Lidar error correction method, autonomous mobile device, medium and program product

Abstract

The present invention provides a laser radar error correction method, an autonomous mobile device, a medium and a program product, the method comprising: obtaining the angular velocity of the laser radar and the measured value of the scanning radius of the laser radar; searching the error parameters corresponding to the scanning radius and the angular velocity in the error lookup table of the laser radar; and correcting the measurement error of the laser radar according to the error parameters. The method of the present invention shortens the error determination time of the laser radar.

Description

Technical Field

[0001] The present invention relates to autonomous mobile device technology, and in particular to a laser radar error correction method, an autonomous mobile device, a medium and a program product. Background Art

[0002] In recent years, autonomous cleaning mobile devices have developed rapidly. For autonomous cleaning mobile devices, the most important point is to achieve efficient and comprehensive cleaning of the area to be cleaned.

[0003] When cleaning, the autonomous mobile device needs to sense obstacles. The autonomous mobile device obtains point cloud information through the laser radar, and then senses obstacles based on the point cloud information. Although the laser radar can obtain relatively stable point cloud information, there is still a certain measurement error. In order to eliminate the measurement error, the autonomous mobile device first determines the measurement error.

[0004] At present, the determination of measurement errors needs to be achieved through complex algorithms, which means that autonomous mobile devices need to spend a lot of time to determine the errors of the lidar, and the error determination time of the lidar is relatively long. Summary of the invention

[0005] The present invention provides a laser radar error correction method, an autonomous mobile device, a medium and a program product, which are used to solve the problem that the error determination time of the laser radar is long.

[0006] In one aspect, the present invention provides a laser radar error correction method, comprising:

[0007] Obtaining the angular velocity of the laser radar and the measurement value of the scanning radius of the laser radar;

[0008] In the error lookup table of the laser radar, searching for error parameters corresponding to the scanning radius and the angular velocity;

[0009] The measurement error of the laser radar is corrected according to the error parameter.

[0010] Further, the error lookup table is composed of error parameters related to the angular velocity and the scanning radius,

[0011] The error parameter is a correction value related to the angular velocity and the scanning radius.

[0012] Furthermore, the correction value is the arithmetic mean of multiple measurements of the laser radar under any combination of the angular velocity and the scanning radius in the error lookup table.

[0013] Furthermore, the correction value is a weighted average of multiple measurements of the laser radar under any combination of the angular velocity and the scanning radius in the error lookup table.

[0014] Furthermore, the error lookup table is composed of error parameters regarding the measured values ​​of the angular velocity and the scanning radius, wherein the error parameters are Gaussian distribution of the errors measured of the angular velocity and the scanning radius; and the Gaussian distribution includes a mean error and a distribution error.

[0015] Further, the error lookup table is composed of error parameters related to the measured values ​​of the angular velocity and the scanning radius, wherein the error parameters are mathematical distributions of the errors measured between the angular velocity and the scanning radius.

[0016] Furthermore, the mathematical distribution includes a Gaussian distribution, and the Gaussian distribution includes a mean error and a distribution error.

[0017] Furthermore, the error lookup table is composed of a first error lookup table and a second error lookup table.

[0018] The first error lookup table is a Gaussian distribution of radial differences between measured values ​​of different scanning radii and actual values ​​of the scanning radius obtained by multiple measurements of the laser radar in a stationary state or in a linear motion state, that is, a Gaussian distribution of radial errors, and the Gaussian distribution of radial errors includes a radial mean error and a radial distribution error;

[0019] Among them, the second error lookup table is the Gaussian distribution of the tangential difference between the measured values ​​of different scanning radii and the actual values ​​of the scanning radius obtained by multiple measurements when the laser radar rotates at different angular velocities, that is, the Gaussian distribution of the tangential error. The Gaussian distribution of the tangential error includes the tangential mean error and the tangential distribution error.

[0020] Furthermore, the measurement error of the laser radar is corrected according to the error parameter, including: obtaining the correction value through the error lookup table, adding the measurement value of the scanning radius of the laser radar to the correction value, and obtaining a corrected measurement value.

[0021] Further, correcting the measurement error of the laser radar according to the error parameter includes: obtaining the error parameters corresponding to the angular velocity and scanning radius of the current laser radar in the error lookup table, the error parameters including the first mean error and the first distribution error, and the first coordinates of the obstacle measured by the current laser radar;

[0022] Obtaining the error parameters corresponding to the angular velocity and scanning radius of the laser radar at the next moment in the error lookup table, wherein the error parameters include the second mean error and the second distribution error, and the second coordinate of the obstacle measured by the current laser radar;

[0023] The obstacle coordinates are corrected according to the first mean error, the first distribution error, and the first coordinates of the obstacle; the second mean error, the second distribution error, and the second coordinates.

[0024] Further, correcting the measurement error of the laser radar according to the error parameter includes: obtaining the error parameters corresponding to the angular velocity and scanning radius of the current laser radar in the error lookup table, the error parameters including the first mean error and the first distribution error, and the first coordinates of the obstacle measured by the current laser radar;

[0025] Obtaining the error parameters corresponding to the angular velocity and scanning radius of the laser radar at the next moment in the error lookup table, wherein the error parameters include the second mean error and the second distribution error, and the second coordinate of the obstacle measured by the current laser radar;

[0026] The obstacle coordinates are corrected according to the first mean error, the first distribution error, and the first coordinates of the obstacle; the second mean error, the second distribution error, and the second coordinates.

[0027] Further, correcting the measurement error of the laser radar according to the error parameter includes:

[0028] The measurement error of the laser radar is corrected according to the formula, the error parameter, and the obstacle coordinates, wherein:

[0029] The error parameters and the obstacle coordinates include: error parameters (μ1, σ1) and obstacle coordinates (x1, y1) at the current moment obtained according to the angular velocity and scanning radius of the laser radar, and error parameters (μ2, σ2) and obstacle coordinates (x2, y2) at the next moment obtained according to the angular velocity and scanning radius of the laser radar;

[0030] The formula is:

[0031] K=σ2(σ2+σ1) -1

[0032] μ′=μ2+K(μ1-μ2)

[0033] Among them, μ′ is a vector, and The corrected obstacle coordinates are (x, y).

[0034] On the other hand, the present invention provides a computer-readable storage medium, which stores computer execution instructions. When the computer execution instructions are executed by a processor, they are used to implement the laser radar error correction method as described above or the laser radar error correction method as described above.

[0035] On the other hand, the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the laser radar error correction method as described above or the laser radar error correction method as described above.

[0036] The laser radar error correction method, autonomous mobile device, medium and program product provided by the present invention obtain the angular velocity of the autonomous mobile device and the scanning radius of the laser radar of the autonomous mobile device, and search the scanning radius and the error parameters corresponding to the angular velocity in the error lookup table through the angular velocity and the scanning radius. The autonomous mobile device of the present invention stores an error lookup table, so that the autonomous mobile device can quickly determine the error parameters in the error lookup table according to its own angular velocity and the scanning radius of the laser radar, without the need to determine the error instantly through an algorithm, thereby shortening the error determination time of the laser radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0038] Figure 1 This is a system architecture diagram of the autonomous mobile device of the present invention;

[0039] Figure 2 It is a schematic diagram of a flow chart of an embodiment of a laser radar error correction method of the present invention;

[0040] Figure 3 It is a detailed flow chart of step S30 in another embodiment of the laser radar error correction method of the present invention;

[0041] Figure 4 Schematic diagram of the hardware structure of the autonomous mobile device of the present invention.

[0042] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0043] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0044] The points in the laser radar point cloud are represented by Gaussian distribution, and Gaussian distribution represents the probability density of the point at a fixed position. The mean error represents the point with the highest probability, which can be understood as the center of the point cloud; the distribution error, that is, the distribution of the probability density represented by the covariance matrix, can be understood as the radius of the point cloud distribution, so the mean error and distribution error can be used for the Gaussian distribution of the point cloud.

[0045] It should be noted that there are many mathematical distributions such as Poisson distribution, and in this disclosure only Gaussian distribution is used as an example for explanation.

[0046] The present invention provides a laser radar error correction method, which can be Figure 1 The autonomous mobile device shown is implemented as Figure 1 As shown, the autonomous mobile device 100 is provided with a laser radar 101. The laser radar 101 is arranged at the center of the autonomous mobile device, and the laser radar 101 is represented by a dotted line. The autonomous mobile device 100 can be any type of autonomous mobile device, such as a sweeping autonomous mobile device, a mopping autonomous mobile device, or a security autonomous mobile device. The autonomous mobile device 100 detects obstacles and indoor spaces through the laser radar 101 to construct an indoor map.

[0047] The following specific embodiments are used to describe in detail the technical solutions of the present invention and how the technical solutions of the present application solve the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0048] Reference Figure 2 , Figure 2 The laser radar error correction method of the present invention is an embodiment of the laser radar error correction method, which comprises the following steps:

[0049] Step S10, obtaining the measurement values ​​of the angular velocity of the laser radar in the autonomous mobile device and the scanning radius of the laser radar in the autonomous mobile device.

[0050] In this embodiment, the execution subject is an autonomous mobile device. The autonomous mobile device is equipped with a laser radar, and the autonomous mobile device senses the surrounding environment, for example, obstacles, through the laser radar. The laser radar can obtain relatively stable point cloud information, but there is still a certain measurement error. Therefore, the autonomous mobile device needs to correct the error of the laser radar.

[0051] Autonomous mobile devices need to obtain the angular velocity of the LiDAR. During the operation of the LiDAR, its internal laser receiver and transmitter collect 360° environmental information points to form a point cloud. The angular velocity here is the rotation speed of the LiDAR when it is working.

[0052] The autonomous mobile device needs to obtain a measurement value of a scanning radius of a laser radar. The measurement value of the scanning radius may be a distance measurement value between the laser radar itself and an obstacle.

[0053] Step S20, searching the error parameters corresponding to the scanning radius and angular velocity in the error lookup table of the laser radar.

[0054] Step S30, correcting the measurement error of the laser radar according to the error parameter.

[0055] In this embodiment, correcting the measurement error of the laser radar according to the error parameter specifically includes: obtaining a correction value through an error lookup table, where the correction value can be an arithmetic average or weighted average of multiple measurements of the laser radar under any angular velocity and scanning radius combination in the error lookup table, and adding the measurement value of the scanning radius of the laser radar to the correction value to obtain a corrected measurement value. The correction value can be a positive number or a negative number.

[0056] An error lookup table is stored in the autonomous mobile device, and the index of the error lookup table is the scanning radius and angular velocity. After obtaining the measured values ​​of the angular velocity and the scanning radius, the autonomous mobile device can find the error parameters corresponding to the angular velocity and the scanning radius in the error lookup table. The error parameters include correction values, which are the arithmetic mean or weighted mean of the data measured by the laser radar at the scanning radius and angular velocity. The measured data refers to the difference between the parameters measured at the scanning radius and angular velocity and the theoretical parameters. Each difference divided by the number of measurements is the arithmetic mean.

[0057] There will be many colors in the home where the autonomous mobile device is located. The colors can be white, gray, blue, etc. These colors have different laser reflectivity, which will affect the measurement accuracy of the lidar. First, the probability of different colors appearing in the home is determined through market research, and the probability of the color is set as the weight. When measuring, the autonomous mobile device determines the current scanned color, and then obtains the weight of the color. The weight is multiplied by the scanning radius and the difference between the measured parameters and the theoretical parameters under the angular velocity to obtain the product. By analogy, multiple products can be obtained. The weighted average can be obtained by adding up the products and dividing them by the number of measurements.

[0058] It should be mentioned that in the step of obtaining the angular velocity and scanning radius, there is a special case, that is, the angular velocity is zero, and the measured value of the scanning radius is not zero. At this time, the laser radar does not rotate, and measures the distance to the obstacle in a fixed direction.

[0059] In another embodiment, the error lookup table is composed of error parameters related to the angular velocity and the scanning radius, wherein the error parameter is a Gaussian distribution of radial errors measured by the angular velocity and the scanning radius; the Gaussian distribution includes a mean error and a distribution error.

[0060] The error lookup table in this embodiment may be composed of two different sub-error lookup tables, where the sub-error lookup table includes a first error lookup table and a second error lookup table.

[0061] The first error lookup table is a Gaussian distribution of radial differences between measured values ​​and actual distance values ​​of different scanning radii obtained by multiple measurements of the laser radar in a stationary state or in a linear motion state, i.e., a Gaussian distribution of radial errors, and the Gaussian distribution of radial errors includes radial mean errors and radial distribution errors. The above-mentioned laser radar in a stationary state or in a linear motion state may refer to the laser radar itself being in a stationary state or in a linear motion state, or the laser radar being in a stationary state or in a linear motion state when it is set on an autonomous mobile device.

[0062] Since the linear speed of the autonomous mobile device is much smaller than the laser speed, it can be assumed that the radial error of the autonomous mobile device is independent of the moving speed of the autonomous mobile device. Therefore, the radial error can be measured when the linear speed of the autonomous mobile device is zero.

[0063] The calibration process of the first error lookup table is as follows: set the laser radar to a fixed position and measure the distance of an obstacle in a fixed direction. Measure obstacles at the same distance to obtain the measured value of the scanning radius. Difference the measured value of the scanning radius and the actual value of the scanning radius to obtain the radial difference. Perform the above operation multiple times to obtain multiple radial differences, and then obtain a Gaussian distribution of radial errors about the current distance. The radial mean error of the Gaussian distribution of the radial error is the average of multiple differences, and the radial distribution error can be obtained by multiple radial differences. Change the obstacle distance and finally obtain a table of Gaussian distributions for different scanning radii. As shown in Table 1:, the radial mean error is μ i , the radial distribution error is σ i .

[0064] Table 1:

[0065]

[0066] Among them, the second error lookup table is the Gaussian distribution of the tangential difference between the measured values ​​and the actual distance values ​​at different scanning radii obtained by multiple measurements when the laser radar rotates at different angular velocities, that is, the Gaussian distribution of the tangential error. The Gaussian distribution of the tangential error includes the tangential mean error and the tangential distribution error.

[0067] The calibration process of the second error lookup table is as follows: set the laser radar to a constant angular velocity, measure the distance of an obstacle at this angular velocity, measure obstacles at the same distance, obtain the measured value of the scanning radius, and find the difference between the measured value of the scanning radius and the actual value of the scanning radius to obtain the tangential difference; perform the above operation multiple times to obtain multiple tangential differences, and then obtain a Gaussian distribution of the tangential error about the current distance. The tangential mean error of the Gaussian distribution of the tangential error is the average of multiple differences, and the tangential distribution error can be obtained by multiple tangential differences. Change the obstacle distance and the angular velocity of the laser radar rotation, and finally obtain a table of Gaussian distributions for different scanning radii and different angular velocities. As shown in Table 2, the tangential mean error is μ i , the tangential distribution error is σ i .

[0068] Table 2:

[0069]

[0070] The above-mentioned laser radar sets a constant angular velocity rotation speed, which may refer to that the laser radar itself is at a certain rotation speed, or it may refer to that when the laser radar is installed on an autonomous mobile device, the rotation speed of the laser radar itself and the rotation speed of the autonomous mobile device are combined.

[0071] In the embodiment, the error lookup table may be synthesized from two different sub-error lookup tables, and the sub-error lookup table includes a first error lookup table and a second error lookup table. The synthesis method is as follows:

[0072] First, obtain the Gaussian distribution (μ1, σ1) of the scanning radius d1 in the first error lookup table and the Gaussian distribution (μ1, σ1) of the scanning radius d1 and the angular velocity w1 in the second error lookup table. a , σ a ).

[0073] The error lookup table shows that the corresponding μ of the scanning radius d1 and the angular velocity w1 is μ=μ1+K(μ1-μ a ), σ=σ1-Kσ1;

[0074] Where K = σ1(σ1+σ a ) -1 .

[0075] Repeat the above steps to obtain the synthesized error lookup table.

[0076] In this embodiment, correcting the measurement error of the laser radar according to the error parameter includes: Figure 3 , that is, step S30 includes:

[0077] Step S31, obtaining the error parameters corresponding to the angular velocity and scanning radius of the current laser radar in the error lookup table, where the error parameters include a first mean error and a first distribution error, and a first coordinate of the obstacle measured by the current laser radar;

[0078] Step S32, obtaining the error parameters corresponding to the angular velocity and scanning radius of the laser radar at the next moment in the error lookup table, the error parameters including the second mean error and the second distribution error, and the second coordinates of the obstacle measured by the current laser radar;

[0079] Step S33, correcting the obstacle coordinates according to the first mean error, the first distribution error and the first coordinates of the obstacle; the second mean error, the second distribution error and the second coordinates.

[0080] Specifically, first obtain the error parameters (μ1, σ1) and obstacle coordinates (x1, y1) at the current moment according to the angular velocity and scanning radius of the laser radar, and then obtain the error parameters (μ2, σ2) and obstacle coordinates (x1, y1) at the next moment.

[0081] According to the conversion formula:

[0082] K=σ2(σ2+σ1) -1

[0083] μ′=μ2+K(μ1-μ2)

[0084] Among them, μ′ is a vector, and The corrected obstacle coordinates are (x, y).

[0085] Furthermore, the error parameters are the mean error and the distribution error. The coordinates of the obstacle detected by the lidar are corrected based on the mean error and the distribution error, and then the distance of the obstacle can be detected based on the corrected coordinates and the coordinates of the autonomous mobile device on the map.

[0086] Regarding μ′ being a vector, it should be noted that when the scanning radius is characterized by x and y, the error lookup table is a three-dimensional table, that is, the autonomous mobile device first uses the angular velocity as an index to find the sub-error tables corresponding to the angular velocity in the three-dimensional error table, and then uses x as an index to determine the target sub-error table in each sub-error table, and finally uses y as an index to find the mean error and the distribution error from the target sub-error table.

[0087] The distribution error is characterized by the covariance matrix. The covariance matrix is ​​expressed as:

[0088]

[0089] The mean error and distribution error are determined by the radial error and tangential error of the lidar. The radial error is the error in measuring the distance to obstacles when the autonomous mobile device is stationary or moving at a low speed. The radial error can be converted into errors on the x and y axes by transforming the polar coordinate system and the Cartesian coordinate system, thus forming f(x) and f(y) in the covariance matrix.

[0090] The tangential error refers to the error in measuring the distance to obstacles when the autonomous mobile device is rotating. The tangential error is f1(x, y), f2(x, y), and f1(x, y) = f2(x, y). The mean error can be obtained by directly superimposing the radial error and the tangential error.

[0091] The autonomous mobile device obtains the angular velocity of the laser radar and the scanning radius of the laser radar, and searches the mean error and the distribution error of the laser radar in the error table through the angular velocity and the scanning radius. The autonomous mobile device of the present invention stores an error table, so that the autonomous mobile device can quickly determine the mean error and the distribution error in the error table according to its own angular velocity and the scanning radius of the laser radar, without the need to determine the error instantly through an algorithm, which shortens the error determination time of the laser radar; in addition, the error of the laser radar is characterized by the mean error and the distribution error, and the mean error and the distribution error are determined by the radial error and the tangential error of the laser radar, which simplifies the error determination process, so that the autonomous mobile device can quickly establish an error table, further shortening the error determination time of the laser radar.

[0092] For ease of understanding, the calibration process of radial error and tangential error is briefly described below using a specific example.

[0093] A. Calibration of radial error:

[0094] The autonomous mobile device is stationary, and obstacles are placed at different radii of the autonomous mobile device. Assuming the measurement error is within 1m, obstacles are placed at intervals of 0.1m, and a total of 10 obstacles are placed at different radii. First, the real value, that is, the actual value of the scanning radius, is measured using a physical method. Assume that the actual values ​​of the scanning radius are:

[0095] ((0.1, 0.1), (0.2, 0.2), (0.3, 0.3), (0.4, 0.4), (0.5, 0.5), (0.6, 0.6), (0.7, 0.7), (0.8, 0.8), (0.9, 0.9), (1, 1)), where (0.1, 01) represents the theoretical value on x and the theoretical value on y. Read the value measured by the laser radar, that is, the measurement value of the scanning radius. Assume that the laser radar data is read 10 times at each scanning radius, and the average value is calculated using the 10 laser radar data. The average value is the measurement value of the scanning radius. Assume that the measured values ​​of each scanning radius are: A = ((0.11, 0.11), (0.22, 0.22), (0.33, 0.33), (0.44, 0.44), (0.55, 0.55), (0.66, 0.66), (0.77, 0.77), (0.88, 0.88), (0.99, 0.99), (1.1, 1.1)), and subtract them from the actual values ​​of the corresponding scanning radius to obtain the radial errors, which are:

[0096] ((0.01, 0.01), (0.02, 0.02), (0.03, 0.03), (0.04, 0.04), (0.05, 0.05), (0.06, 0.06), (0.07, 0.07), (0.08, 0.08), (0.09, 0.09), (0.1, 0.1)).

[0097] The radial distribution error is obtained by calculating each radial error, and the average value of each radial error is obtained as the radial mean error. The radial mean error and the radial distribution error constitute the Gaussian distribution in the first error lookup table. Here, the Gaussian distribution is represented by a covariance matrix, and the covariance matrix is:

[0098] B={(0.01, 0; 0, 0.01), (0.02, 0; 0, 0.02), (0.03, 0; 0, 0.03), (0.04, 0; 0, 0.04), (0.05, 0; 0, 0.05), (0.06, 0; 0, 0.06), (0.07, 0; 0, 0.07), (0.08, 0; 0, 0.08), (0.09, 0; 0, 0.09), (0.1, 0; 0, 0.1)}, then we can calculate G={N(A_1, B_1).....N(A_10, B_10)}.

[0099] B. Calibration of tangential error:

[0100] The autonomous mobile device rotates at different angular velocities. Assume that the autonomous mobile device rotates at 1 rad / m and obstacles are placed at different radius distances. Assume that the error within 1m is measured and obstacles are placed at intervals of 0.1m. A total of 10 obstacles are placed at different radius distances, and the actual value of the radius is scanned using physical methods. Assume that the actual values ​​of the scanned radius are: {(0.1, 0.1), (0.2, 0.2), (0.3, 0.3), (0.4, 0.4), (0.5, 0.5), (0.6, 0.6), (0.7, 0.7), (0.8, 0.8), (0.9, 0.9), (1, 1)}, read the value measured by the lidar, that is, the measured value of the scanned radius. Then change the angular velocity. Continue measuring.

[0101] Assume that at an angular velocity of 1 rad / m, the laser radar data is read 10 times at each scanning radius, and the average value is calculated using the 10 laser radar data. The average value is the tangential measurement value. The tangential measurement values ​​are:

[0102] {(0.11, 0.11), (0.22, 0.22), (0.33, 0.33), (0.44, 0.44), (0.55, 0.55), (0.66, 0.66), (0.77, 0.77), (0.88, 0.88), (0.99, 0.99), (1.1, 1.1)}.

[0103] Similarly, assuming that the angular velocity is 2 rad / m, read the laser radar data 10 times at each scanning radius, and use the 10 laser radar data to calculate the average value, which is the tangential measurement value. The tangential measurement values ​​are:

[0104] {(0.12, 0.11), (0.23, 0.24), (0.35, 0.36), (0.46, 0.47), (0.57, 0.58), (0.68, 0.66), (0.79, 0.72), (0.84, 0.86), (0.93, 0.96), (1.12, 1.11)}.

[0105] And so on, we can get the tangential measurement values ​​of different angular velocities.

[0106] Subtract the measured value of the scanning radius at the same angular velocity from the actual value of the scanning radius to obtain the tangential error. Assuming that the angular velocity is 1 rad / m, the tangential error is A1 = {(0.01, 0.01), (0.02, 0.02), (0.03, 0.03), (0.04, 0.04), (0.05, 0.05), (0.06, 0.06), (0.07, 0.07), (0.08, 0.08), (0.09, 0.09), (0.1, 0.1)};

[0107] Assume that the tangential error at a velocity of 2 rad / m is A2 = {(0.02, 0.01), (0.03, 0.04), (0.05, 0.06), (0.06, 0.07), (0.07, 0.08), (0.08, 0.06), (0.09, 0.02), (0.04, 0.06), (0.03, 0.06), (0.02, 0.01)}. And so on, the tangential errors at different angular velocities are obtained.

[0108] The tangential distribution error is obtained by calculating each tangential error, and the average value of each tangential error is obtained as the tangential mean error. The tangential mean error and the tangential distribution error constitute a second error lookup table. Assume that at a velocity of 1 rad / m the covariance matrix B1 = {(0.01, 0.01; 0.01, 0.01), (0.02, 0.02; 0.02, 0.02), (0.03, 0.03; 0.03, 0.03), (0.04, 0.03; 0.03, 0.04), (0.05, 0.03; 0.03, 0.05), (0.06, 0.05; 0.05, 0.06), (0.07, 0.05; 0.05, 0.07), (0.08, 0.08; 0.08, 0.08), (0.09, 0.08; 0.08, 0.09), (0.1, 0.08; 0.08, 0.1)};

[0109] Assuming that the velocity is 2rad / m, the covariance matrix B1={(0.01, 0.01; 0.01, 0.01), (0.02, 0.02; 0.02, 0.02), (0.03, 0.03; 0.03, 0.03), (0.04, 0.03; 0.03, 0.04), (0.05, 0.03; 0.03, 0.05), (0.06, 0.05; 0.05, 0.06), (0.07, 0.05; 0.05, 0.07), (0.08, 0.08; 0.08, 0.08), (0.09, 0.08; 0.08, 0.09), (0.1, 0.08; 0.08, 0.1)}

[0110] Then the Gaussian distribution of the second error lookup table is calculated as:

[0111] G1={N(A1_1, B1_1)....N(A1_10, B1_10)};

[0112] G2={N(A2_1, B2_1)....N(A2_10, B2_10)}.

[0113] The first error lookup table and the second error lookup table with the same scanning radius are convolved to obtain an error lookup table, thereby obtaining a three-dimensional error lookup table with angular velocity, x and y as indexes.

[0114] Figure 4 It is a block diagram of an autonomous mobile device according to an exemplary embodiment.

[0115] Reference Figure 4 , the autonomous mobile device may include: a processor 81, such as a CPU, a memory 82, and a laser radar 83. Those skilled in the art will appreciate that Figure 4 The structure shown in the figure does not constitute a limitation of the autonomous mobile device, and may include more or less components than shown, or combine certain components, or arrange components differently. The memory 82 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0116] The processor 81 can call the computer program stored in the memory 82 to complete the above-mentioned laser radar error correction method or all or part of the steps of the laser radar error correction method.

[0117] A non-temporary computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an autonomous mobile device, enables the autonomous mobile device to execute the above-mentioned laser radar error correction method or execute the above-mentioned or laser radar error correction method.

[0118] A computer program product comprises a computer program, which, when executed by a processor of an autonomous mobile device, enables the autonomous mobile device to perform the above-mentioned laser radar error correction method or perform the above-mentioned laser radar error correction method.

[0119] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be regarded as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0120] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A laser radar error correction method, characterized in that: include: Obtaining the angular velocity of the laser radar and the measurement value of the scanning radius of the laser radar; In the error lookup table of the laser radar, searching for error parameters corresponding to the scanning radius and the angular velocity; Correcting the measurement error of the laser radar according to the error parameter; The error lookup table is composed of error parameters related to the angular velocity and the scanning radius, wherein the error parameters are correction values ​​related to the angular velocity and the scanning radius; the correction value is the arithmetic mean of multiple measurements of the laser radar at any combination of the angular velocity and the scanning radius in the error lookup table; the correction value is the weighted average of multiple measurements of the laser radar at any combination of the angular velocity and the scanning radius in the error lookup table; or, The error lookup table is composed of error parameters about the measured values ​​of the angular velocity and the scanning radius, wherein the error parameters are the mathematical distribution of the errors measured by the angular velocity and the scanning radius; the mathematical distribution includes a Gaussian distribution, and the Gaussian distribution includes a mean error and a distribution error; the error lookup table is synthesized by a first error lookup table and a second error lookup table, wherein the first error lookup table is a Gaussian distribution of radial differences between measured values ​​of different scanning radii and actual values ​​of the scanning radius obtained by multiple measurements when the laser radar is in a stationary state or a linear motion state, that is, a Gaussian distribution of radial errors, and the Gaussian distribution of radial errors includes a radial mean error and a radial distribution error; wherein the second error lookup table is a Gaussian distribution of tangential differences between measured values ​​of different scanning radii and actual values ​​of the scanning radius obtained by multiple measurements when the laser radar rotates at different angular velocities, that is, a Gaussian distribution of tangential errors, and the Gaussian distribution of tangential errors includes a tangential mean error and a tangential distribution error.

2. The laser radar error correction method according to claim 1, characterized in that: Correcting the measurement error of the laser radar according to the error parameter includes: The correction value is obtained through the error lookup table, and the measured value of the scanning radius of the laser radar is added to the correction value to obtain a corrected measurement value.

3. The laser radar error correction method according to claim 1, characterized in that: Correcting the measurement error of the laser radar according to the error parameter includes: Obtaining error parameters corresponding to the angular velocity and scanning radius of the current laser radar in the error lookup table, wherein the error parameters include a first mean error and a first distribution error, and a first coordinate of the obstacle measured by the current laser radar; Obtaining the error parameters corresponding to the angular velocity and scanning radius of the laser radar at the next moment in the error lookup table, wherein the error parameters include the second mean error and the second distribution error, and the second coordinate of the obstacle measured by the current laser radar; The obstacle coordinates are corrected according to the first mean error, the first distribution error, and the first coordinates of the obstacle; the second mean error, the second distribution error, and the second coordinates.

4. The laser radar error correction method according to claim 3, characterized in that: Correcting the measurement error of the laser radar according to the error parameter includes: The measurement error of the laser radar is corrected according to the formula, the error parameter, and the obstacle coordinates, wherein: The error parameters and the obstacle coordinates include: the error parameters at the current moment obtained according to the angular velocity and scanning radius of the laser radar And the obstacle coordinates , and the error parameters of the next moment obtained according to the angular velocity and scanning radius of the laser radar And the obstacle coordinates ; The formula is: in, is a vector, and , the corrected obstacle coordinates are .

5. An autonomous mobile device, characterized in that: include: LiDAR, memory and processors; The laser radar is used to scan obstacles; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the laser radar error correction method as described in any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the laser radar error correction method as described in any one of claims 1 to 4.

7. A computer program product, characterized in that It includes a computer program, which, when executed by a processor, implements the laser radar error correction method as described in any one of claims 1 to 4.

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