Underwater vehicle path planning method and device and computer equipment

Abstract

This application relates to the field of unmanned underwater vehicle (UUV) technology, and discloses an underwater vehicle path planning method, apparatus, and computer equipment. The method includes: determining a regional coordinate system corresponding to the operational sea area, and determining a static hazard set corresponding to the regional coordinate system based on obstacles in the operational sea area; determining a current feasible path for the underwater vehicle under the constraints of the static hazard set; dynamically analyzing the movement positions of the obstacles, and iteratively updating the static hazard set based on the dynamic analysis results to obtain a dynamic hazard set; analyzing the spatiotemporal intersection of the current feasible path and the dynamic hazard set, and updating the current feasible path based on the spatiotemporal intersection, to obtain a path planning result based on the updated current feasible path. This application can improve the real-time performance, robustness, and accuracy of path planning.

Description

Technical Field

[0001] This application relates to the field of unmanned vehicle technology, and in particular to a method, apparatus and computer equipment for underwater vehicle path planning. Background Technology

[0002] With technological advancements, the application scope of underwater vehicles such as unmanned underwater vehicles (UUVs) has gradually expanded to harsh environments such as complex and specialized sea areas. However, in the path planning and control of underwater vehicles, related technologies have significant limitations when dealing with these dynamically changing and complex environments. This is especially true in specialized sea environments, where special obstacles and obstacle zones not only have uncertain spatial distributions but also change in position and shape over time. This causes the related technologies to be unable to adapt to environmental changes in a timely manner, severely affecting the accuracy of path planning. Summary of the Invention

[0003] This application provides an underwater vehicle path planning method, apparatus, and computer equipment, which solves the technical problem that current underwater vehicle path planning has significant limitations when dealing with these dynamic and complex environments, and achieves the technical effect of improving the real-time performance, robustness, and accuracy of path planning.

[0004] To achieve the above objectives, the main technical solutions adopted in this application include: In a first aspect, this application provides a path planning method for an underwater vehicle, the method comprising: Determine the regional coordinate system corresponding to the operating sea area, and determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area; Determine the current feasible path for the underwater vehicle under the constraints of the static hazard set; The movement position of the obstacle is dynamically analyzed, and the static hazard set is iteratively updated based on the dynamic analysis results to obtain the dynamic hazard set; The spatiotemporal intersection of the current feasible path and the dynamic hazard set is analyzed, and the current feasible path is updated according to the spatiotemporal intersection to obtain the path planning result.

[0005] The underwater vehicle path planning method proposed in this application dynamically updates the expansion range of the danger zone by analyzing the movement and changes of obstacles in special sea areas. Based on a real-time updated dynamic danger set as a constraint, it monitors the spatiotemporal intersection risk between the current feasible path and the danger zone, and then replans the risky portions of the current feasible path. Compared with related technologies, this application effectively improves the real-time performance, robustness, and accuracy of path planning. Furthermore, it only performs local replanning on necessary intervals within the path, avoiding the high computational burden and path oscillation problems caused by frequent global replanning.

[0006] Optionally, determining the regional coordinate system corresponding to the operating sea area and determining the static hazard set corresponding to the regional coordinate system based on obstacles in the operating sea area includes: The geographic coordinates of the operating sea area are projected onto the regional coordinate system, and the regional coordinate system is divided into a three-dimensional grid according to a preset resolution; The locations of obstacles within the operational sea area are voxelized in the three-dimensional grid to form a static hazard set containing multiple hazard voxels.

[0007] Optionally, the preset resolution is determined by a preset grid step size, and the preset grid step size is dynamically adjusted according to the complexity of obstacles in the operating sea area.

[0008] This application projects the geographic coordinates of the operating sea area onto a regional coordinate system and divides it into a three-dimensional grid according to a preset resolution. It also performs voxelization processing on the obstacle positions to form a static hazard set, thereby achieving accurate discretization of the hazard area. Furthermore, through dynamic adaptation of the grid step size, it can reduce computational redundancy in low-complexity areas with sparse obstacles and improve the accuracy of hazard identification in high-complexity areas with dense obstacles, thus enhancing the flexibility of path planning.

[0009] Optionally, determining the current feasible path for the underwater vehicle under the constraints of the static hazard set includes: Determine the starting node and target node of the underwater vehicle; Under the constraints of the static hazard set, the current feasible path is solved based on the A* algorithm.

[0010] Optionally, the step of dynamically analyzing the movement position of the obstacle and iteratively updating the static hazard set based on the dynamic analysis results to obtain a dynamic hazard set includes: The current update time and the reference time are determined based on a preset frequency, and the time difference between the current update time and the reference time is determined, wherein the reference time is determined according to the time of the last update of the static danger set; Obtain the upper limit of the movement speed of the operation sea area, and determine the dynamic expansion radius of the danger zone based on the upper limit of the movement speed and the time difference, so as to use the dynamic expansion radius as the result of the dynamic analysis; The static hazard set is isotropically expanded based on the dynamic expansion radius to obtain the dynamic hazard set.

[0011] This application achieves real-time dynamic tracking of obstacle movement by determining the dynamic expansion radius, and enables each voxel in the static hazard set to expand isotropically based on the dynamic expansion radius, which can fully cover non-directional drifting obstacles. This ensures that the dynamic hazard set can accurately reflect the drift range of obstacles in special sea areas and improves the robustness of path planning.

[0012] Optionally, the preset frequency is dynamically adjusted according to the complexity of obstacles in the operating sea area.

[0013] This application, through dynamic adaptation at a preset frequency, can adaptively adjust the iteration update frequency of the dynamic hazard set according to the complexity of the sparseness of obstacles, ensuring that path planning can reflect the dynamic changes of obstacles in real time, and further improving the flexibility of path planning.

[0014] Optionally, the analysis of the spatiotemporal intersection of the currently feasible path and the dynamic hazard set includes: Based on a preset sampling step size, multiple sampling points of the current feasible path are determined, and the path length parameter corresponding to each sampling point is determined. The nominal speed of the underwater vehicle is obtained, and the arrival time of the underwater vehicle at each of the sampling points is determined based on the nominal speed and the path length parameter. Determine the static hazard center of the static hazard set, and determine the spatial distance between the sampling point and the static hazard center; Determine the sum of the dynamic hazard radius of the dynamic hazard set, the dynamic expansion radius of the dynamic hazard set at the arrival time, and the radius determined by the preset buffer radius; Based on the comparison results of the sum of the spatial distance and the radius, the spatiotemporal intersection of the current feasible path and the dynamic hazard set is determined.

[0015] This application achieves precise spatiotemporal matching between the path and the dynamic hazard zone by discretely sampling the current feasible path and combining it with the nominal velocity to determine the arrival time of each sampling point. Then, it provides navigation safety redundancy space by pre-setting a buffer radius. By combining the dynamic hazard radius of the dynamic hazard set and the dynamic expansion radius at the arrival time, it determines whether the underwater vehicle is at risk of colliding with obstacles. This ensures timely detection of potential collision risks.

[0016] Optionally, updating the current feasible path based on the spatiotemporal intersection to obtain a path planning result based on the updated current feasible path includes: Based on the spatiotemporal intersection situation, an intersection trigger point is determined on the current feasible path, and a local update planning interval is determined based on the current actual position of the underwater vehicle on the current feasible path and the intersection trigger point; Under the constraints of the dynamic hazard set corresponding to the arrival time, the optimal path segment within the local update planning interval is solved based on the A* algorithm; The optimized path segment is used to replace the local path segment of the current feasible path in the local update planning interval to obtain the updated current feasible path.

[0017] This application uses the A* algorithm to generate optimized path segments and replace the corresponding intervals of the original path. It does not require global replanning, but effectively reduces the amount of computation and avoids path oscillation by updating the path locally. At the same time, it ensures that the updated path can accurately avoid the risk of collision with dynamic obstacles.

[0018] Secondly, this application provides an underwater vehicle path planning device, the device comprising: The static planning module is used to determine the regional coordinate system corresponding to the operating sea area, and to determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area, and to determine the current feasible path of the underwater vehicle under the constraints of the static hazard set; The set update module is used to dynamically analyze the movement position of the obstacle and iteratively update the static hazard set based on the dynamic analysis results to obtain the dynamic hazard set; The dynamic programming module is used to analyze the spatiotemporal intersection of the current feasible path and the dynamic hazard set, and update the current feasible path according to the spatiotemporal intersection, so as to obtain the path planning result based on the updated current feasible path.

[0019] The underwater vehicle path planning device proposed in this application dynamically updates the expansion range of the danger zone by analyzing the movement and changes of obstacles in special sea areas through an ensemble update module. Based on the real-time updated dynamic danger ensemble as constraints, it monitors the spatiotemporal intersection risk between the current feasible path and the danger zone, and then replans the risky portions of the current feasible path through a dynamic planning module. Compared with related technologies, this application effectively improves the real-time performance, robustness, and accuracy of path planning, while only locally replanning necessary intervals within the path, avoiding the high computational burden and path oscillation problems caused by frequent global replanning.

[0020] Thirdly, this application provides a computer device, comprising: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes these computer instructions to perform the aforementioned underwater vehicle path planning method.

[0021] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the above-described underwater vehicle path planning method. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 One of the flowcharts for an underwater vehicle path planning method provided in this application embodiment; Figure 2 A second schematic flowchart illustrating an underwater vehicle path planning method provided in this application embodiment; Figure 3 A schematic diagram of the static hazardous aggregate provided in the embodiments of this application; Figure 4 The third flowchart illustrating an underwater vehicle path planning method provided in this application embodiment; Figure 5 The fourth flowchart illustrating an underwater vehicle path planning method provided in this application embodiment; Figure 6 A schematic diagram illustrating the updating of the dynamic hazard set provided in an embodiment of this application; Figure 7 Fifth of a flowchart illustrating an underwater vehicle path planning method provided in this application embodiment; Figure 8 A spatiotemporal intersection diagram of the currently feasible path and the dynamic hazard set provided for embodiments of this application; Figure 9 A flowchart illustrating an underwater vehicle path planning method provided in this application is shown in Figure 6. Figure 10 A schematic diagram of a path local update plan provided in an embodiment of this application; Figure 11An updated schematic diagram of the currently feasible path provided in the embodiments of this application; Figure 12 A schematic diagram of the structure of an underwater vehicle path planning device provided in an embodiment of this application; Figure 13 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] In the field of path planning for UUVs and other underwater vehicles, most technologies employ general-purpose path planning algorithms, which assume that environmental obstacles are static. However, in specific sea areas, special obstacle zones move with changes in water flow and wind direction. The static modeling methods used in these technologies cannot capture and update the dynamic changes of obstacles in real time, resulting in a disconnect between the planned path and the actual sea environment, and a significant decrease in the accuracy of path planning.

[0026] Furthermore, even in order to adapt to the dynamic changes of obstacles in special sea areas, the relevant technologies require periodic global replanning. Each planning process involves recalculating the entire path from scratch, which not only leads to a surge in computational load and frequent path oscillations, but also causes an increase in the energy consumption of underwater vehicles due to frequent computing power consumption, further affecting the endurance and navigation stability of underwater vehicles.

[0027] Therefore, there is an urgent need for a method that can rationally and efficiently plan the path of underwater vehicles in dynamic obstacle environments.

[0028] According to an embodiment of this application, an embodiment of an underwater vehicle path planning method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] This embodiment provides a path planning method for underwater vehicles, which can be used in the control systems of different types of UUVs and other underwater vehicles. Figure 1 This is a flowchart of an underwater vehicle path planning method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps: Step S1: Determine the regional coordinate system corresponding to the operating sea area, and determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area.

[0030] Specifically, the latitude and longitude coordinates of the underwater vehicle's operating area are first determined, and then converted into a regional coordinate system, such as the ENU coordinate system, using a Geographic Information System (GIS) tool. Next, predefined obstacle-related information, including obstacle location, depth, and hazard level, is input. Then, based on the obstacle's location and depth, the coordinates of multiple voxels are determined in the regional coordinate system, and the hazard level is bound to the corresponding coordinates. These voxels form a static hazard set.

[0031] Step S3: Determine the current feasible path for the underwater vehicle under the constraints of the static hazard set.

[0032] Specifically, in this embodiment of the application, under the constraint of a static hazard set, given the starting node and target node of the underwater vehicle, a path planning algorithm is used to solve for the current feasible path P. It can be understood that during path planning, the region containing the static hazard set in the regional coordinate system is set as a restricted area, thereby finding the optimal path within the non-restricted areas of the regional coordinate system as the current feasible path P.

[0033] Step S5: Perform dynamic analysis on the movement position of the obstacles, and iteratively update the static hazard set based on the dynamic analysis results to obtain the dynamic hazard set.

[0034] Specifically, since obstacles in special sea areas often drift over time, their positions must be assessed in real time and incorporated into path planning. This application's embodiments continuously track obstacle position changes and monitor the offset range of each hazard point, thereby dynamically correcting and iteratively updating the initially constructed static hazard set. This allows the dynamic hazard set to represent the actual distribution of obstacles in real time, providing accurate data for subsequent collision risk assessment between underwater vehicles and obstacles.

[0035] Step S7: Analyze the spatiotemporal intersection of the current feasible path and the dynamic hazard set, and update the current feasible path according to the spatiotemporal intersection to obtain the path planning result based on the updated current feasible path.

[0036] Specifically, this embodiment extracts discrete sampling points on the current feasible path and maps each sampling point to the arrival time of the underwater vehicle. Simultaneously, it obtains the extended range of the dynamic hazard region where the dynamic hazard set is located at that arrival time, and calculates the spatial distance between each sampling point and the center of the static hazard region. The spatial distance is compared with the dynamic hazard region corresponding to the dynamic hazard set at the arrival time to determine if there is a spatiotemporal intersection. By parameterizing the arrival time of the path, it is possible to more accurately predict when the underwater vehicle will arrive at the dynamic hazard region, thereby triggering timely path replanning and obtaining the updated current feasible path P'.

[0037] The underwater vehicle path planning method provided in this application dynamically updates the expansion range of the danger zone by analyzing the movement and changes of obstacles in special sea areas. Based on a dynamically updated set of dangers as constraints, it monitors the spatiotemporal intersection risk between the current feasible path and the danger zone, and then replans the risky portions of the current feasible path. Compared with related technologies, this application effectively improves the real-time performance, robustness, and accuracy of path planning. Furthermore, it only performs local replanning on necessary intervals within the path, avoiding the high computational burden and path oscillation problems caused by frequent global replanning.

[0038] Figure 2 A flowchart of step S1 in an embodiment of this application is shown, as follows: Figure 2 As shown, step S1 may include the following steps: Step S11: Project the geographic coordinates of the operating sea area onto the regional coordinate system, and divide the regional coordinate system into a three-dimensional grid according to a preset resolution.

[0039] Specifically, through the grid step size in the horizontal direction (x-axis and y-axis directions). and the grid step size in the vertical direction (z-axis direction) Define a preset resolution, for example, according to , The preset resolution divides the region coordinate system into a three-dimensional grid.

[0040] Step S13: The locations of obstacles within the operating area are voxelized in a three-dimensional mesh to form a static hazard set containing multiple hazard voxels.

[0041] Specifically, the regional coordinate system corresponding to the operational sea area is: Multiple voxels are determined in the region coordinate system based on the location and depth of the obstacles. Its coordinates are These voxels then form a static hazard set. .

[0042] Furthermore, the preset resolution is determined by a preset grid step size, which is dynamically adjusted according to the complexity of obstacles in the operating sea area. For example, in complex areas such as special obstacle zones or drifting special sea areas, the system will automatically adjust the grid density to reduce the computational burden in flat areas with sparse obstacles, while increasing the preset resolution in areas with dense obstacles.

[0043] For example, set the preset resolution according to the following formula (1). : Understandable, Similarly, this will not be elaborated upon here.

[0044] Figure 3 A schematic diagram of the static hazard collection voxelization in an embodiment of this application is shown, such as... Figure 3 As shown, the sea area is converted from latitude and longitude coordinates to a local area coordinate system, and then according to the set... =150m The operation area is divided into sea areas with a preset resolution of 3m, and the dangerous areas are discretized into multiple dangerous points through voxelization.

[0045] This application embodiment projects the geographic coordinates of the operating sea area onto a regional coordinate system and divides it into a three-dimensional grid according to a preset resolution. It also performs voxelization processing on the obstacle positions to form a static hazard set, thereby achieving accurate discretization of the hazard area. Furthermore, through dynamic adaptation of the grid step size, it can reduce computational redundancy in low-complexity areas with sparse obstacles and improve the accuracy of hazard identification in high-complexity areas with dense obstacles, thus enhancing the flexibility of path planning.

[0046] Figure 4 A flowchart of step S3 in an embodiment of this application is shown, as follows: Figure 4 As shown, step S3 may include the following steps: Step S31: Determine the starting node and target node of the underwater vehicle; Step S33: Under the constraints of the static hazard set, solve for the current feasible path based on the A* algorithm.

[0047] Specifically, the A* algorithm is a heuristic search algorithm applicable to path optimization. It evaluates available nodes in a path using a cost function to determine which node should be expanded next to form the path. This cost function is shown in Equation (2) below: In the formula, n is the current node. Let n be the actual cost of the underwater vehicle from the starting node to the current node n. This is an estimated cost for the underwater vehicle to travel from the current node n to the target node. It should be noted that in some embodiments of this application, and Heuristic functions such as Euclidean distance or Manhattan distance can be used.

[0048] During path planning, by considering the obstacle space constraints represented by the static hazard set, the A* algorithm generates the optimal path from the starting node to the target node.

[0049] Figure 5 A flowchart of step S5 in an embodiment of this application is shown, as follows: Figure 5 As shown, step S5 may include the following steps: Step S51: Determine the current update time and the reference time based on the preset frequency, and determine the time difference between the current update time and the reference time, wherein the reference time is determined according to the time of the last update of the static hazard set.

[0050] Specifically, in this application embodiment, the static hazard set is updated based on a preset frequency. The reference time represents the time node of the most recent update of the static hazard set. Based on the time difference between the current update time and the reference time, a quantitative basis is provided for the subsequent deduction of the dynamic expansion range of the hazard area.

[0051] Furthermore, in some embodiments of this application, the preset frequency is dynamically adjusted according to the complexity of obstacles in the operating sea area. For example, the preset frequency is automatically adjusted based on real-time changes in the water flow speed and path planning in a specific sea area; the greater the water flow speed or the greater the change in path planning, the higher the complexity of the sea area. In high-risk areas, the system increases the aforementioned preset frequency to ensure that the path planning can reflect the dynamic changes of obstacles in real time.

[0052] For example, set the preset frequency according to the following formula (3): In the formula, The preset frequency is as described above.

[0053] This application embodiment dynamically adapts the preset frequency to the complexity of the sea area, adaptively adjusting the iteration update frequency of the dynamic hazard set to ensure that the path planning can reflect the dynamic changes of obstacles in real time, further improving the flexibility of path planning.

[0054] Step S53: Obtain the upper limit of the movement speed of the operating sea area, and determine the dynamic expansion radius of the danger zone based on the upper limit of the movement speed and the time difference, so as to use the dynamic expansion radius as the result of dynamic analysis.

[0055] Specifically, the upper limit of the movement speed in the operating sea area refers to the maximum speed of the water flow in the operating sea area. The obstacle will shift its position with the water flow in the operating sea area, so this can be used to characterize the drift of the obstacle in the sea area.

[0056] The dynamic expansion radius is determined according to the following formula (4): In the formula, For dynamically expanding radius, This is the upper limit for movement speed, with a default value of 8 km / day. At the current update time, This is the reference time.

[0057] Step S55: The static hazard set is isotropically expanded based on the dynamic expansion radius to obtain the dynamic hazard set.

[0058] Specifically, the updated dynamic hazard set is determined according to the following formula (5): In the formula, For dynamic hazard set, For radius The disc, The Minkowski sum operation represents the sum of two point sets A and B in Euclidean space, which can be used to characterize static hazard sets. Isotropic expansion of each voxel.

[0059] Figure 6 This illustration shows a schematic diagram of the update of the dynamic hazard set in an embodiment of this application, such as... Figure 6 As shown, through the static hazard set Horizontal isotropic expansion occurs, forming a dynamic hazard zone. By adjusting the expansion radius It can reflect the changes of obstacles in special sea areas over time.

[0060] This application embodiment achieves real-time dynamic tracking of obstacle movement by determining the dynamic expansion radius, and enables each voxel in the static hazard set to expand isotropically based on the dynamic expansion radius, which can fully cover non-directional drifting obstacles, thereby ensuring that the dynamic hazard set can accurately reflect the drift range of obstacles in special sea areas and improve the robustness of path planning.

[0061] Figure 7 A flowchart of step S7 in an embodiment of this application is shown, as follows: Figure 7 As shown, step S7 may include the following steps: Step S711: Determine multiple sampling points of the current feasible path based on the preset sampling step size, and determine the path length parameter corresponding to each sampling point.

[0062] Specifically, in this embodiment, the horizontal grid step size is based on a preset resolution. The known spatial step size is used to discretize the current feasible path, resulting in multiple discrete sampling points. Then, the first path length of each sampling point along the current feasible path relative to the starting node of the current feasible path is determined. Then determine the second path length of the underwater vehicle's actual position at the current update moment relative to the starting node of the current feasible path. With the first path length With the second path length The difference is used as the path length parameter for each sampling point.

[0063] Understandably, the path length parameter represents the distance an underwater vehicle can travel from its actual position at the current update time to the corresponding sampling point if it follows the currently feasible path.

[0064] Step S713: Obtain the nominal speed of the underwater vehicle, and determine the arrival time of the underwater vehicle at each sampling point based on the nominal speed and path length parameters.

[0065] Specifically, the arrival time is determined according to the following formula (6): In the formula, This indicates the arrival time of the underwater vehicle at a certain sampling point. Indicates the current update time. This represents the nominal speed of the underwater vehicle. The nominal speed refers to the preset baseline speed of the underwater vehicle; in some embodiments of this application, this nominal speed is taken as 3 meters per second.

[0066] As can be seen, the embodiments of this application map each sampling point on the current feasible path to the arrival time through the above formula (6), thereby realizing the spatiotemporal matching of the path and the dynamic danger zone.

[0067] Step S715: Determine the static hazard center of the static hazard set and determine the spatial distance between the sampling point and the static hazard center.

[0068] Step S717: Determine the sum of the dynamic hazard radius of the dynamic hazard set, the dynamic expansion radius of the dynamic hazard set at the arrival time, and the radius determined by the preset buffer radius.

[0069] Step S719: Based on the comparison results of the sum of spatial distance and radius, determine the spatiotemporal intersection of the current feasible path and the dynamic hazard set.

[0070] Specifically, if the following formula (7) is satisfied, it is determined that the current feasible path and the dynamic hazard set have spatiotemporal intersection: In the formula, Indicates the location of a sampling point. Represents the static hazard set Static hazard center The spatial distance between the sampling point and the static hazard center. For dynamic hazard set The dynamic danger radius, Arrival time The corresponding dynamic expansion radius, This is a preset buffer radius. It's understandable that at the arrival time... Below, the radius of the dynamic hazard region corresponding to the dynamic hazard set is assessed as follows: .

[0071] It should be noted that in some embodiments of this application, a static hazard set is determined. A static envelope circle is defined, and the center of this static envelope circle is taken as the aforementioned static hazard center. Furthermore, a dynamic hazard set is determined. The dynamic envelope circle is defined, and the radius of the dynamic envelope circle is taken as the dynamic danger radius.

[0072] Preset buffer radius This refers to the lateral buffer radius of the path corridor, which is the preset path width to ensure the safe passage of underwater vehicles, thereby providing safety redundancy space for path planning. In this embodiment, the horizontal grid step size is used... Sure The possible values, for example =2 .

[0073] Figure 8 This illustration shows a spatiotemporal intersection diagram of the currently feasible path and the dynamic hazard set in an embodiment of this application, as shown below. Figure 8 As shown, the current feasible path is discretized into multiple sampling points, and the arrival time of each sampling point is calculated. Meanwhile, the path corridor is buffered by lateral movement. The system expands the scope of the current feasible path to determine whether it intersects with a dynamic hazard area.

[0074] This application embodiment determines the arrival time of each sampling point by discretely sampling the current feasible path and combining it with the nominal velocity. Then, it provides navigation safety redundancy space by setting a preset buffer radius. By combining the dynamic danger radius of the dynamic danger set and the dynamic expansion radius at the arrival time, it determines whether the underwater vehicle is at risk of colliding with obstacles. This achieves accurate spatiotemporal matching between the path and the dynamic danger area, ensuring timely detection of potential collision risks.

[0075] Figure 9 Another flowchart of step S7 in an embodiment of this application is shown, as follows: Figure 9 As shown, step S7 may include the following steps: Step S721: Determine the intersection trigger point on the current feasible path based on the spatiotemporal intersection situation, and determine the local update planning interval based on the current actual position of the underwater vehicle on the current feasible path and the intersection trigger point.

[0076] Specifically, in some embodiments of this application, if the current feasible path and the dynamic hazard set have a spatiotemporal intersection, that is, satisfying the above formula (7), and simultaneously satisfying the preset lead time. and preset minimum interval Determine the intersection trigger point, i.e., the straight line between the sampling point and the static hazard center and the radius is... The intersection of dynamic danger zones.

[0077] Among them, the preset lead time This refers to the time difference between the current update time and the earliest time when they intersect being no less than a preset threshold, where the preset minimum interval is [not specified]. This means that the time interval between two consecutive determinations of trigger points is not less than a preset threshold, thereby avoiding excessively frequent triggering of local update planning. In some embodiments of this application, The value is 20 minutes. The value is 10 minutes.

[0078] Subsequently, the local update planning interval is determined in this embodiment of the application as follows: ,in, This represents the current actual position of the underwater vehicle at the current update moment. This refers to the location of the intersection trigger point. Therefore, this embodiment of the application provides a method for locally updating the planning interval. The redundant space is used to further improve the accuracy of path updates.

[0079] Step S723: Under the constraint of the dynamic hazard set corresponding to the arrival time, solve the optimized path segment within the local update planning interval based on the A* algorithm.

[0080] Specifically, determine the arrival time. Corresponding dynamic hazard set Thus, in this dynamic hazard set Generate nodes from position nodes using the A* algorithm under constraints. To the location node The optimal path is found using the A* algorithm, which works similarly to step S33 above. Please refer to the above explanation for details.

[0081] Step S725: Replace the local path segments of the current feasible path in the local update planning interval with optimized path segments to obtain the updated current feasible path.

[0082] Specifically, in this embodiment, the optimized path segment obtained by the A* algorithm is used to accurately replace the original path segment in the current feasible path that corresponds to the local update planning interval. The other non-intersecting intervals of the path remain unchanged, and finally the updated current feasible path is formed. In this way, only the part of the path that intersects with the dynamic danger area is replanned, avoiding unnecessary path correction.

[0083] Figure 10 A schematic diagram of path local update planning in an embodiment of this application is shown, such as... Figure 10 As shown, it demonstrates how to locally update the path by updating the planning interval when the path corridor intersects with a dynamic hazard area. Figure 10 The green lines in the image indicate parts of the path that need to be updated.

[0084] Figure 11 This document illustrates an update diagram of the currently feasible path in an embodiment of this application, as shown below. Figure 11 As shown, it illustrates how the embodiments of this application perform collision avoidance planning when encountering a dynamic hazardous area in practice. Figure 11 The image shows the original path and the collision avoidance path after the replanned path.

[0085] This application uses the A* algorithm to generate optimized path segments and replace the corresponding intervals of the original path. It does not require global replanning, but effectively reduces the amount of computation and avoids path oscillation by updating the path locally. At the same time, it ensures that the updated path can accurately avoid the risk of collision with dynamic obstacles.

[0086] Accordingly, please refer to Figure 12 This application provides an underwater vehicle path planning device, which includes: The static planning module 100 is used to determine the regional coordinate system corresponding to the operating sea area, and to determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area. Under the constraints of the static hazard set, the current feasible path of the underwater vehicle is determined. For details, please refer to steps S1 and S3. The set update module 200 is used to dynamically analyze the movement position of obstacles and iteratively update the static hazard set based on the dynamic analysis results to obtain the dynamic hazard set. For details, please refer to step S5. The dynamic programming module 300 is used to analyze the spatiotemporal intersection of the current feasible path and the dynamic hazard set, and update the current feasible path according to the spatiotemporal intersection, so as to obtain the path planning result based on the updated current feasible path. For details, please refer to step S7.

[0087] In some alternative implementations, the static planning module 100 includes: The grid division unit is used to project the geographic coordinates of the operating sea area onto the regional coordinate system, and to divide the regional coordinate system into a three-dimensional grid according to a preset resolution.

[0088] Voxelization units are used to voxelize the locations of obstacles within the operational sea area in a three-dimensional mesh, forming a static hazard set containing multiple hazard voxels.

[0089] In some alternative implementations, the static planning module 100 further includes: The first path planning unit is used to determine the starting node and target node of the underwater vehicle, and solves the current feasible path based on the A* algorithm under the constraints of the static hazard set.

[0090] In some alternative implementations, the set update module 200 includes: The time determination unit is used to determine the current update time and the reference time based on a preset frequency, and to determine the time difference between the current update time and the reference time, wherein the reference time is determined based on the time of the last update of the static hazard set; The dynamic analysis unit is used to obtain the upper limit of the movement speed of the operating sea area, and to determine the dynamic expansion radius of the danger zone based on the upper limit of the movement speed and the time difference, so as to use the dynamic expansion radius as the result of dynamic analysis. An extension unit is used to isotropically extend the static hazard set based on the dynamic extension radius to obtain a dynamic hazard set.

[0091] In some alternative implementations, the dynamic programming module 300 includes an intersection analysis unit for: Based on a preset sampling step size, multiple sampling points for the current feasible path are determined, and the path length parameter corresponding to each sampling point is determined. Obtain the nominal speed of the underwater vehicle, and determine the arrival time of the underwater vehicle at each sampling point based on the nominal speed and path length parameters; Determine the static hazard center of the static hazard set, and determine the spatial distance between the sampling point and the static hazard center; Determine the sum of the dynamic hazard radius of the dynamic hazard set, the dynamic expansion radius of the dynamic hazard set at the arrival time, and the preset buffer radius; Based on the comparison of the sum of spatial distance and radius, the spatiotemporal intersection of the current feasible path and the dynamic hazard set is determined.

[0092] In some alternative implementations, the dynamic programming module 300 further includes a second path planning unit for: Based on the spatiotemporal intersection, determine the intersection trigger point on the current feasible path, and determine the local update planning interval based on the current actual position of the underwater vehicle on the current feasible path and the intersection trigger point; Under the constraint of the dynamic hazard set corresponding to the arrival time, the optimal path segment within the local update planning interval is solved based on the A* algorithm; Replace local path segments of the current feasible path within the local update planning interval with optimized path segments to obtain the updated current feasible path.

[0093] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0094] In this embodiment, the underwater vehicle path planning device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0095] Please see Figure 13 , Figure 13 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application, such as... Figure 13 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 13 Take a processor 10 as an example.

[0096] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0097] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0098] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0099] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0100] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0101] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0102] This application provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method of any embodiment of this application.

[0103] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and all such modifications and variations fall within the scope defined by the appended claims.

[0104] The apparatus, module, or unit described in the above embodiments can be implemented by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0105] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0106] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0108] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0110] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0111] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0112] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0113] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A path planning method for an underwater vehicle, characterized in that, The method includes: Determine the regional coordinate system corresponding to the operating sea area, and determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area; Determine the current feasible path for the underwater vehicle under the constraints of the static hazard set; The movement position of the obstacle is dynamically analyzed, and the static hazard set is iteratively updated based on the dynamic analysis results to obtain the dynamic hazard set; The spatiotemporal intersection of the current feasible path and the dynamic hazard set is analyzed, and the current feasible path is updated according to the spatiotemporal intersection to obtain the path planning result.

2. The method according to claim 1, characterized in that, The process of determining the regional coordinate system corresponding to the operational sea area and determining the static hazard set corresponding to the regional coordinate system based on obstacles in the operational sea area includes: The geographic coordinates of the operating sea area are projected onto the regional coordinate system, and the regional coordinate system is divided into a three-dimensional grid according to a preset resolution; The locations of obstacles within the operational sea area are voxelized in the three-dimensional grid to form a static hazard set containing multiple hazard voxels.

3. The method according to claim 2, characterized in that, The preset resolution is determined by a preset grid step size, and the preset grid step size is dynamically adjusted according to the complexity of obstacles in the operating sea area.

4. The method according to claim 1, characterized in that, Determining the current feasible path for the underwater vehicle under the constraints of the static hazard set includes: Determine the starting node and target node of the underwater vehicle; Under the constraints of the static hazard set, the current feasible path is solved based on the A* algorithm.

5. The method according to claim 1, characterized in that, The dynamic analysis of the movement position of the obstacle, and the iterative update of the static hazard set based on the dynamic analysis results, to obtain the dynamic hazard set, includes: The current update time and the reference time are determined based on a preset frequency, and the time difference between the current update time and the reference time is determined, wherein the reference time is determined according to the time of the last update of the static danger set; Obtain the upper limit of the movement speed of the operation sea area, and determine the dynamic expansion radius of the danger zone based on the upper limit of the movement speed and the time difference, so as to use the dynamic expansion radius as the result of the dynamic analysis; The static hazard set is isotropically expanded based on the dynamic expansion radius to obtain the dynamic hazard set.

6. The method according to claim 5, characterized in that, The preset frequency is dynamically adjusted according to the complexity of obstacles in the operating sea area.

7. The method according to claim 1, characterized in that, The analysis of the spatiotemporal intersection of the current feasible path and the dynamic hazard set includes: Based on a preset sampling step size, multiple sampling points of the current feasible path are determined, and the path length parameter corresponding to each sampling point is determined. The nominal speed of the underwater vehicle is obtained, and the arrival time of the underwater vehicle at each of the sampling points is determined based on the nominal speed and the path length parameter. Determine the static hazard center of the static hazard set, and determine the spatial distance between the sampling point and the static hazard center; Determine the sum of the dynamic hazard radius of the dynamic hazard set, the dynamic expansion radius of the dynamic hazard set at the arrival time, and the radius determined by the preset buffer radius; Based on the comparison results of the sum of the spatial distance and the radius, the spatiotemporal intersection of the current feasible path and the dynamic hazard set is determined.

8. The method according to claim 7, characterized in that, The step of updating the current feasible path based on the spatiotemporal intersection situation, and obtaining the path planning result based on the updated current feasible path, includes: Based on the spatiotemporal intersection situation, an intersection trigger point is determined on the current feasible path, and a local update planning interval is determined based on the current actual position of the underwater vehicle on the current feasible path and the intersection trigger point; Under the constraints of the dynamic hazard set corresponding to the arrival time, the optimal path segment within the local update planning interval is solved based on the A* algorithm; The optimized path segment is used to replace the local path segment of the current feasible path in the local update planning interval to obtain the updated current feasible path.

9. A path planning device for an underwater vehicle, characterized in that, The device includes: The static planning module is used to determine the regional coordinate system corresponding to the operating sea area, and to determine the static hazard set corresponding to the regional coordinate system based on the obstacles in the operating sea area, and to determine the current feasible path of the underwater vehicle under the constraints of the static hazard set; The set update module is used to dynamically analyze the movement position of the obstacle and iteratively update the static hazard set based on the dynamic analysis results to obtain the dynamic hazard set; The dynamic programming module is used to analyze the spatiotemporal intersection of the current feasible path and the dynamic hazard set, and update the current feasible path according to the spatiotemporal intersection, so as to obtain the path planning result based on the updated current feasible path.

10. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the underwater vehicle path planning method according to any one of claims 1 to 8 by executing the computer instructions.

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