A trajectory quality detection method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a trajectory quality detection method and device, electronic equipment and storage medium, relating to the technical field of autonomous driving, and particularly to the technical field of high-definition map. The specific implementation scheme is: modeling the motion trajectory of the collection vehicle to obtain a continuous time trajectory curve corresponding to the motion trajectory; using the continuous time trajectory curve, determining the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle; wherein the first estimated value is determined by the motion trajectory of the collection vehicle, and the second estimated value is determined by the measurement value of the first inertial measurement unit of the collection vehicle; and detecting the quality of the motion trajectory according to the overall difference. The present disclosure can realize the quality detection of the motion trajectory by using the inertial measurement unit.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of autonomous driving, and in particular to the technical field of high-definition map. BACKGROUND

[0002] High-definition map mapping required by autonomous driving is a process of modeling the environment by fusing multiple types of sensor data and recovering the motion trajectory of a map collection vehicle. The map collection vehicle uses sensors such as LiDAR (Laser Radar), IMU (Inertial Measurement Unit), wheel speed meter, GNSS (Global Navigation Satellite System), etc. to perform environment perception and motion measurement.

[0003] The quality of the motion trajectory of the collection vehicle has a direct impact on the quality of the high-definition map. Therefore, it is necessary to quality inspect the motion trajectory of the collection vehicle. SUMMARY

[0004] The present disclosure provides a trajectory quality detection method, device, electronic equipment and storage medium.

[0005] According to an aspect of the present disclosure, a trajectory quality detection method is provided, comprising:

[0006] modeling the motion trajectory of the collection vehicle to obtain a continuous time trajectory curve corresponding to the motion trajectory of the collection vehicle;

[0007] determining, by using the continuous time trajectory curve, an overall difference between a first estimated value and a second estimated value of the motion state of the collection vehicle; wherein the first estimated value is determined by the motion trajectory of the collection vehicle, and the second estimated value is determined by the measurement value of the first inertial measurement unit of the collection vehicle; and

[0008] detecting the quality of the motion trajectory according to the overall difference.

[0009] According to another aspect of the present disclosure, a trajectory quality detection device is provided, comprising:

[0010] a modeling module configured to model the motion trajectory of the collection vehicle to obtain a continuous time trajectory curve corresponding to the motion trajectory of the collection vehicle;

[0011] a determination module configured to determine, by using the continuous time trajectory curve, an overall difference between a first estimated value and a second estimated value of the motion state of the collection vehicle; wherein the first estimated value is determined by the motion trajectory of the collection vehicle, and the second estimated value is determined by the measurement value of the first inertial measurement unit of the collection vehicle; and

[0012] a detection module configured to detect the quality of the motion trajectory according to the overall difference.

[0013] According to another aspect of the present disclosure, an electronic device is provided, comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein

[0016] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any embodiment of the present disclosure.

[0017] According to another aspect of the present disclosure, a non-transitory computer readable storage medium storing computer instructions is provided, wherein the computer instructions are used to make the computer perform the method according to any embodiment of the present disclosure.

[0018] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method according to any embodiment of the present disclosure.

[0019] The present disclosure can utilize the measurement value of the inertial measurement unit to detect the quality of the motion trajectory of the collection vehicle.

[0020] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings are used to better understand the present scheme and do not limit the present disclosure. Among them:

[0022] Figure 1 is a schematic diagram of an application scenario of an embodiment of the present disclosure;

[0023] Figure 2 is a flowchart of the implementation of the trajectory quality detection method 200 according to an embodiment of the present disclosure;

[0024] Figure 3 is a schematic flowchart of determining the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle according to an embodiment of the present disclosure;

[0025] Figure 4 is a general framework diagram of the trajectory quality detection method according to an embodiment of the present disclosure;

[0026] Figure 5is a structural schematic diagram of a trajectory quality detection device 500 according to an embodiment of the present disclosure;

[0027] Figure 6 is a structural schematic diagram of a trajectory quality detection device 600 according to an embodiment of the present disclosure;

[0028] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0029] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to assist in understanding them. These should be considered in their context only as illustrative. Thus, those of ordinary skill in the art will recognize various changes and modifications of the embodiments described herein, without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0030] In the production of high-definition maps, the quality of the motion trajectory recovery of the collection vehicle determines the quality of the mapping. If the motion trajectory of the collection vehicle has local jumps, is not smooth, etc., it will often cause ghosting problems in mapping. Therefore, it is crucial to improve the quality of mapping by detecting the quality of the motion trajectory of the collection vehicle.

[0031] The collection vehicle is a mobile collection system precisely integrated by various advanced measurement sensors, generally including lidar, inertial navigation system (INS, Inertial Navigation System), camera, etc. Different types of sensor devices are mounted according to different collection scenarios, and map information is collected uninterruptedly to ensure that map data is always up-to-date.

[0032] Processing high-definition map data requires sorting, classifying and cleaning the original data collected by the collection vehicle, so as to obtain an initial map template without any semantic information or annotations. The processed data is usually point cloud data. After a three-dimensional point cloud map is made, semantic information needs to be labeled to provide for use by autonomous vehicles.

[0033] The embodiments of the present disclosure propose a trajectory quality detection method, which can detect the quality of the motion trajectory of the collection vehicle. Figure 1FIG. 1 is a schematic diagram of an application scenario of an embodiment of the present disclosure, including a collection vehicle 110, a production device 120, and a quality detection device 130. The collection vehicle 110 is configured to collect data on site to obtain basic data for generating a high-definition map. The production device 120 is configured to perform data labeling, extraction, calculation, and the like on the basic data collected by the collection vehicle 110 to generate a high-definition map. In the process of generating the high-definition map, the production device 120 simultaneously generates a motion trajectory of the collection vehicle. The quality detection device 130 is configured to perform quality detection on the motion trajectory of the collection vehicle. The quality detection device 130 can perform the trajectory quality detection method according to an embodiment of the present disclosure to perform quality detection on the motion trajectory of the collection vehicle. In some examples, the collection vehicle 110, the production device 120, and the quality detection device 130 can transmit data through a wired or wireless network.

[0034] Figure 2 FIG. 2 is an implementation flowchart of a trajectory quality detection method 200 according to an embodiment of the present disclosure, including the following steps.

[0035] S210, modeling the motion trajectory of the collection vehicle to obtain a continuous-time trajectory curve corresponding to the motion trajectory.

[0036] S220, determining an overall difference between a first estimated value and a second estimated value of the motion state of the collection vehicle by using the continuous-time trajectory curve, wherein the first estimated value can be determined by the motion trajectory of the collection vehicle, and the second estimated value can be determined by a measurement value of a first inertial measurement unit of the collection vehicle; and

[0037] S230, detecting the quality of the motion trajectory according to the overall difference.

[0038] The first inertial measurement unit (IMU) can refer to an IMU fixedly installed on the collection vehicle. A general IMU is composed of a three-axis gyroscope and a three-axis accelerometer. The three-axis gyroscope can be used to detect angular velocity, and the three-axis accelerometer can be used to detect acceleration. The first IMU of the collection vehicle is used to measure the measurement value of the motion state of the collection vehicle, including data at multiple time points. Each time point data includes angular velocity and angular velocity information.

[0039] The embodiment of the present disclosure can use the measurement value of the IMU installed on the collection vehicle to perform quality detection on the motion trajectory of the collection vehicle. Since the data amount of the IMU data is small and the IMU data is not disturbed by the environment, the trajectory quality detection method according to the embodiment of the present disclosure can improve the quality and efficiency of quality detection.

[0040] The motion state of the collection vehicle includes acceleration of the collection vehicle and angular velocity of the collection vehicle.

[0041] In some embodiments, the overall difference (also referred to as residual, hereinafter referred to as overall difference) between the estimated value of the motion state of the vehicle and the measured value of the motion state of the vehicle is determined by the acceleration difference and the angular velocity difference; wherein,

[0042] The acceleration difference includes the difference between the acceleration determined by the motion trajectory of the vehicle and the acceleration determined by the first inertial measurement unit;

[0043] The angular velocity difference includes the difference between the angular velocity determined by the motion trajectory of the vehicle and the angular velocity determined by the first inertial measurement unit.

[0044] Wherein, the first IMU can measure the acceleration and angular velocity at multiple time points.

[0045] In some examples, the acceleration difference can be referred to as acceleration residual, and in the following content, the acceleration difference is represented by r a ; the angular velocity difference can be referred to as angular velocity residual, and in the following content, the angular velocity difference is represented by r ω .

[0046] In some embodiments, the continuous-time trajectory curve is also referred to as B-spline curve. In some examples, in the above step S210, the embodiments of the present disclosure can optimize the control point state of a continuous-time trajectory curve by using the motion trajectory of the vehicle, so as to obtain the continuous-time trajectory curve (or continuous-time trajectory, or B-spline curve) corresponding to the motion trajectory, so that the continuous-time trajectory curve is substantially coincident with the motion trajectory of the vehicle. The shape of the B-spline curve is calculated by the control point. The motion trajectory of the vehicle can be approximately modeled by the B-spline curve, and the purpose is to facilitate the calculation of the speed, acceleration and other information of different positions of the motion trajectory, so as to determine the overall difference between the first estimated value and the second estimated value of the motion state of the vehicle in the subsequent steps, and to be used for quality detection of the motion trajectory.

[0047] Specifically, in some examples, the continuous-time trajectory curve can include a rotation state curve and a translation state curve; that is, two B-spline curves can be used to model the rotation and translation motion processes of the vehicle, respectively.

[0048] For example, traj = {traj rotation , traj translation}; wherein, traj is the continuous-time trajectory curve, traj rotation represents the rotation state curve (or rotation B-spline curve), and traj translation represents the translation state curve (or translation B-spline curve).

[0049] For traj rotation The initialization process is equivalent to solving the optimization problem represented by the following equation (1):

[0050]

[0051] in, This is the initialization result of the rotated B-spline curve. It utilizes the rotated B-spline curve traj rotation Calculated t i The rotation state at any given moment, t is calculated using the movement trajectory of the collected vehicle. i The rotation state at time t, and angle is a function that calculates the angle between two rotation states.

[0052] For traj translation The initialization process is equivalent to solving the optimization problem represented by the following equation (2):

[0053]

[0054] in, This is the initialization result of translating the B-spline curve. It utilizes the translation of B-spline curves traj translation Calculated t i The translation state at any given moment, t is calculated using the initial trajectory of the map. i The translation state at time t, and distance is a function that calculates the distance between two translation states.

[0055] like Figure 3 As shown, in some embodiments, in a trajectory quality detection method according to an embodiment of this disclosure, the overall difference between a first estimate and a second estimate of the motion state of the vehicle is determined using a continuous-time trajectory curve, including:

[0056] S310. Using the rotational state curve and the translational state curve, determine the acceleration difference (r). a The expression for ) is given, and the angular velocity difference (r) is determined using the rotational state curve. ω The expression;

[0057] S320. Using the expressions for angular velocity difference and acceleration difference, determine the expression for overall difference;

[0058] S330. Determine the minimum value of the expression for the overall difference, and take the minimum value as the overall difference.

[0059] The expression for the overall difference can be adopted as follows: represents; wherein,

[0060] ∑ a is a covariance matrix of acceleration measurements, related to characteristics of the inertial measurement unit;

[0061] ∑ g is a covariance matrix of angular velocity measurements, related to characteristics of the inertial measurement unit;

[0062]

[0063]

[0064] In the above manner, the rotational B-spline curve and the translational B-spline curve are used to determine the angular velocity difference and the acceleration difference respectively by a relatively simple manner, so as to determine the expression of the overall difference in the embodiment of the present disclosure.

[0065] In some embodiments, at least one of the gravitational acceleration, the acceleration bias of the first inertial measurement unit and the angular velocity bias of the first inertial measurement unit is adjusted to minimize the value of the expression of the overall difference; therefore, the process of solving the minimum value of the overall difference expression is also the process of solving the optimization problem. That is, the parameters that affect the value of the overall difference are adjusted (including adjusting the gravitational acceleration, the acceleration bias of the first inertial measurement unit and / or the angular velocity bias of the first inertial measurement unit), so that the value of the overall difference after adjustment is minimized, and the minimum value is the overall difference. It can be seen that the trajectory detection problem is converted into the process of solving the optimization problem in the embodiment of the present disclosure, so as to realize the quality detection of the motion trajectory by using the measurement value of the inertial measurement unit (IMU). In some embodiments, at least one of the gravitational acceleration, the acceleration bias of the first inertial measurement unit and the angular velocity bias of the first inertial measurement unit is adjusted to minimize the value of the expression of the overall difference; therefore, the process of solving the minimum value of the overall difference expression is also the process of solving the optimization problem. That is, the parameters that affect the value of the overall difference are adjusted (including adjusting the gravitational acceleration, the acceleration bias of the first inertial measurement unit and / or the angular velocity bias of the first inertial measurement unit), so that the value of the overall difference after adjustment is minimized, and the minimum value is the overall difference. It can be seen that the trajectory detection problem is converted into the process of solving the optimization problem in the embodiment of the present disclosure, so as to realize the quality detection of the motion trajectory by using the measurement value of the inertial measurement unit (IMU).

[0066] In the case that the overall difference is less than or equal to a predetermined threshold, it is determined that the quality of the motion trajectory is qualified; or in the case that the overall difference is greater than the predetermined threshold, it is determined that the quality of the motion trajectory is unqualified.

[0067] The predetermined threshold can be determined by the noise of the acceleration measurement value and the noise of the angular velocity measurement value. For example, the predetermined threshold can be set as the sum of N1 times of the noise of the acceleration measurement value and N2 times of the noise of the angular velocity measurement value, wherein N1 and N2 are positive numbers.

[0068] In summary, the implementation process of the trajectory quality detection method proposed in the embodiment of the present disclosure is as follows:

[0069] Referring to Figure 4 , Figure 4 ​is a whole framework diagram of a trajectory quality detection method according to an embodiment of the present disclosure. In the trajectory quality detection process of the embodiment of the present disclosure, firstly, a motion trajectory of a collection vehicle is acquired, and the motion trajectory of the collection vehicle is collected for modeling to obtain a continuous time trajectory curve (a B-spline curve) corresponding to the motion trajectory. The B-spline curve can include a rotation B-spline curve and a translation B-spline curve. Then, the expression (r a ) of an acceleration difference and the expression (r ω ) of an angular velocity difference are determined by using the B-spline curve and the measurement value of the IMU. Then, according to r a and r ω , the expression of the overall difference between a first estimated value and a second estimated value is determined, wherein the first estimated value is determined by the motion trajectory of the collection vehicle, and the second estimated value is determined by the measurement value of the IMU of the collection vehicle. Finally, the minimum value of the expression of the overall difference is determined by solving an optimization problem, and it is determined whether the minimum value is less than or equal to a predetermined threshold value; if it is less than or equal to the predetermined threshold value, it is determined that the quality of the motion trajectory is qualified; otherwise, it is determined that the quality of the motion trajectory is unqualified.

[0070] The embodiment of the present disclosure can use one or more IMUs to realize the quality detection of the motion trajectory of the collection vehicle. The following respectively introduces the method of using two IMUs to realize the quality detection and the method of using one IMU to realize the quality detection.

[0071] Method one: using two IMUs to realize quality detection.

[0072] In this method, the motion trajectory of the collection vehicle is equivalent to the motion trajectory of the second inertial measurement unit of the collection vehicle, wherein the first inertial measurement unit and the second inertial measurement unit are two different inertial measurement units of the collection vehicle.

[0073] In the case of installing two IMUs on the collection vehicle, this method can fully utilize the measurement values of the two IMUs to detect the quality of the motion trajectory of the collection vehicle, so as to improve the detection success rate. For example, the measurement value of the first IMU can be used to detect the quality of the trajectory (i.e. the motion trajectory of the collection vehicle) of the second IMU.

[0074] In the following description, the first IMU is denoted as I2, and the second IMU is denoted as I1.

[0075] Since the trajectory to be detected is the motion state of a certain IMU on the collection vehicle, in order to use the measurement value of another IMU to detect the quality of the motion trajectory, a relationship model between the measurement value of the different IMU sensors and the trajectory curve needs to be established, for example:

[0076] The pose state of I1 in the global coordinate system at time t can be expressed as formula (3):

[0077]

[0078] wherein, represents the pose state of I1 in the global coordinate system at time t;

[0079] represents the rotation matrix in the motion trajectory of I1;

[0080] represents the translation component in the motion trajectory of I1;

[0081] G represents the global coordinate system.

[0082] The pose state of I2 in the global coordinate system at time t can be represented by formula (4):

[0083]

[0084] wherein, represents the pose state of I2 in the global coordinate system at time t;

[0085] represents the rotation matrix in the motion trajectory of I2;

[0086] represents the translation component in the motion trajectory of I2;

[0087] G represents the global coordinate system.

[0088] Suppose I1 and I2 are fixedly connected to the vehicle body of the collection vehicle, and the vehicle body is a rigid body, then the external parameters (external parameters) between the two IMUs can be represented by formula (5):

[0089]

[0090] wherein, represents the external parameters between I1 and I2;

[0091] represents the rotation matrix;

[0092] represents the relative position relationship of I1 and I2 in space.

[0093] According to the definition of , there is the following formula (6-1):

[0094]

[0095] Using formulas (3), (4), (5), formula (6-1) can be expanded and calculated to obtain the following formula (6-2):

[0096]

[0097] From equation (6-2), we can get the following two equations:

[0098]

[0099]

[0100] where equation (6-3) can be considered as the rotation component part, and equation (6-4) can be considered as the translation component part. Using equation (6-3) and (6-4) respectively, we can get the expression of angular velocity difference (r ω ) and the expression of acceleration difference (r a ) respectively. Specifically, it includes the following first part and second part.

[0101] First part: using equation (6-3), we get the expression of angular velocity difference (r ω ). For example:

[0102] Taking the derivative of both sides of equation (6-3) with respect to time t, we get equation (7):

[0103]

[0104] where ω1, ω2 are the angular velocities of I1 and I2 in their respective local coordinate systems. Therefore, we have:

[0105]

[0106] where the symbol [] × represents the conversion of a vector into an anti-symmetric matrix.

[0107] As can be seen, equation (8) shows the relationship between the angular velocity of I1 and the angular velocity of I2, i.e., the angular velocity of I2 is a function of the angular velocity of I1 and the rotation component of the external parameter between the two IMUs.

[0108] From equation (8), we can get the following equation (9):

[0109]

[0110] From equation (9), we can get the following equation (10):

[0111]

[0112] It can be seen that formula (10) shows the relationship between the theoretical value (or true value) of the angular velocity of I1 and the theoretical value of the angular velocity of I2, that is, the theoretical value of the angular velocity of I1 is equal to the product of the theoretical value of the angular velocity of I2 and the rotation component of the external parameter between the two IMUs.

[0113] Considering the actual measurement model of the IMU angular velocity, there is the following relationship:

[0114]

[0115] wherein, represents the measured value of the angular velocity of I2;

[0116] represents the zero offset of the angular velocity of I2;

[0117] represents the noise of the angular velocity of I2;

[0118] In combination with formula (10) and (11), the relationship between the true value of the angular velocity of I1 can be established with the measured value of the angular velocity of I2. The true value of the angular velocity of I1 can be calculated by the motion trajectory of I1 (i.e., the motion trajectory of the collection vehicle), which is represented by the following formula (12):

[0119]

[0120] The expression of the angular velocity difference (r ω ) is defined as the following formula (13):

[0121]

[0122] From satisfies the normal distribution, that is,

[0123] There is

[0124] In the above formula (13), ω1 is the angular velocity calculated by the motion trajectory of I1 (the second IMU), is the angular velocity calculated by the angular velocity measurement value of I2 (the first IMU). If the motion trajectory of I1 (i.e., the motion trajectory of the collection vehicle) is accurate, the difference between the two (i.e., r ω ) should be small. Therefore, the embodiment of the present disclosure can take r ω as a standard for quality detection of the motion trajectory of the collection vehicle.

[0125] As can be seen from the above, in some embodiments, the angular velocity difference (r ωThe expression of the acceleration difference (r The angular velocity zero offset of the first inertial measurement unit and the rotation matrix between the first inertial measurement unit and the second inertial measurement unit at least one of the angular velocity true value (ω1) of the second inertial measurement unit, the angular velocity measurement value of the first inertial measurement unit

[0126] wherein the angular velocity true value (ω1) of the second inertial measurement unit can be determined by the rotation state curve. Second part: using equation (6-4), the expression of the acceleration difference (r a ) is obtained. For example:

[0127] Firstly, the content of equation (6-4) is:

[0128] Deriving the left and right sides of the above formula with respect to time t, formula (14) is obtained:

[0129]

[0130] wherein, denotes the derivation of with respect to time t;

[0131] denotes the derivation of with respect to time t;

[0132] denotes the derivation of with respect to time t;

[0133] the symbol [] × denotes the conversion of the vector into an anti-symmetric matrix.

[0134] Continuing to derive the left and right sides of the above formula with respect to time t, formula (15) is obtained

[0135]

[0136] wherein, denotes the derivation of with respect to time t;

[0137] denotes the derivation of ω1 with respect to time t;

[0138] denotes the derivation of with respect to time t.

[0139] Continuing to operate formula (15), the following formula (16) can be obtained:

[0140]

[0141] wherein, represents the true value of the acceleration of I2 in the global coordinate system;

[0142] represents the true value of the acceleration of I1 in the global coordinate system;

[0143] represents the rotation matrix in the motion trajectory of I1;

[0144] Symbol [] × represents the conversion of a vector into an anti-symmetric matrix;

[0145] Considering the actual measurement model of the IMU acceleration, the following relationship exists:

[0146]

[0147] wherein, represents the rotation matrix in the motion trajectory of I2;

[0148] is the measured value of the acceleration of I2

[0149] represents the acceleration bias of I2;

[0150] represents the noise of the acceleration of I2;

[0151] g G represents the gravitational acceleration.

[0152] The expression of the acceleration difference (r a ) is as follows:

[0153]

[0154] is satisfied by a normal distribution, i.e.

[0155]

[0156] In the above expression (18), is the acceleration calculated through the motion trajectory of I1 (the second IMU), is the acceleration calculated through the acceleration measurement value of I2 (the first IMU). If the motion trajectory of I1 (i.e. the motion trajectory of the collection vehicle) is accurate, the difference between the foregoing two (i.e. r a ) should be small. Therefore, the present disclosure can take r a as a standard for quality detection of the motion trajectory of the collection vehicle. ​

[0157] As can be seen from the above, in some embodiments, the expression of the acceleration difference (r a ) can be determined by the rotation matrix of the second inertial measurement unit in the global coordinate system the true value of the angular velocity of the second inertial measurement unit (ω1), the relative position relationship between the first inertial measurement unit and the second inertial measurement unit in space the true value of the acceleration of the second inertial measurement unit in the global coordinate system the rotation matrix between the first inertial measurement unit and the second inertial measurement unit the acceleration measurement value of the first inertial measurement unit the acceleration bias of the first inertial measurement unit and at least one of the gravitational acceleration (g G ) is determined; wherein,

[0158] the rotation matrix of the second inertial measurement unit in the global coordinate system is determined by the rotation state curve; or,

[0159] the true value of the angular velocity of the second inertial measurement unit (ω1) is determined by the rotation state curve; or,

[0160] the true value of the acceleration of the second inertial measurement unit in the global coordinate system is determined by the translation state curve.

[0161] The expression of the angular velocity difference (r ω ) and the expression of the acceleration difference (r a ) determined by the above-mentioned embodiments can determine the expression of the overall difference between the first estimated value and the second estimated value of the motion state of the vehicle. Then, the minimum value of the expression of the overall difference is determined, and the minimum value is taken as the overall difference. As can be seen, determining the minimum value of the expression of the overall difference is essentially constructing an optimization problem based on the continuous-time trajectory curve, which can be represented by equation (19):

[0162]

[0163] where t represents the time;

[0164]

[0165]

[0166] represents the value of that minimizes the value of .

[0167] In determining At the same time, the minimum value of The minimum value of The minimum value of the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle is the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle. In the case where the overall difference is less than or equal to a predetermined threshold, the quality of the motion trajectory of the collection vehicle (i.e., the motion trajectory of I1) is determined to be qualified; in the case where the overall difference is greater than the predetermined threshold, the quality of the motion trajectory of the collection vehicle (i.e., the motion trajectory of I1) is determined to be unqualified.

[0168] In this way, since the external parameters between different IMU sensors are used, it is necessary to ensure that the external parameters between different IMUs have no obvious errors. In a specific implementation, since different IMUs are in the same gravitational field and the global coordinate system is unique, the gravitational acceleration of different IMU sensors in the global coordinate system is the same, so the same value can be set for different IMU sensors when estimating the gravitational acceleration parameter. For different IMUs, the gravitational acceleration parameters are the same.

[0169] If the gravitational acceleration is known (such as obtained directly through the global projection coordinate system (UTM, Universal Transverse Mercator) of the IMU), the detection accuracy can also be improved using this method.

[0170] As can be seen, in the above implementation, two residual terms are combined to construct an optimization problem, and the variables of the optimization problem are the zero bias of the IMU and the gravitational acceleration.

[0171] Method two: using one IMU to implement quality detection.

[0172] In this way, the motion trajectory of the collection vehicle is equivalent to the motion trajectory of the first inertial measurement unit of the collection vehicle.

[0173] In the case where one IMU is installed on the collection vehicle, this way can use the measurement value of the IMU to detect the quality of the motion trajectory of the collection vehicle (i.e., the motion trajectory of the IMU). Since only one IMU is used, in the following description, the first IMU and the second IMU are not distinguished, and I2 and I1 are not distinguished.

[0174] Considering the measurement model of the IMU, in some implementations, the expression of the angular velocity difference (r ω ) can be determined by at least one of the angular velocity The angular velocity measurement value of the first inertial measurement unit The angular velocity zero bias (b ω ) of the first inertial measurement unit

[0175] angular velocity of the first inertial measurement unit in the local coordinate system determined by the rotation state curve.

[0176] For example, the expression of the angular velocity difference (r ω ) can be represented by the following equation (20):

[0177]

[0178] In some embodiments, the expression of the acceleration difference (r a ) can be determined by the orientation (q true acceleration of the first inertial measurement unit in the global coordinate system acceleration measurement value of the first inertial measurement unit acceleration bias (b a ) of the first inertial measurement unit, and the gravitational acceleration (g G ); wherein,

[0179] the orientation (q determined by the rotation state curve; or,

[0180] true acceleration of the first inertial measurement unit in the global coordinate system determined by the translation state curve.

[0181] For example, the expression of the acceleration difference (r a ) can be represented by the following equation (21):

[0182]

[0183] The expression of the angular velocity difference (r ω ) and the expression of the acceleration difference (r a ) determined by the above embodiments can be used to determine the expression of the overall difference between the first estimate and the second estimate of the motion state of the vehicle; then, the minimum value of the expression of the overall difference is determined, and the minimum value is taken as the overall difference. It can be seen that determining the minimum value of the expression of the overall difference is essentially constructing an optimization problem based on the continuous-time trajectory curve, which can be represented by equation (22):

[0184]

[0185] wherein, t represents the time;

[0186]

[0187]

[0188] representing minimizing g G , (b a , b ω ) values.

[0189] While determining , the minimum value of is determined, the minimum value of is the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle. In the case that the overall difference between the first estimated value and the second estimated value of the motion state of the collection vehicle is less than or equal to a predetermined threshold, it is determined that the quality of the motion trajectory of the collection vehicle (i.e., the motion trajectory of the IMU) is qualified; in the case that the overall difference is greater than the predetermined threshold, it is determined that the quality of the motion trajectory of the collection vehicle (i.e., the motion trajectory of the IMU) is unqualified.

[0190] The present approach can use one IMU to detect the quality of the motion trajectory of the collection vehicle, thereby improving the detection effect and efficiency while reducing the requirements for the equipment of the collection vehicle.

[0191] The present disclosure further provides a trajectory quality detection device, Figure 5 is a structural schematic diagram of a trajectory quality detection device 500 according to an embodiment of the present disclosure, comprising:

[0192] a modeling module 510 configured to model the motion trajectory of the collection vehicle to obtain a continuous time trajectory curve corresponding to the motion trajectory;

[0193] a determination module 520 configured to determine an overall difference between a first estimated value and a second estimated value of the motion state of the collection vehicle by using the continuous time trajectory curve; wherein the first estimated value is determined by the motion trajectory of the collection vehicle, and the second estimated value is determined by the measurement value of the first inertial measurement unit of the collection vehicle; and

[0194] a detection module 530 configured to detect the quality of the motion trajectory according to the overall difference.

[0195] In some embodiments, the overall difference is determined by an acceleration difference and an angular velocity difference; wherein,

[0196] the acceleration difference comprises a difference between the acceleration determined by the motion trajectory of the collection vehicle and the acceleration determined by the first inertial measurement unit;

[0197] the angular velocity difference comprises a difference between the angular velocity determined by the motion trajectory of the collection vehicle and the angular velocity determined by the first inertial measurement unit.

[0198] In some embodiments, the continuous-time trajectory curve comprises a rotation state curve and a translation state curve.

[0199] Figure 6 is a structural schematic diagram of a trajectory quality detection device 600 according to an embodiment of the present disclosure, as shown in Figure 6 In some embodiments, the determination module 520 comprises:

[0200] a first determination sub-module 521 configured to determine an expression of the acceleration difference by using the rotation state curve and the translation state curve, and determine an expression of the angular velocity difference by using the rotation state curve;

[0201] a second determination sub-module 522 configured to determine an expression of the overall difference by using the expression of the acceleration difference and the expression of the angular velocity difference;

[0202] a minimum value determination sub-module 523 configured to determine a minimum value of the expression of the overall difference, and take the minimum value as the overall difference.

[0203] In some embodiments, the minimum value determination sub-module 523 is configured to,

[0204] adjust at least one of the gravitational acceleration, the acceleration zero offset of the first inertial measurement unit, and the angular velocity zero offset of the first inertial measurement unit, so that the expression of the overall difference reaches the minimum value.

[0205] In some embodiments, the motion trajectory of the collection vehicle is equivalent to the motion trajectory of a second inertial measurement unit of the collection vehicle; the first inertial measurement unit and the second inertial measurement unit are two different inertial measurement units of the collection vehicle.

[0206] In some embodiments, the expression of the acceleration difference is determined by at least one of a rotation matrix of the second inertial measurement unit in a global coordinate system, an angular velocity true value of the second inertial measurement unit, a relative position relationship between the first inertial measurement unit and the second inertial measurement unit in space, an acceleration true value of the second inertial measurement unit in the global coordinate system, a rotation matrix between the first inertial measurement unit and the second inertial measurement unit, an acceleration measurement value of the first inertial measurement unit, an acceleration zero offset of the first inertial measurement unit, and a gravitational acceleration; wherein,

[0207] the rotation matrix of the second inertial measurement unit in the global coordinate system is determined by the rotation state curve; or,

[0208] the angular velocity true value of the second inertial measurement unit is determined by the rotation state curve; or,

[0209] The acceleration true value of the second inertial measurement unit in the global coordinate system is determined by the translation state curve.

[0210] In some embodiments, the expression of the angular velocity difference is determined by at least one of the angular velocity true value of the second inertial measurement unit, the angular velocity measurement value of the first inertial measurement unit, the angular velocity bias of the first inertial measurement unit, and the rotation matrix between the first inertial measurement unit and the second inertial measurement unit.

[0211] The angular velocity true value of the second inertial measurement unit is determined by the rotation state curve.

[0212] In some embodiments, the motion trajectory of the collection vehicle is equivalent to the motion trajectory of the first inertial measurement unit of the collection vehicle.

[0213] In some embodiments, the expression of the acceleration difference is determined by at least one of the orientation of the first inertial measurement unit, the acceleration true value of the first inertial measurement unit in the global coordinate system, the acceleration measurement value of the first inertial measurement unit, the acceleration bias of the first inertial measurement unit, and the gravitational acceleration; wherein,

[0214] The orientation of the first inertial measurement unit is determined by the rotation state curve; or,

[0215] The acceleration true value of the first inertial measurement unit in the global coordinate system is determined by the translation state curve.

[0216] In some embodiments, the expression of the angular velocity difference is determined by at least one of the angular velocity of the first inertial measurement unit in the local coordinate system, the angular velocity measurement value of the first inertial measurement unit, and the angular velocity bias of the first inertial measurement unit; wherein,

[0217] The angular velocity of the first inertial measurement unit in the local coordinate system is determined by the rotation state curve.

[0218] In some embodiments, the detection module 530 is configured to:

[0219] In a case where the overall difference is less than or equal to a predetermined threshold, determining that the quality of the motion trajectory is qualified;

[0220] Or, in a case where the overall difference is greater than the predetermined threshold, determining that the quality of the motion trajectory is unqualified;

[0221] In some embodiments, the predetermined threshold is determined by the noise of the acceleration measurement value of the collection vehicle and the noise of the angular velocity measurement value of the collection vehicle.

[0222] The specific functions and examples of the modules and sub-modules of the apparatuses in the embodiments of the present disclosure are described in the related description of the corresponding steps in the method embodiments, which will not be described here.

[0223] In the technical solutions of the present disclosure, the acquisition, storage and application of user personal information comply with relevant laws and regulations and do not violate public order and good customs.

[0224] According to the embodiments of the present disclosure, the present disclosure further provides an electronic device, a readable storage medium and a computer program product.

[0225] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed in this document.

[0226] As shown in Figure 7 The device 700 includes a computing unit 701 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0227] A plurality of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a magnetic disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0228] The computing unit 701 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 701 performs various methods and processes described above, such as the trajectory quality detection method. For example, in some embodiments, the trajectory quality detection method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded onto the RAM 703 and executed by the computing unit 701, one or more steps of the trajectory quality detection method described above can be performed. Alternatively, in other embodiments, the computing unit 701 can be configured to perform the trajectory quality detection method by any other appropriate means, such as by means of firmware.

[0229] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0230] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0231] In the context of this disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0232] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0233] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0234] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0235] It should be understood that the various forms of flow shown above can be used to reorder, add, or delete steps. For example, the steps described in the present disclosure can be performed in parallel, in series, or in a different order, as long as the desired results of the technology disclosed in the present disclosure can be achieved, which is not limited herein.

[0236] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A trajectory quality detection method, comprising: The motion trajectory of the vehicle is modeled to obtain the continuous time trajectory curve corresponding to the motion trajectory; Using the continuous-time trajectory curve, the overall difference between a first estimate and a second estimate of the motion state of the data acquisition vehicle is determined; wherein the first estimate is determined by the motion trajectory of the data acquisition vehicle, and the second estimate is determined by the measurement value of the first inertial measurement unit of the data acquisition vehicle; and, Based on the overall differences, the quality of the motion trajectory is detected; The overall difference is determined by the difference in acceleration and the difference in angular velocity; The acceleration difference includes the difference between the acceleration determined by the trajectory of the acquisition vehicle and the acceleration determined by the first inertial measurement unit; The angular velocity difference includes the difference between the angular velocity determined by the trajectory of the acquisition vehicle and the angular velocity determined by the first inertial measurement unit.

2. The method according to claim 1, wherein, The continuous time trajectory curve includes a rotation state curve and a translation state curve. The step of determining the overall difference between the first and second estimates of the motion state of the data acquisition vehicle using the continuous time trajectory curve includes: Using the rotational state curve and the translational state curve, an expression for the acceleration difference is determined; and using the rotational state curve, an expression for the angular velocity difference is determined. Using the expressions for the acceleration difference and the angular velocity difference, determine the expression for the overall difference; Determine the minimum value of the expression for the overall difference, and use the minimum value as the overall difference.

3. The method according to claim 2, wherein, The minimum value of the expression for determining the overall difference includes: Adjust at least one of the gravitational acceleration, the zero bias of the acceleration of the first inertial measurement unit, and the zero bias of the angular velocity of the first inertial measurement unit to minimize the value of the expression for the overall difference.

4. The method according to claim 2 or 3, wherein, The trajectory of the data acquisition vehicle is equivalent to the trajectory of the second inertial measurement unit of the data acquisition vehicle; the first inertial measurement unit and the second inertial measurement unit are two different inertial measurement units of the data acquisition vehicle.

5. The method according to claim 4, wherein, The expression for the acceleration difference is determined by at least one of the following: the rotation matrix of the second inertial measurement unit in the global coordinate system, the true value of the angular velocity of the second inertial measurement unit, the relative positional relationship between the first and second inertial measurement units in space, the true value of the acceleration of the second inertial measurement unit in the global coordinate system, the rotation matrix between the first and second inertial measurement units, the measured acceleration value of the first inertial measurement unit, the zero bias of the acceleration of the first inertial measurement unit, and the gravitational acceleration; wherein, The rotation matrix of the second inertial measurement unit in the global coordinate system is determined by the rotation state curve; or, The true value of the angular velocity of the second inertial measurement unit is determined by the rotational state curve; or, The true value of the acceleration of the second inertial measurement unit in the global coordinate system is determined by the translation state curve.

6. The method according to claim 4, wherein, The expression for the angular velocity difference is determined by at least one of the following: the true value of the angular velocity of the second inertial measurement unit, the measured value of the angular velocity of the first inertial measurement unit, the zero bias of the angular velocity of the first inertial measurement unit, and the rotation matrix between the first inertial measurement unit and the second inertial measurement unit. The true value of the angular velocity of the second inertial measurement unit is determined by the rotational state curve.

7. The method according to claim 2 or 3, wherein, The trajectory of the data acquisition vehicle is equivalent to the trajectory of the first inertial measurement unit of the data acquisition vehicle.

8. The method according to claim 7, wherein, The expression for the acceleration difference is determined by at least one of the following: the orientation of the first inertial measurement unit, the true value of the acceleration of the first inertial measurement unit in the global coordinate system, the measured value of the acceleration of the first inertial measurement unit, the zero bias of the acceleration of the first inertial measurement unit, and the gravitational acceleration; wherein, The orientation of the first inertial measurement unit is determined by the rotation state curve; or, The true value of the acceleration of the first inertial measurement unit in the global coordinate system is determined by the translation state curve.

9. The method according to claim 7, wherein, The expression for the angular velocity difference is determined by at least one of the following: the angular velocity of the first inertial measurement unit in the local coordinate system, the measured angular velocity value of the first inertial measurement unit, and the zero angular velocity bias of the first inertial measurement unit; wherein, The angular velocity of the first inertial measurement unit in the local coordinate system is determined by the rotation state curve.

10. The method according to claim 1, wherein, The step of detecting the quality of the motion trajectory based on the overall difference includes: If the overall difference is less than or equal to a predetermined threshold, the quality of the motion trajectory is determined to be acceptable. Alternatively, if the overall difference is greater than a predetermined threshold, the quality of the motion trajectory is determined to be substandard.

11. The method according to claim 10, wherein, The predetermined threshold is determined by the noise of the measured acceleration of the acquisition vehicle and the noise of the measured angular velocity of the acquisition vehicle.

12. A trajectory quality detection device, comprising: The modeling module is used to model the motion trajectory of the collected vehicle to obtain the continuous time trajectory curve corresponding to the motion trajectory; The determination module is used to determine the overall difference between a first estimate and a second estimate of the motion state of the data acquisition vehicle using the continuous-time trajectory curve; wherein the first estimate is determined by the motion trajectory of the data acquisition vehicle, and the second estimate is determined by the measurement value of the first inertial measurement unit of the data acquisition vehicle; and, A detection module is used to detect the quality of the motion trajectory based on the overall difference. The overall difference is determined by the difference in acceleration and the difference in angular velocity; wherein... The acceleration difference includes the difference between the acceleration determined by the trajectory of the acquisition vehicle and the acceleration determined by the first inertial measurement unit; The angular velocity difference includes the difference between the angular velocity determined by the trajectory of the acquisition vehicle and the angular velocity determined by the first inertial measurement unit.

13. The apparatus according to claim 12, wherein, The continuous time trajectory curve includes a rotation state curve and a translation state curve. The determining module includes: The first determining submodule is used to determine the expression for the acceleration difference using the rotation state curve and the translation state curve; and to determine the expression for the angular velocity difference using the rotation state curve. The second determining submodule is used to determine the expression for the overall difference using the expression for the acceleration difference and the expression for the angular velocity difference; The minimum value determination submodule is used to determine the minimum value of the expression for the overall difference, and to use the minimum value as the overall difference.

14. The apparatus according to claim 13, wherein, The minimum value determination submodule is used for, Adjust at least one of the gravitational acceleration, the zero bias of the acceleration of the first inertial measurement unit, and the zero bias of the angular velocity of the first inertial measurement unit to minimize the value of the expression for the overall difference.

15. The apparatus according to claim 13 or 14, wherein, The trajectory of the data acquisition vehicle is equivalent to the trajectory of the second inertial measurement unit of the data acquisition vehicle; the first inertial measurement unit and the second inertial measurement unit are two different inertial measurement units of the data acquisition vehicle.

16. The apparatus according to claim 15, wherein, The expression for the acceleration difference is determined by at least one of the following: the rotation matrix of the second inertial measurement unit in the global coordinate system, the true value of the angular velocity of the second inertial measurement unit, the relative positional relationship between the first and second inertial measurement units in space, the true value of the acceleration of the second inertial measurement unit in the global coordinate system, the rotation matrix between the first and second inertial measurement units, the measured acceleration value of the first inertial measurement unit, the zero bias of the acceleration of the first inertial measurement unit, and the gravitational acceleration; wherein, The rotation matrix of the second inertial measurement unit in the global coordinate system is determined by the rotation state curve; or, The true value of the angular velocity of the second inertial measurement unit is determined by the rotational state curve; or, The true value of the acceleration of the second inertial measurement unit in the global coordinate system is determined by the translation state curve.

17. The apparatus according to claim 15, wherein, The expression for the angular velocity difference is determined by at least one of the following: the true value of the angular velocity of the second inertial measurement unit, the measured value of the angular velocity of the first inertial measurement unit, the zero bias of the angular velocity of the first inertial measurement unit, and the rotation matrix between the first inertial measurement unit and the second inertial measurement unit. The true value of the angular velocity of the second inertial measurement unit is determined by the rotational state curve.

18. The apparatus according to claim 13 or 14, wherein, The trajectory of the data acquisition vehicle is equivalent to the trajectory of the first inertial measurement unit of the data acquisition vehicle.

19. The apparatus according to claim 18, wherein, The expression for the acceleration difference is determined by at least one of the following: the orientation of the first inertial measurement unit, the true value of the acceleration of the first inertial measurement unit in the global coordinate system, the measured value of the acceleration of the first inertial measurement unit, the zero bias of the acceleration of the first inertial measurement unit, and the gravitational acceleration; wherein, The orientation of the first inertial measurement unit is determined by the rotation state curve; or, The true value of the acceleration of the first inertial measurement unit in the global coordinate system is determined by the translation state curve.

20. The apparatus according to claim 18, wherein, The expression for the angular velocity difference is determined by at least one of the following: the angular velocity of the first inertial measurement unit in the local coordinate system, the measured angular velocity value of the first inertial measurement unit, and the zero angular velocity bias of the first inertial measurement unit; wherein, The angular velocity of the first inertial measurement unit in the local coordinate system is determined by the rotation state curve.

21. The apparatus according to claim 12, wherein, The detection module is used for: If the overall difference is less than or equal to a predetermined threshold, the quality of the motion trajectory is determined to be acceptable. Alternatively, if the overall difference is greater than a predetermined threshold, the quality of the motion trajectory is determined to be substandard.

22. The apparatus according to claim 21, wherein, The predetermined threshold is determined by the noise of the measured acceleration of the acquisition vehicle and the noise of the measured angular velocity of the acquisition vehicle.

23. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-11.

24. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-11.

25. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-11.

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