Four-section type alignment parking method for transport vehicle and gantry crane

Abstract

The invention discloses a four-section type alignment parking method for a transport vehicle and a gantry crane, belongs to the technical field of automatic driving accurate alignment parking, and is technically characterized by comprising a long-distance coarse positioning stage, a middle-distance accurate positioning stage and a short-distance fine adjustment stage, in the long-distance coarse positioning stage, relative position information of the vehicle and the gantry crane is obtained through a millimeter-wave radar and a GPS positioning system, and a driving route for driving to an approximate area of the gantry crane is planned; in the middle-distance accurate positioning stage, scanning the three-dimensional contour of the gantry crane through a laser radar and identifying an identifier through a visual sensor, fusing data to accurately calculate the relative position deviation of the vehicle and the gantry crane, and controlling the driving direction and speed of the vehicle; in the close-range fine tuning stage, the ultrasonic sensor is used for detecting the distance between the vehicle and surrounding objects, the inertial measurement unit is used for measuring the vehicle posture, the automation level and the operation efficiency of port logistics are remarkably improved, and the operation safety is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic driving precise parking, and in particular to a four-stage parking method for a transport vehicle and a gantry crane. Background Art

[0002] As global trade continues to grow, the port logistics industry faces unprecedented challenges, including improving operational efficiency, reducing costs, and enhancing safety. Traditionally, port logistics operations rely on a large amount of manual operations, especially in the alignment process between container transport vehicles and gantry cranes, which requires manual driving of the transport vehicle to the designated location, and then the gantry crane to lift the container. This operation method is not only inefficient, but also has safety risks.

[0003] In recent years, with the rapid development of autonomous driving technology, more and more ports have begun to try to apply autonomous driving technology to container transporters to achieve automated and intelligent logistics operations. However, the alignment of autonomous container transporters and gantry cranes is still a technical challenge. Due to the complexity of the port environment, including narrow passages, frequent traffic flows, various obstacles, and the high-precision operation requirements of gantry cranes, autonomous transporters require extremely high precision and stability during the alignment process.

[0004] At present, although there are some technical solutions for the alignment of autonomous container transport vehicles and gantry cranes, most of these solutions have problems such as insufficient positioning accuracy, slow alignment speed, and poor safety. Therefore, it is particularly important to develop an efficient, accurate and safe technology for the alignment of autonomous container transport vehicles and gantry cranes. Summary of the invention

[0005] In view of the deficiencies in the prior art, an embodiment of the present invention aims to provide a four-stage parking method for a transport vehicle and a gantry crane to solve the problems in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A four-stage parking method for a transport vehicle and a gantry crane, comprising a long-distance rough positioning stage, a medium-distance precise positioning stage and a short-distance fine-tuning stage, and also comprising: In the long-distance rough positioning stage, the millimeter-wave radar and GPS positioning system are used to obtain the relative position information between the vehicle and the gantry crane, and the driving route to the approximate area of ​​the gantry crane is planned; In the mid-range precise positioning stage, the laser radar scans the gantry crane's three-dimensional outline and the visual sensor identifies the logo, and the data is integrated to accurately calculate the relative position deviation between the vehicle and the gantry crane, thereby controlling the vehicle's driving direction and speed. During the close-range fine-tuning stage, ultrasonic sensors are used to detect the distance between the vehicle and surrounding objects and an inertial measurement unit is used to measure the vehicle's posture, and the control algorithm is used to achieve the final precise parking of the vehicle.

[0007] As a further solution of the present invention, the GPS positioning system obtains the absolute geographical location of the vehicle and interacts with the geographic information system to determine the driving path. The positioning accuracy in the long-distance coarse positioning stage allows an error range of ±5 meters.

[0008] As a further solution of the present invention, the laser radar scans the structural features of the gantry crane within 20-50 meters of the vehicle from the gantry crane to obtain three-dimensional contour information, the visual sensor recognizes specific marks on the gantry crane for image analysis, and guides the vehicle to within ±2 meters of the parking position of the gantry crane in the medium-range precise positioning stage.

[0009] As a further solution of the present invention, the laser radar detects the distance between the vehicle and surrounding objects in real time when the vehicle approaches the parking position of the gantry crane, and the inertial measurement unit accurately measures the change of the vehicle's posture, and the parking accuracy in the close-range fine-tuning stage reaches the centimeter level.

[0010] As a further solution of the present invention, the point cloud matching algorithm in the medium-range precise positioning stage adopts an iterative closest point algorithm or its improved algorithm to match the point cloud data acquired by the lidar with the standard three-dimensional model of the gantry crane. The visual sensor identifies the calibration position through an image analysis algorithm based on feature point matching, and uses the Kalman filter algorithm to estimate and predict the vehicle's driving status.

[0011] As a further solution of the present invention, the short-range fine-tuning stage utilizes a proportional-integral-differential control algorithm to perform fine control on the vehicle's wheel steering and braking systems according to ultrasonic sensor distance data and inertial measurement unit attitude data.

[0012] As a further solution of the present invention, the vehicle control system activates a fault handling mechanism when a sensor fails or detects abnormal data, takes different measures according to the importance and type of the faulty sensor, and takes avoidance or braking measures according to the situation of the obstacle when an obstacle is detected on the driving route.

[0013] As a further aspect of the present invention, the vehicle control system adapts to gantry cranes and container transport vehicles of different types and sizes by updating the gantry crane model and vehicle parameters.

[0014] In summary, compared with the prior art, the embodiments of the present invention have the following beneficial effects: The four-stage alignment parking technology of the present invention includes a pre-positioning stage, a fine alignment stage, and a stable parking stage. In the pre-positioning stage, the transport vehicle uses a high-precision positioning system and an environmental perception system to plan and drive to a predetermined alignment point near the gantry crane according to the task instructions and the position information of the gantry crane. In the fine alignment stage, the transport vehicle uses a high-precision positioning system and an environmental perception system to obtain more accurate position information, calculates the position deviation through a control algorithm, and adjusts the steering and drive systems of the vehicle to achieve precise alignment of the gantry crane. In the stable parking stage, the transport vehicle uses a braking system and a stability control system to ensure that it is parked smoothly at the designated position while maintaining the alignment accuracy; By adopting the four-stage parking technology of the present invention, the self-driving container transport vehicle can achieve high-precision and high-efficiency positioning operations in the complex and changeable port environment, which significantly improves the automation level and operation efficiency of port logistics, reduces operating costs, and enhances the safety of operations.

[0015] In order to more clearly illustrate the structural features and effects of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Flowchart of an embodiment of the invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0019] In one embodiment, a four-stage parking method for a transport vehicle and a gantry crane is provided. Figure 1 , including the long-distance coarse positioning stage, the medium-distance precise positioning stage and the close-distance fine-tuning stage, and also includes: In the long-distance rough positioning stage, the millimeter-wave radar and GPS positioning system are used to obtain the relative position information between the vehicle and the gantry crane, and the driving route to the approximate area of ​​the gantry crane is planned; In the mid-range precise positioning stage, the laser radar scans the gantry crane's three-dimensional outline and the visual sensor identifies the logo, and the data is integrated to accurately calculate the relative position deviation between the vehicle and the gantry crane, thereby controlling the vehicle's driving direction and speed. During the close-range fine-tuning stage, ultrasonic sensors are used to detect the distance between the vehicle and surrounding objects and an inertial measurement unit is used to measure the vehicle's posture, and the control algorithm is used to achieve the final precise parking of the vehicle.

[0020] For further information, see Figure 1 The GPS positioning system obtains the absolute geographic location of the vehicle and interacts with the geographic information system to determine the driving path. The positioning accuracy in the long-distance coarse positioning stage allows an error range of ±5 meters.

[0021] For further information, see Figure 1 The laser radar scans the structural features of the gantry crane within 20-50 meters of the vehicle to obtain three-dimensional contour information. The visual sensor recognizes specific marks on the gantry crane for image analysis. In the medium-range precise positioning stage, the vehicle is guided to a range of ±2 meters from the parking position of the gantry crane.

[0022] For further information, see Figure 1 The laser radar detects the distance between the vehicle and surrounding objects in real time when the vehicle approaches the parking position of the gantry crane. The inertial measurement unit accurately measures the change in the vehicle's posture, and the parking accuracy in the close-range fine-tuning stage reaches the centimeter level.

[0023] For further information, see Figure 1 The point cloud matching algorithm in the mid-range precise positioning stage adopts an iterative closest point algorithm or its improved algorithm to match the point cloud data obtained by the lidar with the standard three-dimensional model of the gantry crane. The visual sensor identifies the calibration position through an image analysis algorithm based on feature point matching, and uses the Kalman filter algorithm to estimate and predict the vehicle's driving state.

[0024] For further information, see Figure 1 In the close-range fine-tuning stage, a proportional-integral-differential control algorithm is used to perform fine control on the vehicle's wheel steering and braking systems according to ultrasonic sensor distance data and inertial measurement unit attitude data.

[0025] For further information, see Figure 1 The vehicle control system starts a fault handling mechanism when a sensor fails or detects abnormal data, takes different measures according to the importance and type of the faulty sensor, and takes avoidance or braking measures according to the obstacle situation when an obstacle is detected on the driving route.

[0026] For further information, see Figure 1 The vehicle control system adapts to different types and sizes of gantry cranes and container transporters by updating the gantry crane model and vehicle parameters.

[0027] In this embodiment, (a) system installation and initialization Install lidar, visual sensors, inertial measurement units and GPS positioning systems on container transport vehicles according to design requirements. Ensure that each sensor is installed accurately and firmly, and calibrate it to ensure the accuracy of its measurement data.

[0028] The standard 3D model of the gantry crane, its identification information, and its location information in the port or logistics park are entered into the database of the vehicle control system. At the same time, relevant system parameters such as the positioning accuracy threshold and control algorithm parameters are set at each stage.

[0029] (II) Implementation of long-distance coarse positioning When the vehicle receives the instruction to go to the gantry crane for loading and unloading, the GPS positioning system is activated. The vehicle and gantry crane positions are obtained through the vehicle GPS and gantry crane GPS respectively, and sent to the vehicle control system.

[0030] The vehicle control system calculates the initial deviation of the vehicle relative to the gantry crane based on the GPS data. Based on the preset gantry crane position and the current deviation, a driving route to the general area of ​​the gantry crane is planned. For example, the path planning algorithm calculates the direction, speed and estimated driving time that the vehicle needs to travel.

[0031] The vehicle automatically drives along the planned route. During driving, it continuously updates millimeter-wave radar and GPS data and adjusts the driving direction in real time until it reaches the starting position of the medium-range precise positioning stage.

[0032] 3. Implementation of the medium-range precise positioning phase When the vehicle enters the medium-distance precise positioning stage range (20-50 meters), the lidar and visual sensor are activated. The lidar performs a three-dimensional scan of the gantry crane at a high frequency (such as 20 times per second) to obtain its detailed point cloud data. The visual sensor collects and recognizes the logo on the gantry crane.

[0033] The point cloud data acquired by the LiDAR is matched with the pre-stored standard 3D model of the gantry crane through a point cloud matching algorithm. The point cloud matching algorithm can use an iterative closest point (ICP) algorithm or its improved algorithm to calculate the precise relative position and attitude deviation between the vehicle and the gantry crane.

[0034] The identification information recognized by the visual sensor is further calibrated through image analysis algorithms (such as algorithms based on feature point matching) to further calibrate the relative position of the vehicle and the gantry crane. The data of the laser radar and visual sensor are fused, and the Kalman filter algorithm is used to estimate and predict the driving state of the vehicle.

[0035] Based on the fused data and prediction results, the vehicle control system adjusts the vehicle's driving direction and speed. For example, if it is detected that the vehicle deviates from the target parking position in the lateral direction, it will make corrections by controlling the vehicle's steering system; if there is a speed deviation in the longitudinal direction, the vehicle's driving speed will be adjusted to gradually approach the target parking position until it enters the close-range fine-tuning stage.

[0036] (IV) Implementation of the close-range fine-tuning phase When the vehicle approaches the parking position of the gantry crane (0-2 meters), it enters the precise alignment state machine. The control system calculates the vehicle deceleration based on the distance from the current position of the vehicle to the center point of the gantry crane, and sends it to the vehicle chassis, allowing the vehicle to decelerate according to the preset deceleration until the vehicle stops.

[0037] At the same time, the vehicle attitude data (such as yaw angle, pitch angle and roll angle) measured by the inertial measurement unit is used to adjust the parking attitude of the vehicle in real time. For example, if the yaw angle deviation of the vehicle is detected, the steering system of the vehicle is controlled to make fine adjustments to ensure that the vehicle finally stops at the designated parking position under the gantry crane with the correct attitude.

[0038] (V) Positioning accuracy optimization stage When the vehicle stops, check the difference between the center point of the vehicle and the position of the gantry crane. If it is greater than the accuracy threshold, the vehicle moves forward or backward at a very low speed according to the position of the vehicle relative to the gantry crane until the vehicle enters the accuracy threshold range. Then, a larger deceleration is issued to stop the vehicle.

[0039] The sophisticated path planning algorithm enables centimeter-level positioning of transport vehicles in the complex port environment. This improved accuracy ensures that the transport vehicles can accurately dock at the designated container location, reducing the risk of operation delays and safety accidents caused by positioning errors.

[0040] Improve work efficiency: Traditional manual or simple automated alignment methods are often time-consuming and easily interfered by external factors. The four-stage parking technology significantly shortens the overall time from the arrival of the transport vehicle at the target area to the completion of alignment through precise control of the three stages of pre-positioning, fine alignment and stable parking. This not only speeds up the overall operation rhythm of port logistics, but also reduces the time and resources consumed by frequent position adjustments, improving overall operation efficiency.

[0041] Enhanced work safety: In the port environment, transport vehicles frequently interact with containers, other vehicles and personnel, and safety hazards cannot be ignored. The four-stage parking technology can quickly identify and avoid potential risks such as obstacles and pedestrians in complex and changing operating scenarios through real-time environmental perception and path planning, ensuring that the transport vehicle completes the alignment operation safely and smoothly. At the same time, the technology also improves the response speed and stability of the transport vehicle in emergency situations by optimizing the braking system control strategy, further ensuring operational safety.

[0042] Promoting intelligent transformation of port logistics: The successful application of the four-stage parking technology has provided strong support for the intelligent transformation of port logistics. It not only improves the level of automated operations, but also provides port managers with more accurate and comprehensive operational monitoring and optimization basis through data collection and analysis. In addition, this technology has also achieved seamless connection with other intelligent systems of the port (such as intelligent scheduling system, remote monitoring system, etc.), jointly promoting the development of port logistics in a more efficient, green and intelligent direction.

[0043] In summary, the use of four-stage parking technology for precise positioning of autonomous container transport vehicles not only significantly improves positioning accuracy and operating efficiency, but also enhances operational safety, promotes the intelligent transformation of port logistics, and lays a solid foundation for building smart ports and achieving sustainable development of the logistics industry.

[0044] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A four-stage parking method for a transport vehicle and a gantry crane, comprising a long-distance rough positioning stage, a medium-distance precise positioning stage and a short-distance fine-tuning stage, characterized in that: Also includes: In the long-distance rough positioning stage, the millimeter-wave radar and GPS positioning system are used to obtain the relative position information between the vehicle and the gantry crane, and the driving route to the approximate area of ​​the gantry crane is planned; In the mid-range precise positioning stage, the laser radar scans the gantry crane's three-dimensional outline and the visual sensor identifies the logo, and the data is integrated to accurately calculate the relative position deviation between the vehicle and the gantry crane, thereby controlling the vehicle's driving direction and speed. During the close-range fine-tuning stage, ultrasonic sensors are used to detect the distance between the vehicle and surrounding objects and an inertial measurement unit is used to measure the vehicle's posture, and the control algorithm is used to achieve the final precise parking of the vehicle.

2. The four-stage parking method for a transport vehicle and a gantry crane according to claim 1, characterized in that: The GPS positioning system obtains the absolute geographical location of the vehicle and interacts with the geographic information system to determine the driving path. The positioning accuracy in the long-distance coarse positioning stage allows an error range of ±5 meters.

3. The four-stage parking method for a transport vehicle and a gantry crane according to claim 2, characterized in that: The laser radar scans the structural features of the gantry crane within 20-50 meters of the vehicle to obtain three-dimensional contour information. The visual sensor recognizes specific marks on the gantry crane for image analysis. In the medium-range precise positioning stage, the vehicle is guided to a range of ±2 meters from the parking position of the gantry crane.

4. The four-stage parking method for a transport vehicle and a gantry crane according to claim 3, characterized in that: The laser radar detects the distance between the vehicle and surrounding objects in real time when the vehicle approaches the parking position of the gantry crane, and the inertial measurement unit accurately measures the change in the vehicle's posture. The parking accuracy in the close-range fine-tuning stage reaches the centimeter level.

5. The four-stage parking method for a transport vehicle and a gantry crane according to claim 4, characterized in that: The point cloud matching algorithm in the medium-distance precise positioning stage adopts an iterative closest point algorithm or its improved algorithm to match the point cloud data obtained by the lidar with the standard three-dimensional model of the gantry crane. The visual sensor identifies the calibration position through an image analysis algorithm based on feature point matching, and uses the Kalman filter algorithm to estimate and predict the vehicle's driving state.

6. The four-stage parking method for a transport vehicle and a gantry crane according to claim 5, characterized in that: The close-range fine-tuning stage utilizes a proportional-integral-differential control algorithm to perform fine control of the vehicle's wheel steering and braking systems based on ultrasonic sensor distance data and inertial measurement unit attitude data.

7. The four-stage parking method for a transport vehicle and a gantry crane according to claim 6, characterized in that: The vehicle control system activates a fault handling mechanism when a sensor fails or detects abnormal data, takes different measures according to the importance and type of the faulty sensor, and takes avoidance or braking measures according to the situation of the obstacle when an obstacle is detected on the driving route.

8. The four-stage parking method for a transport vehicle and a gantry crane according to claim 7, characterized in that: The vehicle control system adapts to gantry cranes and container transporters of different types and sizes by updating the gantry crane model and vehicle parameters.

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