Container truck guiding method and device based on area array unilateral point cloud, electronic equipment and storage medium

Abstract

The invention provides a container truck guiding method and device based on area array unilateral point cloud, electronic equipment and a storage medium, and relates to the technical field of crane automation operation, the method comprises the following steps: scanning a loading lane in real time, and converting original point cloud data from a radar coordinate system to a world coordinate system through rotation and translation transformation; acquiring point cloud data of the operating vehicle to obtain vehicle point cloud data; extracting position information of the working vehicle in the length direction through the vehicle point cloud data; according to the position information, generating vehicle adjustment information for the operation vehicle, and displaying the vehicle adjustment information to a container truck position display screen; when the operating vehicle is parked in the automatic operating area, extracting position information of the operating vehicle from the point cloud data of the vehicle, and solving lifting appliance adjustment information from the lifting appliance to a target box grabbing position in combination with posture information of the lifting appliance; and the lifting appliance adjusting information is sent to the automatic control PLC system. According to the automatic grabbing and placing device, automatic grabbing or placing operation of containers for container trucks can be achieved.

Description

Technical Field

[0001] The present application relates to the technical field of automated crane operations, and in particular to a method, device, electronic device, and storage medium for guiding a container truck based on a single-sided point cloud of an array. Background Art

[0002] With the continuous advancement of automation technology, more and more container terminals have implemented automated container pickup and placement operations. The application of this technology has significantly improved operational efficiency and reduced human error. However, the operating environment of truck lanes is more complex than that of traditional container areas, mainly due to the presence of multiple moving vehicles on the lanes, changing traffic conditions, and various interference factors related to the operational process. Therefore, although automated container pickup and placement technology has been relatively successfully implemented in container areas, implementing this operation on truck lanes still poses greater technical challenges. This requires that the system design comprehensively considers the complexity and dynamic changes of the lane environment to further improve the accuracy and safety of automated operations. Therefore, a method is needed to achieve automated container pickup and placement operations for trucks. Summary of the Invention

[0003] The present application provides a container truck guidance method, device, electronic device and storage medium based on a single-side point cloud of an array, which can realize the automatic grabbing or placing of containers for container trucks.

[0004] In a first aspect of the present application, a method for guiding a container truck based on a single-side point cloud of an area array is provided, the method comprising:

[0005] Scan the lane in real time and transform the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation;

[0006] collecting point cloud data of the working vehicle according to a vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data;

[0007] Extracting the position information of the working vehicle in the longitudinal direction through the vehicle point cloud data;

[0008] Generating vehicle adjustment information for the operating vehicle based on the position information, and displaying the vehicle adjustment information on a truck position display screen to assist the driver in controlling the operating vehicle to park within the automatic operating area;

[0009] When the working vehicle is parked in the automatic working area, the position information of the working vehicle in three dimensions, namely, length, width and angle, is extracted from the vehicle point cloud data, and the position information of the working vehicle is combined with the posture information of the spreader to calculate the spreader adjustment information for the spreader to reach the target grabbing box position;

[0010] The spreader adjustment information is sent to the automatic control PLC system, which assists the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

[0011] On the basis of the above technical solution, preferably, when the working vehicle is parked in the automatic working area, the position information of the working vehicle in three dimensions of length, width and angle is extracted from the vehicle point cloud data, and the spreader adjustment information of the spreader to the target grabbing box position is solved in combination with the posture information of the spreader, which specifically includes:

[0012] Using a random sampling consistency algorithm, extracting a vertical surface close to the area array laser radar from the multiple side surfaces of the container;

[0013] Calculating a plane normal vector of the vertical plane;

[0014] Calculating a deflection angle of the container according to the plane normal vector and the first coordinate axis of the world coordinate system;

[0015] Extracting boundary information using the point cloud data of the vertical surface to obtain a first box corner and a second box corner close to the area array laser radar among a plurality of box corners of the vertical surface;

[0016] Determine a first coordinate of a projection point of the first box corner on a preset projection plane, and a second coordinate of a projection point of the second box corner on the preset projection plane;

[0017] Calculate a third coordinate and a fourth coordinate based on the first coordinate, the second coordinate, and the width of the vertical plane, wherein the third coordinate is the coordinate of a third corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane, and the fourth coordinate is the coordinate of a fourth corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane;

[0018] Calculating the center coordinates of the container based on the coordinates of the first corner, the coordinates of the second corner, the third coordinate, and the fourth coordinate;

[0019] According to the center coordinates and the spreader posture of the spreader, the adjustment parameters of the spreader from the current position to the target box grabbing position are solved to obtain the spreader adjustment information.

[0020] Based on the above technical solution, preferably, the third coordinate and the fourth coordinate are calculated according to the first coordinate, the second coordinate and the width of the container, specifically by the following formula:

[0021] x4=x1+W×cosθ

[0022] y4=y1+W×sinθ

[0023] x3=x2+W×cosθ

[0024] y3=y2+W×sinθ

[0025] Among them, (x1, y1) is the first coordinate, (x2, y2) is the second coordinate, (x3, y3) is the third coordinate, (x4, y4) is the fourth coordinate, W is the width of the vertical plane, and θ is the deflection angle.

[0026] On the basis of the above technical solution, preferably, the adjustment parameters of the spreader from the current position to the target grabbing position are solved according to the center coordinates and the spreader posture of the spreader to obtain the spreader adjustment information, which is specifically calculated by the following formula:

[0027] The coordinates of the center of the container are calculated based on the coordinates of the four corners of the container (x c ,y c ), combined with the current spreader posture, the adjustment parameters of the spreader from the current position to the ideal grab box position can be obtained:

[0028] δ x =x c -x s

[0029] δ y =y c -y s

[0030] δ θ =θ c -θ s

[0031] Among them, δ x is the translation adjustment of the spreader along the first direction, δ y is the translation adjustment of the spreader along the second direction, δ θ is the rotation angle of the spreader, (x s ,y s ,θ s ) is the posture of the spreader, (x c ,y c ) are the center coordinates.

[0032] Based on the above technical solution, preferably, after sending the spreader adjustment information to the automatic control PLC system to assist the automatic control PLC system in controlling the spreader to adjust to the operating position for the container of the operating vehicle, the method further includes:

[0033] When the spreader is adjusted to the operating position, the vehicle status of the operating vehicle is monitored in real time;

[0034] According to the vehicle status, when it is determined that the working vehicle has moved abnormally and deviated from the working position, or the distance between the vehicle driver's cab and the spreader is less than the preset distance, an early warning signal is triggered and sent to the automatic control PLC system to stop the spreader action.

[0035] On the basis of the above technical solution, preferably, the real-time scanning of the lane is performed, and the original point cloud data is converted from the radar coordinate system to the world coordinate system through rotation and translation transformation, specifically by the following formula:

[0036]

[0037] Among them, (x world ,y world ,z world ) is the coordinate in the world coordinate system, (x lidar ,y lidar ,z lidar ) is the radar coordinate system, R is the rotation matrix, and T is the translation matrix.

[0038] Based on the above technical solution, preferably, the real-time scanning of the lane and converting the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation specifically includes:

[0039] The world coordinate system is constructed based on the right-hand coordinate system rule, the first coordinate axis of the world coordinate system is parallel to the width direction of the loading lane; the second coordinate axis of the world coordinate system is parallel to the length direction of the loading lane; the first coordinate axis of the world coordinate system is parallel to the height direction of the loading lane, and the origin of the world coordinate system is located at the width center of the loading lane and the length center origin of the loading lane, and is located on the ground of the loading lane.

[0040] In a second aspect of the present application, a container truck guidance device based on a single-side point cloud of an array is provided, the device comprising an acquisition module, a processing module, and an output module, wherein:

[0041] The acquisition module is used to scan the lane in real time and convert the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation;

[0042] The acquisition module is configured to collect point cloud data of the working vehicle according to a vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data;

[0043] The acquisition module is used to extract the position information of the working vehicle in the longitudinal direction through the vehicle point cloud data;

[0044] The processing module is configured to generate vehicle adjustment information for the operating vehicle based on the position information, and display the vehicle adjustment information on a container truck position display screen to assist the driver in controlling the operating vehicle to park within the automatic operating area;

[0045] The processing module is configured to extract position information of the working vehicle in three dimensions, namely, length, width, and angle, from the vehicle point cloud data when the working vehicle is parked in the automatic working area, and calculate the spreader adjustment information for the spreader to reach the target grabbing box position in combination with the spreader posture information;

[0046] The output module is used to send the spreader adjustment information to the automatic control PLC system, so as to assist the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

[0047] On the basis of the above technical solution, preferably, the processing module is used to extract the vertical surface close to the area array laser radar from the multiple side surfaces of the container using a random sampling consistency algorithm;

[0048] The processing module is used to calculate the plane normal vector of the vertical surface;

[0049] The processing module is configured to calculate a deflection angle of the container based on the plane normal vector and the first coordinate axis of the world coordinate system;

[0050] The processing module is used to extract boundary information using the point cloud data of the vertical surface, and obtain a first box corner and a second box corner close to the area array laser radar among the multiple box corners of the vertical surface;

[0051] The processing module is used to determine the first coordinates of the projection point of the first box corner on the preset projection plane, and the second coordinates of the projection point of the second box corner on the preset projection plane;

[0052] The processing module is configured to calculate a third coordinate and a fourth coordinate based on the first coordinate, the second coordinate, and the width of the vertical plane, wherein the third coordinate is the coordinate of a third corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane, and the fourth coordinate is the coordinate of a fourth corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane;

[0053] The processing module is configured to calculate the center coordinates of the container based on the coordinates of the first corner, the coordinates of the second corner, the third coordinate, and the fourth coordinate;

[0054] The processing module is used to solve the adjustment parameters of the spreader from the current position to the target box grabbing position according to the center coordinates and the spreader posture of the spreader to obtain the spreader adjustment information.

[0055] Based on the above technical solution, preferably, the processing module is used to calculate the third coordinate and the fourth coordinate according to the first coordinate, the second coordinate and the width of the container, specifically by the following formula:

[0056] x4=x1+W×cosθ

[0057] y4=y1+W×sinθ

[0058] x3=x2+W×cosθ

[0059] y3=y2+W×sinθ

[0060] Among them, (x1, y1) is the first coordinate, (x2, y2) is the second coordinate, (x3, y3) is the third coordinate, (x4, y4) is the fourth coordinate, W is the width of the vertical plane, and θ is the deflection angle.

[0061] On the basis of the above technical solution, preferably, the processing module is used to calculate the coordinates of the center of the container (x c ,y c ), combined with the current spreader posture, the adjustment parameters of the spreader from the current position to the ideal grab box position can be obtained:

[0062] δ x =x c -x s

[0063] δ y =y c -y s

[0064] δ θ =θ c -θ s

[0065] Among them, δ x is the translation adjustment of the spreader along the first direction, δ y is the translation adjustment of the spreader along the second direction, δ θ is the rotation angle of the spreader, (x s ,y s ,θ s ) is the posture of the spreader, (x c ,y c ) are the center coordinates.

[0066] On the basis of the above technical solution, preferably, the acquisition module is used to monitor the vehicle status of the working vehicle in real time when the spreader is adjusted to the working position;

[0067] The output module is used to trigger an early warning signal and send it to the automatic control PLC system to stop the spreader action when it is determined based on the vehicle status that the working vehicle has moved abnormally and deviated from the working position, or the distance between the vehicle driver's cab and the spreader is less than a preset distance.

[0068] On the basis of the above technical solution, preferably, the processing module is used to scan the lane in real time and convert the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation, specifically through the following formula:

[0069]

[0070] Among them, (x world ,y world ,z world ) is the coordinate in the world coordinate system, (x lidar ,y lidar ,z lidar ) is the radar coordinate system, R is the rotation matrix, and T is the translation matrix.

[0071] On the basis of the above technical solution, preferably, the processing module is used to construct the world coordinate system based on the right-hand coordinate system rule, the first coordinate axis of the world coordinate system is parallel to the width direction of the loading lane; the second coordinate axis of the world coordinate system is parallel to the length direction of the loading lane; the first coordinate axis of the world coordinate system is parallel to the height direction of the loading lane, and the origin of the world coordinate system is located at the width center of the loading lane and the length center origin of the loading lane, and is located on the ground of the loading lane.

[0072] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any of the methods described above.

[0073] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions. When the instructions are executed, any one of the methods described above is executed.

[0074] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0075] 1. This application accurately obtains the position and dynamic information of the operating vehicle by scanning the loading lane in real time and converting the point cloud data from the radar coordinate system to the world coordinate system. Based on the vehicle's point cloud data, the system can extract key position information such as the vehicle's length, width and angle, and generate vehicle adjustment information to help the driver park accurately within the automatic operation area. After the vehicle is parked, the system further analyzes the vehicle's point cloud data and the spreader's posture information, calculates the precise information for adjusting the spreader to the target grabbing position, and sends the adjustment information to the automatic control PLC system, thereby controlling the spreader to automatically dock the container and perform grabbing or placement tasks, achieving efficient and precise automated operations.

[0076] 2. By accurately extracting the spatial position and posture information of the container on the handling vehicle and combining it with the spreader's posture, the spreader is precisely adjusted to the target container grabbing position. A random sampling consistency algorithm is used to extract the vertical surface of the container and calculate its normal vector. Projection and geometric calculations are then used to determine the precise boundary and center position of the container, ensuring that the spreader can accurately dock the container and perform the grab or placement operation.

[0077] 3. By monitoring the status of the operating vehicle in real time, the system ensures that the spreader remains within a safe and effective operating range during adjustment to the target operating position. If the system detects abnormal movement of the operating vehicle or the distance between the vehicle and the spreader falls below a safe preset value, it triggers a warning signal and stops the spreader, effectively avoiding possible collisions or accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is a flow chart of a method for guiding a container truck based on a single-side point cloud of an area array disclosed in an embodiment of the present application;

[0079] Figure 2 This is a module schematic diagram of a container truck guidance device based on a single-side point cloud of an area array disclosed in an embodiment of the present application;

[0080] Figure 3 This is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.

[0081] Explanation of the reference numerals: 201, acquisition module; 202, processing module; 203, output module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0082] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0083] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0084] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0085] This embodiment discloses a method for guiding trucks based on a single-sided point cloud of an array. Figure 1 , including the following steps S110-S160:

[0086] S110 scans the lane in real time and converts the raw point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation.

[0087] The embodiment of the present application discloses a method for guiding container trucks based on a single-side area array point cloud, which is applied to a server. The server includes, but is not limited to, electronic devices such as mobile phones, tablet computers, wearable devices, and personal computers (PCs). It can also be a backend server that runs the method for guiding container trucks based on a single-side area array point cloud. The server can be implemented as a standalone server or a server cluster consisting of multiple servers.

[0088] The server is also connected to an area array lidar, display screen, voice announcer, and industrial computer. The area array lidar is responsible for collecting real-time point cloud data from the operating vehicle. It is installed to the side of the truck's operating lane, with its field of view facing the lane. The area array lidar's horizontal field of view extends along the lane's length and its vertical field of view extends across the lane's width. The area array lidar's operating range must cover the area near the length and width boundaries of the operating vehicle. The area array lidar is mounted on a rotatable support component that allows adjustment of the laser's operating angle for optimal performance.

[0089] In one possible implementation, the loading lane is scanned in real time, and the original point cloud data is converted from the radar coordinate system to the world coordinate system through rotation and translation transformation, specifically including: constructing a world coordinate system based on the right-hand coordinate system rule, with the first coordinate axis of the world coordinate system parallel to the width direction of the loading lane; the second coordinate axis of the world coordinate system is parallel to the length direction of the loading lane; the first coordinate axis of the world coordinate system is parallel to the height direction of the loading lane, and the origin of the world coordinate system is located at the width center and the length center origin of the loading lane, and is located on the ground of the loading lane.

[0090] First, it is necessary to scan the area of the loading lane in real time, and convert the raw point cloud data in the radar coordinate system to the world coordinate system through rotation and translation transformations. In order to achieve this conversion, it is first necessary to establish a world coordinate system according to the rules of the right-hand coordinate system. Specifically, the X-axis of the world coordinate system should be parallel to the width direction of the lane, that is, the running direction of the container crane trolley, and the origin is located at the center of the lane width; the Y-axis should be parallel to the length direction of the lane, that is, the running direction of the container crane trolley, and the origin is located at the center of the lane length; the Z-axis is parallel to the height direction of the lane, that is, the running direction of the spreader, and the origin is set on the ground. Next, the conversion between the radar coordinate system and the world coordinate system is completed through the rotation matrix and translation matrix to ensure that the raw point cloud data can accurately reflect the actual operating environment of the lane, thereby providing accurate data support for subsequent vehicle positioning and operation adjustments.

[0091] Furthermore, the radar coordinate system is relative to the lidar itself. Its origin is typically located at the radar's installation location. The X-axis, Y-axis, and Z-axis correspond to the radar's horizontal and vertical fields of view, respectively, and its altitude. Based on the actual lane layout, the world coordinate system uses the right-hand coordinate system rule, with the X-axis parallel to the lane's width, the Y-axis parallel to the lane's length, and the Z-axis perpendicular to the lane, coinciding with its altitude. The origin is located on the lane's floor, at the center. The conversion from the radar coordinate system to the world coordinate system is achieved using a rotation matrix and a translation matrix. The rotation matrix describes the relative rotation between the radar coordinate system and the world coordinate system, while the translation matrix describes the translation relationship between the origins of the two coordinate systems. The rotation matrix primarily defines the directional relationship between the radar coordinate system and the world coordinate system. By adjusting the appropriate angles, the coordinate axes of the radar coordinate system are aligned with those of the world coordinate system. The translation matrix primarily moves the origin of the radar coordinate system to the origin of the world coordinate system, ensuring the correct spatial relationship between the coordinate systems. Scan the lane in real time and transform the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation. The specific conversion is performed using the following formula:

[0092]

[0093] Among them, (x world ,y world ,z world ) is the coordinate in the world coordinate system, (x lidar ,y lidar ,z lidar ) is the radar coordinate system, R is the rotation matrix, and T is the translation matrix.

[0094] S120 , collecting point cloud data of the working vehicle according to the vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data.

[0095] First, when the server detects the arrival of a work vehicle, it triggers a vehicle arrival signal. This signal is triggered when the actual distance the vehicle passes the center of the spreader length exceeds the set trigger value. Specifically, when a container truck enters the work area, its front and rear positions are detected by the radar server. Based on the front and rear boundary positions extracted from the point cloud, the server determines whether the vehicle has entered the work area and triggers a signal.

[0096] After a vehicle arrival signal triggers, the server begins collecting real-time point cloud data from the vehicle. An area array lidar installed on one side of the work lane scans various parts of the vehicle on the lane, acquiring real-time 3D point cloud data surrounding the vehicle. This data includes multi-dimensional spatial information such as the vehicle's length, width, and height, accurately reflecting the vehicle's real-time position and geometric characteristics.

[0097] The collected vehicle point cloud data undergoes preprocessing and filtering to remove noise and unnecessary interference. This step ensures more accurate and efficient subsequent data processing, minimizing the impact of erroneous data. The filtered point cloud data is then transmitted to an industrial computer for further analysis and processing.

[0098] After the point cloud data is transmitted to the industrial computer, the server uses it to extract key vehicle location information. For example, the front and rear of the vehicle, as well as the location of each boundary, can be used to determine the vehicle's precise parking position. This information is displayed on the truck driver's display screen, assisting the driver in controlling the vehicle's forward, reverse, or parking movements, ensuring it is parked within the designated automated operating area.

[0099] Through these steps, the server can accurately collect and process point cloud data based on the trigger signal from the work vehicle, accurately positioning the work vehicle and providing the necessary location information for subsequent automated operations. This process ensures the safety and efficiency of the entire automated operation.

[0100] S130, extracting the position information of the working vehicle in the longitudinal direction through the vehicle point cloud data.

[0101] Area array lidar collects point cloud data of the operating vehicle in real time, acquiring the vehicle's three-dimensional spatial information. To extract the longitudinal position of the operating vehicle, the server processes the point cloud data. Specifically, the server first identifies the boundaries in the vehicle's point cloud data and uses an algorithm to extract the vehicle's front and rear boundary points. These boundary points are typically reflected signals at the vehicle's front and rear ends, reflecting the vehicle's length. Next, the relative position of the front and rear boundaries in the point cloud data is used to calculate the vehicle's precise longitudinal position. This process requires the conversion between the vehicle's coordinate system and the world coordinate system to ensure that the extracted position information accurately reflects the vehicle's actual position within the operating area. This data is transmitted to the control server and displayed on the truck driver's display screen, assisting the driver in precisely adjusting the vehicle's parking position to ensure it remains within the designated automated operating area.

[0102] S140: Generate vehicle adjustment information for the operating vehicle based on the position information, and display the vehicle adjustment information on a container truck position display screen to assist the driver in controlling the operating vehicle to park within the automatic operating area.

[0103] The server uses the vehicle point cloud data collected by the area array lidar to extract the longitudinal position information of the operating vehicle. This position information can accurately identify the current actual position of the vehicle in the lane. Next, the server compares the extracted vehicle position with the predetermined automatic operation area and calculates the distance and offset between the vehicle's current and target positions. If there is a deviation between the vehicle's current position and the required position of the automatic operation area, the server will generate vehicle adjustment information. This adjustment information includes two aspects: one is the adjustment amount of the vehicle in the longitudinal direction (forward or backward), and the other is the adjustment amount of the vehicle in the width direction (left and right movement). This information can instruct the driver how to achieve precise parking by manipulating the vehicle.

[0104] The generated vehicle adjustment information is then transmitted in real time to the truck's position display. This display clearly displays the adjustment information, including the specific distance the vehicle has moved forward or backward, the amount of adjustment for left or right movement, and the vehicle's current deviation from the target position. The driver follows these instructions, precisely controlling the vehicle to park within the automated operation area, ensuring smooth progress of subsequent automated operations. Through this process, the server efficiently assists the driver in precise vehicle parking and ensures that the vehicle enters the correct operation area, thereby improving the safety and efficiency of automated operations.

[0105] S150, when the working vehicle stops in the automatic working area, the vehicle point cloud data is used to extract the position information of the working vehicle in three dimensions: length, width and angle. Combined with the posture information of the spreader, the spreader adjustment information of the spreader to the target box grabbing position is solved.

[0106] In one possible implementation, when the operating vehicle is parked in the automatic operating area, the vehicle point cloud data is used to extract the position information of the operating vehicle in three dimensions of length, width and angle, and combined with the posture information of the spreader, the spreader adjustment information of the spreader to the target box grabbing position is solved, specifically including: using a random sampling consistency algorithm to extract the vertical surface close to the area array laser radar from multiple side surfaces of the container; calculating the plane normal vector of the vertical surface; calculating the deflection angle of the container based on the plane normal vector and the first coordinate axis of the world coordinate system; using the point cloud data of the vertical surface to extract the boundary information, and obtain the first box corner and the second box corner close to the area array laser radar from multiple box corners of the vertical surface. Angle; determine the first coordinate of the projection point of the first box corner on the preset projection plane, and the second coordinate of the projection point of the second box corner on the preset projection plane; calculate the third coordinate and the fourth coordinate according to the first coordinate, the second coordinate and the width of the vertical plane, wherein the third coordinate is the coordinate of the third box corner farthest from the area array laser radar among the multiple box corners in the vertical plane, and the fourth coordinate is the coordinate of the fourth box corner farthest from the area array laser radar among the multiple box corners in the vertical plane; calculate the center coordinate of the container according to the coordinate of the first box corner, the coordinate of the second box corner, the third coordinate and the fourth coordinate; solve the adjustment parameters of the spreader from the current position to the target container grabbing position according to the center coordinate and the spreader posture of the spreader, and obtain the spreader adjustment information.

[0107] Specifically, when a work vehicle is parked within the automated operation zone, the server extracts the vehicle's position in three dimensions: length, width, and angle, using point cloud data collected by the area array LiDAR. This information is used to determine the vehicle's exact position and, combined with the spreader's current posture, further calculate the spreader's adjustment information to ensure it accurately reaches the target container grabbing position.

[0108] Next, the server uses the Random Sample Consensus Algorithm (RANSAC) algorithm to extract the vertical surface closest to the area array lidar from the container's multiple sides. This process identifies points in the point cloud data that have linear features, determining the boundaries of the container's vertical surface. The normal vector of the vertical surface is calculated, and its direction defines the spatial orientation of the surface relative to the world coordinate system.

[0109] Specifically, before executing the RANSAC algorithm, the point cloud data collected by the area array lidar must be preprocessed. This preprocessing involves removing noise and irrelevant points. Using a filtering algorithm, low-density or irrelevant point cloud data is removed, while retaining the point cloud portions relevant to the container, ensuring processing efficiency and accuracy.

[0110] In point cloud data, the sides of containers are typically flat and have distinct linear features. The Random Sampling Consensus algorithm randomly selects points from the preprocessed point cloud data and fits a plane to these points. This process is repeated until a plane model that best meets the requirements is found. For each set of randomly selected points, RANSAC uses the least squares method or other fitting algorithms to calculate the equation of the fitted plane.

[0111] Assuming that the container surface is rotated relative to the standard coordinate system, the rotation can be represented by the rotation matrix R. The rotation matrix transforms the normal vector of the container surface from the local coordinate system to the global coordinate system.

[0112] The rotation matrix R is a 3×3 matrix that defines the rotation operation and is expressed as:

[0113]

[0114] This matrix converts the components of the normal vector in the local coordinate system (A local ,B local ,C local ) to the world coordinate system:

[0115]

[0116] Among them, (A global ,B global ,C global ) is the normal component of the rotated plane.

[0117] In addition, the container face may be offset relative to the origin, and the offset can be expressed as a translation vector T:

[0118]

[0119] This translation vector represents the distance between the plane and the origin. Typically, the translation vector is added to the constant term in the plane equation.

[0120] If the surface of the container is not perpendicular to the standard coordinate system, the plane equation is expressed as follows:

[0121] Ax+By+Cz+D+α·(x-x0)·(y-y0)=0

[0122] Where α is an additional coefficient used to adjust the plane equation to take into account the changes in the container surface in different directions, (x0, y0) are the coordinates of a reference point on the container surface, and D is a constant term.

[0123] The RANSAC algorithm uses a threshold to calculate the distance between the current fitted plane and other points in the point cloud. If the distance between a point and the plane is less than the threshold, the point is considered an inlier of the plane model. The algorithm then calculates the number of inliers that match the current plane model. The greater the number of inliers, the more reliable the model.

[0124] RANSAC will perform random sampling multiple times in the preprocessed point cloud data, fitting a new plane each time and evaluating its number of inliers. After multiple iterations, the plane with the most inliers is selected as the final model, and this plane is considered to be the vertical plane on the side of the container close to the area array lidar. Since the side of the container is generally perpendicular to the lane direction, RANSAC will select a plane perpendicular to the lane direction from the multiple fitted plane models. By analyzing the direction of the normal vector, it is determined which plane is the vertical plane closest to the side where the area array lidar is located. If necessary, the best vertical plane can be further screened by comparing the angle between the normal vector and the preset direction.

[0125] Finally, the vertical surface extracted by RANSAC can provide the position and orientation of the surface. The point cloud data of this vertical surface can be further used for subsequent processing such as container boundary extraction, corner location, and container posture calculation.

[0126] The server then calculates the container's rotation angle based on the obtained normal vector to the vertical plane and the first axis of the world coordinate system. This angle is calculated by calculating the angle between the normal vector and the X-axis, representing the container's rotation direction relative to the lane.

[0127] Next, the server extracts multiple container corners on the vertical plane from the vertical point cloud data, specifically selecting the first and second container corners on the side closest to the area array lidar. These two corners are used to describe the container's boundaries. Based on these boundary points, the server calculates the coordinates of the projection points of these two container corners on the preset projection plane, obtaining the first and second coordinates.

[0128] After obtaining the first and second coordinates, the server further calculates the third coordinate of the third corner and the fourth coordinate of the fourth corner, which are farther from the area array lidar, based on the width of the vertical plane and the positions of these boundary points. Using these coordinates, the server can fully define the projection positions of the four corners of the container on the preset projection plane. The third and fourth coordinates are calculated based on the first and second coordinates and the width of the container using the following formula:

[0129] x4=x1+W×cosθ

[0130] y4=y1+W×sinθ

[0131] x3=x2+W×cosθ

[0132] y3=y2+W×sinθ

[0133] Among them, (x1, y1) is the first coordinate, (x2, y2) is the second coordinate, (x3, y3) is the third coordinate, (x4, y4) is the fourth coordinate, W is the width of the vertical plane, and θ is the deflection angle.

[0134] With the coordinates of the four corners, the server calculates the center coordinates of the container, which are determined by the geometric center of the four corners. This position represents the exact center of the container and is the key reference point for spreader grabbing.

[0135] Finally, based on the spreader's current posture, including its position and angle, the server calculates the spreader's adjustment parameters from its current position to the target container-grabbing location based on the coordinates of the container center. These adjustment parameters include the trolley's translational amount, the truck's translational amount, and the rotation angle, ensuring the spreader can accurately adjust to the target grabbing position and complete the container grabbing task.

[0136] S160: Send the spreader adjustment information to the automatic control PLC system to assist the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

[0137] After the server extracts the position and posture of the operating vehicle's container through area array lidar and point cloud data analysis, it calculates the adjustment information for the spreader. This adjustment information includes the spreader's translation, rotation angle, and target grasping position. The calculated spreader adjustment information is then transmitted to the automatic control PLC system. After receiving this information, the PLC system adjusts the spreader's movement in real time through control signals. Specifically, the PLC system connects to the spreader's drive server to control the spreader's up and down, left and right, front and back movement, and rotation angle to ensure that the spreader can accurately align with the container's operating position. When the spreader completes the adjustment and reaches the predetermined position, the PLC system will perform the corresponding grasping or placement operation to ensure the efficiency and safety of the operation. The entire process is automated through closed-loop control, reducing human intervention and improving operational accuracy.

[0138] In one possible embodiment, after the spreader adjustment information is sent to the automatic control PLC system to assist the automatic control PLC system in controlling the spreader to adjust to the working position for the container of the working vehicle, the method further includes: when the spreader is adjusted to the working position, real-time monitoring of the vehicle status of the working vehicle; when it is determined based on the vehicle status that the working vehicle has moved abnormally and deviated from the working position, or the distance between the vehicle driver's cab and the spreader is less than a preset distance, triggering a warning signal and sending it to the automatic control PLC system to stop the spreader action.

[0139] Specifically, while the spreader is being adjusted to the operating position, the server uses lidar or visual sensors to monitor the status of the operating vehicle in real time, particularly its dynamic position and trajectory. By analyzing the collected point cloud data or other sensory information, the server can determine whether the operating vehicle is following the predetermined trajectory. If the server detects abnormal vehicle movement, causing it to deviate from the operating position, or when the distance between the vehicle's cab and the spreader falls below the preset safety distance, the server immediately identifies this anomaly. At this point, the server triggers a warning signal and sends it to the automatic control PLC system. Upon receiving the warning signal, the PLC system immediately stops all spreader movements to avoid potential collisions or other safety risks. This real-time monitoring and warning mechanism ensures safety and accuracy during operations and prevents accidents.

[0140] This embodiment also discloses a truck guiding device based on a single-side point cloud of an array, referring to Figure 2 The device includes an acquisition module 201, a processing module 202 and an output module 203, wherein:

[0141] The acquisition module 201 is used to scan the lane in real time and convert the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation.

[0142] The acquisition module 201 is used to collect point cloud data of the working vehicle according to the vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data.

[0143] The acquisition module 201 is used to extract the longitudinal position information of the working vehicle through the vehicle point cloud data.

[0144] The processing module 202 is used to generate vehicle adjustment information for the working vehicle according to the position information, and display the vehicle adjustment information on the container truck position display screen to assist the driver in controlling the working vehicle to park in the automatic working area.

[0145] The processing module 202 is used to use the vehicle point cloud data to extract the position information of the working vehicle in three dimensions: length, width and angle when the working vehicle is parked in the automatic working area, and combine it with the posture information of the spreader to solve the spreader adjustment information for the spreader to the target grab box position.

[0146] The output module 203 is used to send the spreader adjustment information to the automatic control PLC system, so as to assist the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

[0147] In a possible implementation, the processing module 202 is configured to extract a vertical surface close to the area array laser radar from among the multiple side surfaces of the container using a random sampling consistency algorithm.

[0148] The processing module 202 is configured to calculate a plane normal vector of a vertical plane.

[0149] The processing module 202 is configured to calculate the deflection angle of the container according to the plane normal vector and the first coordinate axis of the world coordinate system.

[0150] The processing module 202 is used to extract boundary information using the point cloud data of the vertical surface, and obtain a first box corner and a second box corner close to the area array laser radar among multiple box corners of the vertical surface.

[0151] The processing module 202 is configured to determine a first coordinate of a projection point of a first box corner on a preset projection plane, and a second coordinate of a projection point of a second box corner on the preset projection plane.

[0152] The processing module 202 is used to calculate the third coordinate and the fourth coordinate based on the first coordinate, the second coordinate and the width of the vertical plane, wherein the third coordinate is the coordinate of the third box corner farthest from the array laser radar among the multiple box corners of the vertical plane, and the fourth coordinate is the coordinate of the fourth box corner farthest from the array laser radar among the multiple box corners of the vertical plane.

[0153] The processing module 202 is configured to calculate the center coordinates of the container according to the coordinates of the first corner of the container, the coordinates of the second corner of the container, the third coordinates, and the fourth coordinates.

[0154] The processing module 202 is used to solve the adjustment parameters of the spreader from the current position to the target box grabbing position according to the center coordinates and the spreader posture of the spreader to obtain spreader adjustment information.

[0155] In a possible implementation, the processing module 202 is configured to calculate the third coordinate and the fourth coordinate according to the first coordinate, the second coordinate, and the width of the container, specifically by the following formula:

[0156] x4=x1+W×cosθ

[0157] y4=y1+W×sinθ

[0158] x3=x2+W×cosθ

[0159] y3=y2+W×sinθ

[0160] Among them, (x1, y1) is the first coordinate, (x2, y2) is the second coordinate, (x3, y3) is the third coordinate, (x4, y4) is the fourth coordinate, W is the width of the vertical plane, and θ is the deflection angle.

[0161] In a possible implementation, the processing module 202 is configured to calculate the coordinates of the center of the container (x c ,y c ), combined with the current spreader posture, the adjustment parameters of the spreader from the current position to the ideal grab box position can be obtained:

[0162] δ x =x c -x s

[0163] δ y =y c -y s

[0164] δ θ =θ c -θ s

[0165] Among them, δ x is the translation adjustment of the spreader along the first direction, δ y is the translation adjustment of the spreader along the second direction, δ θ is the rotation angle of the spreader, (x s ,y s ,θ s ) is the hanger posture, (x c ,y c ) are the center coordinates.

[0166] In a possible implementation, the acquisition module 201 is configured to monitor the vehicle status of the operating vehicle in real time when the spreader is adjusted to the operating position.

[0167] The output module 203 is used to trigger an early warning signal and send it to the automatic control PLC system to stop the spreader action when it is determined based on the vehicle status that the working vehicle has moved abnormally and deviated from the working position, or the distance between the vehicle driver's cab and the spreader is less than a preset distance.

[0168] In one possible implementation, the processing module 202 is configured to scan the lane in real time and convert the raw point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformations, specifically using the following formula:

[0169]

[0170] Among them, (x world ,y world ,z world ) is the coordinate in the world coordinate system, (x lidar ,y lidar ,z lidar) is the radar coordinate system, R is the rotation matrix, and T is the translation matrix.

[0171] In one possible implementation, processing module 202 is configured to construct a world coordinate system based on a right-hand coordinate system rule, wherein a first coordinate axis of the world coordinate system is parallel to the width of the loading lane, a second coordinate axis of the world coordinate system is parallel to the length of the loading lane, a first coordinate axis of the world coordinate system is parallel to the height of the loading lane, and the origin of the world coordinate system is located at the width center and the length center of the loading lane, and is located on the ground of the loading lane.

[0172] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0173] This embodiment also discloses an electronic device, referring to Figure 3 The electronic device may include: at least one processor 301 , at least one communication bus 302 , a user interface 303 , a network interface 304 , and at least one memory 305 .

[0174] The communication bus 302 is used to implement the connection and communication between these components.

[0175] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0176] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0177] The processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various parts of the entire server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and calling data stored in the memory 305, the processor 301 performs various server functions and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display; and the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 301 and may be implemented separately on a single chip.

[0178] The memory 305 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also optionally be at least one storage device located away from the aforementioned processor 301. The memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface 303 module, and an application for a method for guiding a container truck based on a single-side point cloud of an array.

[0179] exist Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call an application program stored in the memory 305 for a method for guiding a truck based on a single-sided point cloud of an array. When executed by one or more processors 301, the electronic device executes one or more methods in the above-mentioned embodiments.

[0180] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0181] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0182] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0183] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0184] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0185] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory 305 and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory 305 includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disk.

[0186] The present application also discloses a computer-readable storage medium storing instructions, which, when executed by one or more processors 301, enable an electronic device to execute one or more of the methods described in the above embodiments.

[0187] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for guiding trucks based on single-sided point cloud of an area array, characterized in that: The method comprises: Scan the lane in real time and transform the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation; collecting point cloud data of the working vehicle according to a vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data; Extracting the position information of the working vehicle in the longitudinal direction through the vehicle point cloud data; Generating vehicle adjustment information for the operating vehicle based on the position information, and displaying the vehicle adjustment information on a truck position display screen to assist the driver in controlling the operating vehicle to park within the automatic operating area; When the working vehicle is parked in the automatic working area, the position information of the working vehicle in three dimensions, namely, length, width and angle, is extracted from the vehicle point cloud data, and the position information of the working vehicle is combined with the posture information of the spreader to calculate the spreader adjustment information for the spreader to reach the target grabbing box position; The spreader adjustment information is sent to the automatic control PLC system, which assists the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

2. The method for guiding container trucks based on a single-side point cloud of an area array according to claim 1, characterized in that: When the working vehicle is parked in the automatic working area, the position information of the working vehicle in three dimensions of length, width and angle is extracted from the vehicle point cloud data, and the position information of the working vehicle is combined with the posture information of the spreader to solve the spreader adjustment information for the spreader to the target grabbing box position, specifically including: Using a random sampling consistency algorithm, extracting a vertical surface close to the area array laser radar from the multiple side surfaces of the container; Calculating a plane normal vector of the vertical surface; Calculating a deflection angle of the container according to the plane normal vector and the first coordinate axis of the world coordinate system; Using the point cloud data of the vertical surface, boundary information is extracted to obtain a first box corner and a second box corner close to the area array laser radar among a plurality of box corners of the vertical surface; Determine a first coordinate of a projection point of the first box corner on a preset projection plane, and a second coordinate of a projection point of the second box corner on the preset projection plane; Calculate a third coordinate and a fourth coordinate based on the first coordinate, the second coordinate, and the width of the vertical plane, wherein the third coordinate is the coordinate of a third corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane, and the fourth coordinate is the coordinate of a fourth corner of the vertical plane that is farthest from the area array laser radar among the multiple corners of the vertical plane; Calculating the center coordinates of the container based on the coordinates of the first corner, the coordinates of the second corner, the third coordinate, and the fourth coordinate; According to the center coordinates and the spreader posture of the spreader, the adjustment parameters of the spreader from the current position to the target box grabbing position are solved to obtain the spreader adjustment information.

3. The method for guiding container trucks based on a single-side point cloud of an area array according to claim 2, characterized in that: The third coordinate and the fourth coordinate are calculated according to the first coordinate, the second coordinate and the width of the container, specifically by the following formula: x4=x1+W×cosθ y4=y1+W×sinθ x3=x2+W×cosθ y3=y2+W×sinθ Among them, (x1, y1) is the first coordinate, (x2, y2) is the second coordinate, (x3, y3) is the third coordinate, (x4, y4) is the fourth coordinate, W is the width of the vertical plane, and θ is the deflection angle.

4. The method for guiding container trucks based on a single-side point cloud of an area array according to claim 2, characterized in that: The adjustment parameters of the spreader from the current position to the target grabbing position are solved according to the center coordinates and the spreader posture of the spreader to obtain the spreader adjustment information, which is specifically calculated by the following formula: The coordinates of the center of the container are calculated based on the coordinates of the four corners of the container (x c ,y c ), combined with the current spreader posture, the adjustment parameters of the spreader from the current position to the ideal grab box position can be obtained: δ x =x c -x s δ y =and c -and s d θ =θ c -θ s Among them, δ x is the translation adjustment of the spreader along the first direction, δ y is the translation adjustment of the spreader along the second direction, δ θ is the rotation angle of the spreader, (x s ,y s ,θ s ) is the posture of the spreader, (x c ,y c ) are the center coordinates.

5. The method for guiding container trucks based on single-side point cloud of area array according to claim 1, characterized in that: After sending the spreader adjustment information to the automatic control PLC system to assist the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle, the method further includes: When the spreader is adjusted to the operating position, the vehicle status of the operating vehicle is monitored in real time; According to the vehicle status, when it is determined that the working vehicle has moved abnormally and deviated from the working position, or the distance between the vehicle driver's cab and the spreader is less than the preset distance, an early warning signal is triggered and sent to the automatic control PLC system to stop the spreader action.

6. The method for guiding container trucks based on single-side point cloud of area array according to claim 1, characterized in that: The real-time scanning of the lane is performed, and the original point cloud data is converted from the radar coordinate system to the world coordinate system through rotation and translation transformation. The conversion is specifically performed using the following formula: Among them, (x world ,y world ,z world ) is the coordinate in the world coordinate system, (x lidar ,y lidar ,z lidar ) is the radar coordinate system, R is the rotation matrix, and T is the translation matrix.

7. The method for guiding container trucks based on a single-side point cloud of an area array according to claim 1, characterized in that: The real-time scanning of the lane and the conversion of the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation specifically include: The world coordinate system is constructed based on the right-hand coordinate system rule, the first coordinate axis of the world coordinate system is parallel to the width direction of the loading lane; the second coordinate axis of the world coordinate system is parallel to the length direction of the loading lane; the first coordinate axis of the world coordinate system is parallel to the height direction of the loading lane, and the origin of the world coordinate system is located at the width center of the loading lane and the length center origin of the loading lane, and is located on the ground of the loading lane.

8. A container truck guidance device based on a single-side point cloud array, characterized in that: The device comprises an acquisition module (201), a processing module (202) and an output module (203), wherein: The acquisition module (201) is used to scan the lane in real time and convert the original point cloud data from the radar coordinate system to the world coordinate system through rotation and translation transformation; The acquisition module (201) is used to collect point cloud data of the working vehicle according to the vehicle arrival signal triggered by the working vehicle to obtain vehicle point cloud data; The acquisition module (201) is used to extract the position information of the working vehicle in the longitudinal direction through the vehicle point cloud data; The processing module (202) is used to generate vehicle adjustment information for the operating vehicle based on the position information, and display the vehicle adjustment information on a truck position display screen to assist the driver in controlling the operating vehicle to park within the automatic operating area; The processing module (202) is used to extract the position information of the working vehicle in three dimensions of length, width and angle from the vehicle point cloud data when the working vehicle is parked in the automatic working area, and to calculate the spreader adjustment information for the spreader to the target grabbing box position in combination with the spreader posture information; The output module (203) is used to send the spreader adjustment information to the automatic control PLC system, and assist the automatic control PLC system in controlling the spreader to adjust to the operating position of the container of the operating vehicle.

9. An electronic device, characterized in that: The electronic device comprises a processor (301), a communication bus (302), a user interface (303), a network interface (304) and a memory (305), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are both used to communicate with other devices, the communication bus (302) is used to realize connection and communication between components in the electronic device, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

Images