Intelligent tractor path planning system based on dynamic environment perception

Abstract

The present invention relates to the technical field of tractor path planning, and in particular to an intelligent tractor path planning system based on dynamic environment perception, including: a data acquisition module, a data processing module and an adjustment module. The present invention introduces a risk grid marking mechanism and a path avoidance algorithm, so that the system can perceive and analyze various factors in a dynamic environment in real time, such as rainfall, ground depressions, water accumulation and other unfavorable conditions, so as to flexibly adjust the driving path of the tractor, which is particularly suitable for path planning requirements in complex terrain or bad weather. The system can not only automatically generate the optimal avoidance path, but also monitor the change of the traction path length in real time through the path correction function, and dynamically adjust the grid spacing to ensure the continuity and accuracy of path planning, effectively solving the problem of inaccurate and inefficient path planning due to high latency and poor adaptability in processing real-time environmental information.

Description

Technical Field

[0001] The present invention relates to the technical field of tractor path planning, and in particular to an intelligent tractor path planning system based on dynamic environment perception. Background Art

[0002] As electric tractors are increasingly used in complex and ever-changing environments, such as large warehouses, ports, industrial parks, and outdoor operations in severe weather conditions, traditional path planning systems often face problems such as inaccurate planning, low efficiency, and insufficient response capabilities due to their lack of accurate perception of the real-time environment and dynamic adjustment capabilities.

[0003] The patent document of Chinese patent application publication number CN117968698A discloses a path planning system and remote control method for electric tractors. The system includes: a server, a data acquisition module, a scheduling module, a wireless transmission module, a data screening module, a storage module, and a path selection module. The server is connected to the data acquisition module, the data screening module, the wireless transmission module, the storage module, and the path selection module. The data acquisition module and the scheduling module are connected. The wireless transmission module is used for the electric tractor to seek data from the server. The server receives the signal of the wireless transmission module. The service obtains the scheduling data of the electric tractor from the scheduling module through the data acquisition module. The data acquisition module transmits the acquired scheduling data to the server. The server transmits the scheduling data to the data screening module. The data screening module screens the scheduling data to obtain valid data. The server transmits the valid data to the path selection module. The path selection module processes the electric tractor that needs path planning. The path planning module includes a path calculation unit, a speed calculation unit, a time calculation unit, a turn calculation unit, and a position calculation unit. The path calculation unit, the speed calculation unit, the time calculation unit, and the position calculation unit are used to calculate the dispatched electric tractor and plan the route reasonably.

[0004] It can be seen that the system has a delay in processing data, and the response time is increased due to wireless transmission; it relies on network connection, which affects the scheduling and path planning functions when the network is unstable; the limitations of data screening lead to omissions or errors in valid data; the computing unit does not fully consider dynamic environmental factors, thus affecting the safety of the path; there is a lack of dynamic correction mechanism, and the path cannot be adjusted in time to deal with emergencies; computing resources are too concentrated on the server, resulting in excessive load affecting stability and response speed. Summary of the invention

[0005] To this end, the present invention provides an intelligent tractor path planning system based on dynamic environment perception, so as to overcome the problems in the prior art of inaccurate path planning and low efficiency due to high delay in processing real-time environmental information and poor adaptability.

[0006] To achieve the above objectives, the present invention provides an intelligent tractor path planning system based on dynamic environment perception, comprising:

[0007] A data collection module is used to collect real-time rainfall and real-time depression area in each grid in the monitoring area constructed based on a preset grid spacing, a preset starting point and a preset end point;

[0008] a data processing module connected to the data acquisition module, comprising a risk marking unit, a rainfall marking unit and a path planning unit, wherein the risk marking unit is used to mark the grid according to the real-time depression area and the preset standard area to form a plurality of risk grids, the rainfall marking unit is used to mark the risk grid according to the real-time rainfall in each risk grid within a preset evaluation time to form a plurality of avoidance grids, and the path planning unit is used to determine the traction path according to the avoidance grid, the preset starting point and the preset end point;

[0009] An adjustment module is connected to the data acquisition module and the path planning unit respectively, and is used to adjust the preset grid spacing according to the length of each traction path within a preset correction time.

[0010] Furthermore, the path planning unit includes:

[0011] A coordinate system generating subunit, for generating a rectangular coordinate system in the monitoring area with the preset starting point as the origin and the preset grid spacing as the unit coordinate spacing;

[0012] an ideal path generating subunit, connected to the coordinate system generating subunit, for connecting the coordinates of the preset starting point and the coordinates of the preset end point to form an ideal path;

[0013] A path generation subunit is connected to the ideal path generation subunit and the coordinate system generation subunit respectively, and is used to generate a traction path according to the ideal path and the avoidance grid.

[0014] Furthermore, the path generation subunit includes:

[0015] Determine a subtask unit, which is used to determine the grid to be pulled according to the coordinates of the intersection of the ideal path and the grid and the avoidance grid;

[0016] A selection subtask unit connected to the determination subtask unit, for selecting a path grid according to the coordinates of the intersection of the ideal path and the grid, the preset coordinates and the grid to be towed;

[0017] A path point generation subtask unit, for generating a path point at the origin;

[0018] A correction point generation subtask unit, which is connected to the path point generation subtask unit and the selection subtask unit respectively, and is used to move the path point to an adjacent grid point along the boundary of the path grid to generate a correction grid point;

[0019] A correction path generation subtask unit, which is connected to the correction point generation subtask unit and is used to connect the coordinates of the correction grid point and the coordinates of the preset end point to form a correction path;

[0020] The traction movement subtask unit is respectively connected to the path point generation subtask unit and the correction path generation subtask unit, and is used to move the path point along the ideal path, or move the path point along the correction path until the path point coincides with the preset end point, so as to form a traction path.

[0021] Furthermore, the adjustment module includes:

[0022] A length fluctuation calculation unit, used to calculate the standard deviation of the length to form a length fluctuation value;

[0023] A spacing correction unit is connected to the length fluctuation calculation unit and is used to adjust the preset grid spacing according to the length fluctuation value and a preset standard length fluctuation range.

[0024] Furthermore, the spacing correction unit includes:

[0025] a difference calculation subunit, for calculating the difference between the length fluctuation value and the maximum value when the length fluctuation value is greater than the maximum value of the preset standard length fluctuation range, to form a first adjustment difference;

[0026] A correction subunit is connected to the difference calculation subunit and is used to reduce the preset grid spacing according to a comparison result between the first adjustment difference and a preset standard deviation.

[0027] Furthermore, the difference calculation subunit is further used to calculate the difference between the minimum value and the length fluctuation value when the length fluctuation value is less than the minimum value of the preset standard length fluctuation range, so as to form a second adjustment difference;

[0028] The correction subunit is further configured to increase the preset grid spacing according to a comparison result between the second adjustment difference and a preset standard deviation.

[0029] Furthermore, the risk marking unit includes:

[0030] A risk determination subunit, used for determining that the grid whose real-time sunken area is larger than the preset standard area has a risk, and forming a risk determination result;

[0031] The risk marking subunit is connected to the risk determination subunit and is used to mark the grid according to the risk determination result to form a plurality of risk grids.

[0032] Furthermore, the rainfall marking unit comprises:

[0033] A rainfall fluctuation calculation subunit, used for calculating a rainfall fluctuation value according to the real-time rainfall;

[0034] A rainfall fluctuation comparison subunit, which is connected to the fluctuation calculation subunit, is used to determine whether the risk grid where the rainfall fluctuation value is less than the preset standard rainfall fluctuation value has rainfall anomaly, and form a rainfall determination result;

[0035] A rainfall marking subunit is connected to the fluctuation comparison subunit and is used to mark the risk grid according to the rainfall determination result to form a plurality of avoidance grids.

[0036] Furthermore, the ideal path generating subunit is further configured to determine that it is not necessary to form an ideal path when the abscissa of the starting point is equal to the abscissa of the end point.

[0037] Furthermore, the ideal path generating subunit is further configured to determine that it is not necessary to form an ideal path when the ordinate of the starting point is equal to the ordinate of the end point.

[0038] Compared with the prior art, the beneficial effect of the present invention lies in that, by introducing the risk grid marking mechanism and the path avoidance algorithm, the system can perceive and analyze various factors in the dynamic environment in real time, such as rainfall, ground depressions, water accumulation and other adverse conditions, so as to flexibly adjust the driving path of the tractor, which is particularly suitable for path planning needs in complex terrain or bad weather. The system can not only automatically generate the optimal avoidance path, but also monitor the changes in the length of the traction path in real time through the path correction function, and dynamically adjust the grid spacing to ensure the continuity and accuracy of path planning, effectively solving the problems of inaccurate and inefficient path planning due to high latency and poor adaptability in processing real-time environmental information.

[0039] Furthermore, through precise coordinate system division, the tractor can more effectively identify and avoid potential obstacles, while the generation of ideal paths ensures the optimal driving route, helping to reduce driving time and improve work efficiency.

[0040] Furthermore, the dynamic determination of the to-be-pulled grid and the path grid ensures that the system can flexibly respond to environmental changes and avoid obstacles in a timely manner. The generation of the correction grid points and the formation of the correction path ensure that the path planning not only maintains continuity, but also can be quickly adjusted under the influence of real-time updated environmental information, ensuring the accurate arrival of the final goal, improving the adaptability and reliability of the system, especially in severe weather conditions.

[0041] Furthermore, when the length of the traction path fluctuates greatly, the system can adjust the grid spacing in time to avoid safety risks or reduced efficiency caused by improper path planning. By dynamically correcting the grid spacing, the system can adapt to changes in different environmental conditions, ensuring that the tractor can still complete the task smoothly in complex or changing environments.

[0042] Furthermore, when the actual path is significantly different from the expected path, the system can improve the accuracy of path planning by reducing the grid spacing, thereby reducing the error in path planning. This dynamic adjustment mechanism ensures that the tractor can complete the task safely and efficiently in a changing environment, and by gradually optimizing the grid spacing, it can also reduce fluctuations and errors in future path planning.

[0043] Furthermore, by increasing the grid spacing to reduce unnecessary changes, excessive path adjustments in relatively stable conditions can be effectively avoided, thereby improving the efficiency of path planning.

[0044] Furthermore, by determining and marking risk areas in real time, the system can accurately identify potential dangers in dynamic environments.

[0045] Furthermore, by accurately calculating real-time rainfall fluctuations, rainfall anomalies in risk grids are dynamically evaluated, allowing areas to be avoided to be marked more accurately.

[0046] Furthermore, by reducing unnecessary path changes, the efficiency of path planning is improved, especially when the path is relatively straight or simple, which can significantly save computing resources and traction time, making the tractor travel smoother and the path more optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a schematic diagram of an intelligent tractor path planning system based on dynamic environment perception according to this embodiment;

[0048] Figure 2 A decision logic diagram for selecting a subtask unit decision path grid for this embodiment;

[0049] Figure 3 A determination logic diagram for the correction subunit of this embodiment to determine to reduce the preset grid spacing;

[0050] Figure 4 This is a decision logic diagram for the correction subunit in this embodiment to determine to increase the preset grid spacing. DETAILED DESCRIPTION

[0051] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0052] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0053] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0054] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0055] See also Figure 1 As shown, it is a schematic diagram of the intelligent tractor path planning system based on dynamic environment perception in this embodiment;

[0056] This embodiment provides an intelligent tractor path planning system based on dynamic environment perception, which is applied to a large construction site with changeable weather and frequent rainfall. In this environment, the main task of the tractor is to transport construction materials from the material loading area to the unloading area. The terrain of the construction site is relatively complex, and there is a risk of depression and water accumulation in some areas, which can easily affect the tractor during driving. Therefore, an intelligent path planning system is needed to ensure safety and efficiency.

[0057] The system includes:

[0058] A data collection module is used to collect real-time rainfall and real-time depression area in each grid in the monitoring area constructed based on a preset grid spacing, a preset starting point and a preset end point;

[0059] a data processing module connected to the data acquisition module, comprising a risk marking unit, a rainfall marking unit and a path planning unit, wherein the risk marking unit is used to mark the grid according to the real-time depression area and the preset standard area to form a plurality of risk grids, the rainfall marking unit is used to mark the risk grid according to the real-time rainfall in each risk grid within a preset evaluation time to form a plurality of avoidance grids, and the path planning unit is used to determine the traction path according to the avoidance grid, the preset starting point and the preset end point;

[0060] An adjustment module is connected to the data acquisition module and the path planning unit respectively, and is used to adjust the preset grid spacing according to the length of each traction path within a preset correction time.

[0061] The preset grid spacing refers to the side length of each grid when the entire area is divided into several grids within the monitoring area. This spacing depends on the geographical conditions in the application scenario, the operating accuracy of the tractor, and the accuracy of the monitoring equipment. In more complex terrain or when precise navigation is required, the grid spacing is usually smaller to capture subtle environmental changes. Typically, the grid spacing is set between 0.5 meters and 5 meters. In this embodiment, the preset grid spacing is set to 1 meter, which can ensure that sufficiently accurate ground and rainfall information is obtained in an environment of medium complexity while avoiding excessive data processing.

[0062] The preset starting point and end point are key points in path planning, representing the starting position and destination of the tractor. They depend on the specific task requirements and the working range of the tractor. In the application, the starting point and end point can be important nodes such as warehouses, work points, and unloading points. In this embodiment, the starting point is set as the material loading area of ​​the construction site, and the end point is set as the material unloading area. This setting enables the tractor to effectively plan within the specified working area and quickly reach the destination.

[0063] The preset standard area is used to determine whether the depression or waterlogged area in the monitoring area reaches the risk level. Its size usually depends on the wheel size of the tractor, the terrain characteristics and safety requirements. Larger depressions or waterlogged areas will increase the risk of the vehicle getting stuck or slipping. Usually, the standard area is set between 1 square meter and 5 square meters. In this embodiment, the standard area is set to 2 square meters, which means that when the depression area of ​​a grid is greater than 2 square meters, the grid will be marked as a risk grid. This setting can effectively identify large dangerous areas while avoiding being too sensitive and preventing frequent path adjustments.

[0064] The preset evaluation duration refers to the time window used by the system when analyzing the rainfall within the risk grid. It determines the system's response speed to environmental changes. Shorter evaluation durations are suitable for rapidly changing environments, while longer durations are suitable for stable weather conditions. Usually the evaluation duration is set between 5 minutes and 30 minutes. In this embodiment, the preset evaluation duration is 10 minutes, which can accurately evaluate the rainfall fluctuations in the monitoring area in a short time, ensuring that the path planning can quickly respond to weather changes.

[0065] The preset correction time refers to the time interval when the system adjusts the grid spacing according to the length fluctuation of the traction path. This parameter depends on the complexity of the path planning and the running speed of the tractor. A shorter correction time is suitable for quickly responding to path changes, while a longer correction time is suitable for a stable environment. Usually, the correction time is set between 10 minutes and 1 hour. In this embodiment, the correction time is set to 15 minutes, so that the system can frequently adjust the grid spacing and optimize the path planning. This setting ensures that the tractor can flexibly respond to path changes in a dynamic environment and improve the safety and efficiency of driving.

[0066] The data acquisition module monitors the rainfall and ground depression in the monitoring area in real time. The monitoring area is divided based on the preset grid spacing, starting point and end point. The data acquisition module continuously obtains the real-time rainfall and depression area of ​​each grid and transmits it to the data processing module. The risk marking unit marks the potential risk grids based on the comparison between the real-time depression area of ​​each grid and the preset standard area. Next, the rainfall marking unit marks the grids that need to be avoided based on the rainfall changes of the risk grids within the preset evaluation time. The path planning unit calculates and generates the optimal traction path based on these avoidance grids, combined with the preset starting point and end point. At the same time, the adjustment module monitors the changes in the traction path length in real time, and automatically adjusts the grid spacing according to the preset correction time and path length fluctuations to ensure the accuracy and adaptability of the planned path.

[0067] By introducing the risk grid marking mechanism and path avoidance algorithm, the system can perceive and analyze various factors in the dynamic environment in real time, such as rainfall, ground depressions, water accumulation and other adverse conditions, so as to flexibly adjust the driving path of the tractor. It is particularly suitable for path planning needs in complex terrain or bad weather. The system can not only automatically generate the optimal avoidance path, but also use the path correction function to monitor the changes in the length of the traction path in real time, and dynamically adjust the grid spacing to ensure the continuity and accuracy of path planning, effectively solving the problems of inaccurate and inefficient path planning due to high latency in processing real-time environmental information and poor adaptability.

[0068] Specifically, the path planning unit includes:

[0069] A coordinate system generating subunit, for generating a rectangular coordinate system in the monitoring area with the preset starting point as the origin and the preset grid spacing as the unit coordinate spacing;

[0070] an ideal path generating subunit, connected to the coordinate system generating subunit, for connecting the coordinates of the preset starting point and the coordinates of the preset end point to form an ideal path;

[0071] A path generation subunit is connected to the ideal path generation subunit and the coordinate system generation subunit respectively, and is used to generate a traction path according to the ideal path and the avoidance grid.

[0072] First, the coordinate system generation subunit uses the preset starting point as the origin and the preset grid spacing as the unit coordinate spacing to establish a rectangular coordinate system in the monitoring area, providing a clear framework for subsequent path planning. Then, the ideal path generation subunit automatically generates a shortest ideal path based on the coordinates of the preset starting point and end point as a reference route for the tractor. Finally, the path generation subunit combines the ideal path with the avoidance grid and dynamically adjusts the generated traction path to ensure that the tractor can safely avoid dangerous areas.

[0073] Through precise coordinate system division, the tractor can more effectively identify and avoid potential obstacles, while the generation of ideal paths ensures the optimal driving route, helping to reduce driving time and improve work efficiency.

[0074] Please continue reading Figure 2 As shown, it is a decision logic diagram for selecting a subtask unit decision path grid in this embodiment;

[0075] Specifically, the path generation subunit includes:

[0076] Determine a subtask unit, which is used to determine the grid to be pulled according to the coordinates of the intersection of the ideal path and the grid and the avoidance grid;

[0077] A selection subtask unit connected to the determination subtask unit is used to select a path grid according to the coordinates of the intersection of the ideal path and the grid, the preset coordinates and the grid to be towed, wherein the preset coordinates are the midpoint coordinates of the boundaries of each grid, and when the intersection is located on one side of the midpoint coordinates, the selection subtask unit determines that the grid close to this side that is not the avoidance grid is the path grid;

[0078] A path point generation subtask unit, for generating a path point at the origin;

[0079] A correction point generation subtask unit, which is connected to the path point generation subtask unit and the selection subtask unit respectively, and is used to move the path point to an adjacent grid point along the boundary of the path grid to generate a correction grid point;

[0080] A correction path generation subtask unit, which is connected to the correction point generation subtask unit and is used to connect the coordinates of the correction grid point and the coordinates of the preset end point to form a correction path;

[0081] The traction movement subtask unit is respectively connected to the path point generation subtask unit and the correction path generation subtask unit, and is used to move the path point along the ideal path, or move the path point along the correction path until the path point coincides with the preset end point, so as to form a traction path.

[0082] The determination subtask unit first determines the grid to be pulled based on the coordinates of the intersection of the ideal path and the grid and the information of the avoidance grid. Next, the selection subtask unit further determines the path grid using the intersection coordinates, the preset coordinates and the grid to be pulled. Subsequently, the path point generation subtask unit generates path points at the origin. The correction point generation subtask unit moves the path points along the boundary of the path grid to the adjacent grid points to form correction grid points. Then, the correction path generation subtask unit generates a correction path by connecting the coordinates of the correction grid points with the coordinates of the preset end point. Finally, the traction movement subtask unit moves the path points along the correction path until they coincide with the preset end point, completing the generation of the traction path.

[0083] The dynamic determination of the to-be-pulled grid and the path grid ensures that the system can flexibly respond to environmental changes and avoid obstacles in a timely manner. The generation of the correction grid points and the formation of the correction path ensure that the path planning not only maintains continuity, but also can be quickly adjusted under the influence of real-time updated environmental information, ensuring the accurate arrival of the final goal, improving the adaptability and reliability of the system, especially in severe weather conditions.

[0084] Specifically, the adjustment module includes:

[0085] A length fluctuation calculation unit, used to calculate the standard deviation of the length to form a length fluctuation value;

[0086] A spacing correction unit is connected to the length fluctuation calculation unit and is used to adjust the preset grid spacing according to the length fluctuation value and a preset standard length fluctuation range.

[0087] The preset standard length fluctuation range refers to the acceptable range for evaluating and judging the path length fluctuation in the path planning or dynamic environment perception system. This range usually depends on multiple factors, such as application scenarios, environmental conditions, vehicle characteristics, and safety standards. It is usually set between 0.3 meters and 0.7 meters. In this embodiment, it is set to 0.4 meters to 0.8 meters, which can ensure that the system can adapt to environmental changes while maintaining a high path planning accuracy, thereby improving the operating efficiency and safety of the tractor.

[0088] First, the length fluctuation calculation unit is responsible for calculating the standard deviation of the actual length of the traction path and obtaining the length fluctuation value. This value reflects the change in the length of the traction path during the actual path planning and execution process. If the path length fluctuates greatly, it may mean that the path planning is unstable or affected by the external environment. Secondly, the spacing correction unit compares the length fluctuation value with the preset standard length fluctuation range. If the fluctuation value exceeds the set range, the system will automatically adjust the preset grid spacing so that the new path planning can better cope with environmental changes and ensure the stability and accuracy of the path planning.

[0089] When the length of the traction path fluctuates greatly, the system can adjust the grid spacing in time to avoid safety risks or reduced efficiency caused by improper path planning. By dynamically correcting the grid spacing, the system can adapt to changes in different environmental conditions, ensuring that the tractor can still complete the task smoothly in complex or changing environments.

[0090] Please continue reading Figure 3 As shown, it is a decision logic diagram of the correction subunit in this embodiment for determining to reduce the preset grid spacing;

[0091] Specifically, the spacing correction unit includes:

[0092] a difference calculation subunit, for calculating the difference between the length fluctuation value and the maximum value when the length fluctuation value is greater than the maximum value of the preset standard length fluctuation range, to form a first adjustment difference;

[0093] The correction subunit is connected to the difference calculation subunit and is used to reduce the preset grid spacing according to a preset correction coefficient based on a comparison result of the first adjustment difference and the preset standard deviation, that is, when the first adjustment difference is greater than the preset standard deviation.

[0094] The preset standard deviation value refers to a threshold used in the path planning system to measure whether the path length fluctuation needs to be adjusted. It defines the normal path fluctuation range accepted by the system. Fluctuations beyond this range will trigger the adjustment of the grid spacing, depending on the accuracy requirements of path planning, the degree of dynamic changes in the environment, and the system's requirements for traction path stability. The specific value of the preset standard deviation value varies according to different scenarios. In general applications, the standard deviation value can be determined based on the statistical analysis results of historical path data, and is usually set to a range of 2% to 5% of the change in traction path length to balance stability and flexible adjustment. In this embodiment, the preset standard deviation value is set to 3% of the change in traction path length. This setting is based on the frequency of environmental changes in the monitoring area and the system's requirements for accuracy. It can quickly respond to abnormal changes in the path, and will not be frequently adjusted due to small fluctuations, thereby ensuring the efficiency of the system.

[0095] The preset correction coefficient is a parameter used to adjust the grid spacing, which determines the adjustment range of the grid spacing when the length fluctuation value exceeds the preset standard range. It controls the reduction rate of the grid spacing to ensure that the system can reasonably adjust the path planning when facing environmental changes or path fluctuations. It is generally set between 0.1 and 0.5, and the specific value depends on the system's requirements for accuracy and response speed. In this embodiment, the preset correction coefficient is set to 0.3. This setting ensures that the system can appropriately reduce the grid spacing when the path length fluctuation is detected, while avoiding instability caused by excessive adjustment.

[0096] First, the difference calculation subunit is responsible. When the length fluctuation value of the traction path exceeds the maximum value of the preset standard length fluctuation range, the difference calculation subunit will calculate the difference between the length fluctuation value and the maximum value, which is called the first adjustment difference. This difference reflects the degree of deviation between path planning and execution. Next, the correction subunit compares the first adjustment difference with the preset standard deviation value to determine whether the difference exceeds a certain threshold. If it exceeds, the system will correct the path planning by reducing the preset grid spacing to ensure that the path planning is more accurate.

[0097] When the actual path is significantly different from the expected path, the system can improve the accuracy of path planning by reducing the grid spacing, thereby reducing the error in path planning. This dynamic adjustment mechanism ensures that the tractor can complete the task safely and efficiently in a changing environment, and by gradually optimizing the grid spacing, it can also reduce fluctuations and errors in future path planning.

[0098] Please continue reading Figure 4 As shown, it is a decision logic diagram of the correction subunit in this embodiment for determining to increase the preset grid spacing;

[0099] Specifically, the difference calculation subunit is further used to calculate the difference between the minimum value and the length fluctuation value when the length fluctuation value is less than the minimum value of the preset standard length fluctuation range, to form a second adjustment difference;

[0100] The correction subunit is further configured to increase the preset grid spacing according to the preset correction coefficient based on a comparison result between the second adjustment difference and a preset standard deviation, that is, when the second adjustment difference is greater than the preset standard deviation.

[0101] When the difference calculation subunit detects that the length fluctuation value is less than the minimum value of the preset standard length fluctuation range, it calculates the difference between the minimum value and the current fluctuation value to generate a second adjustment difference value. Subsequently, the correction subunit automatically increases the preset grid spacing based on the comparison result between the adjustment difference value and the preset standard deviation value to ensure that the update of the traction path adapts to environmental changes.

[0102] By increasing the grid spacing to reduce unnecessary changes, it is possible to effectively avoid excessive path adjustments under relatively stable conditions, thereby improving the efficiency of path planning.

[0103] Specifically, the risk marking unit includes:

[0104] A risk determination subunit, used for determining that the grid whose real-time sunken area is larger than the preset standard area has a risk, and forming a risk determination result;

[0105] The risk marking subunit is connected to the risk determination subunit and is used to mark the grid according to the risk determination result to form a plurality of risk grids.

[0106] First, the risk determination subunit compares the real-time sunken area of ​​each grid in the monitoring area with the preset standard area. If the real-time sunken area is larger than the preset standard area, the grid is judged to have potential risks and a risk determination result is formed. Then, the risk marking subunit marks these risky grids according to the determination results and generates a series of risk grids. These marked risk grids will be used for subsequent path planning to avoid potential danger areas.

[0107] By determining and marking risk areas in real time, the system can accurately identify potential dangers in dynamic environments.

[0108] Specifically, the rainfall marking unit includes:

[0109] A rainfall fluctuation calculation subunit, used for calculating a rainfall fluctuation value according to the real-time rainfall;

[0110] A rainfall fluctuation comparison subunit, which is connected to the fluctuation calculation subunit, is used to determine whether the risk grid where the rainfall fluctuation value is less than the preset standard rainfall fluctuation value has rainfall anomaly, and form a rainfall determination result;

[0111] A rainfall marking subunit is connected to the fluctuation comparison subunit and is used to mark the risk grid according to the rainfall determination result to form a plurality of avoidance grids.

[0112] The preset standard rainfall fluctuation value is a key threshold used to determine whether the rainfall fluctuation is abnormal. It represents the range of rainfall changes in the monitoring area. If the actual rainfall fluctuation value exceeds this preset standard, it means that the rainfall changes dramatically and may bring potential road risks. On the contrary, if the rainfall fluctuation value is less than the preset value, it means that the rainfall is relatively stable. It depends on specific environmental conditions, such as local climate characteristics, historical rainfall data, and the drainage capacity of the road. Usually, this value is set to a reasonable range based on the actual geographical and climatic conditions. For example, a rainfall change of no more than 10 mm per hour is considered stable. The preset standard rainfall fluctuation value in this embodiment is set to a rainfall fluctuation of no more than 5 mm per hour to ensure a higher sensitivity, so that potential dangerous areas caused by rainfall changes can be quickly identified and avoided.

[0113] The rainfall fluctuation calculation subunit monitors the real-time rainfall and calculates the rainfall fluctuation value to determine whether the rainfall change is stable. Then, the rainfall fluctuation comparison subunit compares these fluctuation values ​​with the preset standard rainfall fluctuation values. If the rainfall fluctuation value of a risk grid is less than the preset value, it is determined that the grid has rainfall anomaly and forms a rainfall judgment result. Finally, the rainfall marking subunit marks the corresponding risk grid according to the judgment result and marks it as an avoidance grid.

[0114] Through precise calculation of real-time rainfall fluctuations, rainfall anomalies in risk grids are dynamically assessed, allowing areas to be more accurately marked to avoid.

[0115] Specifically, the ideal path generating subunit is further configured to determine that it is not necessary to form an ideal path when the abscissa of the starting point is equal to the abscissa of the end point.

[0116] The system first determines the ideal path and moves along the path step by step. When the horizontal coordinate of the starting point is equal to the horizontal coordinate of the end point, the ideal path generation subunit determines that it is not necessary to form an ideal path, that is, the path point will continue to maintain the current moving direction to avoid lateral deviation.

[0117] Specifically, the ideal path generating subunit is further configured to determine that it is not necessary to form an ideal path when the ordinate of the starting point is equal to the ordinate of the end point.

[0118] After the ideal path is generated, the system gradually moves along the path. When it is detected that the ordinates of the starting point and the end point are equal, the ideal path generation subunit determines that the path point continues to move along the current horizontal line to maintain the original straight path.

[0119] By reducing unnecessary path changes, the efficiency of path planning is improved, especially when the path is relatively straight or simple, which can significantly save computing resources and traction time, making the tractor travel smoother and the path more optimized.

[0120] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0121] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent tractor path planning system based on dynamic environment perception, characterized in that: include: A data collection module is used to collect real-time rainfall and real-time depression area in each grid in the monitoring area constructed based on a preset grid spacing, a preset starting point and a preset end point; a data processing module connected to the data acquisition module, comprising a risk marking unit, a rainfall marking unit and a path planning unit, wherein the risk marking unit is used to mark the grid according to the real-time depression area and the preset standard area to form a plurality of risk grids, the rainfall marking unit is used to mark the risk grid according to the real-time rainfall in each risk grid within a preset evaluation time to form a plurality of avoidance grids, and the path planning unit is used to determine the traction path according to the avoidance grid, the preset starting point and the preset end point; An adjustment module, which is connected to the data acquisition module and the path planning unit respectively, and is used to adjust the preset grid spacing according to the length of each traction path within a preset correction time; The path planning unit comprises: A coordinate system generating subunit, for generating a rectangular coordinate system in the monitoring area with the preset starting point as the origin and the preset grid spacing as the unit coordinate spacing; an ideal path generating subunit, connected to the coordinate system generating subunit, for connecting the coordinates of the preset starting point and the coordinates of the preset end point to form an ideal path; a path generation subunit, which is connected to the ideal path generation subunit and the coordinate system generation subunit respectively, and is used to generate a traction path according to the ideal path and the avoidance grid; The path generation subunit comprises: Determine a subtask unit, which is used to determine the grid to be pulled according to the coordinates of the intersection of the ideal path and the grid and the avoidance grid; A selection subtask unit connected to the determination subtask unit, for selecting a path grid according to the coordinates of the intersection of the ideal path and the grid, the preset coordinates and the grid to be towed; A path point generation subtask unit, for generating a path point at the origin; A correction point generation subtask unit, which is connected to the path point generation subtask unit and the selection subtask unit respectively, and is used to move the path point to an adjacent grid point along the boundary of the path grid to generate a correction grid point; A correction path generation subtask unit, which is connected to the correction point generation subtask unit and is used to connect the coordinates of the correction grid point and the coordinates of the preset end point to form a correction path; The traction movement subtask unit is respectively connected to the path point generation subtask unit and the correction path generation subtask unit, and is used to move the path point along the ideal path, or move the path point along the correction path until the path point coincides with the preset end point, so as to form a traction path.

2. The intelligent tractor path planning system based on dynamic environment perception according to claim 1 is characterized in that: The adjustment module comprises: A length fluctuation calculation unit, used to calculate the standard deviation of the length to form a length fluctuation value; A spacing correction unit is connected to the length fluctuation calculation unit and is used to adjust the preset grid spacing according to the length fluctuation value and a preset standard length fluctuation range.

3. The intelligent tractor path planning system based on dynamic environment perception according to claim 2 is characterized in that: The spacing correction unit comprises: a difference calculation subunit, for calculating the difference between the length fluctuation value and the maximum value when the length fluctuation value is greater than the maximum value of the preset standard length fluctuation range, to form a first adjustment difference; A correction subunit is connected to the difference calculation subunit and is used to reduce the preset grid spacing according to a comparison result between the first adjustment difference and a preset standard deviation.

4. The intelligent tractor path planning system based on dynamic environment perception according to claim 3 is characterized in that: The difference calculation subunit is further used to calculate the difference between the minimum value and the length fluctuation value when the length fluctuation value is less than the minimum value of the preset standard length fluctuation range, to form a second adjustment difference; The correction subunit is further configured to increase the preset grid spacing according to a comparison result between the second adjustment difference and a preset standard deviation.

5. The intelligent tractor path planning system based on dynamic environment perception according to claim 4 is characterized in that: The risk marking unit includes: A risk determination subunit, used for determining that the grid whose real-time sunken area is larger than the preset standard area has a risk, and forming a risk determination result; The risk marking subunit is connected to the risk determination subunit and is used to mark the grid according to the risk determination result to form a plurality of risk grids.

6. The intelligent tractor path planning system based on dynamic environment perception according to claim 5 is characterized in that: The rainfall marking unit comprises: A rainfall fluctuation calculation subunit, used for calculating a rainfall fluctuation value according to the real-time rainfall; A rainfall fluctuation comparison subunit, which is connected to the fluctuation calculation subunit, is used to determine whether the risk grid where the rainfall fluctuation value is less than the preset standard rainfall fluctuation value has rainfall anomaly, and form a rainfall determination result; A rainfall marking subunit is connected to the fluctuation comparison subunit and is used to mark the risk grid according to the rainfall determination result to form a plurality of avoidance grids.

7. The intelligent tractor path planning system based on dynamic environment perception according to claim 6 is characterized in that: The ideal path generating subunit is further configured to determine that it is not necessary to form an ideal path when the abscissa of the starting point is equal to the abscissa of the end point.

8. The intelligent tractor path planning system based on dynamic environment perception according to claim 7 is characterized in that: The ideal path generation subunit is further configured to determine that it is not necessary to form an ideal path when the ordinate of the starting point is equal to the ordinate of the end point.

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