) • Classification D: Measurement when a moving object is moving at a slow speed in a satellite-invisible environment. • Classification F: Normal fixation in satellite visibility, but measurement when the moving object is moving at a slow speed.

[0028] Figure 3 shows an example of distortion caused by misfix according to this embodiment. Figure 4 shows the factors causing distortion due to misfix according to this embodiment. The following phenomena are occurring in the areas where misfixes have occurred. • The forward solution and the backward solution do not match. The dependency between the forward and backward processing results changes, and the output results fluctuate between the forward and backward solutions.

[0029] Dependency refers to the ratio of the dependency between forward processing and backward processing, and is also called confidence. For example, the dependency ratio between forward processing and backward processing can be expressed as 5:5, 1:9, or 7:3. When calculating a combined solution from forward and backward solutions while stationary or at low speed, distortion may occur due to changes in the degree of dependence. In this embodiment, the forward solution is also referred to as the forward position and orientation 42 or the forward processing result. The backward solution is also referred to as the backward position and orientation 43 or the backward processing result. The combined solution is also referred to as the moving body position and orientation 41 or the forward / backward combined result.

[0030] Here, we will explain one example of what causes the degree of dependence to change. A fixed solution has both a forward and a backward solution, and these are inherently misaligned at the location of a misfix. When both forward and backward solutions exist, the combined solution is located almost in the middle. However, if for some reason a backward solution is unavailable, the combined solution is pulled towards the forward solution, meaning its dependence on the forward solution increases. Similarly, if a forward solution is unavailable, the combined solution is pulled towards the backward solution, meaning its dependence on the backward solution increases. Thus, while the distortion of the combined solution is correct in the sense of "finding a more accurate position," it contradicts the requirement that point cloud data should not be distorted.

[0031] In the situation where distortion occurs in Figure 4, the composite solution is close to the forward solution before distortion, and close to the backward solution after distortion. Furthermore, the forward and backward solutions are significantly different. Also, within the section where distortion occurs, the moving object is either stopped or traveling at a low speed. Low speed means traveling at a very slow speed.

[0032] Figure 5 shows an example of distortion occurring in point cloud data 201 according to this embodiment. As shown in Figures 3 and 4, distortion occurs in the point cloud data 201 when distortion occurs in the composite solution, which is the self-position and orientation of the moving object. As described above, distortion in the composite solution, that is, distortion of the position and orientation of the moving object 41, refers to phenomena such as inconsistencies or unnatural changes in the self-position of the moving object, or impossible movements. Figure 5 shows an example where the lane is distorted in point cloud data 201 in a section where distortion occurred in the composite solution.

[0033] ***Explanation of operation*** Next, the operation of the distortion correction device 100 according to this embodiment will be described. The operation procedure of the distortion correction device 100 corresponds to the distortion correction method. Furthermore, the program that realizes the operation of the distortion correction device 100 corresponds to the distortion correction program.

[0034] Figure 6 is a diagram showing the processing flow of the distortion correction device 100 according to this embodiment. In Figure 6, the post-processing computer 200 corrects the distortion of classification B using the measurement data, calculates its own position and attitude, and outputs the mobile body position and attitude 41, forward position and attitude 42, backward position and attitude 43, and satellite visibility determination file 44. The mobile body position and orientation 41 is a composite solution calculated by the post-processing computer 200. The forward position and attitude 42 is a forward solution calculated by the post-processing computer 200. The backward position and orientation 43 is a backward solution calculated by the post-processing computer 200. The satellite visibility determination file 44 is a file that specifies whether the satellite is visible or invisible within the measurement interval. Specifically, the satellite visibility determination file 44 is rover.gga.

[0035] <Strain detection process: Steps S101 and S102> In the distortion detection process, the distortion detection unit 110 detects distortion of the mobile body position and orientation 41, which represents the self-position and orientation of the mobile body used to calculate the point cloud data, and which is a cause of distortion in the point cloud data. The distortion detection unit 110 outputs the section 50 in which distortion was detected in the mobile body position and orientation 41. The strain detection process comprises a first strain detection process by a first strain detection unit 111 and a second strain detection process by a second strain detection unit 112.

[0036] In step S101, the first strain detection unit 111 acquires the position and orientation 41 of the moving body and executes the first strain detection process. The first strain detection unit 111 executes the first strain detection process which outputs the time period in which there is a discrepancy between the change in the position of the moving body and the change in the orientation of the moving body as section 50. The section output by the first strain detection unit 111 is designated as the first section 51.

[0037] In step S102, the second strain detection unit 112 acquires the forward position and attitude 42 and the backward position and attitude 43, and executes the second strain detection process. The second strain detection unit 112 executes the second strain detection process which outputs the time period in which the dependency ratio, which represents the ratio of the dependency between the forward processing and the backward processing, changes to a predetermined threshold or more as section 50. The section output by the second strain detection unit 112 is designated as the second section 52.

[0038] Here, we will specifically explain the two types of algorithms for detecting distortion: the first distortion detection process and the second distortion detection process.

[0039] <<First distortion detection process: Detection of distortion in classification D (when a moving object is moving at a slow speed in a satellite-invisible environment)>> In the first strain detection process, the mobile object's position and attitude 41 is acquired, and the time period in which there is a discrepancy between the change in the mobile object's position and the change in its attitude is output as the first interval 51. The first strain detection process detects strain during slow-speed movement when the satellite is not visible, i.e., strain of classification D. In the first strain detection process, the first strain detection unit 111 performs all of the following detection methods 1 and 2.

[0040] <<<Detection Method 1 in the First Strain Detection Process>>> In the first strain detection process, detection method 1 detects areas where the relationship between position and yaw angle, and the relationship between height and pitch angle, are disrupted.

[0041] Figure 7 shows an example of detecting strain from the relationship between position and yaw angle, which is one of the detection methods 1 in the first strain detection process according to this embodiment. In principle, position may be distorted, but posture should not. As a result, in areas of distortion, a discrepancy arises between the posture calculated from the position by the moving object position / posture 41 and the posture recorded in the moving object position / posture 41. The same applies to height. However, calculating posture from position requires that the object is moving to some extent, so it cannot be used when the object is completely stationary.

[0042] When stopped, moving at low speed, or in the event of a misfix, the forward and backward attitudes change smoothly, resulting in position distortion but no attitude distortion. Consequently, in areas where the position is distorted, there is a mismatch between the attitude calculated from the position and the attitude calculated from the forward and backward solutions, i.e., the attitude obtained in post-processing. Detection method 1 in the first distortion detection process detects such mismatches.

[0043] As shown in Figure 7, the attitude calculated from the position of P1 is 90°, and if the attitude at P1 stored in the MMS is also 90°, there is no problem. On the other hand, if the attitude calculated from the position of P2 is 200°, but the attitude at P2 stored in the MMS is 90°, then this is detected as a point where the relationship between position and yaw angle is broken.

[0044] Figures 8 and 9 show an example of detecting strain from the relationship between height and pitch angle, which is one of the detection methods 1 in the first strain detection process according to this embodiment. Height distortion can be detected by analyzing the pitch difference between the MMS pitch and the height. However, the attitude cannot be calculated when the object is stationary, so it needs to be moving at least slightly. This detection method applies the principle explained in Figure 7 to height. The upper part of Figure 8 shows that a step of 4 cm in height occurred at location 173827. The lower part of Figure 8 shows the change in pitch difference.

[0045] The conditions under which an image appears distorted are A, B, and C below. Condition A: The absolute value of the pitch difference is greater than or equal to a certain value. For example, if the absolute value of the pitch difference is approximately 8 or greater, distortion occurs. Condition B: The height difference is different from when the pitch difference is small. Condition C: The absolute value of the height difference relative to the unit progress is greater than or equal to a certain value. For example, if this difference is 0.012 m or more, it is considered strain. The system determines whether or not an image appears distorted under all three conditions A, B, and C. A distortion is detected only when all three conditions are met. Simply relying on height differences alone can lead to misjudgments, such as on inclines or when moving quickly.

[0046] The upper left diagram in Figure 9 shows the relationship between pitch difference and height difference. This diagram represents condition A, where distortion is detected. The upper right diagram in Figure 9 shows the relationship between pitch difference and height difference. This is the diagram for condition B, where "no distortion" is determined. In the upper left diagram of Figure 9, there is a height difference of about 7 cm, whereas in the upper right diagram, the height difference is only about 2.5 cm. Therefore, distortion is less noticeable in the upper right diagram. The lower part of Figure 9 shows the relationship between pitch difference and height difference corresponding to condition C.

[0047] <<<Detection Method 2 in the First Strain Detection Process>>> Furthermore, detection method 2 in the first strain detection process detects rapid positional changes and rapid height changes. However, the orientation is not considered in detection method 2 in the first strain detection process. Specifically, it detects cases where the amount of movement of the vehicle's own position is too large or too small compared to the amount of movement of the odometer. It also detects cases where the change in position or height is determined to be abnormal for the vehicle's movement.

[0048] <<Second strain detection process: Detection of strain classified as C (misfix in environments where the distance or elevation difference from the reference point is large, or where multipath occurs)>> In the second strain detection process, the time period in which the dependency ratio, which represents the ratio of the dependency between the forward and backward processing, changes to a predetermined threshold is output as the second interval 52. The second strain detection process detects strain due to misfixes in environments where the distance or elevation difference from the reference point is large, or where multipath occurs, i.e., strain classified as C.

[0049] Figure 10 shows the second strain detection process according to this embodiment. In the second strain detection process, the system detects portions of the composite solution where the dependency between the forward and backward solutions changes abruptly. For example, the second strain detection unit 112 outputs the time period in which the dependency changes to a predetermined threshold or higher as the second interval 52. If the dependency changes gradually, no problem is identified.

[0050] In Figure 10, the solid line represents the difference between the combined solution (CTS) and the forward solution (FTS). The dotted line represents the difference between the combined solution (CTS) and the backward solution (RTS). Detecting areas where the dependency changes abruptly means detecting points where the amount of change is not constant but increases or decreases when plotting the "difference between CTS and FTS" or the "difference between CTS and RTS" as shown in the graph. The graph in the lower left, labeled "Misfix," is an example of a problem where distortion is detected, as seen in the enlarged upper left graph, where the FTS_RTS dependency changes abruptly. On the other hand, the upper and lower right graphs show examples where distortion is not detected, which is considered a problem.

[0051] As described above, the strain detected by the first strain detection process is classified as D. In other words, the first interval 51 is the time period in which strain was detected according to classification D. Furthermore, the strain detected by the second strain detection process is classified as C. In other words, the second interval 52 is the time period in which strain was detected according to classification C.

[0052] In addition, during the strain detection process, the detected strain may be output to separate files indicating whether it is classified as C or D. The first strain detection unit 111 outputs the strain to a file indicating that it is classified as D along with the first section 51. The second strain detection unit 112 outputs the strain to a separate file indicating that it is classified as C along with the second section 52, in a file separate from the first section 51.

[0053] <Correction process: Step S103> In step S103, the correction unit 120 corrects the distortion of the mobile body position and attitude 41 corresponding to section 50. Specifically, the correction unit 120 corrects the distortion of the mobile body position and attitude 41 corresponding to the first section 51 and the second section 52. Hereinafter, when section 50 is mentioned, it refers to both or each of the first section 51 and the second section 52. The correction unit 120 corrects the distortion of the moving body's position and attitude 41 and outputs the corrected position and attitude 53, which is the self-position and attitude of the moving body obtained after the correction.

[0054] When correcting the distortion of the mobile body position and orientation 41, the correction unit 120 corrects the distortion of the mobile body position and orientation 41 in section 50 so that the mobile body position and orientation 41 before and after the start of section 50 and the mobile body position and orientation 41 before and after the end of section 50 are smoothly continuous.

[0055] <<Example of correction process method 1>> Figure 11 shows an example of a modification process method 1 according to this embodiment. The correction unit 120 acquires the forward position and orientation 42 and the backward position and orientation 43. The correction unit 120 calculates the corrected position and orientation 53 by taking the average of the forward position and orientation 42 and the backward position and orientation 43 in the interval 50. Specifically, distortion is removed by integrating the forward and backward solutions for the target interval 50 and taking the average of the positions at the same time.

[0056] As shown in Figure 11, when adopting the correction method example 1, section 50 is defined as the time period in which the forward solution and the backward solution do not coincide. By setting the strain detection unit 110 to output section 50 in this way, the strain of the moving body position and orientation 41 in section 50 can be corrected so that the moving body position and orientation 41 before and after the start of section 50 and the moving body position and orientation 41 before and after the end of section 50 are smoothly continuous.

[0057] In the first example of the correction process, when calculating the composite solution for interval 50, the dependency ratio is not referenced, and the average of the forward and backward solutions is calculated as the composite solution, i.e., the corrected position and attitude 53. Then, the predicted error value for interval 50 is used as the satellite invisible interval, and the satellite visibility determination file 44 is deleted. Specifically, if the time for interval 50 is (from a second to b seconds), the predicted error value of the self-position and attitude data from a second to b seconds is set to a large value, and the line for the time period from a second to b seconds in rover.gga (satellite visibility determination file 44) is deleted.

[0058] According to the first example of the correction method, the distortion of the moving object's position and orientation 41 will be reliably corrected. However, the range of the section 50 to be corrected may become too wide.

[0059] <<Example of correction process method 2>> Figure 12 shows an example of a modification process method 2 according to this embodiment. The correction unit 120 acquires the forward position and attitude 42 and the backward position and attitude 43. The correction unit 120 calculates the corrected position and attitude 53 as the weighted average of the forward position and attitude 42 and the backward position and attitude 43 in the interval 50.

[0060] Specifically, a predetermined range, for example 10m before and after the target position where distortion is suspected, is set as section 50. The predetermined range from the target position that constitutes section 50 is set to fall within the measurement section. The correction unit 120 then corrects the distortion of the moving body position and posture 41 in section 50 so that the moving body position and posture 41 before and after the start of section 50 and the moving body position and posture 41 before and after the end of section 50 are smoothly continuous. At this time, the correction unit 120 performs weighted simultaneous averaging in section 50. In particular, since posture inconsistencies occur at each junction of the start and end of section 50, a process to smoothly connect them is necessary. It should be noted that the weighting change must be performed at the cumulative position of the correction section, not at time. That is, the weighting of the change must be calculated not at the change in time, but at the cumulative distance traveled by the vehicle.

[0061] In the example in Figure 12, weighted simultaneous position calculation is performed at the start of interval 50. At the start of interval 50, the dependency ratio (backward solution:forward solution) is 1:9, so this dependency ratio is used to smoothly connect the position and orientation. At the end of interval 50, weighted simultaneous position calculation is performed. At the end of interval 50, the dependency ratio (backward solution:forward solution) is 7:3, so this dependency ratio is used to smoothly connect the position and orientation. Then, a straight line is drawn connecting the position and orientation at the start and end points of section 50.

[0062] In the second example of the correction process, a predetermined range can be set, so the range of section 50 will not become too wide.

[0063] <<Examples of processing common to Method 1 and Method 2 of the correction process>> Figure 13 shows an example of processing common to Method Example 1 and Method Example 2 of the modification process according to this embodiment. A certain threshold is set to determine whether the forward solution and the backward solution are far apart; if they are far apart above this value, they are judged to be "far apart." In the correction method examples 1 and 2, it is necessary to smooth the transitions at the beginning and end of interval 50. The distance range between the forward solution and the backward solution is predetermined, and the dependency ratio is changed to make the transitions smoother.

[0064] The correction unit 120 outputs a corrected position and attitude 53, which is the self-position and attitude of the moving body obtained by correcting the distortion of the moving body position and attitude 41 through the correction process described above. In the corrected position and orientation 53, distortions due to classifications C and D have been corrected. It should be assumed that the distortion due to classification B has already been corrected when the post-processing computer 200 calculates the mobile body position and orientation 41.

[0065] <Correction confirmation process: Step S104> In step S104, the correction verification unit 130 obtains the corrected position and attitude 53 obtained by correcting the distortion of the moving body position and attitude 41. The correction verification unit 130 determines whether or not distortion remains in the corrected position and attitude 53. If the correction confirmation unit 130 determines that distortion remains in the corrected position and attitude, it outputs a satellite mask 54 for the section in the corrected position and attitude 53 where distortion remains, and which defines the section in the corrected position and attitude 53 as a satellite invisible section. Specifically, it is as follows:

[0066] The correction confirmation unit 130 performs the same distortion detection process as in steps S101 and S102 on the corrected position and orientation 53. Through this distortion detection process, the correction confirmation unit 130 reconfirms whether any distortion remains in the corrected position and orientation 53 after the distortion has been corrected. Of the remaining distortions, those in the satellite-visible region that can potentially be improved by satellite masking will undergo satellite masking. The user is responsible for deciding whether or not to perform satellite masking. The distortions detected here are those classified as F, i.e., distortions that occur during slow-speed movement when the satellite is visible. Satellite masking is effective in addressing distortions during slow-speed movement when the satellite is visible (distortions caused by positioning errors). This is because, since these distortions are caused by positioning errors, making the satellite invisible will resolve the problem. However, this method requires recalculating the self-position and reprocessing all distortions, resulting in a huge processing time, so it is preferable to leave this to the user's discretion. The correction verification unit 130 performs the same strain detection process as in steps S101 and S102 and outputs the sections in which strain was detected. At this time, the correction verification unit 130 outputs the sections in which strain of classification F was detected to a file. Specifically, it enables user decision-making as follows:

[0067] The display unit 140 displays a satellite mask processing necessity screen 60 on the display device, which accepts requests to perform satellite mask processing. The satellite mask processing necessity screen 60 includes the section in which distortion remains in the corrected position and attitude, the trajectory data of the moving object representing the corrected position and attitude in the section in which distortion remains, and the point cloud data in the section in which distortion remains. The satellite mask processing necessity screen 60 also displays that the distortion is classified as F. The correction confirmation unit 130 outputs the satellite mask 54 when it receives a request to perform satellite mask processing via the satellite mask processing necessity screen 60.

[0068] Specifically, when the correction confirmation unit 130 receives a request to perform satellite mask processing, it outputs the corrected position and attitude 53 and the satellite mask 54 to the post-processing computer 200. The post-processing computer 200 performs satellite mask processing on the corrected position and attitude 53. Then, the post-processing computer 200 generates point cloud data using the corrected position and attitude 53, after which satellite mask processing has been performed, as the mobile object position and attitude. If there is no request to perform satellite mask processing, the correction verification unit 130 outputs the corrected position and attitude 53 to the post-processing computer 200. The post-processing computer 200 generates point cloud data using the corrected position and attitude 53 as the moving object position and attitude.

[0069] The satellite mask processing necessity screen 60 allows users to check the trajectory data and point cloud data in the sections where distortion remains and determine whether satellite mask processing is necessary.

[0070] ***Other configurations*** <Example 1> In this embodiment, the correction unit 120 detects distortions according to classifications C and D and corrects the detected distortions according to classifications C and D. In addition, the correction confirmation unit 130 detects distortions according to classification F and presents the user with a satellite mask processing necessity screen 60 to determine whether or not to correct the detected distortion according to classification F. In a modified example of this embodiment, the distortion correction device 100 is further equipped with a function to detect distortion according to classifications A and E and to correct the detected distortion according to classifications A and E.

[0071] Figure 14 is a diagram showing the processing flow of the distortion correction device 100 according to Modification 1 of this embodiment. In the first modified example of this embodiment, the strain detection unit 110 has a function to detect strain according to classifications A and E. In addition, the correction unit 120 has a function to correct the detected strain according to classifications A and E. The distortion corrections in categories A and E address the problem of the object's position and orientation changing even when the object is completely stationary. For example, one correction method involves determining when the object is stationary using an odometer that detects movement, and then taking measures to prevent the object's position and orientation from changing during that time. In addition to the strain detection unit 110 and the correction unit 120, the system may also include a functional element for detecting strain according to classifications A and E, or a functional element for correcting the detected strain according to classifications A and E.

[0072] <Modification 2> In this embodiment, the functions of each part of the distortion correction device 100 are implemented by software. As a modified example 2, the functions of each part of the distortion correction device 100 may be implemented by hardware. Specifically, the distortion correction device 100 includes an electronic circuit 909 in place of the processor 910.

[0073] Figure 15 shows an example of the configuration of a distortion correction device 100 according to a modified example 2 of this embodiment. The electronic circuit 909 is a dedicated electronic circuit that realizes the functions of each part of the distortion correction device 100. Specifically, the electronic circuit 909 is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, or an FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array.

[0074] The functions of each part of the distortion correction device 100 may be realized by a single electronic circuit, or they may be realized by distributing them across multiple electronic circuits.

[0075] As another variation, some functions of the distortion correction device 100 may be implemented by electronic circuits, while the remaining functions are implemented by software. Alternatively, some or all functions of the distortion correction device 100 may be implemented by firmware.

[0076] Each of the processor and electronic circuit is also called a processing circuit. In other words, the functions of each part of the distortion correction device 100 are realized by the processing circuit.

[0077] <Variation 3> In Modification 3, we will describe a strain processing status display screen 61 that allows the user of the strain correction device 100 to confirm what classification of the detected strain is and what processing is currently being performed.

[0078] Figure 16 shows an example of the configuration of the strain processing status display screen 61 according to this embodiment. The display unit 140 displays the distortion processing status display screen 61 on the display device. The distortion processing status display screen 61 is configured to display the processing status of distortion CD countermeasure processing, distortion AE countermeasure processing, and distortion F final confirmation processing in chronological order. In the distortion processing status display screen 61 of Figure 16, a dark shading pattern indicates "abnormal termination," a light shading pattern indicates "normal termination," and a diagonal shading pattern indicates "remaining distortion (classification F)." No shading pattern indicates unprocessed, and the checked processing is in progress. In the distortion CD correction process and distortion AE correction process, "successful completion" means that distortion was detected and corrected. In the distortion F final confirmation process, "successful completion" means that a satellite mask file is not output, i.e., there is no residual distortion. In the distortion F final confirmation process, "residual distortion present (classification F)" means that residual distortion is present and a satellite mask file has been output. In all processes, "abnormal termination" means that the necessary files for the process were not present, and therefore the distortion detection and correction process was not executed.

[0079] According to Modification 3, the user of the distortion correction device 100 can check what classification of the detected distortion is and what distortion correction process is currently being performed.

[0080] ***Description of the effects of this embodiment*** Figure 17 shows an example of distortion correction of point cloud data 201 according to this embodiment. In Figure 17, in the section where distortion occurred in the composite solution, the lane distortion is present in the uncorrected point cloud data 201, but the lane distortion is corrected in the corrected point cloud data 201.

[0081] Figure 18 shows an example of distortion correction of point cloud data 201 according to this embodiment. In Figure 18, in the section where distortion occurred in the composite solution, the lane is distorted in the uncorrected top view point cloud data 201, and there is a height difference of approximately 3 cm in the cross-sectional view point cloud data 201. On the other hand, in the corrected point cloud data 201, the lane distortion is corrected, and the height difference is also corrected.

[0082] Figure 19 shows an example of distortion correction of point cloud data 201 according to this embodiment. In Figure 19, in the section where distortion occurred in the composite solution, the point cloud data 201 before correction showed a misalignment between the marker point cloud and the white line in the image, but this has been improved in the corrected point cloud data 201.

[0083] Figure 20 shows an example of distortion correction of point cloud data 201 according to this embodiment. In Figure 20, in the section where distortion occurred in the composite solution, the height is distorted in the uncorrected point cloud data 201. Furthermore, height distortion remains in the corrected point cloud data 201. On the other hand, the height distortion is improved in the point cloud data 201 after satellite mask processing.

[0084] According to the distortion correction device 100 of this embodiment, distortion of the self-position and orientation of the moving object is eliminated, and the point cloud data becomes natural. Furthermore, the distortion correction device 100 according to this embodiment can eliminate distortion without using an expensive IMU. Also, remeasurement becomes unnecessary; distortion can be corrected simply by adding the distortion correction process according to this embodiment as a post-processing step. Furthermore, the distortion correction device 100 according to this embodiment ensures that the parts that are not distorted remain unchanged. Furthermore, the distortion correction device 100 according to this embodiment automatically checks whether any distortion remains after the distortion has been corrected, thereby eliminating the need for visual inspection.

[0085] In the above Embodiment 1, each part of the distortion correction device was described as an independent functional block. However, the configuration of the distortion correction device does not have to be as in the above embodiment. The functional blocks of the distortion correction device can be configured in any way as long as they can realize the functions described in the above embodiment. Furthermore, the distortion correction device does not have to be a single device, but may be a system composed of multiple devices. Furthermore, multiple parts of Embodiment 1 may be combined and implemented. Alternatively, only one part of this embodiment may be implemented. In addition, this embodiment may be combined and implemented in any way, either as a whole or in parts. In other words, in Embodiment 1, it is possible to freely combine each embodiment, modify any component of each embodiment, or omit any component in each embodiment.

[0086] The embodiments described above are essentially preferred examples and are not intended to limit the scope of the Disclosure, the scope of the Applications of the Disclosure, or the scope of Uses of the Disclosure. The embodiments described above can be modified in various ways as needed. For example, the procedures described using process flow diagrams or sequence diagrams may be modified as appropriate.

[0087] The various aspects of this disclosure are summarized below as an appendix.

[0088] (Note 1) In a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile body, A distortion detection unit that detects the distortion of the mobile body's position and orientation, which represents the self-position and orientation of the mobile body used in calculating the point cloud data, and which is a factor in the distortion of the point cloud data; A correction unit corrects the distortion of the position and orientation of the moving body and outputs the self-position and orientation of the moving body obtained by correcting the distortion of the position and orientation of the moving body as the corrected position and orientation. A distortion correction device equipped with the following features. (Note 2) The aforementioned strain detection unit is Output the section in which distortion was detected in the position and orientation of the moving object. The aforementioned modification section is, A distortion correction device according to Appendix 1 for correcting the distortion of the position and orientation of the moving body corresponding to the aforementioned section. (Note 3) The aforementioned strain detection unit is A first strain detection unit obtains the mobile body position and attitude calculated using the forward position and attitude of the mobile body obtained by forward processing and the backward position and attitude of the mobile body obtained by backward processing, and outputs the time period in which there is a discrepancy between the change in the mobile body's position and the change in the mobile body's attitude as the interval, A second strain detection unit outputs the time period in which the dependency ratio, which represents the ratio of the dependency between the forward processing and the backward processing, changes to a predetermined threshold or higher, as the interval. A distortion correction device as described in Appendix 2, comprising the following features. (Note 4) The aforementioned modification section is, A distortion correction device according to Appendix 3, which corrects the distortion of the position and orientation of the moving body in the section so that the position and orientation of the moving body before and after the start of the section and the position and orientation of the moving body before and after the end of the section are smoothly continuous. (Note 5) The aforementioned modification section is, A distortion correction device according to Appendix 3 or Appendix 4, which calculates the average value of the forward position and the backward position in the aforementioned section as the corrected position. (Note 6) The aforementioned modification section is, The distortion correction device according to Appendix 5, which calculates the corrected position and attitude as the weighted average value of the forward position and attitude and the backward position and attitude in the aforementioned section. (Note 7) The distortion correction device is, A distortion correction device according to any one of the appendices 1 to 6, comprising a correction confirmation unit that acquires the corrected position and orientation and determines whether or not distortion remains in the corrected position and orientation. (Note 8) The aforementioned correction verification unit, A distortion correction device according to Appendix 7, which, upon determining that distortion remains in the corrected position and orientation, outputs a satellite mask for performing satellite mask processing on the section in the corrected position and orientation where distortion remains, wherein the section in the corrected position and orientation where distortion remains is defined as a satellite invisible section. (Note 9) The aforementioned correction verification unit, The distortion correction device according to Appendix 8, which, when it is determined that distortion remains in the corrected position and orientation, includes a section in which distortion remains in the corrected position and orientation, trajectory data of the moving body representing the corrected position and orientation in the section in which distortion remains in the corrected position and orientation, and point cloud data in the section in which distortion remains in the corrected position and orientation, and a display unit that displays a satellite mask processing necessity screen on a display device for receiving a request to perform the satellite mask processing. (Note 10) The aforementioned correction verification unit, A distortion correction device according to Appendix 9 that outputs the satellite mask when it receives a request to perform the satellite mask processing via the satellite mask processing necessity screen. (Note 11) In a distortion correction method used in a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile object, The distortion of the mobile body's position and orientation, which represents the self-position and orientation of the mobile body used in calculating the point cloud data, is detected as a factor in the distortion of the point cloud data. A distortion correction method for correcting the distortion of the position and orientation of the moving object. (Note 12) In a distortion correction program used in a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile object, A distortion detection process used in calculating the point cloud data, which detects the distortion of the mobile body's position and orientation that represents the self-position and orientation of the mobile body and is a factor in the distortion of the point cloud data, Correction process for correcting distortion of the position and orientation of the moving body, A distortion correction program that is executed by a computer. [Explanation of Symbols]

[0089] 41 Mobile object position and attitude, 42 Forward position and attitude, 43 Backward position and attitude, 44 Satellite visibility determination file, 50 Section, 51 First section, 52 Second section, 53 Corrected position and attitude, 54 Satellite mask, 60 Satellite mask processing requirement screen, 61 Distortion processing status display screen, 100 Distortion correction device, 110 Distortion detection unit, 111 First distortion detection unit, 112 Second distortion detection unit, 120 Correction unit, 130 Correction confirmation unit, 140 Display unit, 150 Storage unit, 200 Post-processing computer, 201 Point cloud data, 909 Electronic circuit, 910 Processor, 921 Memory, 922 Auxiliary storage device, 930 Input interface, 940 Output interface, 950 Communication device.

Claims

1. In a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile body, A distortion detection unit that detects the distortion of the mobile body's position and orientation, which represents the self-position and orientation of the mobile body used in calculating the point cloud data, and which is a factor in the distortion of the point cloud data; A correction unit corrects the distortion of the position and orientation of the moving body and outputs the self-position and orientation of the moving body obtained by correcting the distortion of the position and orientation of the moving body as the corrected position and orientation. Equipped with, The strain detection unit is A combined solution of the mobile body's position and orientation is obtained using the forward position and orientation, which is the self-position and orientation of the mobile body obtained by the forward processing, and the backward position and orientation, which is the self-position and orientation of the mobile body obtained by the backward processing. Distortion in the mobile body's position and orientation is detected based on the dependency ratio, which represents the ratio of the dependency between the forward processing and the backward processing in the combined solution. The aforementioned modification section is, A distortion correction device that corrects the distortion of the moving body's position and attitude based on the forward position and attitude and the backward position and attitude.

2. The strain detection unit is Output the section in which distortion was detected in the position and orientation of the moving object. The aforementioned modification section is, The distortion correction device according to claim 1, which corrects the distortion of the position and orientation of the moving body corresponding to the aforementioned section.

3. The strain detection unit is A first strain detection unit obtains the moving body position and attitude calculated using the forward position and attitude and the backward position and attitude, and outputs the time period in which a contradiction occurs between the change in the position of the moving body and the change in the attitude of the moving body as the interval, A second strain detection unit outputs the time period in which the dependency changes to a predetermined threshold or more as the interval. The distortion correction device according to claim 2, comprising:

4. The aforementioned modification section is, The distortion correction device according to claim 3, which corrects the distortion of the position and posture of the moving body in the section so that the position and posture of the moving body before and after the start of the section and the position and posture of the moving body before and after the end of the section are smoothly continuous.

5. The aforementioned modification section is, The distortion correction device according to claim 3 or 4, wherein in the aforementioned section, the average value of the forward position and the backward position is calculated as the corrected position and posture.

6. The aforementioned modification section is, The distortion correction device according to claim 5, wherein in the aforementioned section, the weighted average value of the forward position and the backward position and the position is calculated as the corrected position and the position.

7. The distortion correction device is, A distortion correction device according to any one of claims 1 to 4, further comprising a correction confirmation unit that acquires the corrected position and orientation and determines whether or not distortion remains in the corrected position and orientation.

8. The aforementioned correction verification unit, The distortion correction device according to claim 7, which, when it is determined that distortion remains in the corrected position and orientation, outputs a satellite mask for performing satellite mask processing on the section in the corrected position and orientation in which distortion remains, wherein the section in the corrected position and orientation in which distortion remains is defined as a satellite invisible section.

9. The aforementioned correction verification unit, The distortion correction device according to claim 8, which, when it is determined that distortion remains in the corrected position and orientation, includes a display unit that displays a satellite mask processing necessity screen on a display device, which includes the section in which distortion remains in the corrected position and orientation, trajectory data of the moving body representing the corrected position and orientation in the section in which distortion remains in the corrected position and orientation, and point cloud data in the section in which distortion remains in the corrected position and orientation, and accepts a request to perform the satellite mask processing.

10. The aforementioned correction verification unit, The distortion correction device according to claim 9, which outputs the satellite mask when it receives a request to perform the satellite mask processing via the satellite mask processing necessity screen.

11. In a distortion correction method used in a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile object, The distortion of the mobile body's position and orientation, which represents the self-position and orientation of the mobile body used in calculating the point cloud data, is detected as a factor in the distortion of the point cloud data. A distortion correction method for correcting the distortion of the position and orientation of the moving body, A combined solution of the mobile body's position and orientation is obtained using the forward position and orientation, which is the self-position and orientation of the mobile body obtained by the forward processing, and the backward position and orientation, which is the self-position and orientation of the mobile body obtained by the backward processing. Distortion in the mobile body's position and orientation is detected based on the dependency ratio, which represents the ratio of the dependency between the forward processing and the backward processing in the combined solution. A distortion correction method for correcting the distortion of the moving body's position and attitude based on the forward position and attitude and the backward position and attitude.

12. In a distortion correction program used in a distortion correction device that corrects the distortion of point cloud data calculated based on measurement data acquired by a measurement system mounted on a mobile object, A distortion detection process used in calculating the point cloud data, which detects the distortion of the mobile body's position and orientation that represents the self-position and orientation of the mobile body and is a factor in the distortion of the point cloud data, Correction process for correcting distortion of the position and orientation of the moving body, This is a distortion correction program that causes a computer to execute, The aforementioned strain detection process is: A combined solution of the mobile body's position and orientation is obtained using the forward position and orientation, which is the self-position and orientation of the mobile body obtained by the forward processing, and the backward position and orientation, which is the self-position and orientation of the mobile body obtained by the backward processing. Distortion in the mobile body's position and orientation is detected based on the dependency ratio, which represents the ratio of the dependency between the forward processing and the backward processing in the combined solution. The aforementioned correction process is: A distortion correction program that corrects the distortion of the moving body's position and attitude based on the forward position and attitude and the backward position and attitude.

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