Positioning Method and Device for Driverless Yard Trucks

Abstract

The present application discloses a positioning method and device for an unmanned container truck, belonging to the field of automotive electronics technology. The unmanned container truck is equipped with a lidar; the method includes: converting the distance value output by the lidar to a global coordinate system to obtain a first position value, where the distance value is the value of the distance from the target object of the bridge crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system; obtaining a second position value of the target object in the global coordinate system; obtaining the matching degree between the first position and the second position; and in the case where the matching degree is greater than the matching degree threshold, obtaining a target positioning result of the unmanned container truck according to the distance value and the second position value. The present application can solve the problem of high-precision positioning of unmanned container trucks in the bridge crane occlusion area at the lowest cost.

Description

Technical Field

[0001] This application belongs to the field of automotive electronics technology, and particularly relates to a positioning method and device for an unmanned container truck. Background Art

[0002] The quay crane in the port is a large container handling equipment. To achieve automated operations in the port, the unmanned container truck needs to autonomously and accurately stop at the designated position of the quay crane to complete the operation of loading and unloading containers. Since the large quay crane is likely to block the satellite positioning signal of the unmanned container truck, the positioning method using satellites cannot meet the precise positioning requirements of the unmanned container truck under the quay crane.

[0003] Currently, a positioning technology that introduces Ultra Wide Band (UWB) devices and Time Difference Of Arrival (TDOA) in the blocked area of the quay crane is used for positioning. This positioning technology can better ensure the requirement of centimeter-level positioning accuracy.

[0004] However, in addition to the cost of the device itself and the cost of algorithm development, the above positioning technology also requires a large investment in aspects such as communication with the port side and verification of device safety when installing other devices on the quay crane, which has high requirements for the overall structural safety. It can be seen that although the above positioning technology can meet the positioning accuracy, the technical cost is relatively high. Summary of the Invention

[0005] The embodiments of this application provide a positioning method and device for an unmanned container truck, which can solve the problem of high-precision positioning of the unmanned container truck in the blocked area of the quay crane at the lowest cost.

[0006] In a first aspect, the embodiments of this application provide a positioning method for an unmanned container truck, where the unmanned container truck is equipped with a lidar, and the method includes:

[0007] Convert the distance value output by the lidar to the global coordinate system to obtain a first position value, where the distance value is the value of the distance from the target object of the quay crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system;

[0008] Obtain a second position value of the target object in the global coordinate system;

[0009] Calculate the matching value between the first position and the second position;

[0010] When the matching value is greater than the matching threshold, obtain the target positioning result of the unmanned container truck according to the distance value and the second position value;

[0011] Among them, the fact that the matching degree is greater than the matching degree threshold indicates that the first position value and the second position value correspond to the target object of the same gantry crane.

[0012] In some embodiments, obtaining the matching degree between the first position value and the second position includes:

[0013] Calculating a matching value between the first position value and the second position value through the following formula, where the matching value is used to represent the matching degree between the first position value and the second position value and is negatively correlated with the matching degree;

[0014] gap = |(x Lidar - x Crane ) × cosθ Crane + (y Lidar - y Crane ) × sinθ Crane |

[0015] Among them, gap is the matching value; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; x Crane is the abscissa value of the second position in the global coordinate system; y Crane is the ordinate value of the second position in the global coordinate system; θ Crane is the operating angle of the gantry crane relative to the running track in the global coordinate system.

[0016] In some embodiments, the driverless container truck is also equipped with a camera;

[0017] Before obtaining the target positioning result of the driverless container truck according to the distance value and the second position value, the method further includes:

[0018] Obtaining a first gantry crane identifier collected by the camera;

[0019] Obtaining a second gantry crane identifier corresponding to the matching of the second position value;

[0020] Obtaining the target positioning result of the driverless container truck according to the distance value and the second position value includes:

[0021] In the case where the first gantry crane identifier and the second gantry crane identifier match, obtaining the target positioning result of the driverless container truck according to the distance value and the second position value.

[0022] In some embodiments, the driverless container truck is also equipped with a positioning device;

[0023] Before obtaining the target positioning result of the driverless container truck according to the distance value and the second position value, the method further includes:

[0024] Obtain a first positioning result collected by the positioning device;

[0025] The obtaining the target positioning result of the driverless container truck according to the distance value and the second position value includes:

[0026] Calculate a second positioning result of the driverless container truck according to the distance value and the second position value;

[0027] Calculate the difference between the first positioning result and the second positioning result to obtain a positioning correction amount;

[0028] Input the positioning correction amount into a Kalman filter to obtain the target positioning result of the driverless container truck.

[0029] In some embodiments, the converting the distance value output by the lidar to the global coordinate system to obtain a first position value includes:

[0030] Obtain the distance value corresponding to the first detection moment output by the lidar;

[0031] Obtain a third positioning result of the driverless container truck in the global coordinate system at the first detection moment;

[0032] Obtain the heading angle of the driverless container truck in the global coordinate system at the first detection moment;

[0033] Obtain the installation position of the lidar on the driverless container truck;

[0034] Calculate the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

[0035] In some embodiments, the calculating the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position includes:

[0036] Calculate a fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle;

[0037] Calculate the first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle.

[0038] In some embodiments, calculating the fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle includes:

[0039] Calculating the fourth positioning result of the lidar in the global coordinate system at the first detection moment through the following formula:

[0040] X Lidar = X Location +(x mount * cosθ yaw - y mount * * sinθ yaw )

[0041] Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw )

[0042] Calculating the first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle includes:

[0043] Calculating the first position value of the target object in the global coordinate system through the following formula:

[0044] x Lidar = X Lidar + D Lidar * sinθ yaw

[0045] y Lidar = Y Lidar + D Lidar * cosθ yaw

[0046] Wherein, X Lidar is the abscissa value of the fourth positioning result in the global coordinate system; Y Lidar is the ordinate value of the fourth positioning result in the global coordinate system; X Location is the abscissa value of the third positioning result in the global coordinate system; Y Location is the ordinate value of the third positioning result in the global coordinate system; x mount is the abscissa value of the installation position in the vehicle coordinate system; y mount is the ordinate value of the installation position in the vehicle coordinate system; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidaris the ordinate value of the first position in the global coordinate system; θ yaw is the heading angle.

[0047] In some embodiments, obtaining the second position value of the target object in the global coordinate system includes:

[0048] Receiving the position value of the bridge crane in the global coordinate system;

[0049] Obtaining the installation position of the target object on the bridge crane;

[0050] Obtaining the running angle of the bridge crane relative to the running track in the global coordinate system;

[0051] Calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position and the running angle.

[0052] In some embodiments, calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position and the running angle includes:

[0053] Calculating the second position value of the target object in the global coordinate system through the following formula:

[0054] x crane = X Crane - D * sinθ Crane

[0055] y crane = Y Crane + D * cosθ Crane

[0056] wherein, X Crane is the abscissa value of the bridge crane position value in the global coordinate system; Y Crane is the ordinate value of the bridge crane position value in the global coordinate system; D is the distance value from the center point of the target object to the center point of the bridge crane; θ Crane is the running angle.

[0057] In a second aspect, an embodiment of the present application provides a positioning device for an unmanned container truck. The unmanned container truck is equipped with a lidar. The device includes:

[0058] A first acquisition module, configured to convert the distance value output by the lidar into the global coordinate system to obtain a first position value, where the distance value is the value of the distance from the target object of the bridge crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system;

[0059] A second acquisition module, configured to obtain the second position value of the target object in the global coordinate system;

[0060] A first calculation module, configured to calculate a matching value between the first position and the second position;

[0061] A third acquisition module, configured to, when the matching value is greater than a matching threshold, acquire a target positioning result of the driverless yard truck according to the distance value and the second position value;

[0062] Wherein, that the matching degree is greater than the matching degree threshold indicates that the first position value and the second position value correspond to a target object of the same gantry crane.

[0063] In some embodiments, the third calculation module is configured to:

[0064] Calculate a matching value between the first position value and the second position value through the following formula, where the matching value is used to represent the matching degree between the first position value and the second position value and is negatively correlated with the matching degree;

[0065] gap = |(x Lidar - x Crane ) × cosθ Crane + (y Lidar - y Crane ) × sinθ Crane |

[0066] Wherein, gap is the matching value; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; x Crane is the abscissa value of the second position in the global coordinate system; y Crane is the ordinate value of the second position in the global coordinate system; θ Crane is the running angle of the gantry crane relative to the running track in the global coordinate system.

[0067] In some embodiments, the driverless yard truck is further equipped with a camera;

[0068] The device further includes:

[0069] A fifth acquisition module, configured to acquire a first gantry crane identifier collected by the camera;

[0070] A sixth acquisition module, configured to acquire a second gantry crane identifier corresponding to the second position value match;

[0071] The fourth acquisition module is configured to:

[0072] When the first gantry crane identifier and the second gantry crane identifier match, obtain the target positioning result of the driverless yard truck according to the distance value and the second position value.

[0073] In some embodiments, the driverless yard truck is further equipped with a positioning device;

[0074] The device further includes:

[0075] A seventh acquisition module, configured to acquire a first positioning result collected by the positioning device;

[0076] The fourth acquisition module includes:

[0077] A first calculation sub-module, configured to calculate a second positioning result of the driverless yard truck according to the distance value and the second position value;

[0078] A second calculation sub-module, configured to calculate the difference between the first positioning result and the second positioning result to obtain a positioning correction amount;

[0079] A first acquisition sub-module, configured to input the positioning correction amount into a Kalman filter to obtain the target positioning result of the driverless yard truck.

[0080] In some embodiments, the first acquisition module includes:

[0081] A first acquisition sub-module, configured to acquire a distance value corresponding to a first detection moment output by the lidar;

[0082] A second acquisition sub-module, configured to acquire a third positioning result of the driverless yard truck in the global coordinate system at the first detection moment;

[0083] A third acquisition sub-module, configured to acquire the heading angle of the driverless yard truck in the global coordinate system at the first detection moment;

[0084] A fourth acquisition sub-module, configured to acquire the installation position of the lidar on the driverless yard truck;

[0085] A third calculation sub-module, configured to calculate a first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

[0086] In some embodiments, the third calculation sub-module includes:

[0087] A first calculation unit, configured to calculate a fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle;

[0088] A second calculation unit, configured to calculate a first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle.

[0089] In some embodiments, the first calculation unit is configured to:

[0090] Calculate the fourth positioning result of the lidar in the global coordinate system at the first detection moment through the following formula:

[0091] X Lidar = X Location +(x mount * cosθ yaw - y mount * * sinθ yaw )

[0092] Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw )

[0093] The second calculation unit is configured to:

[0094] Calculate the first position value of the target object in the global coordinate system through the following formula:

[0095] x Lidar = X Lidar + D Lidar * sinθ yaw

[0096] y Lidar = Y Lidar + D Lidar * cosθ yaw

[0097] Wherein, X Lidar is the abscissa value of the fourth positioning result in the global coordinate system; Y Lidar is the ordinate value of the fourth positioning result in the global coordinate system; X Location is the abscissa value of the third positioning result in the global coordinate system; Y Location is the ordinate value of the third positioning result in the global coordinate system; x mount is the abscissa value of the installation position in the vehicle coordinate system; y mount is the ordinate value of the installation position in the vehicle coordinate system; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidaris the ordinate value of the first position in the global coordinate system; θ yaw is the heading angle.

[0098] In some embodiments, obtaining the second position value of the target object in the global coordinate system includes:

[0099] A receiving sub-module, configured to receive the position value of the bridge crane in the global coordinate system;

[0100] A fifth obtaining sub-module, configured to obtain the installation position of the target object on the bridge crane;

[0101] A sixth obtaining sub-module, configured to obtain the running angle of the bridge crane relative to the running track in the global coordinate system;

[0102] A fourth calculating sub-module, configured to calculate the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position, and the running angle.

[0103] In some embodiments, the fourth calculating sub-module is configured to:

[0104] Calculate the second position value of the target object in the global coordinate system through the following formula:

[0105] x crane = X Crane - D * sinθ Crane

[0106] y crane = Y Crane + D * cosθ Crane

[0107] where X Crane is the abscissa value of the bridge crane position value in the global coordinate system; Y Crane is the ordinate value of the bridge crane position value in the global coordinate system; D is the distance value from the center point of the target object to the center point of the bridge crane; θ Crane is the running angle.

[0108] In a third aspect, an embodiment of the present application provides a positioning device for an unmanned container truck, where the device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the positioning method for the unmanned container truck as described in the first aspect is implemented.

[0109] In a fourth aspect, an embodiment of the present application provides a computer storage medium, where computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by a processor, the positioning method for the unmanned container truck as described in the first aspect is implemented.

[0110] Fifth aspect, an embodiment of the present application provides a computer program product, characterized in that when the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is caused to execute the positioning method of the driverless container truck as described in the first aspect.

[0111] In an embodiment of the present application, on the one hand, the first position value of the target object in the global coordinate system can be obtained by using the distance value output by the lidar installed on the driverless container truck. On the other hand, the second position value of the target object in the global coordinate system can be obtained based on the position value of the gantry crane in the global coordinate system, that is, the position value of the target object in the global coordinate system can be obtained through two ways. After that, the position values of the target object in the global coordinate system obtained by the two ways can be matched. When the matching value between the two is less than the matching threshold, that is, when the matching degree between the two meets a certain requirement, the target positioning result of the driverless container truck can be obtained according to the distance value output by the lidar and the second position value. In this way, by using the first position and the second position with a matching degree meeting a certain requirement to obtain the target positioning result of the driverless container truck, the accuracy of the driverless container truck positioning can be ensured, and there is no need to install additional positioning devices and adopt new positioning technologies, so that the high-precision positioning problem of the driverless container truck in the gantry crane occlusion area can be solved at the lowest cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0112] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0113] Figure 1 is a schematic diagram of the application scenario provided by the embodiment of the present application;

[0114] Figure 2 is one of the flowcharts of the positioning method of the driverless container truck provided by the embodiment of the present application;

[0115] Figure 3 is a schematic diagram of the transmission of the gantry crane position value provided by the embodiment of the present application;

[0116] Figure 4 is a schematic diagram of the vehicle coordinate system and the global coordinate system provided by the embodiment of the present application;

[0117] Figure 5 is another flowchart of the positioning method of the driverless container truck provided by the embodiment of the present application;

[0118] Figure 6 is a matching flowchart of the laser detection value and the gantry crane position value provided by the embodiment of the present application;

[0119] Figure 7It is a structural diagram of the positioning device of the driverless container truck provided by the embodiment of the present application;

[0120] Figure 8 It is a structural diagram of the positioning device of the driverless container truck provided by the embodiment of the present application. Specific embodiments

[0121] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than limiting the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The following description of the embodiments is only intended to provide a better understanding of the present application by showing examples of the present application.

[0122] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, elements defined by the statement "including..." do not exclude the presence of additional identical elements in the process, method, article or device including the said elements.

[0123] For ease of understanding, the following is combined with Figure 1 Elements involved in the embodiment of the present application are described:

[0124] Element S1: Ship-to-shore crane. A ship-to-shore crane is a device used in ports for loading and unloading containers. After the driverless container truck enters the ship-to-shore crane area, the Global Positioning System (GPS) signal deteriorates, which will cause the positioning error to increase, seriously affecting the parking accuracy of the driverless vehicle and thus affecting the container loading and unloading operation. In Figure 1 it, the ship-to-shore crane is manifested as a quay crane, which is used for loading and unloading containers on the ship on the quay surface. However, it can be understood that in other implementation manners, the ship-to-shore crane can also be a yard crane, which is used for loading and unloading containers in the yard.

[0125] Element S2: The target object of the ship-to-shore crane. The target object is the detection object of the lidar installed on the driverless container truck. In Figure 1Among them, the target object of the bridge crane is manifested as the crossbeam of the bridge crane. The height of the crossbeam is much higher than that of the driverless container truck. A bridge crane has two crossbeams, one in the front and one in the back, that is, the number of crossbeams is twice the number of quay cranes. However, it can be understood that in other implementation manners, the target object can be other structures of the bridge crane.

[0126] Element S3: Lidar. The lidar can be installed on the roof of the driverless container truck and is used to detect and output the longitudinal distance between the target object and the lidar, that is, the value of the radial distance projection of the target object and the driverless container truck on the longitudinal axis of the vehicle coordinate system. Hereinafter, the value output by the lidar is referred to as the distance value or the lidar detection value.

[0127] Element S4: Camera. The camera is installed on the side of the driverless container truck and is used to detect the quay crane identifier. In Figure 1 Among them, the quay crane identifier is manifested as a quay crane identification code, but the specific manifestation form of the quay crane identifier is not limited thereby.

[0128] Element S5: Quay crane track. The quay crane track is one of the structures of the quay crane. The quay crane slides on the track to a suitable position for operation, and the offset of the current position of the quay crane relative to the reference position (hereinafter referred to as the quay crane offset) can be sent in real time.

[0129] Element S6: Quay crane offset. The quay crane offset is used to determine the position of the quay crane, that is, the position of the quay crane in the global coordinate system.

[0130] Element S7: Quay crane identification code. The quay crane identification code is the identity number of the quay crane and can be printed on the inner side of the longitudinal beam near the moving wheel of the quay crane and is the detection object of the camera.

[0131] Element S8: Signal occlusion area. In this area, the satellite signal is occluded and the satellite positioning accuracy of the driverless container truck is poor. In actual applications, the signal occlusion area varies according to the operation requirements, that is, the number of side-by-side quay cranes and the operation position determine the position and occlusion range of the signal occlusion area.

[0132] Next, in conjunction with the accompanying drawings, the positioning method of the driverless container truck provided by the embodiments of the present application will be described in detail through some embodiments and their application scenarios.

[0133] See Figure 2 , Figure 2 which is one of the flowcharts of the positioning method of the driverless container truck provided by the embodiments of the present application. The driverless container of the embodiments of the present application is at least equipped with a lidar.

[0134] As Figure 2 shown, the positioning method of the driverless container truck may include the following steps:

[0135] Step 201: Convert the distance value output by the lidar to the global coordinate system to obtain the first position value, where the distance value is the value of the distance from the target object of the bridge crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system.

[0136] When the lidar enters the effective range of the target object, it can output at least one distance value. In an alternative implementation, the effective range of the target object can be: within ±20 meters of the target object, but not limited to this. In another alternative implementation, the effective range of the target object can be determined based on characteristic information such as the intensity of the laser emitted by the lidar. For example, the greater the intensity of the laser, the greater the effective range of the target object, and vice versa.

[0137] The distance value of the target object of the bridge crane detected by the lidar can specifically be: the radial distance value between the target object and the unmanned container truck. The distance value output by the lidar is the value of the above radial distance projected onto the longitudinal axis of the vehicle coordinate system, that is, the distance value output by the lidar is the longitudinal distance between the target object and the lidar.

[0138] After obtaining the distance value output by the lidar, it can be converted to the global coordinate system to obtain the position value of the target object detected by the lidar in the global coordinate system, that is, the first position value.

[0139] It can be understood that the number of distance values output by the lidar can be greater than or equal to 1. In the case of greater than 1, the distance values output by the lidar can correspond to different target objects, that is, the output is the longitudinal distance between different target objects and the lidar.

[0140] In some embodiments, the unmanned container truck can activate the lidar when it detects that it has entered or is about to enter the occlusion area of the bridge crane, so that the lidar outputs at least one distance value when it enters the effective range of the target object. Specifically, the unmanned container truck can detect whether it has entered or is about to enter the occlusion area of the bridge crane based on the received position value of the bridge crane and its own positioning value. In this embodiment, when the unmanned container truck has not entered the occlusion area of the bridge crane or is far from the occlusion area of the bridge crane, there is no need to turn on the lidar, which can reduce the power consumption of the unmanned container truck.

[0141] Step 202: Obtain the second position value of the target object in the global coordinate system, where the second position value is calculated based on the position value of the bridge crane in the global coordinate system.

[0142] In some embodiments, obtaining the second position value of the target object in the global coordinate system can specifically be:

[0143] Receive the position value of the bridge crane;

[0144] According to the position value of the gantry crane, the second position value of the target object in the global coordinate system is calculated.

[0145] The position value of the gantry crane, that is, the position value of the gantry crane in the global coordinate system.

[0146] In specific implementation, when the gantry crane moves on the track, the moving distance (or displacement) of the gantry crane can be sensed through the track or magnetic nails buried underground, that is, the aforementioned offset.

[0147] Such as Figure 3 As shown, after the gantry crane server obtains the gantry crane offset, it can send the gantry crane offset to the solution provider server through wireless communication, such as 5G communication.

[0148] After the solution provider server receives the gantry crane offset, it can verify the received gantry crane offset. Then, for the verified gantry crane offset, the position of the gantry crane in the global coordinate system can be calculated according to the gantry crane offset, that is, the position value of the gantry crane. Then, the position value of the gantry crane can be sent to the 5G device installed on the driverless container truck through 5G communication.

[0149] After the 5G device of the driverless container truck receives the gantry crane position value sent by the solution provider server, it can be sent to the signal processing device of the driverless container truck through the industrial Ethernet, and then can be sent to the controller of the driverless container truck through the in-vehicle Ethernet, so that the controller can perform positioning calculation of the driverless container truck based on the received gantry crane position value.

[0150] It can be understood that the number of gantry crane position values received by the driverless container truck can be greater than or equal to 1. In the case of being greater than 1, the gantry crane position values can correspond to different gantry cranes. To distinguish the position values of different gantry cranes, the sender of the gantry crane position value can send the gantry crane position value and its corresponding gantry crane identifier to the driverless container truck together.

[0151] After obtaining the position value of the gantry crane in the global coordinate system, the position value of the target object of the gantry crane in the global coordinate system, that is, the second position value, can be calculated in combination with the installation position of the target object on the gantry crane.

[0152] In some other embodiments, obtaining the second position value of the target object in the global coordinate system can be specifically manifested as:

[0153] Receiving the second position value of the target object in the global coordinate system.

[0154] In this embodiment, the driverless container truck can directly obtain the position value of the target object in the global coordinate system by receiving. In this way, the calculation amount of the driverless container truck can be reduced, and further the operation burden of the driverless container truck can be reduced.

[0155] In an alternative implementation, the second position value can be calculated by the Figure 3 scheme provider server in Figure 3 and sent to the driverless yard truck through the

[0156] Step 203: Obtain the matching degree between the first position and the second position.

[0157] As can be seen from the foregoing, the first position is the position value of the target object in the global coordinate system calculated based on the distance value output by the lidar; the second position value is: the position value of the target object of the bridge crane in the global coordinate system calculated based on the position value of the bridge crane in the global coordinate system. That is, the position values of the target object in the global coordinate system are obtained through two different methods. It should be noted that the target object in step 201 (i.e., the target object corresponding to the first position value) and the target object in step 202 (i.e., the target object corresponding to the second position value) may or may not be the target objects of the same bridge crane. In the case where the two position values correspond to the target objects of the same bridge crane, theoretically, the two should be equal or approximate.

[0158] Therefore, in the embodiment of the present application, it can be verified whether the two correspond to the target objects of the same bridge crane, and the accuracy of the distance value output by the lidar and the obtained second position value can be verified by comparing the matching degree between the two with the matching degree threshold. In the embodiment of the present application, the matching degree between the two distance values can be understood as the proximity degree between the two distances.

[0159] In the case where the matching degree between the two is greater than the matching degree threshold, it indicates that the proximity degree between the two is high, the two correspond to the target objects of the same bridge crane, and the accuracy verification of the distance value output by the lidar and the obtained second position value passes, and step 204 can be executed. In this way, the positioning accuracy of the driverless yard truck can be guaranteed. That is, the matching degree being greater than the matching degree threshold indicates that the first position value and the second position value correspond to the target objects of the same bridge crane, that is to say, the first position value and the second position value are the position values of the target objects of the same bridge crane.

[0160] In the case where the matching degree between the two is less than or equal to the matching degree threshold, it indicates that the proximity degree between the two is low, the two do not correspond to the target objects of the same bridge crane, and / or the accuracy verification of the distance value output by the lidar and the obtained second position value fails, and step 201 can be executed again.

[0161] Understandably, in the case where the first position value or the second position value is multiple, the matching degree between each first position value and each second position value can be obtained respectively, and a position value matching pair with a matching degree greater than the matching degree threshold is found. Each position value includes a first position value and a second position value. After that, based on each position value matching pair, the target positioning result of the driverless straddle carrier can be obtained.

[0162] Step 204, when the matching degree is greater than the matching degree threshold, obtain the target positioning result of the driverless straddle carrier according to the distance value and the second position value.

[0163] The distance value is: the longitudinal distance between the target object and the lidar; the second position value is: the position value of the target object in the global coordinate system. Understandably, by combining the distance value, the second position value, and the installation position of the lidar on the driverless straddle carrier, the positioning result of the driverless straddle carrier in the global coordinate system can be calculated, that is, the following second positioning result.

[0164] In some embodiments, the second positioning result can be directly determined as the target positioning result of the driverless straddle carrier.

[0165] In other embodiments, the driverless straddle carrier can also be equipped with a positioning device;

[0166] Before obtaining the target positioning result of the driverless straddle carrier according to the distance value and the second position value, the method further includes:

[0167] Obtain the first positioning result collected by the positioning device;

[0168] Obtaining the target positioning result of the driverless straddle carrier according to the distance value and the second position value includes:

[0169] Calculate the second positioning result of the driverless straddle carrier according to the distance value and the second position value;

[0170] Calculate the difference between the first positioning result and the second positioning result to obtain a positioning correction amount;

[0171] Input the positioning correction amount into the Kalman filter to obtain the target positioning result of the driverless straddle carrier.

[0172] In this embodiment, the final positioning result of the driverless straddle carrier, that is, the target positioning result, can be determined by combining the self-positioning result of the driverless straddle carrier, that is, the first positioning result, and the second positioning result.

[0173] In specific implementation, the difference between the two positioning results can be used as the positioning correction amount and input into the Kalman filter to obtain the target positioning result of the driverless container truck. The operating principle of the Kalman filter can refer to related technologies and will not be described here.

[0174] In this way, by using the second positioning result to correct the positioning of the driverless container truck, the positioning accuracy of the driverless container truck can be improved.

[0175] For the positioning method of the driverless container truck in this embodiment, on the one hand, the distance value output by the lidar installed on the driverless container truck can be used to obtain the first position value of the target object in the global coordinate system. On the other hand, based on the position value of the bridge crane in the global coordinate system, the second position value of the target object in the global coordinate system can be obtained, that is, the position value of the target object in the global coordinate system can be obtained through two ways. After that, the position values of the target object in the global coordinate system obtained by the two ways can be matched. When the matching value between the two is less than the matching threshold, that is, when the matching degree between the two meets certain requirements, the target positioning result of the driverless container truck can be obtained according to the distance value output by the lidar and the second position value. In this way, by using the first position and the second position with a matching degree meeting certain requirements to obtain the target positioning result of the driverless container truck, the positioning accuracy of the driverless container truck can be guaranteed, and there is no need to install additional positioning equipment or adopt new positioning technologies, thus solving the high-precision positioning problem of the driverless container truck in the bridge crane occlusion area at the lowest cost.

[0176] In some embodiments, obtaining the matching degree between the first position value and the second position includes:

[0177] Calculate the matching value between the first position value and the second position value through the following formula. The matching value is used to represent the matching degree between the first position value and the second position value and is negatively correlated with the matching degree;

[0178] gap = |(x Lidar - x Crane ) × cosθ Crane + (y Lidar - y Crane ) × sinθ Crane |

[0179] where gap is the matching value; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; x Crane is the abscissa value of the second position in the global coordinate system; y Crane is the ordinate value of the second position in the global coordinate system; θCrane is the running angle of the bridge crane relative to the running track in the global coordinate system.

[0180] In this embodiment, the matching degree between the first position and the second position can be characterized by the matching value between the two. Among them, the matching value between the two is negatively correlated with the matching degree, that is, the smaller the matching value between the two, the higher the matching degree, and vice versa, the higher the matching degree. In this embodiment, the matching degree is greater than the matching degree threshold, which can be expressed as: the matching value is less than the matching threshold.

[0181] In an alternative implementation, the difference between the two can be directly used as the matching value between the two.

[0182] In another alternative implementation, the running angle of the bridge crane in the global coordinate system can be further combined to calculate the matching value between the two. For specific calculations, please refer to the above formula.

[0183] It can be understood that in the case where there are multiple first position values and multiple second position values, the matching value gap between the i-th first position value and the j-th second position value ij can be calculated by the following formula:

[0184]

[0185] where is the abscissa of the i-th first position in the global coordinate system; is the ordinate of the i-th first position in the global coordinate system; is the abscissa of the j-th second position in the global coordinate system; is the ordinate of the j-th second position in the global coordinate system; θ Crane is the running angle of the bridge crane on the track in the global coordinate system.

[0186] The matching value calculated by the above method can accurately reflect the matching degree between the first position value and the second position value.

[0187] In some other embodiments, the similarity value between the first position value and the second position value can be calculated, and the matching degree between the two can be reflected by the similarity value between the two. Among them, the similarity value between the two is positively correlated with the matching degree, that is, the larger the similarity value between the two, the higher the matching degree, and vice versa, the lower the matching degree. In this embodiment, the matching degree is greater than the matching degree threshold, which can be expressed as: the similarity value is less than the similarity threshold. The calculation of the similarity value can refer to the related technology and will not be described here.

[0188] In some embodiments, the driverless container truck is also equipped with a camera;

[0189] Before obtaining the target positioning result of the driverless yard truck according to the distance value and the second position value, the method may further include:

[0190] Obtain the first gantry crane identifier collected by the camera;

[0191] Obtain the second gantry crane identifier corresponding to the matched second position value;

[0192] The obtaining the target positioning result of the driverless yard truck according to the distance value and the second position value includes:

[0193] When the first gantry crane identifier and the second gantry crane identifier match, obtain the target positioning result of the driverless yard truck according to the distance value and the second position value.

[0194] As can be seen from the foregoing, the driverless yard truck can obtain the gantry crane identifier corresponding to the matched second position value.

[0195] After obtaining at least one position value matching pair, the gantry crane identifier corresponding to the second position value in each position value matching pair can be matched with the gantry crane identifier collected by the camera.

[0196] When there is a gantry crane identifier in the gantry crane identifiers collected by the camera that matches the gantry crane identifier corresponding to the second position value in a certain position value matching pair, the position value matching pair can pass the verification, and the target positioning result of the driverless yard truck can be obtained by using it; otherwise, the position value matching pair fails the verification and is an extra position value matching pair or an incorrect position value matching pair, and the position value matching pair can be removed.

[0197] The matching of the first gantry crane identifier and the second gantry crane identifier can be understood as: the first gantry crane identifier and the second gantry crane identifier identify the same gantry crane.

[0198] In this embodiment, the gantry crane identifier collected by the camera can be used to verify the matching accuracy of the position value matching pair, so as to further remove extra position value matching pairs or incorrect position value matching pairs, thereby further improving the positioning accuracy of the driverless yard truck.

[0199] The following describes the specific implementation of step 201.

[0200] In some embodiments, the converting the distance value output by the lidar to the global coordinate system to obtain the first position value includes:

[0201] Obtain the distance value corresponding to the first detection moment output by the lidar;

[0202] Obtain the third positioning result of the driverless yard truck in the global coordinate system at the first detection moment;

[0203] Obtain the heading angle of the driverless yard truck in the global coordinate system at the first detection moment;

[0204] Obtain the installation position of the lidar on the driverless yard truck;

[0205] Calculate the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

[0206] It can be understood that each distance value output by the lidar corresponds to a detection moment.

[0207] To convert the distance value corresponding to a certain detection moment output by the lidar to the global coordinate system, the following information at this detection moment can be obtained:

[0208] The positioning result of the driverless yard truck in the global coordinate system, that is, the third positioning result, can be obtained by means of the positioning device of the driverless yard truck, etc.;

[0209] The heading angle of the driverless yard truck in the global coordinate system;

[0210] The installation position on the driverless yard truck.

[0211] In this way, based on the distance value corresponding to this detection moment output by the lidar and the above information, the position value of this distance value in the global coordinate system, that is, the first position value, can be calculated.

[0212] Further, the calculating the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position may include:

[0213] Calculate the fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle;

[0214] Calculate the first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle.

[0215] In specific implementation, the positioning result of the lidar in the global coordinate system at the first detection moment, that is, the fourth positioning result, can be calculated first; then, based on the fourth positioning result, the distance value corresponding to the first detection moment output by the lidar, and the heading angle of the driverless yard truck in the global coordinate system at the first moment, calculate the position value of the distance value corresponding to the first detection moment output by the lidar in the global coordinate system, that is, the position value of the target object in the global coordinate system.

[0216] In an alternative implementation, calculating the fourth positioning result of the lidar in the global coordinate system at the first detection moment based on the third positioning result, the installation position, and the heading angle may include:

[0217] Calculate the fourth positioning result of the lidar in the global coordinate system at the first detection moment through the following formula:

[0218] X Lidar = X Location +(x mount * cosθ yaw - y mount * sinθ yaw )

[0219] Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw )

[0220] Calculating the first position value of the target object in the global coordinate system based on the fourth positioning result, the distance value, and the heading angle may include:

[0221] Calculate the first position value of the target object in the global coordinate system through the following formula:

[0222] x Lidar = X Lidar + D Lidar * sinθ yaw

[0223] y Lidar = Y Lidar + D Lidar * cosθ yaw

[0224] where X Lidar is the abscissa value of the fourth positioning result in the global coordinate system; Y Lidar is the ordinate value of the fourth positioning result in the global coordinate system; X Location is the abscissa value of the third positioning result in the global coordinate system; Y Location is the ordinate value of the third positioning result in the global coordinate system; x mount is the abscissa value of the installation position in the vehicle coordinate system; y mount is the ordinate value of the installation position in the vehicle coordinate system; x Lidar is the abscissa value of the first position in the global coordinate system; yLidar is the ordinate value of the first position in the global coordinate system; θ yaw is the heading angle.

[0225] For ease of understanding the meanings of the parameters, reference may be made to Figure 4 .

[0226] By converting the distance values output by the lidar to the global coordinate system in the above manner, the accuracy of the conversion can be improved, and further, the accuracy of the positioning of the driverless container truck can be improved.

[0227] It can be understood that the above calculation formula is only one calculation method for the above parameters, and the calculation method of calculating the above parameters is not limited thereto. Those skilled in the art can simply transform the above formula to calculate the above parameters, and all of them can fall within the protection scope of the embodiments of the present application.

[0228] The following describes the specific implementation of step 202.

[0229] In some embodiments, the obtaining the second position value of the target object in the global coordinate system includes:

[0230] Receiving the position value of the bridge crane in the global coordinate system;

[0231] Obtaining the installation position of the target object on the bridge crane;

[0232] Obtaining the running angle of the bridge crane relative to the running track in the global coordinate system;

[0233] Calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position, and the running angle.

[0234] In this embodiment, after the driverless container truck receives the position value of the bridge crane in the global coordinate system, it can calculate the position value of the target object of the bridge crane in the global coordinate system, that is, the second position value, based on the installation position of the target object on the bridge crane and the running angle of the bridge crane in the global coordinate system.

[0235] In this way, based on the position values of each bridge crane in the global coordinate system, the position values of the target objects of each bridge crane in the global coordinate system can be accurately obtained.

[0236] In an alternative implementation, the calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position, and the running angle may include:

[0237] Calculating the second position value of the target object in the global coordinate system through the following formula:

[0238] x crane= X Crane -D * sinθ Crane

[0239] y crane = Y Crane +D * cosθ Crane

[0240] Wherein, X Crane is the abscissa value of the position value of the bridge crane in the global coordinate system; Y Crane is the ordinate value of the position value of the bridge crane in the global coordinate system; D is the distance value from the center point of the target object to the center point of the bridge crane; θ Crane is the running included angle.

[0241] By the above method, based on the position value of the bridge crane in the global coordinate system, calculating the position value of the target object of the bridge crane in the global coordinate system can improve the calculation accuracy of the position value of the target object of the bridge crane in the global coordinate system, and further improve the positioning accuracy of the driverless yard truck.

[0242] It can be understood that the above calculation formula is only one calculation method of the above parameters. It can be understood that the above calculation formula is only one calculation method of the above parameters. Those skilled in the art can fall within the protection scope of the embodiments of the present application by simply transforming the above formula to calculate the above parameters.

[0243] It should be noted that the various optional implementation manners introduced in the embodiments of the present application can be combined with each other or implemented separately without conflict, and the embodiments of the present application do not make any limitations thereto.

[0244] For ease of understanding, the positioning method of the driverless yard truck in the embodiments of the present application will be described below with a specific scenario embodiment.

[0245] In this scenario embodiment, the bridge crane is a quay crane; the target object is the crossbeam of the quay crane; the distance value output by the lidar is called the lidar detection value, and the lidar outputs n lidar detection values; the driverless yard truck receives m bridge crane position values and obtains m * 2 crossbeam position values. This scenario embodiment is directed to the signal occlusion scenario of the quay crane on the dock surface in the port unmanned operation area.

[0246] Referring to Figure 5 , the positioning method of the driverless yard truck based on the port quay crane may include the following steps:

[0247] Step S1, the driverless yard truck enters the quay crane signal occlusion area.

[0248] After the operation of the driverless container truck, based on the real-time received positions of the quay cranes and the self-vehicle positioning, it is determined whether it has reached the quay surface and is approaching the signal shielding area of the quay crane. In the case of approaching the signal shielding area, the lidar can be turned on. When approaching and reaching the effective range for detecting the crossbeam of the quay crane by laser, for example: in the laser coordinate system, the detected crossbeam is within the range of ±20 meters, the laser outputs the detection value.

[0249] Step S2, verification of the key input signals of the positioning function.

[0250] In the embodiment of this scenario, the key input signals are: the laser detection values, with the number being n; the quay crane position values, with the number being m; where n and m have no relationship and are independent of each other.

[0251] It can be understood that the above key input signals are the laser detection values and quay crane position values that have passed the verification.

[0252] Step S3, matching the laser detection values with the quay crane position values.

[0253] In specific implementation, the n output laser detection values are matched with the m*2 quay crane crossbeam position values, and after the matching, the correction amount is obtained to correct the positioning result.

[0254] Reference Figure 3 , the acquisition of the quay crane position values in the key input signals can include the following steps:

[0255] Step S2_1, when the quay crane on the quay surface moves, it can sense the moving distance through the magnetic nails buried underground, and the quay crane server sends the displacement amount to the solution provider server through 5G communication.

[0256] Step S2_2, after the solution provider server receives the quay crane displacement amount, it conducts information verification (if the verification passes, it outputs the valid quay crane position value, if the verification fails, it does not output, which will be reflected in the number m), then calculates the position of the quay crane in the global coordinate system according to the displacement amount, and finally sends the quay crane position value to the 5G device of the driverless container truck through 5G communication.

[0257] Steps S2_3, S2_4, S2_5, after the 5G device equipped on the driverless container truck receives the quay crane position sent by the solution provider server, it can be forwarded to the controller through the industrial Ethernet and in-vehicle Ethernet links for positioning calculation.

[0258] Reference Figure 6 , the matching of the laser detection values and the quay crane crossbeam position values can include the following steps:

[0259] Step S3_1, the laser detection value n.

[0260] During specific implementation, when approaching the quay crane, the laser can simultaneously detect and output n (n ≤ 4) valid distance values of the quay crane crossbeam. It should be noted that this distance value refers to the value obtained by projecting the radial distance between the laser and the crossbeam surface onto the longitudinal axis of the vehicle coordinate system.

[0261] Step S3_2, project the detection value n.

[0262] During specific implementation, the laser detection value can be projected onto the global coordinate system, i.e., the same coordinate system as the quay crane position, by using the vehicle's own positioning and the installation position parameters of the lidar on the vehicle, such as Figure 4 . The formula is:

[0263] X Lidar = X Location +(x mount * cosθ yaw - y mount * sinθ yaw )

[0264] Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw )

[0265] x Lidar = X Lidar + D Lidar * sinθ yaw

[0266] y Lidar = Y Lidar + D Lidar * cosθ yaw

[0267] Among them, X / Y Lidar represents the positioning result of the lidar in the global coordinate system, X / Y Location represents the positioning result of the vehicle itself in the global coordinate system at the current moment, x / y mount represents the installation position of the lidar in the vehicle coordinate system, x / y Lidar represents the position of the laser detection value in the global coordinate system, D Lidar represents the projection of the distance value detected by the lidar for the crossbeam onto the longitudinal axis of the vehicle coordinate system, θ yaw represents the heading angle of the vehicle itself in the global coordinate system at the current moment.

[0268] Step S3_3, the position of the quay crane crossbeam m * 2.

[0269] During specific implementation, the position value of the crossbeam of the quay crane can be obtained from the position value of the quay crane and the relevant dimensions of the quay crane. The formula is:

[0270] x Fcrane = X Crane - D F * sinθ Crane

[0271] y Fcrane = Y Crane + D F * cosθ Crane

[0272] x Rcrane = X Crane + D R * sinθ Crane

[0273] y Rcrane = Y Crane - D R * cosθ Crane

[0274] Among them, x / y Fcrane represents the position of the front beam of the quay crane in the global coordinate system, and x / y Rcrane represents the position of the rear beam of the quay crane in the global coordinate system; X / Y Crane represents the position of the geometric center of the quay crane, and D F represents the distance from the geometric center of the quay crane to the front beam surface, and D R represents the distance from the geometric center of the quay crane to the rear beam surface, and θ Crane represents the running direction of the quay crane on the track in the global coordinate system.

[0275] Step S3_4, match the laser with the crossbeam of the quay crane.

[0276] During specific implementation, match the n laser detection values projected into the global coordinate system with the (m×2) crossbeam position values of the quay crane to find the n values with the highest matching degree. The matching degree formula is:

[0277]

[0278] Among them, gap ij represents the matching degree value between the i-th laser detection value and the j-th crossbeam of the quay crane. The smaller the value, the higher the matching degree; represents the i-th laser detection value (i ∈ n), represents the position value of the j-th crossbeam of the quay crane (j ∈ m×2).

[0279] Step S3_5, determine whether at least one pair is matched.

[0280] In specific implementation, if there is a gap ij <gap thresholds , then it enters step S3_7; otherwise, it enters step S3_9.

[0281] Step S3_6: The camera identifies the gantry crane code.

[0282] In specific implementation, the camera uses image detection technology to identify the code on the gantry crane.

[0283] Step S3_7: Matching accuracy verification.

[0284] The subscript j of the gap ij screened out in step S3_5 has the attribute of the gantry crane code. Then, compare the code identified in step S3_6, eliminate redundant or incorrect matching results, and retain the matching values that pass the mutual verification.

[0285] Step S3_8: Determine whether the verification passes.

[0286] In the case where the verification fails, it enters step S3_9. In the case where the verification passes, it enters step S3_10.

[0287] Step S3_9: Abnormal positioning diagnosis.

[0288] Step S3_10: Calculate the positioning correction amount.

[0289] For the matching results that pass the verification, perform positioning correction, and input the correction amount into the Kalman filter to obtain the final positioning value.

[0290] In the embodiment of this scenario, the existing resources of the port are fully utilized to solve the high-precision positioning problem in the special scenario of signal occlusion of the quay crane at the lowest cost; there is no need to install additional positioning equipment or adopt new positioning technologies, and the positioning scheme can be quickly deployed and implemented.

[0291] Based on the positioning method of the driverless yard truck provided in the above embodiment, correspondingly, the present application also provides a specific implementation manner of the positioning device for the driverless yard truck. Please refer to the following embodiments.

[0292] Refer to Figure 7 , the positioning device for the driverless yard truck provided in the embodiment of the present application may include:

[0293] The first acquisition module 701 is configured to convert the distance value output by the lidar into the global coordinate system to obtain a first position value, where the distance value is the value of the distance from the target object of the gantry crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system;

[0294] The second acquisition module 702 is configured to acquire a second position value of the target object in the global coordinate system, where the second position value is calculated based on the position value of the bridge crane in the global coordinate system;

[0295] The third calculation module 703 is configured to acquire the matching degree between the first position and the second position;

[0296] The fourth acquisition module 704 is configured to, when the matching degree is greater than a matching degree threshold, acquire a target positioning result of the driverless yard truck according to the distance value and the second position value;

[0297] Wherein, the matching degree being greater than the matching degree threshold indicates that the first position value and the second position value correspond to the target object of the same bridge crane.

[0298] In some embodiments, the third calculation module 703 is configured to:

[0299] Calculate a matching value between the first position value and the second position value through the following formula, where the matching value is used to represent the matching degree between the first position value and the second position value and is negatively correlated with the matching degree;

[0300] gap = |(x Lidar - x Crane ) × cosθ Crane + (y Lidar - y Crane ) × sinθ Crane |

[0301] Wherein, gap is the matching value; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; x Crane is the abscissa value of the second position in the global coordinate system; y Crane is the ordinate value of the second position in the global coordinate system; θ Crane is the running angle of the bridge crane relative to the running track in the global coordinate system.

[0302] In some embodiments, the driverless yard truck is further equipped with a camera;

[0303] The device further includes:

[0304] The fifth acquisition module is configured to acquire a first bridge crane identifier collected by the camera;

[0305] The sixth acquisition module is configured to acquire a second bridge crane identifier corresponding to the second position value matching;

[0306] The fourth acquisition module 704 is configured to:

[0307] When the first gantry crane identifier and the second gantry crane identifier match, obtain a target positioning result of the driverless container truck according to the distance value and the second position value.

[0308] In some embodiments, the driverless container truck is further equipped with a positioning device;

[0309] The device further includes:

[0310] A seventh acquisition module, configured to obtain a first positioning result collected by the positioning device;

[0311] The fourth acquisition module 704 includes:

[0312] A first calculation sub-module, configured to calculate a second positioning result of the driverless container truck according to the distance value and the second position value;

[0313] A second calculation sub-module, configured to calculate a difference between the first positioning result and the second positioning result to obtain a positioning correction amount;

[0314] A first acquisition sub-module, configured to input the positioning correction amount into a Kalman filter to obtain a target positioning result of the driverless container truck.

[0315] In some embodiments, the first acquisition module 701 includes:

[0316] A first acquisition sub-module, configured to obtain a distance value corresponding to a first detection moment output by the lidar;

[0317] A second acquisition sub-module, configured to obtain a third positioning result of the driverless container truck in a global coordinate system at the first detection moment;

[0318] A third acquisition sub-module, configured to obtain a heading angle of the driverless container truck in the global coordinate system at the first detection moment;

[0319] A fourth acquisition sub-module, configured to obtain an installation position of the lidar on the driverless container truck;

[0320] A third calculation sub-module, configured to calculate a first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

[0321] In some embodiments, the third calculation sub-module includes:

[0322] A first calculation unit, configured to calculate a fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle;

[0323] A second calculation unit, configured to calculate a first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle.

[0324] In some embodiments, the first calculation unit is configured to:

[0325] Calculate the fourth positioning result of the lidar in the global coordinate system at the first detection moment through the following formula:

[0326] X Lidar = X Location +(x mount * cosθ yaw - y mount * sinθ yaw )

[0327] Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw )

[0328] The second calculation unit is configured to:

[0329] Calculate the first position value of the target object in the global coordinate system through the following formula:

[0330] x Lidar = X Lidar + D Lidar * sinθ yaw

[0331] y Lidar = Y Lidar + D Lidar * cosθ yaw

[0332] Wherein, X Lidar is the abscissa value of the fourth positioning result in the global coordinate system; Y Lidar is the ordinate value of the fourth positioning result in the global coordinate system; X Location is the abscissa value of the third positioning result in the global coordinate system; Y Location is the ordinate value of the third positioning result in the global coordinate system; x mountis the abscissa value of the installation position in the vehicle coordinate system; y mount is the ordinate value of the installation position in the vehicle coordinate system; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; θ yaw is the heading angle.

[0333] In some embodiments, obtaining the second position value of the target object in the global coordinate system includes:

[0334] A receiving sub-module, configured to receive the gantry crane position value in the global coordinate system;

[0335] A fifth obtaining sub-module, configured to obtain the installation position of the target object on the gantry crane;

[0336] A sixth obtaining sub-module, configured to obtain the running angle of the gantry crane relative to the running track in the global coordinate system;

[0337] A fourth calculating sub-module, configured to calculate the second position value of the target object in the global coordinate system according to the gantry crane position value, the installation position, and the running angle.

[0338] In some embodiments, the fourth calculating sub-module is configured to:

[0339] Calculate the second position value of the target object in the global coordinate system through the following formula:

[0340] x crane = X Crane - D * sinθ Crane

[0341] y crane = Y Crane + D * cosθ Crane

[0342] wherein, X Crane is the abscissa value of the gantry crane position value in the global coordinate system; Y Crane is the ordinate value of the gantry crane position value in the global coordinate system; D is the distance value from the center point of the target object to the center point of the gantry crane; θ Crane is the running angle.

[0343] The positioning device of the driverless container truck provided by the embodiments of the present application can implement Figure 2 each process implemented by the positioning device of the driverless container truck in the method embodiment. To avoid repetition, it will not be elaborated here.

[0344] Figure 8The hardware structure diagram of the positioning device of the driverless container truck provided by the embodiment of the present application is shown. The positioning device of the driverless container truck may include a processor 801 and a memory 802 storing computer program instructions.

[0345] Specifically, the above-mentioned processor 801 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0346] The memory 802 may include a mass storage for data or instructions. By way of example and not limitation, the memory 802 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In a suitable case, the memory 802 may include removable or non-removable (or fixed) media. In a suitable case, the memory 802 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 802 is a non-volatile solid-state memory.

[0347] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described in reference to the method according to one aspect of the present disclosure.

[0348] The processor 801 reads and executes the computer program instructions stored in the memory 802 to implement any one of the positioning methods of the driverless container truck in the above embodiments.

[0349] In one example, the positioning device of the driverless container truck may further include a communication interface 803 and a bus 810. Among them, as Figure 8 shown, the processor 801, the memory 802, and the communication interface 803 are connected through the bus 810 and complete communication with each other.

[0350] The communication interface 803 is mainly used to implement communication between each module, device, unit, and / or device in the embodiments of the present application.

[0351] The bus 810 includes hardware, software, or both, and couples the components of the positioning device of the driverless container truck to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, the bus 810 may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0352] In addition, in combination with the positioning method of the driverless container truck in the above embodiments, the embodiments of the present application can provide a computer storage medium to implement. Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the positioning methods in the above embodiments is implemented.

[0353] It should be clear that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0354] The functional blocks shown in the above block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), appropriate firmware, a plug-in, a function card, and so on. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link. A "machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0355] It should also be noted that, in the exemplary embodiments mentioned in this application, some methods or systems are described based on a series of steps or devices. However, this application is not limited to the order of the above steps. That is, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0356] As described above with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each block in the flowchart and / or block diagram, and the combinations of blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more blocks of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It should also be understood that each block in the block diagram and / or flowchart, and the combinations of blocks in the block diagram and / or flowchart, can also be implemented by dedicated hardware that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0357] As mentioned above, the above is only the specific implementation manner of this application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of various equivalent modifications or replacements, and these modifications or replacements should all be covered within the protection scope of this application.

Claims

1. A positioning method for an unmanned container truck, characterized in that, The driverless container truck is installed with a lidar, and the method includes: Converting the distance value output by the lidar to the global coordinate system to obtain a first position value of the target object in the global coordinate system, where the distance value is the value of the distance from the target object of the bridge crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system; Obtaining a second position value of the target object in the global coordinate system, where the second position value is calculated based on the position value of the bridge crane in the global coordinate system; Obtaining the matching degree between the first position and the second position; When the matching degree is greater than the matching degree threshold, obtaining the target positioning result of the driverless container truck according to the distance value and the second position value; Wherein, the matching degree being greater than the matching degree threshold indicates that the first position value and the second position value correspond to the target object of the same bridge crane; Wherein, the converting the distance value output by the lidar to the global coordinate system to obtain a first position value of the target object in the global coordinate system includes: Obtaining the distance value corresponding to the first detection moment output by the lidar; Obtaining the third positioning result of the driverless container truck in the global coordinate system at the first detection moment; Obtaining the heading angle of the driverless container truck in the global coordinate system at the first detection moment; Obtaining the installation position of the lidar on the driverless container truck; Calculating the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

2. The method according to claim 1, characterized in that, The obtaining the matching degree between the first position value and the second position includes: Calculating a matching value between the first position value and the second position value through the following formula, where the matching value is used to represent the matching degree between the first position value and the second position value and is negatively correlated with the matching degree; gap = |(x Lidar - x Crane ) × cosθ Crane + (y Lidar - y Crane ) × sinθ Crane | wherein, gap is the matching value; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; x Crane is the abscissa value of the second position in the global coordinate system; y Crane is the ordinate value of the second position in the global coordinate system; θ Crane is the running angle of the bridge crane relative to the running track in the global coordinate system.

3. The method according to claim 1, wherein The driverless container truck is also installed with a camera; Before obtaining the target positioning result of the driverless container truck according to the distance value and the second position value, the method further includes: Obtaining the first bridge crane identifier collected by the camera; Obtaining the second bridge crane identifier corresponding to the matching of the second position value; The obtaining the target positioning result of the driverless container truck according to the distance value and the second position value includes: When the first bridge crane identifier and the second bridge crane identifier match, obtaining the target positioning result of the driverless container truck according to the distance value and the second position value.

4. The method according to claim 1, wherein The driverless container truck is also installed with a positioning device; Before obtaining the target positioning result of the driverless container truck according to the distance value and the second position value, the method further includes: Obtaining the first positioning result collected by the positioning device; The obtaining the target positioning result of the driverless container truck according to the distance value and the second position value includes: Calculating a second positioning result of the driverless container truck according to the distance value and the second position value; Calculating the difference between the first positioning result and the second positioning result to obtain a positioning correction amount; Input the positioning correction amount into the Kalman filter to obtain the target positioning result of the driverless yard truck.

5. The method according to claim 1, wherein The calculating the first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position includes: Calculating a fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle; Calculating the first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle.

6. The method according to claim 5, wherein The calculating the fourth positioning result of the lidar in the global coordinate system at the first detection moment according to the third positioning result, the installation position, and the heading angle includes: Calculating the fourth positioning result of the lidar in the global coordinate system at the first detection moment through the following formula: X Lidar = X Location +(x mount * cosθ yaw - y mount * sinθ yaw ) Y Lidar = Y Location +(x mount * sinθ yaw + y mount * cosθ yaw ) The calculating the first position value of the target object in the global coordinate system according to the fourth positioning result, the distance value, and the heading angle includes: Calculating the first position value of the target object in the global coordinate system through the following formula: x Lidar = X Lidar + D Lidar * sinθ yaw y Lidar = Y Lidar + D Lidar * cosθ yaw Among them, X Lidar is the abscissa value of the fourth positioning result in the global coordinate system; Y Lidar is the ordinate value of the fourth positioning result in the global coordinate system; X Location is the abscissa value of the third positioning result in the global coordinate system; Y Location is the ordinate value of the third positioning result in the global coordinate system; x mount is the abscissa value of the installation position in the vehicle coordinate system; y mount is the ordinate value of the installation position in the vehicle coordinate system; x Lidar is the abscissa value of the first position in the global coordinate system; y Lidar is the ordinate value of the first position in the global coordinate system; θ yaw is the heading angle.

7. The method according to claim 1, wherein The obtaining the second position value of the target object in the global coordinate system includes: Receiving the position value of the bridge crane in the global coordinate system; Obtaining the installation position of the target object on the bridge crane; Obtaining the running angle of the bridge crane relative to the running track in the global coordinate system; Calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position, and the running angle.

8. The method according to claim 7, wherein The calculating the second position value of the target object in the global coordinate system according to the bridge crane position value, the installation position, and the running angle includes: Calculating the second position value of the target object in the global coordinate system through the following formula: x crane = X Crane -D * sinθ Crane y crane = Y Crane + D * cosθ Crane Wherein, X Crane is the abscissa value of the position value of the bridge crane in the global coordinate system; Y Crane is the ordinate value of the position value of the bridge crane in the global coordinate system; D is the distance value from the center point of the target object to the center point of the bridge crane; θ Crane is the running angle.

9. A positioning device for an unmanned container truck, characterized in that, The driverless yard truck is equipped with a lidar, and the device includes: A first acquisition module, configured to convert the distance value output by the lidar into the global coordinate system to obtain a first position value of the target object in the global coordinate system, where the distance value is the value of the distance from the target object of the bridge crane detected by the lidar projected onto the longitudinal axis of the vehicle coordinate system; A second acquisition module, configured to obtain a second position value of the target object in the global coordinate system, where the second position value is calculated based on the position value of the bridge crane in the global coordinate system; A third acquisition module, configured to obtain the matching degree between the first position and the second position; A fourth acquisition module, configured to obtain the target positioning result of the driverless yard truck according to the distance value and the second position value when the matching degree is greater than the matching degree threshold; Wherein, the matching degree being greater than the matching degree threshold indicates that the first position value and the second position value correspond to the target object of the same bridge crane; Wherein, the first acquisition module includes: A first acquisition sub-module, configured to obtain the distance value corresponding to the first detection moment output by the lidar; The second acquisition sub-module is configured to acquire a third positioning result of the driverless yard truck in the global coordinate system at the first detection moment; The third acquisition sub-module is configured to acquire the heading angle of the driverless yard truck in the global coordinate system at the first detection moment; The fourth acquisition sub-module is configured to acquire the installation position of the lidar on the driverless yard truck; The third calculation sub-module is configured to calculate a first position value of the target object in the global coordinate system according to the distance value, the third positioning result, the heading angle, and the installation position.

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