Pilot control method and device, security inspection vehicle, medium and program product

Abstract

The present disclosure provides a guidance control method applied to a security vehicle, the security vehicle comprising a vehicle body, a security door and at least one multi-line laser radar. The method comprises: acquiring environmental point cloud data of the security vehicle by using the at least one multi-line laser radar; determining position information of a plurality of reference objects located in an external environment of the security vehicle based on the environmental point cloud data; then, determining a guidance path based on the position information of the plurality of reference objects; and then, performing guidance control on the vehicle body based on the guidance path. When the at least one multi-line laser radar comprises a plurality of multi-line laser radars, at least two multi-line laser radars of the plurality of multi-line laser radars are distributed on the outside of the vehicle body; when the security vehicle is in a security state, at least one multi-line laser radar of the plurality of multi-line laser radars, except the at least two multi-line laser radars, is located in an inspection channel.

Description

[0001] This application is a divisional application. The parent application number is 202010866853.9, the application date is August 25, 2020, and the invention title is: Guiding Control Method, Device, Security Inspection Vehicle, Medium, and Program Product. Technical Field

[0002] Embodiments of this disclosure relate to the field of security inspection, specifically to a guidance control method, apparatus, security inspection vehicle, medium, and procedure product. Background Technology

[0003] When a security inspection vehicle conducts a security check on an individual, the vehicle needs to be guided so that the individual passes through the security gate. In one approach, the automatic guidance system of security inspection vehicles often uses single-line LiDAR for environmental perception. However, due to the limited detection capabilities of single-line LiDAR, the detection information it provides only supports linear guidance control of the security inspection vehicle. Furthermore, single-line LiDAR has a large blind spot, preventing the security inspection vehicle from effectively avoiding obstacles located within this blind spot. Summary of the Invention

[0004] According to embodiments of this disclosure, a guidance control method, apparatus, security inspection vehicle, medium, and procedure product are proposed.

[0005] In one aspect of this disclosure, a guidance control method is proposed for use in a security inspection vehicle, which includes a vehicle body, a security gate, and at least one multi-line lidar. The method includes: acquiring environmental point cloud data of the security inspection vehicle using at least one multi-line lidar; determining the position information of multiple reference objects in the external environment of the security inspection vehicle based on the environmental point cloud data; determining a guidance path based on the position information of the multiple reference objects; and guiding the vehicle body based on the guidance path, wherein when the security inspection vehicle is in a security inspection state, the vehicle body, guided by the guidance, moves the security gate relative to the object to be inspected in the external environment, so that the object to be inspected passes through the security gate; wherein when the at least one multi-line lidar includes multiple multi-line lidars, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body to acquire environmental point cloud data on the outside of the security inspection vehicle; when the security inspection vehicle is in a security inspection state, at least one of the multiple multi-line lidars other than the at least two multi-line lidars is located in the inspection channel to acquire environmental point cloud data of the inspection channel.

[0006] According to embodiments of this disclosure, the aforementioned at least one multi-line lidar includes multiple multi-line lidars. The method of acquiring environmental point cloud data of a security inspection vehicle using at least one multi-line lidar includes: for any given time, acquiring point cloud data from each of the multiple multi-line lidars. Furthermore, transforming the point cloud data of each of the multiple multi-line lidars from the coordinate system of each multi-line lidar to a reference coordinate system to form the environmental point cloud data for that given time.

[0007] According to an embodiment of this disclosure, the method further includes: before transforming the point cloud data of each multi-line lidar from its own coordinate system to a reference coordinate system, determining the rotation and translation transformation relationships between the coordinate systems of each multi-line lidar and the reference coordinate system based on the positional relationship of each multi-line lidar relative to the vehicle body. The transformation of the point cloud data of each multi-line lidar from its own coordinate system to the reference coordinate system includes: transforming the point cloud data of each multi-line lidar from its own coordinate system to the reference coordinate system according to the aforementioned rotation and translation transformation relationships.

[0008] According to embodiments of this disclosure, the method further includes: before transforming the point cloud data of each multi-line lidar from its own coordinate system to a reference coordinate system, each multi-line lidar acquires detection data for a predetermined target, and extracts corresponding vector representations and corresponding point representations for characterizing the predetermined target from the detection data using a random sample consensus algorithm. Then, the corresponding vector representations of each of the multiple multi-line lidars are processed based on the Rodrigues rotation equation to obtain the rotational transformation relationship between the coordinate system of any one of the multiple multi-line lidars and the reference coordinate system. Furthermore, based on the corresponding point representations of each of the multiple multi-line lidars, the translational transformation relationship between the coordinate system of any one of the multiple multi-line lidars and the reference coordinate system is determined. Based on this, the above-mentioned transformation of the point cloud data of each multi-line lidar from the coordinate system of each multi-line lidar to the reference coordinate system includes: transforming the point cloud data of the multiple multi-line lidars from their respective coordinate systems to the reference coordinate system according to the rotation transformation relationship and translation transformation relationship between the coordinate system of any one of the multi-line lidars and the reference coordinate system.

[0009] According to an embodiment of this disclosure, the determination of the location information of multiple reference objects in the external environment of a security inspection vehicle based on environmental point cloud data includes: extracting first feature point cloud data from the environmental point cloud data; clustering the first feature point cloud data to obtain multiple clustering results, each of which serves as a sub-point cloud data for a given reference object. Then, based on the sub-point cloud data of each reference object, the location information of each reference object is determined.

[0010] According to an embodiment of this disclosure, determining the guide path based on the position information of multiple reference objects includes: performing curve fitting based on the position information of each of the multiple reference objects to obtain a fitted lane line. Furthermore, based on the fitted lane line, a guide line is determined such that the distance between any point on the guide line and the fitted lane line is the radius of a predetermined circle.

[0011] According to an embodiment of this disclosure, the radius of the predetermined circle is larger than the radius of the circumcircle of the security inspection vehicle.

[0012] According to embodiments of this disclosure, the method further includes: extracting second feature point cloud data from environmental point cloud data at any given time; using a predetermined matching algorithm to match the second feature point cloud data at any given time with the second feature point cloud data at the previous time to determine a rotation matrix and a translation matrix. Then, based on the rotation matrix and translation matrix, the attitude change information of the security inspection vehicle at any given time is determined.

[0013] According to embodiments of this disclosure, the above-mentioned guidance control of the vehicle body based on the guidance path includes: determining the magnitude and direction of the traction force for the security inspection vehicle based on the guidance path and attitude change information; and then performing guidance control of the vehicle body based on the traction force.

[0014] According to embodiments of this disclosure, the method further includes: determining the contour information of the vehicle body and the contour information of at least one obstacle based on environmental point cloud data; then, for each of the at least one obstacle, determining the distance between the vehicle body and the obstacle based on the contour information of the vehicle body and the contour information of the obstacle, and determining the magnitude and direction of the repulsive force based on the distance between them. The magnitude and direction of the traction force for the security inspection vehicle are determined based on the guidance path and attitude change information. Next, a comprehensive traction force is determined based on the traction force and the repulsive force against the at least one obstacle, and the vehicle body is guided and controlled based on the comprehensive traction force.

[0015] According to an embodiment of this disclosure, determining the comprehensive traction force based on the traction force and the repulsive force against the at least one obstacle includes: using a preset first weight and a second weight to perform a weighted summation of the traction force and the repulsive force against the at least one obstacle to obtain the comprehensive traction force.

[0016] In another aspect of this disclosure, a guidance control device is proposed for use in a security inspection vehicle, which includes a vehicle body, a security gate, and at least one multi-line lidar. The guidance control device includes: an acquisition module, a first determination module, a second determination module, and a control module. The acquisition module is used to acquire environmental point cloud data of the security inspection vehicle using the at least one multi-line lidar. The first determination module is used to determine the position information of multiple reference objects located in the external environment of the security inspection vehicle based on the environmental point cloud data. The second determination module is used to determine a guidance path based on the position information of the multiple reference objects. The control module is used to perform guidance control on the vehicle body based on the guidance path. When the security inspection vehicle is in security inspection mode, the vehicle body, guided by a steering mechanism, moves the security gate relative to the object being inspected in the external environment, allowing the object to pass through the gate. When the at least one multi-line lidar includes multiple multi-line lidars, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body to acquire environmental point cloud data of the outside of the security inspection vehicle. When the security inspection vehicle is in security inspection mode, at least one multi-line lidar other than the at least two is located within the inspection channel to acquire environmental point cloud data of the inspection channel.

[0017] In another aspect of this disclosure, a security inspection vehicle is proposed, comprising: a vehicle body, a security gate, at least one multi-line LiDAR, a memory, and at least one processor. The memory is used to store instructions. The at least one processor executes the instructions stored in the memory to implement the method as described in any of the above embodiments.

[0018] According to an embodiment of this disclosure, when the above-mentioned at least one multi-line lidar includes multiple multi-line lidars, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body so that the scanning range of the at least two multi-line lidars covers 360° around the vehicle body.

[0019] According to an embodiment of this disclosure, at least one of the multiple multi-line lidars, other than the at least two multi-line lidars, is located inside the security gate.

[0020] In another aspect of this disclosure, a computer-readable storage medium is provided that stores computer instructions thereon, which, when executed by a processor, implement the methods described in any of the above embodiments.

[0021] In another aspect of this disclosure, a computer program product is proposed, including executable instructions that, when executed by a processor, implement the methods described in any of the above embodiments.

[0022] According to the guidance control scheme of this disclosure, for a security inspection vehicle in a security inspection state, at least one multi-line lidar is used to collect environmental point cloud data. Based on the environmental point cloud data, path planning and guidance control are performed to guide the object to be inspected through the security gate in the security inspection vehicle. Since multi-line lidar has a relatively larger detection range and a smaller detection blind zone, it has stronger identification capabilities and anti-interference capabilities for surrounding environmental information, and can acquire more accurate and comprehensive environmental point cloud data. This environmental point cloud data can support guidance control of various types of paths for the security inspection vehicle in various locations, improving the environmental adaptability and flexibility of the guidance control of the security inspection vehicle, thereby increasing the applicability of the security inspection vehicle for security inspections. Attached Figure Description

[0023] To better understand the embodiments of this disclosure, the embodiments of this disclosure will be described in detail with reference to the following drawings:

[0024] Figure 1 This illustration schematically depicts an application scenario of the guidance control method and apparatus according to embodiments of the present disclosure;

[0025] Figure 2 A flowchart illustrating a guidance control method according to an embodiment of the present disclosure is shown schematically.

[0026] Figure 3 This diagram schematically illustrates an example of a security inspection vehicle using a multi-line lidar for environmental perception according to an embodiment of the present disclosure.

[0027] Figure 4 An example top view of a security inspection vehicle according to an embodiment of the present disclosure is shown schematically;

[0028] Figures 5A-5B An example top view of a security inspection vehicle according to another embodiment of this disclosure is shown schematically;

[0029] Figures 6A to 6C This diagram schematically illustrates an example of a process for determining a boot path according to an embodiment of the present disclosure.

[0030] Figure 7 A block diagram of a guidance control device according to an embodiment of the present disclosure is schematically shown; and

[0031] Figure 8 An example structural diagram of a security inspection vehicle suitable for implementing the methods described above, according to embodiments of the present disclosure, is illustrated schematically. Detailed Implementation

[0032] Specific embodiments of the present disclosure will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the present disclosure. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to those skilled in the art that these specific details are not necessary to implement the embodiments of the present disclosure. In other instances, well-known structures, materials, or methods have not been specifically described to avoid obscuring the embodiments of the present disclosure.

[0033] Throughout this specification, references to "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of this disclosure. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0034] This disclosure provides a guidance control method and apparatus for security inspection vehicles, as well as the security inspection vehicle, media, and program products. The security inspection vehicle may include a vehicle body, a security gate, and at least one multi-line lidar. The guidance control method may include an acquisition process, a first determination process, a second determination process, and a control process. In the acquisition process, environmental point cloud data of the security inspection vehicle is acquired using at least one multi-line lidar. Then, based on the acquired environmental point cloud data, a first determination process is performed to determine the position information of multiple reference objects located in the external environment of the security inspection vehicle. Next, based on the position information of the multiple reference objects, a second determination process is performed to determine a guidance path. Then, based on the guidance path, a control process is performed, i.e., guiding the vehicle body of the security inspection vehicle. When the security inspection vehicle is in a security inspection state, the guided vehicle body moves the security gate relative to the object to be inspected in the external environment, allowing the object to pass through the security gate.

[0035] Figure 1 The illustration schematically depicts an application scenario of the guidance control method and apparatus according to embodiments of the present disclosure. It should be noted that... Figure 1 The examples shown are merely examples of scenarios in which the embodiments of this disclosure can be applied, to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0036] like Figure 1The diagram illustrates an exemplary scenario where a security inspection vehicle 110 performs a security check on an object 120. It should be noted that this example and the following text refer to the vehicle coordinate system o-xyz, where the x and y directions are parallel to the horizontal plane and perpendicular to each other, and the z direction is perpendicular to the horizontal plane. In this example, the security inspection vehicle 110 may include a vehicle body 111, at least one lidar 112, and a security gate 113. At least one lidar 112 is used to acquire environmental information of the security inspection vehicle 110 during movement or when stationary. Based on this environmental information, the security inspection vehicle 110 can guide and control its movement. When the security inspection vehicle 110 is in the security inspection state, the vehicle body 111 is fixedly connected to the security gate 113. The movement of the vehicle body 111 can cause the security gate 113 to move relative to the object 120, allowing the object 120 to pass through the security gate 113. For example, the security gate 113, acting as an X-ray inspection device, scans the object 120 passing through it with X-rays to obtain an X-ray perspective view of the object 120. Exemplarily, the security vehicle 110 can conduct security checks on objects such as containers, large vehicles, and small vehicles in locations such as customs, ports, and border crossings. The X-ray projection scan images are used to determine whether the material, volume, and quantity of goods inside the object match the checklist, and to determine whether the object contains dangerous or prohibited items.

[0037] exist Figure 1 In the example shown, when the security vehicle is in security inspection mode, the security gate is located on the outside of one side of the vehicle body. In other examples, the security gate may also be located inside the vehicle body. The object being inspected can be moving or stationary.

[0038] It should be noted that the guidance control method provided in this embodiment can be executed by the security inspection vehicle 110 described above. Accordingly, the guidance control device provided in this embodiment can be installed in the security inspection vehicle 110. Alternatively, the guidance control method provided in this embodiment can also be executed by a server or server cluster that is different from the security inspection vehicle 110 but capable of communicating with it. Accordingly, the guidance control device provided in this embodiment can also be installed in a server or server cluster that is different from the security inspection vehicle 110 but capable of communicating with it.

[0039] Based on the above application scenarios, when security inspection vehicles conduct security checks on objects, it is necessary to guide the vehicle body so that the objects pass relatively through the security gate of the vehicle, thereby achieving security checks. In one approach, the automatic guidance control system of security inspection vehicles mostly uses single-line LiDAR for environmental perception. However, single-line LiDAR has limited detection capabilities, emitting only one detection scan line, and its maximum horizontal scanning angle is only 190°. This results in weak environmental recognition capabilities, strict requirements on the flatness of the work area and the arrangement of reference objects, and poor environmental adaptability. The detection information obtained by single-line LiDAR only supports straight-line guidance control for the security inspection vehicle and cannot control its turning or other movements. Furthermore, because single-line LiDAR has a large detection blind spot, the security inspection vehicle cannot effectively avoid obstacles located in the blind spot.

[0040] According to embodiments of this disclosure, a guidance control method is provided to further improve the environmental adaptability and flexibility of guidance control. The method is illustrated below with reference to figures. It should be noted that the sequence numbers of each operation in the following method are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0041] Figure 2 A flowchart illustrating a guidance control method according to an embodiment of the present disclosure is shown schematically. This guidance control method can be applied to, for example... Figure 1 The security inspection vehicle shown may include a vehicle body, a security gate, and at least one multi-line lidar.

[0042] like Figure 2 As shown, the guidance control method may include the following operations S210 to S240.

[0043] During operation S210, at least one of the aforementioned multi-line lidars is used to acquire environmental point cloud data of the security inspection vehicle.

[0044] As one of the most important sensors for environmental perception in security inspection vehicles, lidar's effectiveness varies depending on its installation and usage. According to embodiments of this disclosure, the automatic guidance system of a security inspection vehicle is improved by replacing a single-line lidar with at least one multi-line lidar for environmental perception. Environmental perception can include sensing the vehicle's own attitude and contour information, as well as sensing information about the external environment. Compared to single-line lidar, multi-line lidar has a larger detection range and a smaller blind spot, enabling more accurate environmental perception. Multi-line lidars include, for example, 4-line, 16-line, 32-line, and 64-line lidars; a 16-line lidar is used as an example below.

[0045] Figure 3 The illustration schematically shows an example diagram of a security inspection vehicle utilizing a multi-line lidar for environmental perception according to an embodiment of the present disclosure. Figure 3 As shown, the security inspection vehicle 310 includes a vehicle body 311 and at least one multi-line lidar 312, such as a 16-line lidar. The 16-line lidar has a horizontal scanning range of 360° and 16 vertical scanning lines evenly distributed at 2° intervals, with a scanning angle range of -15° to +15°. Compared to single-line lidar, it has stronger capabilities in identifying surrounding environmental information and better anti-interference, and can acquire stable information about reference objects and obstacles in the environment. Figure 3 In the example shown, a reference object 320 exists in the external environment of the security inspection vehicle 310. The environmental point cloud data acquired by the multi-line lidar 312 can reflect the three-dimensional information of the reference object 320.

[0046] Continue reading Figure 2 During operation of S220, the location information of multiple reference objects in the external environment of the security inspection vehicle is determined based on environmental point cloud data.

[0047] According to embodiments of this disclosure, when guiding security inspection vehicles, multiple reference points need to be pre-set in the guidance control area to determine the guidance path. Operation S220 determines the position information of the pre-set reference points based on environmental point cloud data acquired by a multi-line lidar.

[0048] In operation S230, the guide path is determined based on the position information of multiple reference objects.

[0049] When operating S240, the vehicle body is guided and controlled based on the guide path.

[0050] According to embodiments of this disclosure, when the security inspection vehicle is in security inspection mode, the vehicle body, guided by guidance control, moves the security gate relative to the object to be inspected in the external environment, allowing the object to pass through the security gate, thereby achieving security inspection of the object. When the security inspection vehicle is in non-security inspection mode, the above-described guidance control process can control the vehicle body to move to a predetermined position, perform site transfers, etc. For example, during the guidance control process, the above-described operations S210 to S240 can be executed periodically, for example, once every predetermined time interval, to achieve real-time guidance control for the security inspection vehicle.

[0051] Those skilled in the art will understand that, according to the guidance control method of the embodiments of this disclosure, for a security inspection vehicle in a security inspection state, at least one multi-line lidar is used to collect environmental point cloud data, and path planning and guidance control are performed based on the environmental point cloud data to allow the object to be inspected to pass through the security gate in the security inspection vehicle. Because multi-line lidar has a relatively larger detection range and a smaller detection blind zone, it has stronger identification capabilities and anti-interference capabilities for surrounding environmental information, and can acquire more accurate and comprehensive environmental point cloud data. This environmental point cloud data can support guidance control of various types of paths for security inspection vehicles in various locations, improving the environmental adaptability and flexibility of the guidance control of security inspection vehicles, thereby increasing the applicability of security inspection vehicles for security checks.

[0052] According to embodiments of this disclosure, to obtain more comprehensive environmental point cloud data, the aforementioned at least one multi-line lidar may include multiple multi-line lidars. When the aforementioned at least one multi-line lidar includes multiple multi-line lidars, at least two of the multiple multi-line lidars are distributed on the outer side of the vehicle body, so that the scanning range of the at least two multi-line lidars covers the 360° perimeter of the vehicle body as much as possible. In some cases, due to the shape of the vehicle body or equipment obstruction, the scanning range of the aforementioned at least two multi-line lidars cannot reach 360°.

[0053] Figure 4 The schematic illustration shows an example top view of a security inspection vehicle according to an embodiment of the present disclosure, exemplarily demonstrating one configuration of a multi-line lidar system on the vehicle. Figure 4 As shown, the security inspection vehicle 410 includes a vehicle body 411 and two multi-line lidar sensors 4121-4122. Exemplarily, on the o-xy plane, the two multi-line lidar sensors 4121-4122 are disposed on the outer side of the vehicle body 411 and are symmetrically arranged about the center point o of the vehicle body 411. Figure 4 The image shows that the scanning range of two multi-line lidars 4121 and 4122 can cover 360° around the vehicle body 411, thereby further reducing the detection blind spot of lidar in security inspection vehicles or even achieving no detection blind spot.

[0054] The following two examples illustrate how to set up a multi-line lidar. Figure 5A An example top view of a security inspection vehicle according to another embodiment of this disclosure is schematically shown. Figure 5B An example top view of a security inspection vehicle according to another embodiment of this disclosure is shown schematically.

[0055] like Figure 5AAs shown, the security inspection vehicle 510 includes a vehicle body 511, a first multi-line lidar 5121, a second multi-line lidar 5122, a third multi-line lidar 5123, and a security gate 513. In this example, the vehicle body 511 has an inverted U-shaped structure, and the security gate 513 is located inside the vehicle body 511 to form an inspection channel. During the security inspection process, this inspection channel allows the inspected object to pass through actively or passively. The first multi-line lidar 5121 and the second multi-line lidar 5122 are located outside the vehicle body 511 and are symmetrically arranged about the center point of the vehicle body 511. Figure 4 The two multi-line lidars 4121 and 4122 are configured in the same way. The first and second multi-line lidars 5121 can acquire environmental point cloud data of the outer side of the security inspection vehicle. Based on this environmental point cloud data, for example, the position and contour information of reference objects and obstacles in the external environment can be extracted, the contour information of the security inspection vehicle can be extracted, and the attitude information of the security inspection vehicle can be calculated. The third multi-line lidar 5123 can be arranged inside the security gate 513 and can be used to acquire environmental point cloud data of the inspection channel. Based on this environmental point cloud data, relevant information within the inspection channel can be determined, such as the attitude information of the object being inspected within the inspection channel and whether there are other obstacles within the inspection channel.

[0056] like Figure 5B As shown, the security inspection vehicle 510' includes a vehicle body 511', a first multi-line LiDAR 5121', a second multi-line LiDAR 5122', a third multi-line LiDAR 5123', and a security gate 513'. In this example, the security inspection vehicle 510' unfolds or retracts the security gate 513' via a boom. When the security gate 513' is retracted, the security inspection vehicle 510' is in a non-security inspection state and can perform operations such as site relocation. At this time, the first multi-line LiDAR 5121' is located at the front of the security inspection vehicle, the second multi-line LiDAR 5122' is located at the left rear of the security inspection vehicle, and the third multi-line LiDAR 5123' is located at the right rear of the security inspection vehicle. All three multi-line LiDARs can be used to acquire environmental point cloud data outside the security inspection vehicle to extract contour information, calculate attitude information, and perform obstacle avoidance functions. When the security gate 513' is unfolded via the boom, an inspection channel is formed, and the security inspection vehicle 510' can begin security inspection operations. At this time, the third multi-line lidar 5123' is located within the inspection channel. The third multi-line lidar 5123' can be used to acquire environmental point cloud data within the inspection channel, and based on this environmental point cloud data, relevant information within the inspection channel can be determined, such as providing functions like intruder identification, vehicle model identification, and vehicle speed and position measurement. Figure 5B The security inspection vehicle 510', which is in the security inspection state, is shown.

[0057] According to embodiments of this disclosure, the process of acquiring environmental point cloud data of a security inspection vehicle using at least one multi-line lidar may include: for any given moment, acquiring point cloud data from multiple multi-line lidars respectively, and transforming the point cloud data of each multi-line lidar from its own coordinate system to a reference coordinate system to form the environmental point cloud data for that given moment. Here, the point cloud data of each multi-line lidar refers to the point cloud data collected by each multi-line lidar, and the coordinate system of each multi-line lidar refers to its measurement coordinate system. The purpose of this embodiment is to fuse the point cloud data collected by multiple multi-line lidars into the same reference coordinate system, i.e., to calibrate the multiple multi-line lidars to form complete environmental point cloud data for the scene. The reference coordinate system can be selected according to the actual situation, for example, it can be the vehicle coordinate system, or it can be the coordinate system of a single multi-line lidar; no limitation is made here.

[0058] For example, to complete the above calibration process, it is necessary to pre-determine the transformation relationship between the coordinate system of each multi-line lidar and the reference coordinate system. For instance, the guidance control method according to the embodiments of this disclosure may further include: before transforming the point cloud data of each multi-line lidar from its own coordinate system to the reference coordinate system, determining the rotation transformation relationship and translation transformation relationship between the coordinate system of each multi-line lidar and the reference coordinate system based on the positional relationship of each multi-line lidar relative to the vehicle body. The above-mentioned transformation of the point cloud data of each multi-line lidar from its own coordinate system to the reference coordinate system includes: transforming the point cloud data of each multi-line lidar from its own coordinate system to the reference coordinate system according to the above-mentioned rotation transformation relationship and translation transformation relationship.

[0059] For example, the coordinate system of a multi-line lidar is S1, and the reference coordinate system is S2. There is a transformation relationship between the two coordinate systems by rotation (R) and translation (T). The point cloud data of the multi-line lidar can be transformed from coordinate system S1 to coordinate system S2 according to formula (1).

[0060] S2=RS1+T (1)

[0061] For example, R is a 3×3 rotation transformation matrix, and T is a 3×1 translation transformation matrix.

[0062] Given the dimensions of the security inspection vehicle and the installation positions of each lidar, the transformation relationships between coordinate systems can be directly derived based on the above embodiments. If the above transformation relationships cannot be obtained, a predetermined target can be placed in the common observation area of ​​multiple lidars. Based on the corresponding vectors and points used to characterize the predetermined target detected in different lidar coordinate systems, the rotation transformation matrix R can be solved using the Rodrigues rotation equation. The translation transformation matrix T can then be solved using the representations of the corresponding points in different coordinate systems.

[0063] For example, the guidance control method according to the embodiments of this disclosure may further include: before transforming the point cloud data of each multi-line lidar in the plurality of multi-line lidars from the coordinate system of each multi-line lidar to the reference coordinate system, each multi-line lidar acquires detection data for a predetermined target, and extracts the corresponding vector representation and corresponding point representation for characterizing the predetermined target from the detection data of each multi-line lidar using the Random Sample Consensus (RANSAC) algorithm.

[0064] Then, based on the Rodriguez rotation equation, the corresponding vector representations of each of the multiple multi-line lidars are processed to obtain the rotational transformation relationship between the coordinate systems of any two multi-line lidars. Furthermore, based on the corresponding point representations of each of the multiple multi-line lidars, the translational transformation relationship between the coordinate systems of any two multi-line lidars is determined.

[0065] For example, a predetermined target with three observable planes is placed in the measurement environment. Multiple multi-line lidars are used to observe the target, obtaining detection data for each lidar. For each lidar detection data, the following operations are performed: sub-point cloud data of the target is extracted from the detection data. Then, the RANSAC algorithm is used to segment the sub-point cloud data of the target into planes to extract the plane parameters for each of the three observable planes. Based on these plane parameters, the normal vectors of the three planes are taken as corresponding vectors, and the intersection of the three planes is taken as corresponding points. It can be understood that, based on the detection data of each lidar, a set of corresponding vector representations and corresponding point representations for the coordinate system of that lidar can be obtained.

[0066] According to the Rodrigues rotation equation, the rotation matrix R between coordinate systems can be obtained with only two or more sets of corresponding vectors. Based on this, the translation matrix T can be determined knowing the coordinate vector of at least one corresponding point. This allows us to solve for the rotation and translation transformation relationships between the coordinate system and the reference coordinate system of any multi-line lidar.

[0067] Based on this, the process of transforming the point cloud data of each multi-line lidar from the coordinate system of each multi-line lidar to the reference coordinate system can include: transforming the point cloud data of the multiple multi-line lidars from their respective coordinate systems to the reference coordinate system according to the rotation transformation relationship and translation transformation relationship between the coordinate system of any one of the multiple multi-line lidars and the reference coordinate system.

[0068] The above embodiments can convert the point cloud data of multiple LiDARs in a security inspection vehicle to the same reference coordinate system for calibration. For each measurement moment, a frame of environmental point cloud data describing the complete environmental information around the vehicle can be generated to characterize the above-mentioned... Figure 4 The external environment information is shown. Based on the first feature point cloud data in this environmental point cloud data, relevant information about reference objects in the external environment can be determined. If there are no other devices obstructing the scan line near the LiDAR installation location, the vehicle body contour information of the security inspection vehicle can be extracted from the fused environmental point cloud data. The contour information of obstacles in the external environment of the security inspection vehicle can also be extracted from this environmental point cloud data. The vehicle body contour information and obstacle contour information can be used to determine the distance between obstacles and the vehicle body during obstacle avoidance. Furthermore, for each frame of environmental point cloud data, second feature point cloud data can be extracted based on the distribution characteristics of the environmental point cloud data. For the second feature point cloud data between adjacent frames, the optimal match between the second feature point cloud data between frames can be found using a predetermined matching algorithm iteratively using the Iterative Closest Point (ICP) algorithm. This allows the calculation of the rigid body rotation matrix R' and translation matrix T' between the environmental point cloud data of adjacent frames, thereby determining the attitude change information of the security inspection vehicle. For example, the predetermined matching algorithm can be the Iterative Closest Point (ICP) algorithm. In other examples, the predetermined matching algorithm can be an improved algorithm of various ICPs, such as PL-ICP (Point to Line ICP), N-ICP (Normal ICP), IMLS-ICP (Implicit Moving Least Square ICP), and matching algorithms based on other principles such as NDT (Normal Distribution). It should be noted that the above process can be performed on the security inspection vehicle or on other equipment that can pass through the security inspection vehicle.

[0069] The following is an illustrative example of the process of acquiring environmental information and vehicle information based on environmental point cloud data, and then performing guidance control based on the environmental information and vehicle information.

[0070] According to embodiments of this disclosure, the location information of multiple reference objects in the external environment of a security inspection vehicle can be determined based on environmental point cloud data. This process may include: extracting first feature point cloud data from the environmental point cloud data; clustering the first feature point cloud data to obtain multiple clustering results, each of which serves as a sub-point cloud data for a specific reference object. Then, based on the sub-point cloud data of each reference object, the location information of each reference object is determined. The first feature point cloud data is point cloud data that matches the feature information of a pre-defined reference object. The reference object may be, for example, a predetermined road sign or other predetermined target object, and the reference object may be positioned on one side of the vehicle body where a multi-line lidar is mounted on the front of the security inspection vehicle, for example... Figure 5A In the example shown, a first multi-line LiDAR 5121 is mounted on the left side of the front of the security inspection vehicle. Therefore, reference objects can be placed in the external environment on the left side of the vehicle body to ensure that high-precision point cloud data for the reference objects can be obtained using the first multi-line LiDAR 5121. In other examples, auxiliary reference objects can be placed on the other side of the vehicle body, using fused environmental point cloud data to assist in vehicle attitude adjustment. After determining the position information of each of the multiple reference objects, a guidance path can be determined based on this information, allowing for guidance control of the security inspection vehicle.

[0071] For example, security inspection vehicles may include two movement modes: one is linear reciprocating movement during the security inspection process, and the other is movement along a trajectory curve during vehicle transfer or complex security inspection processes. The guidance control scheme according to embodiments of this disclosure must ensure that the security inspection vehicle does not deviate from its original route due to road conditions, control deviations, or other reasons, and must provide a centering function. The process of determining the guidance path is illustrated below with specific examples.

[0072] Taking the use of road signs as a reference for the automatic guidance control system as an example, road signs are placed on the left side of the direction of travel of the security inspection vehicle. The distance between adjacent road signs must be less than the width of the vehicle body to prevent the gap between road signs from being identified as a passable area for the security inspection vehicle during the guidance control process.

[0073] Figures 6A to 6C The diagram illustrates an example of a process for determining a boot path according to an embodiment of the present disclosure.

[0074] like Figure 6AAs shown, multiple road sign reference objects 620 are set in the external environment of the security inspection vehicle 610. In this example, the road sign reference objects are placed in a curved manner, exemplifying a scheme for guidance control along a trajectory curve. Reference object information in the external environment of the security inspection vehicle can be obtained from environmental point cloud data. Sub-point cloud data for each reference object is obtained through point cloud segmentation and clustering methods. The position information of the corresponding reference object can be extracted from the sub-point cloud data for each reference object. Based on the position information of multiple reference objects, curve fitting is performed, for example, by using the least squares method to perform piecewise linear fitting on the position information of multiple reference objects to obtain the fitted lane line 630. Figure 6B As shown, after determining the fitted lane line 630, a guide line 640 is determined based on the fitted lane line 630, such that the distance between any point on the guide line 640 and the fitted lane line 630 is the radius of a predetermined circle 650. The size of the predetermined circle 650 defines the lateral attitude offset space of the security inspection vehicle. In subsequent guidance control processes, the guide line 640 can be used as the guidance path for the security inspection vehicle.

[0075] To ensure the smooth movement of security inspection vehicles along the guidance path and avoid collisions with reference objects, the method described above for obtaining the driving guidance path by fitting lane lines can be as follows: Figure 6C As shown. Using the origin of the vehicle coordinate system as the center, the circumcircle of the vehicle body contour, 660, is obtained based on the vehicle body contour information. Based on this, retaining the required safe distance r during vehicle operation, a predetermined circle 650 for safe vehicle operation, centered on the origin of the vehicle coordinate system, is obtained. Figure 6B In this process, the predetermined circle 650 is made to move tangent to the fitted lane line 630, and the trajectory of the center of the predetermined circle 650 is the guide line 640. The guidance control scheme according to the embodiment of this disclosure can calculate the vehicle's running direction and speed based on the current vehicle posture information, and make the origin of the vehicle coordinate system move along the trajectory on the guide path as much as possible during the guidance control of the vehicle.

[0076] In the example of the straight-line guidance scheme, the reference object can be placed in a straight line. According to the guidance control scheme of this disclosure, the position information of the reference object can be directly fitted into a straight-line fitted lane line using the least squares method, thereby determining a guide line at a predetermined distance from the fitted lane line, and causing the security inspection vehicle to move along the guide line to complete the guidance control work. To reserve safe movement space, the distance between the guide line and the fitted lane line is greater than the radius of the vehicle's outer circle.

[0077] In one embodiment of this disclosure, the process of guiding the vehicle body based on the guidance path includes: determining the magnitude and direction of the traction force for the security inspection vehicle based on the determined guidance path (e.g., guide line) and attitude change information; and then automatically guiding the vehicle body based on the traction force so that the security inspection vehicle travels along the guidance path.

[0078] In another embodiment of this disclosure, during the guidance control process, the impact of obstacles in the external environment on the operation of the security inspection vehicle can also be assessed. For example, based on environmental point cloud data, the contour information of the vehicle body and the contour information of at least one obstacle can be determined. Then, for each of the at least one obstacle, based on the contour information of the vehicle body and the contour information of the obstacle, the distance between the vehicle body and the obstacle is determined, and the magnitude and direction of the repulsive force are determined based on the distance between them. According to the guidance path and attitude change information, the magnitude and direction of the traction force for the security inspection vehicle are determined. Next, based on the traction force and the repulsive force for the at least one obstacle, a combined traction force is determined, and the vehicle body is guided based on the combined traction force.

[0079] For example, when the distance between the obstacle and the vehicle body is within a certain range, the obstacle will exert a repulsive force on the vehicle body. The magnitude of the repulsive force is inversely proportional to the distance between the obstacle and the vehicle body, and the direction of the repulsive force is from the obstacle towards the vehicle body. According to the embodiments of this disclosure, the traction force and repulsive force exerted on the vehicle body form a combined traction force, which together determine the actual running direction of the vehicle body. For example, the combined traction force can be calculated using formula (2), as shown in the following formula:

[0080] ρ(θ)=μ α ·α+μ β ·β (2)

[0081] Where ρ(θ), α, and β are vectors, ρ(θ) represents the combined traction force, α represents the traction force, p represents the repulsive force, and μ represents the repulsive force. α and μ β These are the first weight and the second weight, respectively, and μ α +μ β =1. μ α and μ β The value of μ is determined by the guiding control strategy. α >μ β When μ is present, the system behaves primarily as a guide; when μ is present... α <μ β At that time, the system primarily focuses on obstacle avoidance.

[0082] According to the guidance control scheme of the embodiments of this disclosure, the vehicle body is controlled to move forward along the calculated driving guide line, and the driving route is adjusted according to the distribution of obstacles until the security inspection vehicle runs to the end of the driving guide line (that is, no reference object can be detected in front of the vehicle body in the direction of travel, and no forward fitted lane line can be obtained), then it is considered that the destination has been reached and the guidance control process ends.

[0083] In other embodiments of this disclosure, based on environmental point cloud data, it is also possible to detect, such as Figures 5A-5BThe information shown refers to the relevant information within the inspection lane. For example, in the event of emergencies such as unauthorized personnel entering the inspection lane or the inspected object deviating from the inspection lane, an alarm can be triggered and the security vehicle can be stopped from conducting the security inspection process according to a predetermined strategy.

[0084] It is understood that, based on the descriptions of the above embodiments, the guidance control scheme according to the embodiments of this disclosure uses multi-line lasers as scanning devices to enhance the detection accuracy of obstacles, reference objects, etc. in the environment, reduce the scanning blind zone, and improve the operational safety of security inspection vehicles. Furthermore, by calibrating and fusing point cloud data from multiple multi-line laser radars on the vehicle body, it is convenient to obtain vehicle contour information, vehicle attitude information, and surrounding environment information, thereby improving the accuracy of the positioning and automatic guidance system. In addition, by combining the guiding effect based on the guidance path with the repulsion effect based on obstacle distribution, the driving path of the security inspection vehicle is precisely controlled.

[0085] Figure 7 A block diagram of a guidance control device according to an embodiment of the present disclosure is shown schematically. This guidance control device can be applied to a security inspection vehicle, which may include a vehicle body, a security gate, and at least one multi-line lidar.

[0086] like Figure 7 As shown, the guidance control device 700 may include: an acquisition module 710, a first determination module 720, a second determination module 730, and a control module 740.

[0087] The acquisition module 710 is used to acquire environmental point cloud data of the security inspection vehicle using at least one of the above-mentioned multi-line lidars.

[0088] The first determining module 720 is used to determine the location information of multiple reference objects in the external environment of the security inspection vehicle based on environmental point cloud data.

[0089] The second determining module 730 is used to determine the guiding path based on the location information of multiple reference objects.

[0090] The control module 740 is used to guide the vehicle body based on a guide path. Specifically, when the security inspection vehicle is in security inspection mode, the guided vehicle body moves the security gate relative to the object to be inspected in the external environment, so that the object to be inspected can pass through the security gate.

[0091] It should be noted that the implementation methods, technical problems solved, functions achieved, and technical effects of each module / unit / subunit in the device embodiments are the same as or similar to the implementation methods, technical problems solved, functions achieved, and technical effects of each corresponding step in the method embodiments, and will not be repeated here.

[0092] Figure 8An example structural diagram of a security inspection vehicle suitable for implementing the methods described above, according to embodiments of the present disclosure, is illustrated schematically. Figure 8 The security inspection vehicle shown is merely an example and should not impose any limitations on the structure, function, or scope of use of the embodiments disclosed herein.

[0093] like Figure 8 As shown, the security inspection vehicle 800 includes a processor 810 and a computer-readable storage medium 820, a vehicle body 830, a security gate 840, and at least one multi-line lidar 850. The security inspection vehicle 800 can perform methods according to embodiments of this disclosure.

[0094] According to an embodiment of this disclosure, when the at least one multi-line lidar 850 includes multiple multi-line lidars, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body so that the scanning range of the at least two multi-line lidars covers 360° around the vehicle body.

[0095] According to an embodiment of this disclosure, at least one of the plurality of multi-line lidars 850, other than the at least two multi-line lidars, is located inside the security gate.

[0096] Specifically, processor 810 may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. Processor 810 may also include onboard memory for caching purposes. Processor 810 may be a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this disclosure.

[0097] The computer-readable storage medium 820 may be a non-volatile computer-readable storage medium, including but not limited to: magnetic storage devices such as magnetic tape or hard disk (HDD); optical storage devices such as optical disc (CD-ROM); memory such as random access memory (RAM) or flash memory; and so on.

[0098] Computer-readable storage medium 820 may include computer program 821, which may include code / computer-executable instructions that, when executed by processor 810, cause processor 810 to perform a method or any variation thereof according to embodiments of the present disclosure.

[0099] Computer program 821 may be configured to have computer program code, for example, including computer program modules. For example, in an exemplary embodiment, the code in computer program 821 may include one or more program modules, such as 821A, module 821B, ... It should be noted that the division and number of modules are not fixed. Those skilled in the art can use appropriate program modules or combinations of program modules according to actual circumstances. When these combinations of program modules are executed by processor 810, processor 810 can perform the methods according to embodiments of this disclosure or any variations thereof.

[0100] According to an embodiment of the present invention, at least one of the acquisition module 710, the first determination module 720, the second determination module 730, and the control module 740 can be implemented as a reference. Figure 8 The described computer program module, when executed by processor 810, can implement the method described above.

[0101] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0102] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0103] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0104] Although this disclosure has been shown and described with reference to specific exemplary embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made to this disclosure without departing from the spirit and scope of the disclosure as defined by the appended claims and their equivalents. Therefore, the scope of this disclosure should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents.

Claims

1. A guidance control method applied to a security inspection vehicle, the security inspection vehicle comprising a vehicle body, a security gate, and multiple multi-line lidar sensors, the method comprising: The environmental point cloud data of the security inspection vehicle is acquired using the multiple multi-line lidars. Based on the environmental point cloud data, the location information of multiple reference objects in the external environment of the security inspection vehicle is determined; Based on the location information of the multiple reference objects, a guidance path is determined; as well as Based on the guidance path, the vehicle body is guided and controlled. When the security inspection vehicle is in the security inspection state, the vehicle body guided by the guidance control moves the security gate relative to the object to be inspected in the external environment, so that the object to be inspected can pass through the security gate. Among them, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body to acquire environmental point cloud data on the outside of the security inspection vehicle. At least one of the multiple multi-line lidars, excluding the at least two multi-line lidars, is located on the right rear of the security inspection vehicle and is used to acquire environmental point cloud data within the inspection channel when the security inspection vehicle is in security inspection mode.

2. The method according to claim 1, wherein, The process of acquiring environmental point cloud data of the security inspection vehicle using the multiple multi-line lidars includes: At any given moment, the multiple multi-line lidars acquire their respective point cloud data; and The point cloud data of each of the plurality of multi-line lidars is transformed from the coordinate system of each multi-line lidar to the reference coordinate system to form the environmental point cloud data at any given time.

3. The method according to claim 2, further comprising: Before transforming the point cloud data of each multi-line lidar from the coordinate system of each multi-line lidar to the reference coordinate system, the rotation transformation relationship and translation transformation relationship between the coordinate system of each multi-line lidar and the reference coordinate system are determined based on the positional relationship of each multi-line lidar relative to the vehicle body. The step of transforming the point cloud data of each multi-line lidar from its coordinate system to the reference coordinate system includes: transforming the point cloud data of each multi-line lidar from its coordinate system to the reference coordinate system according to the rotation transformation relationship and the translation transformation relationship.

4. The method according to claim 2, further comprising: Before transforming the point cloud data of each of the plurality of multi-line lidars from the coordinate system of each multi-line lidar to the reference coordinate system, Each multi-line lidar acquires detection data for a predetermined target, and a random sampling consensus algorithm is used to extract the corresponding vector representation and corresponding point representation for characterizing the predetermined target from the detection data; The corresponding vector representations of the multiple multi-line lidars are processed based on the Rodriguez rotation equation to obtain the rotational transformation relationship between the coordinate system of any one of the multiple multi-line lidars and the reference coordinate system. as well as Based on the corresponding point representations of the multiple multi-line lidars, the translation transformation relationship between the coordinate system of any one of the multiple multi-line lidars and the reference coordinate system is determined. The step of transforming the point cloud data of each of the plurality of multi-line lidars from the coordinate system of each multi-line lidar to the reference coordinate system includes: transforming the point cloud data of the plurality of multi-line lidars from their respective coordinate systems to the reference coordinate system according to the rotation transformation relationship and translation transformation relationship between the coordinate system of any one of the plurality of multi-line lidars and the reference coordinate system.

5. The method according to claim 1, wherein, The determination of the location information of multiple reference objects in the external environment of the security inspection vehicle based on the environmental point cloud data includes: Extract first feature point cloud data from the environmental point cloud data; The first feature point cloud data is clustered to obtain multiple clustering results, and each of the multiple clustering results serves as a sub-point cloud data for each of the multiple reference objects; and Based on the sub-point cloud data of each of the multiple reference objects, the location information of each of the multiple reference objects is determined.

6. The method according to claim 1, wherein, The determination of the guidance path based on the location information of the multiple reference objects includes: Based on the position information of the multiple reference objects, curve fitting is performed to obtain the fitted lane line; and Based on the fitted lane line, a guide line is determined such that the distance between any point on the guide line and the fitted lane line is the radius of a predetermined circle.

7. The method according to claim 6, wherein, The radius of the predetermined circle is greater than the radius of the circumcircle of the security inspection vehicle.

8. The method according to claim 2, further comprising: Extract the second feature point cloud data from the environmental point cloud data at any given time. Using a predetermined matching algorithm, the second feature point cloud data at any given time is matched with the second feature point cloud data at the previous time to determine the rotation matrix and translation matrix; and Based on the rotation matrix and the translation matrix, the attitude change information of the security inspection vehicle at any given time is determined.

9. The method according to claim 8, wherein, The guidance control of the vehicle body based on the guidance path includes: Based on the guidance path and the attitude change information, determine the magnitude and direction of the traction force applied to the security inspection vehicle; and The vehicle body is guided and controlled based on the traction force.

10. The method of claim 8, further comprising: Based on the environmental point cloud data, the contour information of the vehicle body and the contour information of at least one obstacle are determined; For each of the at least one obstacle, based on the contour information of the vehicle body and the contour information of the obstacle, the distance between the vehicle body and the obstacle is determined, and the magnitude and direction of the repulsive force are determined based on the distance; Based on the guidance path and the attitude change information, the magnitude and direction of the traction force applied to the security inspection vehicle are determined; The combined traction force is determined based on the traction force and the repulsive force against the at least one obstacle; as well as The vehicle body is guided and controlled based on the combined traction force.

11. The method according to claim 10, wherein, The determination of the combined traction force based on the traction force and the repulsive force against the at least one obstacle includes: The traction force and the repulsive force against the at least one obstacle are weighted and summed using a preset first weight and second weight to obtain the comprehensive traction force.

12. The method according to claim 1, wherein, The plurality of multi-line lidars includes a first multi-line lidar, a second multi-line lidar, and a third multi-line lidar. The first multi-line lidar is located at the front of the security inspection vehicle, the second multi-line lidar is located at the left rear of the security inspection vehicle, and the third multi-line lidar is located at the right rear of the security inspection vehicle.

13. The method according to claim 12, wherein, The first, second, and third multi-line lidars are all used to acquire environmental point cloud data outside the security inspection vehicle.

14. The method according to claim 12, wherein, The security inspection vehicle deploys or retracts the security gate via a boom. When the security gate is deployed via the boom, the inspection channel is formed, the security vehicle is in the security inspection state, and the third multi-line lidar is located in the inspection channel to acquire environmental point cloud data within the inspection channel.

15. A guidance control device applied to a security inspection vehicle, the security inspection vehicle comprising a vehicle body, a security gate, and multiple multi-line lidar sensors, the device comprising: The acquisition module is used to acquire environmental point cloud data of the security inspection vehicle using the multiple multi-line lidars; The first determining module is used to determine the position information of multiple reference objects in the external environment of the security inspection vehicle based on the environmental point cloud data. The second determining module is used to determine the guiding path based on the position information of the multiple reference objects; as well as The control module is used to guide the vehicle body based on the guidance path. When the security inspection vehicle is in the security inspection state, the vehicle body, guided by the guidance, drives the security gate to move relative to the object to be inspected in the external environment, so that the object to be inspected can pass through the security gate. Among them, at least two of the multiple multi-line lidars are distributed on the outside of the vehicle body to acquire environmental point cloud data on the outside of the security inspection vehicle. At least one of the multiple multi-line lidars, excluding the at least two multi-line lidars, is located on the right rear of the security inspection vehicle and is used to acquire environmental point cloud data of the inspection channel when the security inspection vehicle is in security inspection mode.

16. A security inspection vehicle, comprising: Vehicle body; Security gate; Multiple multi-line lidar; Memory, used to store instructions; as well as At least one processor, the at least one processor being configured to execute instructions stored in memory to implement the method according to any one of claims 1 to 14.

17. The security inspection vehicle according to claim 16, wherein, The plurality of multi-line lidars includes a first multi-line lidar, a second multi-line lidar, and a third multi-line lidar. The first multi-line lidar is located at the front of the security inspection vehicle, the second multi-line lidar is located at the left rear of the security inspection vehicle, and the third multi-line lidar is located at the right rear of the security inspection vehicle.

18. The security inspection vehicle according to claim 17, wherein, The first, second, and third multi-line lidars are all used to acquire environmental point cloud data outside the security inspection vehicle.

19. The security inspection vehicle according to claim 17, wherein, The security inspection vehicle deploys or retracts the security gate via a boom. When the security gate is deployed via the boom, the inspection channel is formed, the security vehicle is in the security inspection state, and the third multi-line lidar is located in the inspection channel to acquire environmental point cloud data within the inspection channel.

20. A computer-readable storage medium applied to a security inspection vehicle, the security inspection vehicle comprising a vehicle body, a security gate and a plurality of multi-line lidar sensors, wherein computer instructions are stored on the computer-readable storage medium, and the computer instructions, when executed by a processor, implement the method according to any one of claims 1 to 14.

21. A computer program product applied to a security inspection vehicle, the security inspection vehicle comprising a vehicle body, a security gate and a plurality of multi-line lidar sensors, the computer program product comprising executable instructions which, when executed by a processor, implement the method according to any one of claims 1 to 14.

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