A method and system for survey path planning of offshore new energy power stations under multiple constraints

Abstract

This application discloses a method and system for planning the scanning path of offshore new energy power stations under multiple constraints, belonging to the field of path planning technology. The method includes: constructing a gridded map and generating a set of candidate scanning strips; calculating the passage cost based on the basic cost components and coupling relationships of multiple constraints; obtaining the target scanning strip set through strip association structure and directional angle constraints; constructing and smoothing the global scanning path; then dividing the global scanning path into a frozen segment, a currently executing segment, and an active segment based on the real-time coverage state sequence; and locally reconstructing the affected intervals of the active segment to obtain the updated global scanning path. This method solves the technical problems of inaccurate multi-constraint processing, incomplete coverage, poor dynamic adaptability, and high overall replanning overhead.

Description

Technical Field

[0001] This application relates to the field of path planning technology, and in particular to a method and system for path planning of offshore new energy power stations under multiple constraints. Background Technology

[0002] With the large-scale construction of offshore new energy power stations (such as offshore wind farms and offshore photovoltaic power stations), their operation and maintenance place higher demands on the accuracy and timeliness of environmental information acquisition in the station area. Surveying operations, as an important means of acquiring information on marine topography, obstacle distribution, and the state of the operating environment, typically rely on a work platform equipped with surveying equipment to scan the target area along a pre-planned path. Therefore, how to generate a surveying path that is comprehensive, stable, and adaptable to environmental changes has become a key issue of concern in related technical fields.

[0003] In existing technologies, scanning paths are mostly planned using regular strip or gridded coverage methods. While these methods can achieve area coverage in ideal environments, they are typically generated in a single step based on static environmental assumptions, lacking the ability to respond to dynamic environmental changes during actual operations. For example, CN111640220A discloses an unmanned surface vessel (USV) inspection system and its working method for offshore wind farms. This system achieves submarine cable tracking and comprehensive scanning around wind turbine foundations through preliminary path planning and dynamic correction during navigation. CN111612217A proposes an improved GA-SA path planning method for offshore wind farm inspection USVs, which improves the overall efficiency of the inspection path through global optimization. When sea conditions, obstacle distribution, or equipment operation constraints change, existing paths are difficult to adjust in a timely manner, easily leading to repeated or missed scanning of local areas, thus affecting overall operational efficiency and coverage quality.

[0004] On the other hand, while some existing solutions introduce path adjustment mechanisms, they mostly rely on overall path replanning, resulting in significant computational overhead. Furthermore, they lack an effective distinction between executed and currently executing paths during path updates, which can easily lead to path discontinuity or unstable execution. In addition, existing technologies often determine the scan coverage status at a coarse-grained level, lacking fine-grained modeling based on grid cells, making it difficult to support a structured representation of the path execution status and subsequent local optimization processing.

[0005] Therefore, it is necessary to provide a path planning method that can structurally divide and locally adaptively reconstruct the scanning path while ensuring the integrity of global coverage, taking into account the real-time location of the scanning equipment and changes in environmental constraints, so as to improve the stability and efficiency of scanning operations. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for planning survey paths for offshore new energy power stations under multiple constraints. This invention constructs a gridded map of the survey operation area and generates a set of candidate survey strips according to a preset direction. It calculates the passage cost of grid cells and strips based on the coupling relationship between the basic cost components of various constraints and the constraints themselves. Furthermore, it divides the global survey path into coverage state sequences and reconstructs the active segment path intervals, thereby achieving efficient coverage path planning and real-time adaptive updates under multiple constraints.

[0007] To achieve the above objectives, in a first aspect, the present invention provides a method for survey path planning of offshore new energy power stations under multiple constraints, comprising the following steps: S1: Construct a gridded map of the scanning operation area, and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction; S2: Obtain the constraints that affect the scanning operation, map the passage state of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. S3: Based on the passage cost of the grid cells corresponding to each candidate scan strip, determine the feasible scan strip, select the strip based on the strip association structure, strip passage cost and strip connection cost, and constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip; S4: Construct strip scanning paths according to the combination order of target scanning strips, and generate connecting paths between adjacent target scanning strips to obtain the initial scanning path; S5: Discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. S6: Based on the real-time location and scanning range of the scanning equipment, determine the coverage status of the grid cell corresponding to the track point and construct the coverage status sequence. Divide the coverage status sequence into continuous intervals and divide the global scanning path into frozen segment, currently executing segment and active segment. S7: Determine the change area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

[0008] Secondly, the present invention provides a survey path planning system for offshore new energy power stations under multiple constraints, comprising: The candidate scanning strip generation module is used to construct a gridded map of the scanning operation area and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction. The passage cost calculation module is used to obtain the various constraints affecting the scanning operation, map the passage status of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. The target scan strip acquisition module is used to determine feasible scan strips based on the passage cost of the grid cells corresponding to each candidate scan strip, to select a combination based on the strip association structure, the strip passage cost and the strip connection cost, and to constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip. The initial scan path acquisition module is used to construct the strip scan path according to the combination order of the target scan strips, and generate connecting paths between adjacent target scan strips to obtain the initial scan path; The global scan path acquisition module is used to discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. The status calibration module is used to determine the coverage status of the grid cells corresponding to the track points based on the real-time position and scanning range of the scanning equipment and to construct a coverage status sequence. The coverage status sequence is divided into continuous intervals, and the global scanning path is divided into frozen segments, currently executing segments and active segments. The path interval reconstruction module is used to determine the changed area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and then concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

[0009] One or more technical solutions provided in this invention have at least the following technical effects or advantages: By mapping the passage state corresponding to each grid cell under various constraints to basic cost components, and determining the passage cost of each grid cell based on the coupling relationship between each basic cost component and constraints, the impact of sea state constraints, obstacle constraints, energy consumption constraints, operation time window constraints, and navigation safety constraints on the survey operation can be accurately quantified; based on the passage cost of the grid cells corresponding to each candidate survey strip, feasibility is determined and a strip association structure is constructed; combined with the strip passage cost, strip connection cost, and directional angle constraint control between adjacent feasible survey strips, the target survey is obtained. Strip sets enable the selection of combinations that cover the entire scanning operation area while minimizing overall cost. By discretizing the initial scanning path and constructing a smooth curve that satisfies curvature constraints at the turning nodes, a global scanning path is obtained. Based on the real-time position and scanning range of the scanning equipment, a coverage state sequence is constructed and divided into a frozen segment, a currently executing segment, and an active segment. Then, based on the change area determined by the change of constraint parameters, the affected path intervals in the active segment are reconstructed. This allows for local adaptive updates while maintaining the stability of the frozen segment and the currently executing segment, thereby effectively improving the coverage integrity, execution stability, and adaptability to dynamic environmental changes of the scanning path.

[0010] Compared with existing technologies, this invention effectively solves the problems of incomplete coverage and single constraint processing in traditional static strip planning by generating gridded maps and candidate scan strip sets, combined with multi-constraint coupled passage cost calculation and directional angle constraint control. It achieves fine differentiation of path execution status through continuous interval division of coverage state sequence and structured calibration of frozen segments, currently executed segments and active segments. At the same time, it reconstructs local path intervals of active segments based on connectivity analysis of changing regions, ensuring the stability of executed paths and improving the real-time adaptability of scan operations to dynamic changes in sea conditions and constraints.

[0011] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1A flowchart illustrating a method for survey path planning of offshore new energy power stations under multiple constraints, provided in an embodiment of this application; Figure 2 A schematic diagram of a survey path planning system for offshore new energy power stations under multiple constraints, provided as an embodiment of this application; The attached diagrams show the following modules: Candidate scan strip generation module, passage cost calculation module, target scan strip acquisition module, initial scan path acquisition module, global scan path acquisition module, state calibration module, and path interval reconstruction module. Detailed Implementation

[0014] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0015] Example 1, as Figure 1 As shown, this application provides a method for survey path planning of offshore new energy power stations under multiple constraints, wherein the method includes: S1: Construct a gridded map of the scanning operation area, and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction; Furthermore, the step of generating candidate scanning strips composed of continuous grid cells based on a gridded map in a preset direction includes: Obtain the effective scanning width of the scanning equipment, determine the spacing between adjacent strips according to the preset coverage overlap requirements, and determine the grid cell size according to the scanning accuracy requirements; The scanning operation area is divided into regular sections based on the grid cell size, a grid map is constructed, and a corresponding spatial location is assigned to each grid cell. Several strip generation directions are set. For each strip generation direction, consecutive and adjacent grid cells along that direction are connected in sequence to form multiple candidate scanning strips. Assign corresponding directional attributes to each candidate scan strip to obtain a set of candidate scan strips.

[0016] Specifically, the effective scanning width of the scanning equipment is obtained based on its technical parameters; the spacing between adjacent strips is determined according to preset coverage overlap requirements to ensure that adjacent scanning trajectories meet the coverage integrity requirements; and the grid cell size is determined according to the scanning accuracy requirements to match the grid division accuracy with the scanning accuracy. Based on the design data of the offshore new energy power station, the spatial range data of the survey operation area is obtained. This spatial range data consists of multiple boundary coordinate points. These boundary coordinate points are connected in spatial order to form a closed area. Based on the previously determined grid unit size, a regular grid is constructed within this closed area to obtain a gridded map covering the entire survey operation area. Each grid unit is assigned a unique identifier and a corresponding spatial coordinate position. Based on the overall shape of the scanning area or the preset operating direction, several stripe generation directions are determined. For each stripe generation direction, adjacent grid cells arranged continuously along that direction are connected sequentially to form multiple candidate scanning stripes. The continuity between grid cells is determined based on their adjacency relationship, which includes edge adjacency or corner adjacency. Each candidate scan strip is assigned a corresponding directional attribute, which is consistent with the strip generation direction that generated the candidate scan strip, thus obtaining a set of candidate scan strips.

[0017] S2: Obtain the constraints that affect the scanning operation, map the passage state of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. Further, determining the passage cost of the grid cell and the strip passage cost of the candidate scan strip includes: Obtain various constraints that affect the survey operation, including sea state constraints, obstacle constraints, energy consumption constraints, operation time window constraints, and navigation safety constraints; For each grid cell, obtain the constraint parameter values ​​corresponding to various constraints; and based on the relationship between the constraint parameter values ​​and the preset passable thresholds and prohibited passable thresholds of various constraints, map the passability state to the basic cost component. Based on the basic cost components and constraint coupling relationships, the passage cost of the corresponding mesh cell is determined: When any basic cost component is 1, the access cost of the corresponding grid cell is directly set to the unreachable flag value; When all basic cost components are not equal to 1, the passage cost of the corresponding grid cell is calculated according to the following formula: ; Where k is the grid cell index, Let $\frac{k}{k}$ be the passage cost for the $k$-th grid cell. For constrained indexes, Let be the weight coefficient of the i-th type of constraint. Respectively, the i-th type of constraint and the i-th type of constraint The basic cost component of class constraints; For the i-th type of constraint and the th Coupling coefficients between class constraints; Based on the travel cost of each grid cell constituting the same candidate scan strip, the strip travel cost of the candidate scan strip is calculated. The calculation formula is: ; Where n is the number of grid cells contained in the candidate strip, and k is the grid cell index. Let $\frac{k}{k}$ be the passage cost for the $k$-th grid cell. This is the risk amplification factor.

[0018] Specifically, based on the design data of the offshore new energy power station, on-site monitoring data, operating parameters of the surveying equipment, and operation scheduling information, various constraints affecting the surveying operation are obtained, including sea state constraints, obstacle constraints, energy consumption constraints, operation time window constraints, and navigation safety constraints. Each type of constraint has preset passable and prohibited passable thresholds. The passable threshold defines the boundary that can be traversed without additional cost; the prohibited passable threshold defines the boundary that is completely impassable. The passable and prohibited passable thresholds are set according to equipment operating capacity, operation safety requirements, and scheduling rules. The constraint parameters corresponding to each type of constraint include: sea state parameters (current speed, wind speed, wave height), spatial distance parameters (distance from the grid cell to the nearest obstacle), energy consumption parameters (energy consumption per unit path), time parameters (operation time), and navigation status parameters (safety index values). For each grid cell, the constraint parameter values ​​for various constraints are obtained: For sea state constraints, the current velocity, wind speed, and wave height data at the grid cell are obtained, normalized according to their respective passable and prohibited passable thresholds, and the maximum value among the three is taken as the constraint parameter value; For obstacle constraints, the spatial distance from the center of the grid cell to the nearest obstacle (including wind turbine foundations, cable area boundaries, and prohibited area boundaries) is calculated as the constraint parameter value; For energy consumption constraints, the energy consumption per unit path required to pass through the grid cell is estimated based on the dynamic model of the scanning equipment and the navigation resistance at the grid cell, and is taken as the constraint parameter value; For operation time window constraints, the operation time corresponding to the grid cell is determined based on the estimated arrival time of the scanning path, and is taken as the constraint parameter value; For navigation safety constraints, the navigation safety index value is calculated based on the sea state and equipment status parameters at the grid cell, and is taken as the constraint parameter value. After obtaining the constraint parameter values ​​for each constraint, the constraint parameter values ​​for each type of constraint i in each grid cell are... With respect to the preset passability threshold of this constraint and no-passage threshold The relationship between the states maps the passage states to the basic cost components. The specific mapping rules are as follows: For constraints whose larger parameter values ​​result in poorer passage capability (such as sea state constraints, energy consumption constraints, and navigation safety constraints): when When it is passable, When it is impassable, This is a restricted passage state; for constraints where smaller parameter values ​​result in poorer passage capacity (such as obstacle constraints): when When it is passable, When it is impassable, The current state is a restricted passage condition. The basic cost component for the passable state is 0; the basic cost component for the impassable state is 1; the basic cost component for the restricted passage state is calculated as follows: for constraints where a larger constraint parameter value indicates poorer passage capability... For constraints where smaller parameter values ​​result in poorer traffic capacity... For the task time window constraint (interval constraint with upper and lower limits), first convert the time window into a parameter that represents the degree of deviation from the allowable time range, so that the larger the value, the worse it is, and then calculate according to the first formula. The passage cost of a grid cell is determined based on its fundamental cost components and constraint coupling relationships (characterized by coupling coefficients). Specifically, for each grid cell, its corresponding fundamental cost components are first determined: When any basic cost component is 1, it means that the grid cell is in an impassable state under the corresponding constraint conditions. At this time, the passage cost is no longer calculated, and the passage cost of the grid cell is directly set to the unreachable flag value. When all basic cost components are not equal to 1, the basic cost components are coupled and calculated to determine the passage cost of the grid cell. The calculation formula is as follows: ; Where k is the grid cell index, Let $\frac{k}{k}$ be the passage cost for the $k$-th grid cell. For constrained indexes, The weight coefficient of the i-th type of constraint is used to characterize the degree of influence of the constraint on the traffic capacity. It is obtained by normalizing the proportion of the influence of each constraint on the efficiency or risk of the survey operation in the historical survey data. Respectively, the i-th type of constraint and the i-th type of constraint The basic cost component of class constraints; For the i-th type of constraint and the th The coupling coefficient between the two types of constraints is used to characterize the synergistic amplification or cancellation effect when both types of constraints coexist. It is determined by statistically analyzing the rate of change in traffic efficiency when the two types of constraints coexist in historical operations. Used to demonstrate the limiting effect of the combined action of constraints; After obtaining the passage cost of each grid cell, the strip passage cost T of the candidate scan strip is determined based on the passage costs of each grid cell constituting the same candidate scan strip. The calculation formula is as follows: ; Where n is the number of grid cells contained in the candidate strip, and k is the grid cell index. The passage cost for the k-th grid cell; This is the risk amplification factor (preset according to safety requirements, with a value range of 0 to 1, used to adjust the degree of impact of local high risk on the overall strip).

[0019] S3: Based on the passage cost of the grid cells corresponding to each candidate scan strip, determine the feasible scan strip, select the strip based on the strip association structure, strip passage cost and strip connection cost, and constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip; Further, obtaining the target scanning strip includes: For each candidate scan strip, a feasibility determination is made based on the passage cost of each grid cell constituting the candidate scan strip. Infeasible scan strips are eliminated, and the remaining candidate scan strips constitute a set of feasible scan strips. For any two feasible scan strips in the set of feasible scan strips, the strip connection cost is constructed based on the connection distance and directional angle between their termination and start points. The calculation formula is as follows: ; in, For feasible scanning strips and The cost of strip connectivity, For feasible scanning strips Termination location and feasible scanning strip The distance between the starting points For feasible scanning strips and The angle between the directions, The directional influence coefficient. This is the distance compensation coefficient. For distance scale parameters; Construct a strip association structure with feasible scan strips as nodes and strip connection costs as edge weights; Based on the strip association structure, strip passage cost, and strip connection cost, feasible scanning strips are combined and selected to form a corresponding combination order; the combination selection is to select feasible scanning strips so that the selected feasible scanning strips cover the entire scanning operation area and minimize the overall cost. The directional angle between adjacent feasible scanning strips in the combination sequence is constrained and controlled. When the directional angle is greater than a preset angle threshold, the corresponding connection relationship is prohibited from participating in the combination, so as to obtain the target scanning strip.

[0020] Specifically, firstly, for each candidate scan strip, the passage cost of each grid that constitutes the candidate scan strip is obtained, and a feasibility determination is made: when the passage cost of any grid cell is an unreachable value, the candidate scan strip is determined to be an infeasible scan strip and is removed from the candidate scan strip set; the remaining candidate scan strips constitute the feasible scan strip set. For any two feasible scan strips in the feasible scan strip set, pairwise combinations are performed to establish the connection relationship between the feasible scan strips. Specifically, for any two feasible scan strips... and , obtain The termination point and The starting point is determined, and the connection distance between the two points is calculated based on the Euclidean distance. At the same time, acquire and The direction vectors are calculated, and the angle between their directions is calculated based on the dot product relationship. Based on this, the connection distance and the direction angle are coupled to construct the strip connection cost. The calculation formula is: ; in, This is the directional influence coefficient, set according to the ratio of equipment turning cost to heading adjustment energy consumption; This is the distance compensation coefficient, set according to the proportion of additional energy consumption during long-distance voyages; The distance scale parameter is determined based on the average spacing between the scanning strips within the work area. After obtaining the connection costs between all feasible scan strips, construct a strip association structure with feasible scan strips as nodes and strip connection costs as edge weights; Based on the strip association structure and strip travel cost and strip connection cost, feasible scanning strips are combined and selected to form a corresponding combination order. The combination order is an ordered arrangement formed as selected strips are added sequentially during the combination selection process. Specifically, the combination selection involves: using the grid coverage of the scanning operation area as a constraint, progressively selecting feasible scanning strips so that the grid cells corresponding to the selected feasible scanning strips can cover the entire scanning operation area; and minimizing the overall cost of the selected feasible scanning strips while ensuring coverage integrity. The overall cost is the sum of the strip travel costs of the selected feasible scanning strips and the sum of the connection costs between adjacent feasible scanning strips. The directional angle between adjacent feasible scanning strips in the combination sequence is constrained and controlled. When the directional angle is greater than a preset angle threshold, the connection between these two feasible scanning strips is prohibited from participating in the combination, thereby obtaining the target scanning strip. The preset angle threshold is set according to the turning capability of the scanning equipment or the maximum allowable turning angle.

[0021] S4: Construct strip scanning paths according to the combination order of target scanning strips, and generate connecting paths between adjacent target scanning strips to obtain the initial scanning path; Furthermore, the stitching to obtain the initial scanning path includes: According to the combination order of the target scanning strips, each target scanning strip is executed in sequence; for each target scanning strip, the center points of each grid cell constituting the strip are connected in sequence according to their spatial position along the extension direction of the strip to form the corresponding strip scanning path; Between adjacent target scanning strips, a connection path is constructed based on the end point of the previous target scanning strip and the start point of the next target scanning strip; The strip scanning path and the connecting path are spliced ​​together to obtain the initial scanning path.

[0022] Specifically, firstly, for each target scanning strip in the target scanning strip set, the spatial coordinate information of each grid cell constituting the strip is extracted, and the grid cells are sorted according to their arrangement order in the strip extension direction; based on the sorted grid cell sequence, the center points of adjacent grid cells are connected in sequence to construct the corresponding strip scanning path, so that a continuous scanning trajectory is formed inside the target scanning strip. Subsequently, for two adjacent target scanning strips in the combination sequence, the termination point of the previous target scanning strip and the starting point of the next target scanning strip are obtained, and the connection path between the strips is generated based on the spatial relationship between the two points, so that the scanning device can continuously transition from the previous strip to the next strip. Finally, the scanning paths corresponding to each target scanning strip and the connection paths between strips are sequentially spliced ​​together in the order of combination to form an initial scanning path covering all target scanning strips.

[0023] S5: Discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. Furthermore, obtaining the global scanning path includes: The initial scanning path is discretized to construct a sequence of track points arranged according to the path travel direction; Path direction vectors are constructed based on adjacent waypoints in the waypoint sequence, and turning nodes are determined based on the angle between adjacent path direction vectors. For the turning node, a transition interval is selected on the path before and after it, and a smooth curve is constructed using the start point, the turning node and the end point of the transition interval as control points. Apply curvature constraints to the smooth curve. When the curvature exceeds the preset upper limit, the smooth curve is reconstructed until the curvature constraints are met. The path within the original transition interval is replaced by a smooth curve that satisfies the curvature constraint to obtain the global scan path.

[0024] Specifically, firstly, the initial scanning path is discretized and represented as a sequence of track points arranged sequentially according to the path's direction of travel. Specifically, the initial scanning path is formed by sequentially splicing together the strip scanning path and the connecting paths between strips. For the strip scanning path, its corresponding track points are the center points of each grid cell constituting the strip, arranged sequentially according to the strip's extension direction. For the connecting paths between strips, their corresponding track points are the points obtained by sampling the connecting path according to a preset sampling step size. The discrete points obtained by equal-interval sampling are arranged sequentially according to the direction of travel of the connecting path; the track point sequences of each strip scanning path are sequentially concatenated with the track point sequences of adjacent connecting paths according to the splicing order of the initial scanning path, thereby forming a unified track point sequence. Based on waypoint sequence For any three consecutive waypoints Processing is performed to construct path direction vectors respectively. and And calculate the angle between the two vectors. When the included angle Greater than the preset steering determination threshold At that time, the point It is determined to be a turning node, where the turning determination threshold is... Based on the maximum permissible turning angle setting of the scanning equipment, the preferred value range is 20°~45°; For each turning node, a path interval of length L is selected on the path before and after it as a transition interval. ;in and These are the preset minimum and maximum transition lengths, respectively. The path discrete sampling step size is determined, preferably 1 to 3 times the sampling step size, to ensure that the transition path segment contains at least a sufficient number of waypoints to achieve path smoothing. The value is determined based on the width of the scanning strip or the spacing between adjacent strips, preferably 0.5 to 1 times the strip spacing, to avoid the transition path segment crossing adjacent strips or affecting the existing scanning path structure; This is the proportionality coefficient. The minimum turning radius of the scanning equipment is defined. Next, a smooth curve is constructed within the transition zone. Specifically, the starting point of the transition zone is determined. and the finish line and starting from Turning nodes and the endpoint As control points, a smooth curve is generated using cubic interpolation to ensure it meets the requirements of... and And in Tangential direction and vector at point Consistency, in Tangential direction and vector at point Consistency is maintained, thus ensuring the first-order continuity of the path at the connection points; To ensure the feasibility of the scanning equipment, curvature constraints are applied to the smooth curve. Specifically, this is based on the minimum turning radius of the scanning equipment. Determine the upper limit of curvature The curvature is calculated point-by-point for discrete points of the smooth curve; when there is a curvature exceeding... In such cases, adjustments should be made according to the following rules: prioritize adjusting the step size according to the preset length. Increase the transition interval length L and regenerate the smooth curve; if the curvature constraint is still not satisfied, adjust the control points along the original path direction. and Perform outward adjustment until the curvature meets the constraint conditions; The path within the original transition interval is replaced by a smooth curve that satisfies the curvature constraint. After replacing the path corresponding to all turning nodes, the global scan path is obtained.

[0025] S6: Based on the real-time location and scanning range of the scanning equipment, determine the coverage status of the grid cell corresponding to the track point and construct the coverage status sequence. Divide the coverage status sequence into continuous intervals and divide the global scanning path into frozen segment, currently executing segment and active segment. Furthermore, the division of the global scanning path into a frozen segment, a currently executing segment, and an active segment includes: Based on the real-time positioning information of the scanning equipment, the current position of the scanning equipment is obtained, and the set of grid cells scanned at the current moment is determined according to the scanning range of the scanning equipment. For the scanned set of grid cells, the coverage status of each grid cell is determined according to the preset coverage integrity determination conditions. The coverage status includes a covered state and an uncovered state. The continuous track points with the same value in the coverage state sequence are divided into continuous intervals, where the continuous intervals corresponding to the covered state are called covered segments, and the continuous intervals corresponding to the uncovered state are called uncovered segments. Based on the spatial distance relationship between the current position of the scanning device and each track point, determine the corresponding index c of the current position in the track point sequence; The continuous intervals are labeled with index c as the dividing point, and the global scanning path is divided, including: merging covered segments with endpoint index less than c into frozen segments, marking the continuous interval containing index c as the currently executed segment, and merging uncovered segments with starting index greater than c into active segments.

[0026] Specifically, firstly, based on the real-time positioning information of the scanning device, the spatial position of the scanning device at the current moment is obtained, and the position is mapped to the corresponding grid cell in the gridded map; at the same time, the set of grid cells scanned at the current moment is determined according to the scanning range of the scanning device. For the scanned set of grid cells, the coverage status of each grid cell is determined according to preset coverage integrity criteria. If the effective scan coverage ratio of the scanning device within a grid cell is not less than a preset coverage ratio threshold, the grid cell is considered covered; otherwise, it is considered uncovered. The effective scan coverage ratio is the ratio of the actual coverage area formed by the scanning trajectory of the scanning device within the grid cell to the area of ​​the grid cell. The preset coverage ratio threshold is set according to the scanning accuracy requirements. Based on this, the grid cells corresponding to each track point are obtained from the track point sequence corresponding to the global scanning path, and the coverage status of the grid cells corresponding to each track point is extracted according to the path travel direction to construct a coverage status sequence. ,in , This indicates that the content has been covered. Indicates an uncovered state; Divide the consecutive track points with the same value in the covered state sequence into consecutive intervals: A continuous range of waypoints is defined as a covered segment. The interval of continuous waypoints is defined as the uncovered segment; Based on the spatial relationship between the current position of the scanning device and the track point sequence, the corresponding index c of the current position in the track point sequence is determined. Specifically, the spatial distance between the current position of the scanning device and each track point is calculated, and the track point with the smallest distance is selected as the corresponding track point of the current position. Its position index in the track point sequence is defined as c. Using index c as the dividing point, the continuous intervals are labeled with their status to achieve stable division of the global scanning path. This includes: merging all continuous intervals with endpoint indices less than c that belong to covered segments and marking them as frozen segments; marking continuous intervals containing index c as currently executed segments; and merging all continuous intervals with starting indexes greater than c that belong to uncovered segments and marking them as active segments.

[0027] S7: Determine the change area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

[0028] Furthermore, the updated global scanning path includes: Obtain the constraint parameter values ​​of each grid cell at the current moment, and compare them with the corresponding constraint parameter values ​​in the path planning stage to determine the changing grid cells; Connectivity analysis is performed based on the adjacency relationship of the changing grid cells, and adjacent changing grid cells are aggregated using a region growing method to obtain the changing region; For each changed region, traverse the grid cells corresponding to each track point in the active segment. When it belongs to the changed region, mark it as an affected track point. Then, according to its index position in the track point sequence, merge the affected track points with consecutive indices into the affected path interval. The affected path intervals are reconstructed, and the reconstructed path intervals are concatenated with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

[0029] Furthermore, the path interval is reconstructed by recalculating the passage cost of the corresponding grid cell set with the starting and ending track points of the affected path interval as boundaries; determining the grid cell sequence that connects the starting and ending track points and has the smallest cumulative passage cost based on the passage cost; and constructing the path interval according to the grid cell sequence to obtain the reconstructed path interval.

[0030] Specifically, during path execution, real-time data of various constraint parameters affecting the survey operation are continuously acquired. The constraint parameter values ​​corresponding to each grid cell at the current moment are compared with the corresponding constraint parameter values ​​used in the path planning stage when calculating the passage cost, and the parameter changes of each grid cell under each constraint are calculated. Specifically, for each grid cell corresponding to each track point in the activity segment, its constraint parameter value at the current moment and the constraint parameter value used by the corresponding grid cell in the passage cost calculation during the path planning stage are acquired, and the difference between the two is calculated as the change. When the change of any grid cell under any constraint exceeds the corresponding preset change threshold, the grid cell is marked as a changed grid cell, where the change threshold is set according to the sensitivity of the corresponding constraint to the passage cost. Connectivity analysis is performed based on the adjacency relationships of changing grid cells in a gridded map. The adjacency relationships between grid cells are determined by the topology of the gridded map: two grid cells are defined as edge adjacency when they share a common edge, and as corner adjacency when they share a common vertex. Changing grid cells that satisfy the adjacency relationship are merged. A region growing approach is used to recursively search for adjacent changing grid cells starting from any given changing grid cell, until no new adjacent changing grid cells exist, thus forming a changing region. For each changed region, obtain the set of grid cells that constitute the changed region, and traverse the grid cells corresponding to each track point in the active segment. When the grid cell corresponding to a track point belongs to the changed region, mark the track point as an affected track point. According to the index position of the affected track point in the track point sequence, merge the affected track points with consecutive indices into the affected path interval. When an affected path interval exists, the starting and ending track points of the affected path interval are used as boundaries to extract the corresponding set of grid cells for that interval. The passage cost of each grid cell in the set is recalculated. Based on the passage cost, a path connecting the starting and ending track points is determined within the set of grid cells. This path is formed by sequentially connecting continuous grid cells, and the cumulative passage cost of each grid cell on the path is minimized. The corresponding path interval is then constructed based on the determined grid cell sequence, resulting in the reconstructed path interval. During the path update process, the frozen segment path remains unchanged. The boundary between the currently executing segment and the active segment is used as the connection boundary. The reconstructed path interval is then concatenated with the path intervals corresponding to the frozen segment and the currently executing segment to obtain the updated global scanning path. The updated global scanning path is used to guide subsequent scanning operations of the scanning equipment.

[0031] Example 2, based on the same inventive concept as the multi-constraint condition survey path planning method for offshore new energy power stations in the aforementioned examples, such as... Figure 2This application provides a survey path planning system for offshore new energy power stations under multiple constraints. The system and method embodiments in this application are based on the same inventive concept. The system includes: The candidate scanning strip generation module is used to construct a gridded map of the scanning operation area and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction. The passage cost calculation module is used to obtain the various constraints affecting the scanning operation, map the passage status of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. The target scan strip acquisition module is used to determine feasible scan strips based on the passage cost of the grid cells corresponding to each candidate scan strip, to select a combination based on the strip association structure, the strip passage cost and the strip connection cost, and to constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip. The initial scan path acquisition module is used to construct the strip scan path according to the combination order of the target scan strips, and generate connecting paths between adjacent target scan strips to obtain the initial scan path; The global scan path acquisition module is used to discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. The status calibration module is used to determine the coverage status of the grid cells corresponding to the track points based on the real-time position and scanning range of the scanning equipment and to construct a coverage status sequence. The coverage status sequence is divided into continuous intervals, and the global scanning path is divided into frozen segments, currently executing segments and active segments. The path interval reconstruction module is used to determine the changed area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and then concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

[0032] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0033] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for survey path planning for offshore new energy power stations under multiple constraints, characterized in that, The method includes the following steps: S1: Construct a gridded map of the scanning operation area, and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction; S2: Obtain the constraints that affect the scanning operation, map the passage state of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. S3: Based on the passage cost of the grid cells corresponding to each candidate scan strip, determine the feasible scan strip, select the strip based on the strip association structure, strip passage cost and strip connection cost, and constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip; S4: Construct strip scanning paths according to the combination order of target scanning strips, and generate connecting paths between adjacent target scanning strips to obtain the initial scanning path; S5: Discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. S6: Based on the real-time location and scanning range of the scanning equipment, determine the coverage status of the grid cell corresponding to the track point and construct the coverage status sequence. Divide the coverage status sequence into continuous intervals and divide the global scanning path into frozen segment, currently executing segment and active segment. S7: Determine the change area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

2. The method as described in claim 1, characterized in that, The process of generating candidate scanning strips composed of continuous grid cells based on a gridded map in a preset direction includes: Obtain the effective scanning width of the scanning equipment, determine the spacing between adjacent strips according to the preset coverage overlap requirements, and determine the grid cell size according to the scanning accuracy requirements; The scanning operation area is divided into regular sections based on the grid cell size, a grid map is constructed, and a corresponding spatial location is assigned to each grid cell. Several strip generation directions are set. For each strip generation direction, consecutive and adjacent grid cells along that direction are connected in sequence to form multiple candidate scanning strips. Assign corresponding directional attributes to each candidate scan strip to obtain a set of candidate scan strips.

3. The method as described in claim 1, characterized in that, The determination of the passage cost of the grid cell and the strip passage cost of the candidate scan strips includes: Obtain various constraints that affect the survey operation, including sea state constraints, obstacle constraints, energy consumption constraints, operation time window constraints, and navigation safety constraints; For each grid cell, obtain the constraint parameter values ​​corresponding to various constraints; and based on the relationship between the constraint parameter values ​​and the preset passable thresholds and prohibited passable thresholds of various constraints, map the passability state to the basic cost component. Based on the basic cost components and constraint coupling relationships, the passage cost of the corresponding mesh cell is determined: When any basic cost component is 1, the access cost of the corresponding grid cell is directly set to the unreachable flag value; When all basic cost components are not equal to 1, the passage cost of the corresponding grid cell is calculated according to the following formula: ； in, For grid cell indexing, For the first The passage cost of each grid cell For constrained indexes, Let be the weight coefficient of the i-th type of constraint. Respectively, the i-th type of constraint and the i-th type of constraint The basic cost component of class constraints; For the first Class constraints and the first Coupling coefficients between class constraints; Based on the travel cost of each grid cell constituting the same candidate scan strip, the strip travel cost of the candidate scan strip is calculated. The calculation formula is: ； in, This represents the number of grid cells contained in the candidate strip. For grid cell indexing, For the first The passage cost of each grid cell This is the risk amplification factor.

4. The method as described in claim 1, characterized in that, The process of obtaining the target scanning strip includes: For each candidate scan strip, a feasibility determination is made based on the passage cost of each grid cell constituting the candidate scan strip. Infeasible scan strips are eliminated, and the remaining candidate scan strips constitute a set of feasible scan strips. For any two feasible scan strips in the set of feasible scan strips, the strip connection cost is constructed based on the connection distance and directional angle between their termination and start points. The calculation formula is as follows: ； in, For feasible scanning strips and The cost of strip connectivity, For feasible scanning strips Termination location and feasible scanning strip The distance between the starting points For feasible scanning strips and The angle between the directions, The directional influence coefficient. This is the distance compensation coefficient. For distance scale parameters; Construct a strip association structure with feasible scan strips as nodes and strip connection costs as edge weights; Based on the strip association structure, strip passage cost, and strip connection cost, feasible scanning strips are combined and selected to form a corresponding combination order; the combination selection is to select feasible scanning strips so that the selected feasible scanning strips cover the entire scanning operation area and minimize the overall cost. The directional angle between adjacent feasible scanning strips in the combination sequence is constrained and controlled. When the directional angle is greater than a preset angle threshold, the corresponding connection relationship is prohibited from participating in the combination, so as to obtain the target scanning strip.

5. The method as described in claim 1, characterized in that, The initial scanning path is obtained by splicing, including: According to the combination order of the target scanning strips, each target scanning strip is executed in sequence; for each target scanning strip, the center points of each grid cell constituting the strip are connected in sequence according to their spatial position along the extension direction of the strip to form the corresponding strip scanning path; Between adjacent target scanning strips, a connection path is constructed based on the end point of the previous target scanning strip and the start point of the next target scanning strip; The strip scanning path and the connecting path are spliced ​​together to obtain the initial scanning path.

6. The method as described in claim 1, characterized in that, The process of obtaining the global scanning path includes: The initial scanning path is discretized to construct a sequence of track points arranged according to the path travel direction; Path direction vectors are constructed based on adjacent waypoints in the waypoint sequence, and turning nodes are determined based on the angle between adjacent path direction vectors. For the turning node, a transition interval is selected on the path before and after it, and a smooth curve is constructed using the start point, the turning node and the end point of the transition interval as control points. Apply curvature constraints to the smooth curve. When the curvature exceeds the preset upper limit, the smooth curve is reconstructed until the curvature constraints are met. The path within the original transition interval is replaced by a smooth curve that satisfies the curvature constraint to obtain the global scan path.

7. The method as described in claim 6, characterized in that, The division of the global scanning path into a frozen segment, a currently executing segment, and an active segment includes: Based on the real-time positioning information of the scanning equipment, the current position of the scanning equipment is obtained, and the set of grid cells scanned at the current moment is determined according to the scanning range of the scanning equipment. For the scanned set of grid cells, the coverage status of each grid cell is determined according to the preset coverage integrity determination conditions. The coverage status includes a covered state and an uncovered state. Based on the track point sequence corresponding to the global scanning path, obtain the grid cell corresponding to each track point, and extract the coverage status of the grid cell corresponding to each track point according to the path travel direction to construct the coverage status sequence. The continuous track points with the same value in the coverage state sequence are divided into continuous intervals, where the continuous intervals corresponding to the covered state are called covered segments, and the continuous intervals corresponding to the uncovered state are called uncovered segments. Based on the spatial distance relationship between the current position of the scanning device and each track point, determine the corresponding index c of the current position in the track point sequence; The continuous intervals are labeled with index c as the dividing point, and the global scanning path is divided, including: merging covered segments with endpoint index less than c into frozen segments, marking the continuous interval containing index c as the currently executed segment, and merging uncovered segments with starting index greater than c into active segments.

8. The method as described in claim 1, characterized in that, The updated global scan path includes: Obtain the constraint parameter values ​​of each grid cell at the current moment, and compare them with the corresponding constraint parameter values ​​in the path planning stage to determine the changing grid cells; Connectivity analysis is performed based on the adjacency relationship of the changing grid cells, and adjacent changing grid cells are aggregated using a region growing method to obtain the changing region; For each changed region, traverse the grid cells corresponding to each track point in the active segment. When it belongs to the changed region, mark it as an affected track point. Then, according to its index position in the track point sequence, merge the affected track points with consecutive indices into the affected path interval. The affected path intervals are reconstructed, and the reconstructed path intervals are concatenated with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

9. The method as described in claim 8, characterized in that, The path interval reconstruction involves recalculating the passage cost of the corresponding grid cell set using the starting and ending track points of the affected path interval as boundaries; determining the grid cell sequence that connects the starting and ending track points and has the minimum cumulative passage cost based on the passage cost; and constructing the path interval based on the grid cell sequence to obtain the reconstructed path interval.

10. A survey path planning system for offshore new energy power stations under multiple constraints, characterized in that, The system is used to implement the multi-constraint offshore new energy station survey path planning method according to any one of claims 1 to 9, and the system includes: The candidate scanning strip generation module is used to construct a gridded map of the scanning operation area and generate candidate scanning strips composed of continuous grid cells based on the gridded map in a preset direction. The passage cost calculation module is used to obtain the various constraints affecting the scanning operation, map the passage status of the grid cell under each constraint to the basic cost component, and determine the passage cost of the grid cell and the strip passage cost of the candidate scanning strip by combining the constraint coupling relationship. The target scan strip acquisition module is used to determine feasible scan strips based on the passage cost of the grid cells corresponding to each candidate scan strip, to select a combination based on the strip association structure, the strip passage cost and the strip connection cost, and to constrain the directional angle between adjacent feasible scan strips to obtain the target scan strip. The initial scan path acquisition module is used to construct the strip scan path according to the combination order of the target scan strips, and generate connecting paths between adjacent target scan strips to obtain the initial scan path; The global scan path acquisition module is used to discretize the initial scan path to obtain a sequence of waypoints, identify turning nodes based on adjacent waypoints, select transition intervals before and after the turning nodes to construct smooth curves, apply curvature constraints to replace the original path, and obtain the global scan path. The status calibration module is used to determine the coverage status of the grid cells corresponding to the track points based on the real-time position and scanning range of the scanning equipment and to construct a coverage status sequence. The coverage status sequence is divided into continuous intervals, and the global scanning path is divided into frozen segments, currently executing segments and active segments. The path interval reconstruction module is used to determine the changed area based on the change of grid cell constraint parameters, identify the affected path intervals in the active segment and reconstruct the path intervals, and then concatenate the reconstructed path intervals with the corresponding path intervals of the frozen segment and the currently executed segment to obtain the updated global scan path.

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