A method and system for dynamic planning of a work path of a towed disturbance platform

Abstract

The application provides a method and system for dynamically planning a working path of a towed disturbance platform, and relates to the technical field of path planning. The method comprises the following steps: acquiring real-time force vector data of a towed cable, including a tension amplitude and a tension direction angle; acquiring a disturbance medium state distribution map of a working area, which represents disturbance effect intensity values corresponding to each position point; using a towed dynamics inverse solution model to generate a reachable position set at the next moment based on the real-time force vector data; performing spatial mapping and gain calculation on the reachable position set and the disturbance medium state distribution map to generate a disturbance effect prediction map; and based on the disturbance effect prediction map, reversely solving an optimal towed direction and a towed speed to generate an optimal towed working path under the condition of satisfying a maximum disturbance effect gain.

Description

Technical Field

[0001] This invention relates to the field of path planning technology, and in particular to a method and system for dynamic path planning of a towed disturbance platform. Background Technology

[0002] Towed disturbance platforms rely on tow cables for traction operations, and their operational efficiency is significantly affected by the real-time stress state of the tow cable and the distribution of the disturbance medium. Existing path planning methods do not incorporate the differences between the real-time stress vector of the tow cable and the spatial distribution of the disturbance medium into the decision-making process. This results in planned paths exceeding the actual movable range of the towed disturbance platform under the current stress conditions, or failing to consider the varying intensity of the disturbance medium's effects, thus failing to maximize the disturbance effect gain and ultimately underperforming the operational efficiency. During operation, the tow cable experiences varying tension, and the magnitude and direction of this tension dynamically constrain the reachable position of the towed disturbance platform. Ignoring these constraints will lead to unreachable commands in path planning. Furthermore, the disturbance intensity varies at different locations within the operational area, and static paths cannot optimize the reachable position and traction parameters based on the distribution to maximize the cumulative disturbance effect. Therefore, there is an urgent need for a path planning method that integrates real-time stress perception and disturbance medium distribution to dynamically optimize the towing direction and speed. Summary of the Invention

[0003] To address the aforementioned problems in the existing technology, the first aspect of this invention proposes a dynamic planning method for the operation path of a towed disturbance platform, comprising: Acquire real-time force vector data of the towed cable of the towed disturbance platform. The real-time force vector data includes the tension amplitude and tension direction angle. Obtain the disturbance medium state distribution map of the work area. The disturbance medium state distribution map represents the disturbance intensity value corresponding to each location point in the work area. Based on real-time force vector data, a set of reachable positions of the towed disturbance platform at the next moment is generated using a pre-defined inverse dynamics model. The set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. Based on the set of reachable locations and the state distribution map of the disturbance medium, spatial mapping and gain calculation are performed to generate a disturbance effect prediction map. The disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. Based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path.

[0004] Secondly, this invention proposes a dynamic planning system for the operation path of a towed disturbance platform. The system employs a dynamic planning method for the operation path of a towed disturbance platform as described in any of the above embodiments. The system includes: The drag force sensing module is used to perform the following steps: acquiring real-time force vector data of the drag cable of the dragged disturbance platform, including the tension amplitude and tension direction angle; The medium state acquisition module is used to perform the following steps: acquire the disturbance medium state distribution map of the work area, which represents the disturbance intensity value corresponding to each location point in the work area; The reachability generation module is used to perform the following steps: Based on real-time force vector data, using a preset inverse dynamics model, generate the set of reachable positions of the towed disturbance platform at the next moment; the set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. The prediction map generation module is used to perform the following steps: based on the set of reachable locations and the state distribution map of the disturbance medium, perform spatial mapping and gain calculation to generate a disturbance effect prediction map; the disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. The optimal path planning module is used to execute the following steps: based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path.

[0005] Compared with the prior art, the beneficial effects of the present invention are as follows: Real-time force vector data of the towing cable of the towed disturbance platform is acquired, including the tension amplitude and tension direction angle, to perceive the motion constraints of the towed cable on the towed disturbance platform. A disturbance medium state distribution map of the work area is obtained, representing the disturbance intensity value at each location point within the work area, providing spatial distribution basis for disturbance effect evaluation. Based on the real-time force vector data, a pre-defined inverse kinematics model of towing dynamics is used to generate a set of reachable positions for the towed disturbance platform in the next moment. This set of reachable positions represents the extreme range of positions the towed disturbance platform can reach under the constraints of the real-time force vector data, thus transforming the time-varying traction constraints into a set of selectable positions and preventing the planning results from exceeding the towing capacity boundary. Based on the set of reachable locations and the state distribution map of the disturbance medium, spatial mapping and gain calculation are performed to generate a disturbance effect prediction map. This map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location within the reachable location set. It quantifies and correlates the reachability domain with the disturbance effect, providing predictive information for path decision-making. Based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and speed of the towed disturbance platform are solved in reverse, generating the optimal towing operation path and achieving optimization of the disturbance effect under real-time force constraints.

[0006] This invention solves the problem that existing methods ignore real-time force constraints and disturbance space differences, resulting in unreachable paths or unmaximized disturbance gains, and improves the operating efficiency and adaptability of towed disturbance platforms under complex working conditions. Attached Figure Description

[0007] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in 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 the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0008] Figure 1 The diagram shown is a flowchart illustrating a dynamic planning method for the operation path of a towed disturbance platform according to an embodiment of the present invention. Figure 2 The diagram shown is a schematic diagram of a dynamic planning system for the operation path of a towed disturbance platform provided in an embodiment of the present invention. Detailed Implementation

[0009] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0010] The specific embodiments of the present invention will be described below.

[0011] Example 1 like Figure 1 As shown, the first aspect of this invention proposes a dynamic planning method for the operation path of a towed disturbance platform, comprising: Acquire real-time force vector data of the towed cable of the towed disturbance platform. The real-time force vector data includes the tension amplitude and tension direction angle. Obtain the disturbance medium state distribution map of the work area. The disturbance medium state distribution map represents the disturbance intensity value corresponding to each location point in the work area. Based on real-time force vector data, a set of reachable positions of the towed disturbance platform at the next moment is generated using a pre-defined inverse dynamics model. The set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. Based on the set of reachable locations and the state distribution map of the disturbance medium, spatial mapping and gain calculation are performed to generate a disturbance effect prediction map. The disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. Based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path.

[0012] During the operation of a towed disturbance platform, the tow cable generates real-time varying tensile amplitude and tensile direction angle under the combined action of traction force and external load. These parameters directly determine the potential location range of the towed disturbance platform at the next moment. Simultaneously, different locations within the operation area exhibit varying disturbance intensity values ​​due to differences in medium distribution. To integrate these two aspects of information into the path decision-making process, this method first acquires real-time force vector data of the tow cable of the towed disturbance platform. This real-time force vector data includes tensile amplitude and tensile direction angle. Acquisition can be achieved by directly measuring with force sensors installed at the towing point. After signal conditioning and filtering, the tensile amplitude and tensile direction angle are extracted through vector decomposition. The real-time force vector data reflects the magnitude and spatial orientation of the instantaneous traction force exerted by the tow cable on the towed disturbance platform.

[0013] The disturbance medium state distribution map characterizes the disturbance intensity value corresponding to each location point within the work area. The disturbance medium state distribution map is generated by collecting the disturbance intensity values ​​at discrete locations using disturbance medium sensing nodes pre-deployed within the work area, followed by spatial interpolation to produce a continuous distribution map covering the entire work area. This distribution map describes the disturbance intensity generated by the towed disturbance platform at any location within the work area using spatial coordinate indexing, providing a quantitative basis for subsequent evaluation of the disturbance contribution of candidate locations to the work area.

[0014] It should be noted that, in this application, the disturbance medium refers to a physical field or material distribution in the work area that can be acted upon by the towed disturbance platform and produce a measurable response, such as a sound field, magnetic field, fluid field, or particulate matter concentration field. The disturbance intensity value is a quantitative indicator of the intensity of the physical field or material distribution at a certain point in space.

[0015] Using a pre-defined inverse kinematics model of towing dynamics, a set of reachable positions for the towed disturbance platform at the next moment is generated. This set represents the limit range of positions the towed disturbance platform can reach under real-time force vector data constraints. The construction of the inverse kinematics model of towing dynamics is based on the mechanical properties of the towing cable: taking the tension amplitude and tension direction angle as inputs, and combining the towing point position and the physical parameters of the towing cable, the morphological parameters of the towing cable under the action of traction force and the tension distribution along the towing cable are calculated. The morphological parameters describe the bending shape and pose of the towing cable in space, and the tension distribution gives the force state at each cross-section of the towing cable. Based on the morphological parameters and the pre-defined motion constraints of the towing point, the movable range of the towing point at the next moment can be determined. The motion constraints of the towing point are defined by the motion capability boundary of the towing drive mechanism. The movable range of the towing point is mapped to the set of reachable positions of the towed disturbance platform according to the morphological parameters of the towing cable. This mapping process transforms the motion space of the towing point into the position space of the towed disturbance platform through the shape transformation of the towing cable, thereby converting the time-varying traction constraints into a set of well-defined position boundaries. The set of reachable locations refers to all locations that the towed disturbance platform can safely and effectively reach under the current real-time force conditions. Any path planning result that exceeds the set of reachable locations cannot be achieved in actual execution. Therefore, the set of reachable locations defines a feasible search space for path decision-making.

[0016] Spatial mapping and gain calculation are performed between the set of reachable locations and the state distribution map of the disturbance medium to generate a disturbance effect prediction map. This map indicates the disturbance effect gain on the work area if the towed disturbance platform moves to each candidate location within the reachable location set. Specifically, the reachable location set is discretized to obtain a set of candidate location points. The discretization density can be selected based on a trade-off between operational accuracy requirements and computational resource constraints. Each candidate location point is mapped to the state distribution map of the disturbance medium, and the disturbance effect intensity value corresponding to that point is extracted. Since the disturbance effect generated by the towed disturbance platform at a candidate location depends not only on the disturbance effect intensity value at that location but also decreases with increasing distance, a preset disturbance attenuation function is introduced. Based on the disturbance effect intensity value and the attenuation function, the disturbance effect gain corresponding to each candidate location point is calculated. The disturbance attenuation function can be established based on the physical propagation characteristics of the disturbance medium, describing the energy loss law during the outward diffusion of the disturbance effect from the disturbance source location. The disturbance effect prediction map is composed of the disturbance effect gain of all candidate location points. The disturbance effect prediction map expresses the geometric constraints of reachable locations and the spatial distribution of disturbance effects in a unified way as predictive information that can be directly called upon for path decision-making, so that the selection of towing direction and towing speed is based on the quantified disturbance gain prediction.

[0017] The disturbance attenuation function describes how the disturbance generated by the platform at a certain location decreases with increasing distance. In this embodiment, the disturbance attenuation function adopts an exponential decay model, and its expression is: G(d) = S×e -βd , where G(d) is the disturbance intensity generated at a distance d from the disturbance source, d is the distance between the candidate location point and the target point in the area to be acted upon, S is the disturbance intensity value at the candidate location point (extracted from the disturbance medium state distribution map), and β is the attenuation coefficient.

[0018] The calibration method for the attenuation coefficient β is as follows: Within the work area, multiple test points are selected. A standard disturbance is applied at a fixed location using a towed disturbance platform, and sensing nodes are deployed at different distances from the disturbance source to measure the change in disturbance intensity. For the collected data pairs of distance d and disturbance intensity G, the least squares method is used to fit an exponential curve, thus determining the optimal estimate of the attenuation coefficient β. For disturbance media with different physical properties, the corresponding attenuation coefficients can be pre-calibrated and stored, and then retrieved based on the actual working medium type during path planning.

[0019] Based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path. Specifically, the process involves constructing an objective function that maximizes the disturbance effect gain of the target area in the disturbance effect prediction map. The target area can be defined within the operation area according to the task requirements, such as a sub-area requiring priority disturbance processing. The objective function can be set as the cumulative disturbance effect gain obtained by each point within the target area during the towed disturbance platform's movement along a candidate towing trajectory. Within the feasible region of the towing direction angle and towing speed, a numerical optimization method is used to search the objective function to determine the optimal towing direction angle and optimal towing speed that maximize the disturbance effect gain. The optimal towing direction angle and optimal towing speed together define the motion command vector at the next moment of the towing point. Based on the optimal towing direction angle and optimal towing speed, the towing trajectory of the towed disturbance platform is generated as the optimal towing operation path. The optimal towing operation path guides the towed disturbance platform to a position that maximizes the disturbance effect gain under real-time force constraints, ensuring that each towing action takes into account both feasibility and effectiveness, thereby achieving a systematic improvement in operation efficiency.

[0020] In some implementations, real-time force vector data of the tow cable of the towed disturbance platform is obtained, including: Acquire the time-domain signal of the tension from the force sensor installed at the towing point; The tensile time-domain signal is low-pass filtered to obtain the filtered signal. Based on the filtered signal, the tensile amplitude and tensile direction angle are obtained by vector decomposition, which serve as real-time force vector data.

[0021] Furthermore, the process of acquiring real-time force vector data of the towing cable of the towed disturbance platform improves the accuracy and reliability of force sensing through progressive processing of signal acquisition, filtering, and vector decomposition. Specifically, the time-domain signal of tension from a force sensor installed at the towing point is acquired. The force sensor can be a strain gauge or piezoelectric sensor, fixedly installed at the connection between the towing cable retraction mechanism and the towing cable, directly sensing the axial tension transmitted by the towing cable. The acquired time-domain tension signal may contain high-frequency noise components caused by mechanical vibration, water flow pulsation, etc. The time-domain tension signal is then low-pass filtered to obtain the filtered signal. Low-pass filtering can be implemented in the analog or digital domain; the cutoff frequency should retain the effective signal frequency band caused by the towing motion while suppressing noise frequency bands. Based on the filtered signal, vector decomposition is used to obtain the tension amplitude and tension direction angle, which serve as real-time force vector data. Vector decomposition, based on the installation coordinate system of the force sensor at the towing point, decomposes the scalar tension value into components along preset coordinate axes, and then synthesizes these components to calculate the tension amplitude and the tension direction angle in space. The real-time force vector data processed in this way can more realistically reflect the transient mechanical state of the towed cable, providing accurate input parameters for subsequent inverse kinematics models of towing dynamics.

[0022] In some implementations, the distribution map of the disturbance medium state in the work area is obtained, including: By deploying disturbance medium sensing nodes in the work area, the intensity value of disturbance effect at the location of each sensing node is collected. Spatial interpolation is performed on the disturbance intensity values ​​of each sensing node to generate a continuous distribution map covering the operation area, which serves as a state distribution map of the disturbance medium.

[0023] During implementation, disturbance intensity values ​​are collected at the locations of disturbance medium sensing nodes deployed within the work area. These sensing nodes can be fixed at typical locations on or within the work area's boundaries, possessing the ability to detect or indirectly measure the disturbance intensity at their respective locations. Due to the limited number of sensing nodes, the collected disturbance intensity values ​​only cover discrete spatial points and cannot directly provide values ​​for arbitrary locations within the work area. Spatial interpolation is performed on the collected disturbance intensity values ​​from each sensing node to generate a continuous distribution map covering the work area, serving as a disturbance medium state distribution map. Spatial interpolation can employ methods such as Kriging interpolation and inverse distance weighted interpolation, estimating the disturbance intensity values ​​at unknown locations based on known discrete point data. The interpolation results constitute a spatially continuous function or grid data.

[0024] The continuous representation of the state distribution map of the perturbation medium enables the direct extraction of the corresponding perturbation intensity value based on the spatial coordinates of the candidate location points in subsequent processing, thereby improving the accuracy and consistency of the perturbation effect gain calculation.

[0025] In some implementations, based on real-time force vector data, a set of reachable positions of the towed disturbance platform at the next moment is generated using a pre-defined inverse kinematics model of towing dynamics, including: Based on the tensile force amplitude and tensile force direction angle, calculate the morphological parameters of the towed cable; Based on morphological parameters and preset drag point motion constraints, the movable range of the drag point in the next moment is determined. The movable range of the towing point is mapped to the set of reachable locations of the towing disturbance platform based on the shape parameters of the towing cable.

[0026] Based on real-time force vector data, and utilizing a pre-defined inverse kinematics model of towing dynamics, the real-time force constraints are transformed into explicit reachable boundary conditions through stepwise derivation of tension calculation, towing point mobility range determination, and position space mapping. The specific process includes: calculating the tension distribution and morphological parameters of the towing cable based on the tension amplitude and tension direction angle; inputting the tension amplitude and tension direction angle into the catenary equation to obtain the suspension shape of the towing cable and the tension distribution along the cable; the catenary equation describes the equilibrium state of the flexible cable under its own weight and end tension, and the solution process yields the coordinate positions of each point on the towing cable and the tension values ​​at each cross-section along the cable length; determining the reachable range of the towing point at the next moment based on the morphological parameters and pre-defined towing point motion constraints; the towing point motion constraints include the maximum displacement of the towing point achievable by the towing drive mechanism within a unit time step and the allowable range of motion directions; and mapping the reachable range of the towing point to the reachable set of the towing disturbance platform according to the morphological parameters of the towing cable. The mapping process takes the location of the dragging point as input, transforms the shape parameters of the dragging cable, and outputs the corresponding coordinates of the dragging disturbance platform. The union of all mapping results constitutes the set of reachable locations.

[0027] In this embodiment, the inverse kinematics model for towing is constructed based on the catenary equation. The catenary equation describes the equilibrium state of the towing cable under its own weight and end tension, and its expression is: Where a = H / w, H is the horizontal tension on the drag cable, w is the weight per unit length of the drag cable, y is the vertical coordinate of a point on the drag cable, x is the horizontal coordinate of a point on the drag cable, a is the catenary parameter that determines the degree of bending of the cable, x0 is the horizontal coordinate of the lowest point (vertex) of the catenary, c is the vertical coordinate of the lowest point (vertex) of the catenary, and cosh is the hyperbolic cosine function.

[0028] The specific inverse solution process is as follows: Step S31: Substitute the obtained tension amplitude F and tension direction angle θ as boundary conditions into the catenary equation. The horizontal component H and vertical component V of the tension amplitude F satisfy H = F×cosθ and V = F×sinθ, respectively. Solve the catenary equation and its derivative equation simultaneously, and numerically solve using the Newton-Raphson iteration method to obtain the suspension morphology parameters of the towed cable. The morphology parameters include the coordinates of each point on the cable and the cable tension distribution.

[0029] Step S32: Obtain the preset towing point motion constraints, which include the maximum displacement ΔL of the towing drive mechanism within a unit time step. max and the permissible steering angle range [-α] max α max ].

[0030] Step S33: Based on the cable morphology parameters obtained in step S31, establish the coordinates of the dragging point (x... t y t ) and the coordinates of the towed disturbance platform (x p y p The coordinate transformation relationship between the two is constrained by the cable length. (L is the total length of the cable) and the cable suspension shape determined in step S31 are jointly determined.

[0031] Step S34: The movable range of the towing point determined in step S32 at the next moment is mapped to the set of reachable positions of the towing disturbance platform through the coordinate transformation relationship established in step S33.

[0032] The set of reachable locations obtained through the above steps is constrained by the mechanical behavior of the towed cable under real-time stress conditions, ensuring that the path planning results match the actual capabilities of the towed system.

[0033] In some implementations, spatial mapping and gain calculation are performed based on the set of reachable locations and the state distribution map of the disturbing medium to generate a predicted disturbance effect map, including: Discretization can reach a set of locations, resulting in a group of candidate location points; Each candidate location point is mapped to the state distribution map of the disturbed medium, and the disturbance intensity value corresponding to the candidate location point is extracted. Based on the perturbation intensity value and the preset perturbation attenuation function, the perturbation effect gain corresponding to each candidate location point is calculated, and the perturbation effect gain of all candidate location points constitutes the perturbation effect prediction map.

[0034] By discretizing the set of reachable locations and calculating the disturbance effect gain point by point, the evaluation of the disturbance effect on the work area is upgraded from a qualitative judgment of location space to a quantitative prediction of the gain value, providing a data foundation for constructing the objective function for the reverse solution of the optimal path.

[0035] The specific implementation process is as follows: The set of reachable locations is discretized to obtain a set of candidate location points. Discretization can be performed using uniform grid division or random sampling, and the number of candidate location points is determined based on the map accuracy and real-time computation requirements. Each candidate location point is mapped to the perturbation medium state distribution map, and the perturbation intensity value corresponding to the candidate location point is extracted. This mapping is completed through spatial coordinate matching; if the coordinates of a candidate location point fall within a grid cell of the perturbation medium state distribution map, the perturbation intensity value stored in that grid cell is extracted. Based on the perturbation intensity value and a preset perturbation attenuation function, the perturbation effect gain corresponding to each candidate location point is calculated. The form of the perturbation attenuation function is pre-calibrated according to the physical mechanism of perturbation medium propagation, such as an exponential attenuation function or a power-law attenuation function, with the distance between the candidate location point and the target location as the independent variable. The perturbation effect prediction map is composed of the perturbation effect gain of all candidate locations. The perturbation effect prediction map fully describes the spatial distribution of the perturbation effect gain that the towed perturbation platform can achieve when reaching different candidate locations within the range of the current reachable location set. Thus, the guidance of the towed target in path planning is based on quantifiable gain distribution information.

[0036] In some implementations, based on the disturbance effect prediction map and assuming the disturbance effect gain is maximized, the optimal towing direction and speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path, including: Construct an objective function that aims to maximize the perturbation effect gain of the region to be affected in the perturbation effect prediction map; Within the feasible region of the drag direction angle and drag speed, the objective function is optimized to determine the optimal drag direction angle and optimal drag speed. Based on the optimal towing direction angle and optimal towing speed, the towing trajectory of the towing disturbance platform is generated as the optimal towing operation path.

[0037] Based on the disturbance effect prediction map, and assuming the disturbance effect gain is maximized, the optimal towing direction and speed of the towed disturbance platform are solved in reverse, generating the optimal towing operation path. Through objective function construction, feasible region optimization, and trajectory generation, the disturbance gain prediction is transformed into executable optimal motion commands, maximizing both feasibility and efficiency of the traction action. After generating the disturbance effect prediction map, it already contains the disturbance effect gain value corresponding to each candidate location point within the reachable location set. To determine the optimal motion control parameters, an objective function is first constructed with the goal of maximizing the disturbance effect gain of the region to be affected in the disturbance effect prediction map. The area to be affected is pre-defined within the work area according to the requirements of the task. The objective function is constructed as follows: For a given set of towing direction angles and towing speeds, the arrival position of the towed disturbance platform at the next moment is determined. The disturbance effect gain corresponding to that position is retrieved from the disturbance effect prediction map, and the cumulative amount of disturbance effect gain of the area to be affected at the positions traversed during the movement between the current position and the arrival position is included. The above cumulative amount or the instantaneous gain at the arrival moment is used as the evaluation index of the objective function. The form of the objective function establishes a mapping relationship between the spatially distributed disturbance effect gain and the motion control parameters.

[0038] Within the feasible region of the towing direction angle and towing speed, an optimization search is performed on the objective function to determine the optimal towing direction angle and optimal towing speed. The feasible region of the towing direction angle is jointly limited by the steering capability boundary of the towing drive mechanism and the lateral constraints of the towing cable under stress. The feasible region of the towing speed is jointly limited by the speed adjustment range of the towing drive mechanism and the tension safety margin of the towing cable. The optimization search can adopt gradient search, iteratively calculating the objective function values ​​corresponding to different combinations of towing direction angles and towing speeds within the feasible region, and selecting the parameter combination that maximizes the disturbance effect gain as the optimal solution. Based on the optimal towing direction angle and optimal towing speed, the towing trajectory of the towing disturbance platform is generated as the optimal towing operation path. The towing trajectory is the spatial path generated by the movement of the towing point according to the optimal towing direction angle and optimal towing speed within a unit time step. This path, mapped onto the towing disturbance platform, is the operation path.

[0039] The optimal towing operation path generated through the above process is obtained by solving under real-time force constraints with the direction of maximizing the disturbance effect gain as the guide, effectively avoiding the problem of mismatch between the planning results and the actual executable range.

[0040] In some implementations, the morphological parameters of the towed cable are calculated, including: Input the tensile force amplitude and tensile force direction angle into the catenary equation, and solve to obtain the morphological parameters of the towed cable.

[0041] In practice, the tension amplitude and tension direction angle are input as boundary conditions into the catenary equation. The catenary equation describes the equilibrium state of a flexible cable with uniform weight per unit length under tension at both ends and gravity. Solving the catenary equation yields the coordinate positions of each point on the towed cable in space, i.e., the suspension shape, and the tension values ​​along the tangential direction at each cross-section of the towed cable, i.e., the tension distribution along the towed cable. The tension amplitude and tension direction angle at the tow point determine the catenary's angle and span, while the physical parameters of the towed cable, including the cable's weight per unit length and bending stiffness, determine the catenary's curvature characteristics. The joint solution results of the suspension shape and tension distribution constitute the morphological parameters of the towed cable. These morphological parameters provide a definite geometric transformation relationship for the subsequent mapping process from the movable range of the tow point to the set of reachable positions of the towed disturbance platform. When the towing point moves to a new position, the towing cable forms a new suspension shape under the new boundary tension conditions. The new position of the towing point is correspondingly converted into the position of the towing disturbance platform by the cable shape and pose described by the morphological parameters. The position conversion results within the movable range of all towing points constitute the set of reachable positions.

[0042] Therefore, the tension and shape solutions obtained using the catenary equation serve as a link between the motion of the drag point and the motion of the platform, ensuring the mechanical self-consistency of the reachable position set.

[0043] In some implementations, the method also includes: During the execution of the optimal towing operation path, feedback data on the actual disturbance effect in the operation area is obtained; If the deviation between the actual disturbance effect and the corresponding disturbance effect gain in the disturbance effect prediction map exceeds the preset range, the disturbance medium state distribution map is updated based on the actual disturbance effect feedback data, and the process returns to execute the set of reachable positions of the towed disturbance platform at the next moment, based on the real-time force vector data and using the preset drag dynamics inverse solution model.

[0044] During the execution of the optimal towing operation path, the state of the disturbance medium in the work area may change due to environmental changes or the cumulative effects of previous disturbance operations, leading to a deviation between the actual disturbance effect and the disturbance effect gain predicted during the planning stage. To address this issue, this method continuously introduces actual disturbance effect feedback during the execution of the optimal towing operation path, dynamically updates the disturbance medium state distribution map, and triggers a replanning closed loop to re-plan the reachable location set to the optimal path. This ensures that the path planning continuously adapts to real-time changes in the disturbance medium state, maintaining the maximization of disturbance effect gain. Specifically, the implementation process involves acquiring actual disturbance effect feedback data of the work area during the execution of the optimal towing operation path. This data can be collected through disturbance effect monitoring nodes deployed within the work area. These nodes measure the actual change in disturbance intensity or disturbance effect characterization parameters obtained during the operation of the towing disturbance platform at their respective locations. The collected actual disturbance effect feedback data is compared with the disturbance effect gain at the corresponding location and time in the disturbance effect prediction map to calculate the deviation. If the deviation between the actual disturbance effect and the corresponding disturbance effect gain in the disturbance effect prediction map exceeds a preset range, it indicates that the disturbance medium state distribution map can no longer accurately reflect the true disturbance medium state of the current working area. In this case, the disturbance medium state distribution map is updated based on the actual disturbance effect feedback data. The update method is as follows: the disturbance effect intensity value of the corresponding area or the entire disturbance medium state distribution map is corrected using the actual disturbance effect feedback data. This correction can be achieved using data assimilation or recursive update methods, so that the updated disturbance medium state distribution map approximates the true state again. After the update is completed, the process returns to the step of generating the set of reachable positions of the towed disturbance platform at the next moment based on real-time force vector data and a preset towing dynamics inverse model. Subsequently, the generation of the disturbance effect prediction map and the optimal towing operation path are executed sequentially.

[0045] This method enables path planning to promptly correct the prediction model and re-solve the optimal towing parameters when the state of the disturbing medium undergoes unexpected changes. This avoids a decrease in the disturbance effect due to model mismatch and improves the adaptability and operational robustness of the towed disturbance platform in non-stationary operating environments.

[0046] Example 2 like Figure 2 As shown, in a second aspect, the present invention proposes a dynamic planning system for the operation path of a towed disturbance platform. The system employs a dynamic planning method for the operation path of a towed disturbance platform as proposed in any of the above embodiments. The system includes: The drag force sensing module is used to perform the following steps: acquiring real-time force vector data of the drag cable of the dragged disturbance platform, including the tension amplitude and tension direction angle; The medium state acquisition module is used to perform the following steps: acquire the disturbance medium state distribution map of the work area, which represents the disturbance intensity value corresponding to each location point in the work area; The reachability generation module is used to perform the following steps: Based on real-time force vector data, using a preset inverse dynamics model, generate the set of reachable positions of the towed disturbance platform at the next moment; the set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. The prediction map generation module is used to perform the following steps: based on the set of reachable locations and the state distribution map of the disturbance medium, perform spatial mapping and gain calculation to generate a disturbance effect prediction map; the disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. The optimal path planning module is used to execute the following steps: based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic planning method for the operation path of a towed disturbance platform, characterized in that, include: Acquire real-time force vector data of the towed cable of the towed disturbance platform. The real-time force vector data includes the tension amplitude and tension direction angle. Obtain the disturbance medium state distribution map of the work area. The disturbance medium state distribution map represents the disturbance intensity value corresponding to each location point in the work area. Based on real-time force vector data, a set of reachable positions of the towed disturbance platform at the next moment is generated using a pre-defined inverse dynamics model. The set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. Based on the set of reachable locations and the state distribution map of the disturbance medium, spatial mapping and gain calculation are performed to generate a disturbance effect prediction map. The disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. Based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path. Based on real-time force vector data, and using a pre-defined inverse kinematics model of towing dynamics, a set of reachable positions of the towed disturbance platform at the next moment is generated, including: Based on the tensile force amplitude and tensile force direction angle, calculate the morphological parameters of the towed cable; Based on morphological parameters and preset drag point motion constraints, the movable range of the drag point in the next moment is determined. The movable range of the towing point is mapped to the set of reachable locations of the towing disturbance platform based on the shape parameters of the towing cable.

2. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, Obtain real-time force vector data of the tow cable of the towed disturbance platform, including: Acquire the time-domain signal of the tension from the force sensor installed at the towing point; The time-domain signal of tension is low-pass filtered to obtain the filtered signal. Based on the filtered signal, the tensile amplitude and tensile direction angle are obtained by vector decomposition, which serve as real-time force vector data.

3. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, Obtain a distribution map of the disturbance medium state in the work area, including: By deploying disturbance medium sensing nodes in the work area, the intensity value of disturbance effect at the location of each sensing node is collected. Spatial interpolation is performed on the disturbance intensity values ​​of each sensing node to generate a continuous distribution map covering the operation area, which serves as a state distribution map of the disturbance medium.

4. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, Based on the set of reachable locations and the state distribution map of the disturbing medium, spatial mapping and gain calculation are performed to generate a predicted disturbance effect map, including: Discretization can reach a set of locations, resulting in a group of candidate location points; Each candidate location point is mapped to the state distribution map of the disturbed medium, and the disturbance intensity value corresponding to the candidate location point is extracted. Based on the perturbation intensity value and the preset perturbation attenuation function, the perturbation effect gain corresponding to each candidate location point is calculated, and the perturbation effect gain of all candidate location points constitutes the perturbation effect prediction map.

5. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, Based on the disturbance effect prediction map, and assuming the disturbance effect gain is maximized, the optimal towing direction and speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path, including: Construct an objective function that aims to maximize the perturbation effect gain of the region to be affected in the perturbation effect prediction map; Within the feasible region of the drag direction angle and drag speed, the objective function is optimized to determine the optimal drag direction angle and optimal drag speed. Based on the optimal towing direction angle and optimal towing speed, the towing trajectory of the towing disturbance platform is generated as the optimal towing operation path.

6. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, Calculate the morphological parameters of the towed cable, including: Input the tensile force amplitude and tensile force direction angle into the catenary equation, and solve to obtain the morphological parameters of the towed cable.

7. The method for dynamic planning of the operation path of a towed disturbance platform according to claim 1, characterized in that, The method also includes: During the execution of the optimal towing operation path, feedback data on the actual disturbance effect in the operation area is obtained; If the deviation between the actual disturbance effect and the corresponding disturbance effect gain in the disturbance effect prediction map exceeds the preset range, the disturbance medium state distribution map is updated based on the actual disturbance effect feedback data, and the process returns to execute the set of reachable positions of the towed disturbance platform at the next moment, based on the real-time force vector data and using the preset drag dynamics inverse solution model.

8. A dynamic planning system for the operation path of a towed disturbance platform, characterized in that, The system employs a dynamic path planning method for a towed disturbance platform as described in any one of claims 1 to 7, and the system comprises: The drag force sensing module is used to perform the following steps: acquiring real-time force vector data of the drag cable of the dragged disturbance platform, including the tension amplitude and tension direction angle; The medium state acquisition module is used to perform the following steps: acquire the disturbance medium state distribution map of the work area, which represents the disturbance intensity value corresponding to each location point in the work area; The reachability generation module is used to perform the following steps: Based on real-time force vector data, using a preset inverse dynamics model, generate the set of reachable positions of the towed disturbance platform at the next moment; the set of reachable positions represents the range of extreme positions that the towed disturbance platform can reach under the constraints of real-time force vector data. The prediction map generation module is used to perform the following steps: based on the set of reachable locations and the state distribution map of the disturbance medium, perform spatial mapping and gain calculation to generate a disturbance effect prediction map; the disturbance effect prediction map describes the disturbance effect gain on the work area when the towed disturbance platform moves to each candidate location in the set of reachable locations. The optimal path planning module is used to execute the following steps: based on the disturbance effect prediction map, and with the condition of maximizing the disturbance effect gain, the optimal towing direction and towing speed of the towed disturbance platform are solved in reverse to generate the optimal towing operation path.

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