Shore power system carrying platform movement control method and device and electronic equipment

Abstract

The invention relates to a shore power system carrying platform movement control method and device and electronic equipment, and belongs to the technical field of mobile equipment power transmission, and the method comprises the steps: obtaining the positioning data of a shore power carrying platform; based on a topological map, according to a preset target point position and the positioning data, generating an optimal path; according to the total path distance of the optimal path, target state information of the carrying platform under each time node is calculated, and the state information comprises position information, driving direction information and speed information; determining theoretical motion state information of the carrying platform according to error information between the real-time state information of the carrying platform and the target state information under the corresponding time node; and according to the theoretical motion state information, controlling the carrying platform to move to a preset target point position according to an optimal path. The technical problem that the positioning precision and the moving efficiency are low due to the fact that the shore power system mainly depends on manual operation and is operated by a driver or remotely controlled to move is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile device power transmission, and in particular to a shore power system carrying platform movement control method, device and electronic equipment. Background Art

[0002] With the introduction of the concept of green port development, the use of shore power systems to power ships at berth has gradually replaced the traditional way of using ships' own power supply systems to power ships. The shore power system consists of three parts: the shore power supply system, the cable connection equipment, and the ship power receiving system. The power supply interface of the shore power supply system is mainly a fixed power connection box and a mobile vehicle-mounted type. The current technology can realize the installation of the shore power supply system as a whole on a transport vehicle. When the berthed ship needs to connect to shore power, the system is transported to the port berth by a transport vehicle. The operation and driving of the transport vehicle is still manual, which has the disadvantages of low efficiency and the need for driver training. The autonomous mobile control and remote scheduling of the vehicle-mounted shore power system can improve the work efficiency of the port and reduce the manpower burden. Therefore, a solution for autonomous mobile control of the vehicle-mounted shore power system is needed.

[0003] The existing vehicle-mounted shore power system is mainly moved by manual operation, which is operated by the driver or remotely controlled. It mainly controls the movement of the vehicle-mounted shore power system between the power supply interface positions of each berth. When the berthing position of the ship is offset, the vehicle-mounted shore power system needs to adjust its position, but it cannot be adjusted quickly. The multi-positioning information fusion technology is used to obtain the positioning combined with the vehicle chassis walking control algorithm. Under the premise of meeting the positioning accuracy and movement efficiency of the vehicle-mounted shore power system, the autonomous movement of the vehicle-mounted shore power equipment can be realized, thereby improving the terminal operation efficiency. Summary of the invention

[0004] In view of this, it is necessary to provide a shore power system carrying platform movement control method, device and electronic equipment to solve the technical problem that the movement of the shore power system in the prior art mainly relies on manual operation, which is operated by the driver or remotely controlled, resulting in low positioning accuracy and movement efficiency.

[0005] In order to solve the above problems, the present invention provides a shore power system carrying platform movement control method, comprising: Obtain the positioning data of the shore power platform; Based on the topological map, an optimal path is generated according to the preset target point position and the positioning data; and according to the total path distance of the optimal path, the target state information of the shore power carrying platform at each time node is calculated, wherein the state information includes position information, driving direction and speed information; Determine theoretical motion state information of the shore power carrying platform according to error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; According to the theoretical motion state information, the shore power carrying platform is controlled to move to a preset target point position along an optimal path.

[0006] In a possible implementation, the obtaining of the positioning data of the shore power carrying platform includes: Acquire positioning data based on differential GPS, inertial navigation system data, and drive wheel encoder data; The positioning data of the differential GPS, the data of the inertial navigation system and the data of the driving wheel encoder are fused to obtain fused positioning data.

[0007] In a possible implementation, fusing the positioning data of the differential GPS, the inertial navigation system data, and the data of the driving wheel encoder to obtain the fused positioning data includes: The preset extended Kalman filter method is used to predict the vehicle's state information based on the data from the inertial navigation system and the drive wheel encoder to obtain the initial positioning data; Based on the preset extended Kalman filter method, the initial positioning data is corrected according to the positioning data of the differential GPS to obtain the fused positioning data.

[0008] In a possible implementation, the generating of the optimal path based on the topological map according to the preset target point position and the positioning data includes: Establish a topological map that matches the GPS positioning information in the working port environment; According to the preset target point position and the fused positioning data, the preset Dijkstra algorithm is used to generate the optimal path.

[0009] In a possible implementation, the calculating the target state information of the shore power carrying platform at each time node according to the total path distance of the optimal path includes: Based on the total path distance and the principle of smooth driving, determine the function of speed changing with time and the function of distance changing with time; According to the speed-time variation function and the distance-time variation function, the inverse solution method is used to determine the target state information of the shore power platform at each time node.

[0010] In a possible implementation, determining the theoretical motion state information of the shore power carrying platform according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node includes: Obtaining real-time orientation information of the shore power carrying platform, and determining the orientation error between the real-time orientation information and the target orientation information; A left-handed coordinate system is established with the center of the shore power platform as the origin and the direction of travel as the x-axis; and the real-time position information and direction error are converted into the left-handed coordinate system; With x-axis error, y-axis error, angle error, theoretical speed and theoretical angular velocity as input, a preset controller is used to obtain theoretical motion state information.

[0011] In a possible implementation, the method further includes: According to the obstacle information fed back by the lidar monitoring, the shore power platform is controlled to stop running.

[0012] In a second aspect, the present invention further provides a shore power system carrying platform movement control device, comprising: An acquisition module is used to obtain the positioning data of the shore power carrying platform; The target state information determination module is used to generate an optimal path based on the topological map, according to the preset target point position and the positioning data; and calculate the target state information of the shore power carrying platform at each time node according to the total path distance of the optimal path, wherein the state information includes position information, driving direction and speed information; Theoretical motion state information determination module, used to determine the theoretical motion state information of the shore power carrying platform according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; The motion module is used to control the shore power carrying platform to move to a preset target point along an optimal path according to the theoretical motion state information.

[0013] In a third aspect, the present invention further provides an electronic device, comprising: a processor and a memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps in the shore power system carrying platform movement control method as described above are implemented.

[0014] In a fourth aspect, the present invention further provides a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the shore power system carrying platform movement control method as described above.

[0015] The beneficial effects of the present invention are: firstly, the positioning data of the shore power carrying platform is obtained; then, based on the topological map of the working port of the shore power system, the optimal path is generated according to the preset target point position and the positioning data; and according to the total path distance of the optimal path, the target state information of the shore power carrying platform at each time node is calculated, wherein the state information includes the position information, the driving direction and the speed information; thus, the theoretical motion state information of the shore power carrying platform can be determined according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; finally, according to the theoretical motion state information, the shore power carrying platform is controlled to move to the preset target point position according to the optimal path. The task of quickly and accurately processing and dispatching mobile shore power equipment is realized, the smooth progress of the work is ensured, and the problem of low efficiency caused by the need for manual driving or remote operation is eliminated. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A method flow chart of an embodiment of a shore power system carrying platform movement control method provided by the present invention; Figure 2 A schematic structural diagram of a shore power carrying platform in the shore power system carrying platform movement control method provided by the present invention; Figure 3 This is a flow chart of an embodiment of step S102 in the shore power system carrying platform movement control method provided by the present invention; Figure 4 This is a flow chart of an embodiment of step S103 in the shore power system carrying platform movement control method provided by the present invention; Figure 5 is a schematic diagram of an embodiment of a shore power system carrying platform movement control device provided by the present invention; Figure 6 It is a schematic diagram of the operating environment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0018] The power supply interface of the shore power supply system is mainly a fixed power connection box and a mobile vehicle-mounted one. The current technology can realize the installation of the shore power supply system as a whole set on a transport vehicle. The shore power supply system is driven by a mobile platform, and the carrying platform can be a transport vehicle, a container, a self-propelled platform, a trailer frame, a platform vehicle, an unmanned vehicle, and a mobile power generation vehicle.

[0019] A specific embodiment of the present invention discloses a shore power system carrying platform movement control method, please refer to Figure 1,include: S101, obtaining positioning data of the shore power carrying platform; S102, based on the topological map of the shore power system working port, according to the preset target point position and the positioning data, generate an optimal path; and according to the total path distance of the optimal path, calculate the target state information of the shore power carrying platform at each time node, wherein the state information includes position information, driving direction and speed information; S103, determining theoretical motion state information of the shore power carrying platform according to error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; S104: According to the theoretical motion state information, the shore power carrying platform is controlled to move to a preset target point along an optimal path.

[0020] In this embodiment, the positioning data of the shore power carrying platform is first obtained; then, based on the topological map of the working port of the shore power system, the optimal path is generated according to the preset target point position and the positioning data; and according to the total path distance of the optimal path, the target state information of the shore power carrying platform at each time node is calculated, wherein the state information includes position information, driving direction and speed information; thus, the theoretical motion state information of the shore power carrying platform can be determined according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; finally, according to the theoretical motion state information, the shore power carrying platform is controlled to move to the preset target point position according to the optimal path. The task of quickly and accurately processing and dispatching mobile shore power equipment is realized, ensuring the smooth progress of work, and getting rid of the problem of low efficiency caused by manual driving or remote operation.

[0021] In step S101, the positioning data of the shore power platform is fused data, including positioning data based on differential GPS, inertial navigation system data and data of the drive wheel encoder. Figure 2 As shown in the figure, first install a 5G communication module on the top of the container to communicate with the dispatching platform. Install a differential GPS and an inertial measurement unit, and combine it with the vehicle drive wheel encoder to form a fusion positioning module. Use an industrial computer as a vehicle control module to receive positioning and communication data and control the vehicle chassis. Laser radars are installed at the front and rear ends of the vehicle as obstacle avoidance modules.

[0022] Furthermore, the positioning data can be fused through methods such as Kalman filtering, particle filtering, weighted averaging or deep learning methods. Since Kalman filtering is suitable for real-time fusion of dynamic systems and is more suitable for updating the real-time position of shore power platforms, in this embodiment, the Kalman filtering method is selected to predict the vehicle's state information based on the data of the inertial navigation system and the drive wheel encoder to obtain initial positioning data; based on the preset extended Kalman filtering method, the initial positioning data is corrected according to the positioning data of the differential GPS to obtain the fused positioning data. Extended Kalman filtering is a data fusion method used to combine sensor data from different sources. It can use the short-term high precision of inertial navigation and drive wheel encoders and the long-term stability of differential GPS to provide more accurate positioning.

[0023] Specifically, the system state equation is established according to the vehicle inertial navigation positioning model, and the state equation is Taylor expanded to discard high-order terms to obtain the system state equation:

[0024] ; ; ; .

[0025] In the formula is the predicted value of the system at time k; represents the optimal estimate of the system state at time k −1; They represent the abscissa, ordinate, heading angle, speed, angular velocity, and acceleration of the vehicle at time k; T represents the time interval, , , and is an intermediate parameter.

[0026] Taking the GPS positioning data as observation data, first convert the latitude and longitude information returned by GPS into plane coordinates in the Gaussian plane coordinate system through Gaussian projection, and then convert it into the local navigation plane coordinate system. Establish the observation equation of the system based on the GPS positioning information:

[0027] In the formula represents the observation noise of the system, which respectively represents the noise in the x direction, the noise in the y direction, the heading angle noise and the speed noise in the GPS return information. is the system status, is the system observation quantity.

[0028] After establishing the state equation and observation equation of the system, the running state of the vehicle can be predicted according to the state prediction and observation update steps of the extended Kalman filter. The fusion positioning system obtains the position of the onboard shore power device according to the extended Kalman filter algorithm for vehicle motion control. When the vehicle has no dispatching task, only the low-frequency differential GPS positioning data is obtained and sent to the dispatching platform to monitor the system position.

[0029] In step S102, the optimal path is generated according to the preset target point position and the positioning data, and the Dijkstra algorithm, A* algorithm, genetic algorithm or reinforcement learning algorithm can be used. In a specific embodiment of step S102, the topological map of the working port of the shore power system is used to generate the optimal path according to the preset target point position and the positioning data. Figure 3 ,include: S301, establishing a topological map matching the GPS positioning information in the working port environment; S302: Generate an optimal path using a preset Dijkstra algorithm according to the preset target point position and the fused positioning data.

[0030] In this embodiment, a topological map of the working port environment is established and matched with the GPS positioning information of the port. On the topological map, key nodes such as main channels, intersections, ship berthing work areas and parking areas are set. After the on-board shore power device obtains the target point information of the dispatching platform through the 5G communication module, the Dijkstra algorithm is used to generate the optimal path passing through the key points. Based on the total distance of the path, an S-shaped speed curve is generated to calculate the vehicle's moving distance and speed change function over time. Through inverse solution, the vehicle position, direction and speed information at each time node in the entire motion process are planned.

[0031] Among them, the reverse solution refers to the process of working backward from the target state (such as target position and speed) to the starting state to determine the position, direction and speed information of the vehicle at each time node. By integrating the speed function and calculating the position function, the position change and direction of the vehicle on the entire path are determined.

[0032] In some embodiments, the theoretical motion state information of the shore power carrying platform is determined based on the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node. Figure 4 ,include: S401, obtaining real-time orientation information of the shore power carrying platform, and determining an orientation error between the real-time orientation information and the target orientation information; S402, establishing a left-handed coordinate system with the center of the shore power carrying platform as the origin and the direction of the forward direction as the x-axis; and converting the real-time position information and the direction error into the left-handed coordinate system; S403, using the x-axis error, y-axis error, angle error, theoretical speed and theoretical angular speed as input, using a preset controller to obtain theoretical motion state information.

[0033] In this embodiment, trajectory tracking control is a control method that aims to make the vehicle follow a predetermined path. The controller calculates the error between the current position and the target position in real time and adjusts the control input (such as acceleration, steering angle) to reduce the error, so that the vehicle can travel along the ideal trajectory. The control signal (such as speed and angular velocity) is adjusted through error feedback (position and angle error) so that the vehicle can accurately follow the predetermined trajectory.

[0034] Model Predictive Control (MPC) is an optimization-based control method that uses a dynamic model of the system to predict future states and minimizes the prediction error by optimizing the control input. MPC takes into account the constraints and objectives of the system to generate the optimal control input.

[0035] PID control (Proportional-Integral-Derivative Control) is a classic feedback control method that adjusts the control input through proportional, integral and derivative terms to reduce errors.

[0036] In a specific embodiment, backstepping control is used as the trajectory control method. Backstepping control is a control method based on Lyapunov stability and feedback control theory. The basic principle is to decompose and simplify a complex high-order system to obtain multiple simple subsystems, and then select a virtual control quantity for each subsystem, and select a suitable Lyapunov function based on the virtual control quantity and the corresponding subsystem. Finally, the Lyapunov function of each subsystem is subjected to stability analysis, and the asymptotic stability of the entire system is ensured by ensuring that each subsystem is asymptotically stable, and the control law of the system is designed according to the asymptotic stability conditions of each subsystem.

[0037] Specifically, the x-axis error, y-axis error, angle error, ideal speed and ideal angular speed are input into the controller, and the specific control law is as follows:

[0038] In the formula, v is the output speed control quantity, w is the output angular velocity control quantity, is the adjustable control variable of the system, are coordinate error and angle error, are the ideal speed and the ideal angular velocity.

[0039] Solve to obtain the vehicle's driving wheel speed and steering wheel angle. Send the speed and angle control to the vehicle's chassis actuator to achieve vehicle trajectory tracking control.

[0040] Furthermore, during the movement, the vehicle will use the laser radar arranged in the direction of the vehicle's advance to detect non-preset fixed obstacles in the path, and control the vehicle to stop in time according to the set braking distance to prevent damage to the vehicle and port facilities.

[0041] Based on the above shore power system carrying platform movement control method, the embodiment of the present invention also provides a shore power system carrying platform movement control device, please refer to Figure 5 ,include: An acquisition module 510 is used to acquire the positioning data of the shore power carrying platform; The target state information determination module 520 is used to generate an optimal path based on the topological map of the shore power system working port, according to the preset target point position and the positioning data; and calculate the target state information of the shore power carrying platform at each time node according to the total path distance of the optimal path, wherein the state information includes position information, driving direction and speed information; Theoretical motion state information determination module 530 is used to determine the theoretical motion state information of the shore power carrying platform according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; The motion module 540 is used to control the shore power carrying platform to move to a preset target point along an optimal path according to the theoretical motion state information.

[0042] like Figure 6 As shown, based on the above shore power system carrying platform movement control method, the present invention also provides an electronic device, which can be a computing electronic device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The electronic device includes a processor 610, a memory 620, and a display 630. Figure 6 Only some components of the electronic device are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0043] In some embodiments, the memory 620 may be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device. In other embodiments, the memory 620 may also be an external storage electronic device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 620 may also include both an internal storage unit of the electronic device and an external storage electronic device. The memory 620 is used to store application software and various types of data installed in the electronic device, such as program codes for installing the electronic device. The memory 620 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the memory 620 stores a shore power system onboard platform movement control program 640, and the shore power system onboard platform movement control program 640 can be executed by the processor 610, thereby realizing the shore power system onboard platform movement control method of each embodiment of the present application.

[0044] In some embodiments, the processor 610 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 620, such as executing a shore power system carrying platform movement control method.

[0045] In some embodiments, the display 630 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 630 is used to display information of the mobile control electronic device on the platform of the shore power system and to display a visual user interface. The components 610-630 of the electronic device communicate with each other through a system bus.

[0046] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0047] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A shore power system carrying platform movement control method, characterized in that: include: Obtain the positioning data of the shore power platform; Based on the topological map, generating an optimal path according to the preset target point position and the positioning data; And according to the total distance of the optimal path, the target state information of the shore power platform at each time node is calculated, where the state information includes location information, driving direction and speed information; Determine theoretical motion state information of the shore power carrying platform according to error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; According to the theoretical motion state information, the shore power carrying platform is controlled to move to a preset target point position along an optimal path.

2. The shore power system carrying platform movement control method according to claim 1 is characterized in that: The obtaining of the positioning data of the shore power carrying platform includes: Acquire positioning data based on differential GPS, inertial navigation system data, and drive wheel encoder data; The positioning data of the differential GPS, the data of the inertial navigation system and the data of the driving wheel encoder are fused to obtain fused positioning data.

3. The shore power system carrying platform movement control method according to claim 2 is characterized in that: The step of fusing the positioning data of the differential GPS, the data of the inertial navigation system and the data of the driving wheel encoder to obtain the fused positioning data includes: The preset extended Kalman filter method is used to predict the vehicle's state information based on the data from the inertial navigation system and the drive wheel encoder to obtain the initial positioning data; Based on the preset extended Kalman filter method, the initial positioning data is corrected according to the positioning data of the differential GPS to obtain the fused positioning data.

4. The shore power system carrying platform movement control method according to claim 2, characterized in that: The generating of the optimal path based on the topological map according to the preset target point position and the positioning data includes: Establish a topological map that matches the GPS positioning information in the working port environment; According to the preset target point position and the fused positioning data, the preset Dijkstra algorithm is used to generate the optimal path.

5. The shore power system carrying platform movement control method according to claim 2, characterized in that: The calculating of target state information of the shore power carrying platform at each time node according to the total path distance of the optimal path includes: Based on the total path distance and the principle of smooth driving, determine the function of speed changing with time and the function of distance changing with time; According to the speed-time variation function and the distance-time variation function, the inverse solution method is used to determine the target state information of the shore power platform at each time node.

6. The shore power system carrying platform movement control method according to claim 2, characterized in that: The determining of the theoretical motion state information of the shore power carrying platform according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node includes: Obtaining real-time orientation information of the shore power carrying platform, and determining the orientation error between the real-time orientation information and the target orientation information; With the center of the shore power platform as the origin and the direction of travel as the x-axis, a left-handed coordinate system is established; and the real-time position information and direction error are converted into the left-handed coordinate system; With x-axis error, y-axis error, angle error, theoretical speed and theoretical angular velocity as input, a preset controller is used to obtain theoretical motion state information.

7. The shore power system carrying platform movement control method according to claim 1, characterized in that: Also includes: According to the obstacle information fed back by the lidar monitoring, the shore power platform is controlled to stop running.

8. A shore power system carrying platform movement control device, characterized in that: include: An acquisition module is used to obtain the positioning data of the shore power carrying platform; A target state information determination module, used to generate an optimal path based on a topological map, according to a preset target point position and the positioning data; And according to the total distance of the optimal path, the target state information of the shore power platform at each time node is calculated, where the state information includes location information, driving direction and speed information; Theoretical motion state information determination module, used to determine the theoretical motion state information of the shore power carrying platform according to the error information between the real-time state information of the shore power carrying platform and the target state information at the corresponding time node; The motion module is used to control the shore power carrying platform to move to a preset target point along an optimal path according to the theoretical motion state information.

9. An electronic device, characterized in that: include: Processor and memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps in the shore power system carrying platform movement control method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the shore power system carrying platform movement control method as described in any one of claims 1-7.

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