A method for optimizing trajectory of Spartina alterniflora light-weight operation equipment for inland narrow habitat

Abstract

The application provides a Spartina alterniflora light operation equipment trajectory optimization method for an inland narrow habitat, and relates to the technical field of trajectory optimization. The method comprises the following steps: obtaining habitat three-dimensional terrain data, bank slope rock-soil mechanics parameters, image data, equipment characteristic parameters and water dynamic disturbance threshold; extracting a water-land boundary line and constructing a discrete source patch topology graph containing multiple patch nodes; calculating a bank slope anti-sliding stability coefficient, and constructing a safe operation space model limiting the driving boundary of operation equipment; generating a global reference path sequentially connecting the patch nodes in the safe operation space model; constructing a multi-objective cost functional containing a water body disturbance penalty term, and solving to generate an optimal operation trajectory. The application takes into account the bank slope mechanics safety and water body low disturbance constraint of the narrow habitat, and realizes full coverage removal of complex discrete sources.

Description

Technical Field

[0001] This invention relates to the field of trajectory optimization technology, and in particular to a trajectory optimization method for lightweight operation equipment of Spartina alterniflora in narrow inland river habitats. Background Technology

[0002] The invasive alien plant *Spartina alterniflora* has rapidly expanded in coastal wetlands and along inland rivers in my country. This large-scale spread has severely damaged the habitats of native benthic organisms. Mechanized physical removal methods are characterized by their rapid effectiveness and lack of chemical residues. Currently, the industry mainly employs methods such as mowing, tilling, and rotary tillage. For large areas of open tidal flats, existing technologies have developed relatively mature large-scale mechanized combined operation models. Existing mechanized operation equipment and path planning methods are mostly developed for flat and open tidal flat terrain. The application of these methods presupposes uniform sediment bearing capacity.

[0003] The current management of Spartina alterniflora is gradually extending to narrow inland waterway habitats such as aquaculture exchange channels within dikes, tidal inland waterways, and abandoned aquaculture ponds. These habitats are characterized by limited spatial scale, steep bank slopes, high sediment moisture content, and variable hydrological conditions. Traditional heavy wheeled or tracked equipment cannot operate normally in these scenarios. Developing amphibious lightweight operational equipment with chassis self-adaptive capabilities has become an important development direction for the industry. Relying on environmental perception technology to achieve intelligent and unmanned trajectory optimization decision-making can improve the operational accuracy in complex and discrete habitats.

[0004] However, existing trajectory planning algorithms for agricultural machinery or unmanned vessels are mostly designed based on geometric obstacle avoidance and coverage calculations in a two-dimensional plane. Existing algorithms do not incorporate the three-dimensional geotechnical constraints and hydrodynamic safety constraints unique to narrow waterways into the system modeling.

[0005] First, existing trajectory planning does not consider the bearing capacity of the slope's soil and rock. When equipment operates close to narrow slopes, it is very easy to trigger the critical threshold for slope instability, which can lead to the collapse of the embankment.

[0006] Secondly, existing path generation methods lack a water disturbance dynamics penalty mechanism. High-frequency turning and sudden velocity changes during operation can easily trigger violent churning of bottom sediment, resulting in secondary ecological pollution of the water body.

[0007] Finally, existing full-coverage algorithms cannot adapt to discrete patch habitats formed by micro-topographical undulations. Due to the lack of adaptive planning capabilities based on the spatial topological relationships of seed sources, the removal of residual seed sources is incomplete, ultimately leading to the risk of secondary invasion in the treated areas. Summary of the Invention

[0008] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a trajectory optimization method for lightweight operation equipment for Spartina alterniflora in narrow inland river habitats. This invention solves the technical problems in the prior art that cannot simultaneously take into account the mechanical safety of narrow habitat banks, the constraint of low water disturbance, and the full coverage removal of discrete patches.

[0009] To achieve the above objectives, the present invention provides the following solution: A method for optimizing the trajectory of lightweight operational equipment for Spartina alterniflora in narrow inland river habitats includes: Acquire three-dimensional topographic data of the target narrow habitat, slope geomechanical parameters, Spartina alterniflora distribution image data, and equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operating equipment used for control operations; Based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, the water-land boundary line is extracted, and a discrete seed source patch topology map representing the spatial topological relationship of Spartina alterniflora is constructed, wherein the discrete seed source patch topology map contains multiple patch nodes. Based on the aforementioned slope geomechanical parameters and the water-land boundary line, the anti-sliding stability coefficient reflecting the slope's stability state is calculated. Based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold, a safe operating space model is constructed to define the driving boundary of the lightweight operating equipment. Within the safe operating space model, a global reference path is constructed by using the multiple patch nodes as traversal nodes, sequentially connecting the multiple patch nodes and satisfying the equipment characteristic parameters. Based on the global reference path, a multi-objective cost functional including a water disturbance penalty term is constructed in conjunction with the safe operation space model, and the multi-objective cost functional is solved to generate the optimal operation trajectory.

[0010] A trajectory optimization system for lightweight operational equipment of Spartina alterniflora targeting narrow inland river habitats includes: The multi-source data acquisition module is used to acquire three-dimensional topographic data of the target narrow habitat, slope rock and soil mechanical parameters, Spartina alterniflora distribution image data, as well as equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operation equipment for control operations. The feature extraction and topology construction module is used to extract the land-water boundary line based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, and construct a discrete seed source patch topology map that represents the spatial topological relationship of Spartina alterniflora, wherein the discrete seed source patch topology map contains multiple patch nodes; The bank slope stability calculation module is used to calculate the anti-sliding stability coefficient, which reflects the stability state of the bank slope, based on the bank slope geotechnical parameters and the water-land boundary line. The safe operating space modeling module is used to construct a safe operating space model that defines the driving boundary of the lightweight operating equipment based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold. The global reference path generation module is used to construct a global reference path within the safe operation space model, using the multiple patch nodes as traversal nodes, that sequentially connects the multiple patch nodes and satisfies the device characteristic parameters. The optimal operation trajectory solution module is used to construct a multi-objective cost functional including a water disturbance penalty term based on the global reference path and the safe operation space model, and to solve the multi-objective cost functional to generate the optimal operation trajectory.

[0011] The present invention discloses the following technical effects: This invention provides a trajectory optimization method for lightweight equipment used in the treatment of Spartina alterniflora in narrow inland river habitats. By integrating the unique geomechanical parameters of the riverbanks in narrow waterways with the equipment's characteristic parameters, this invention constructs a safe operating space model. This fundamentally overcomes the technical shortcomings of existing technologies, which are prone to causing embankment collapse due to the lack of consideration for the bank's bearing capacity, thus ensuring the mechanical safety of lightweight equipment operating close to narrow riverbanks. Furthermore, this method utilizes a discrete seed source patch topology map representing the spatial topological relationships of Spartina alterniflora to generate a global reference path. It also introduces a multi-objective cost functional including a water disturbance penalty term to jointly solve the operating trajectory. This not only achieves precise and comprehensive removal of complex discrete residual seed sources under micro-topographical undulations, effectively solving the problem of Spartina alterniflora "seed bank" resurgence within the embankment, but also strictly constrains the sediment uplift amplitude through optimal control at the dynamic level, significantly reducing secondary ecological disturbance to the water body caused during the operation. Ultimately, this method comprehensively achieves high safety, low disturbance, and precise treatment effects in the treatment of narrow inland river habitats. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the 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 1 A flowchart illustrating a method for optimizing the trajectory of lightweight equipment for Spartina alterniflora in narrow inland river habitats, as provided in this embodiment of the invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] like Figure 1 As shown, this invention provides a method for optimizing the trajectory of lightweight operational equipment for Spartina alterniflora in narrow inland river habitats, comprising: Step 100: Acquire three-dimensional topographic data of the target narrow habitat, slope rock and soil mechanical parameters, Spartina alterniflora distribution image data, and equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operating equipment used for control operations. Step 200: Based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, extract the land-water boundary line and construct a discrete seed source patch topology map that characterizes the spatial topological relationship of Spartina alterniflora, wherein the discrete seed source patch topology map contains multiple patch nodes; Step 300: Based on the slope geomechanical parameters and the land-water boundary line, calculate the anti-sliding stability coefficient that reflects the slope's stability state; Step 400: Based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold, construct a safe operating space model that defines the travel boundary of the lightweight operating equipment; Step 500: Within the safe operating space model, using the multiple patch nodes as traversal nodes, construct a global reference path that sequentially connects the multiple patch nodes and satisfies the equipment characteristic parameters; Step 600: Based on the global reference path, construct a multi-objective cost functional including a water disturbance penalty term in conjunction with the safe operation space model, and solve the multi-objective cost functional to generate the optimal operation trajectory.

[0017] Furthermore, the specific implementation process of steps 100-200 is as follows: This embodiment executes step 100 to comprehensively acquire three-dimensional topographic data, bank slope geotechnical parameters, Spartina alterniflora distribution image data, and equipment characteristic parameters and hydrodynamic disturbance safety thresholds of the target narrow habitat. Specifically, the three-dimensional topographic data and Spartina alterniflora distribution image data are obtained by orthorectifying and inverting point clouds of the target water area using a low-altitude mapping UAV equipped with an airborne lidar and multispectral camera. The bank slope geotechnical parameters are obtained by matching the spatial coordinates of the target water area using a historical database of coastal geological exploration. The equipment characteristic parameters define the mechanical performance boundaries of the underlying physical actuator, fully encompassing the total weight, track contact area, minimum turning radius, and maximum climbing angle of the lightweight equipment. In this embodiment, the total weight is limited to 1500 kg, the track contact area to 1.2 square meters, the minimum turning radius to 2.5 meters, and the maximum climbing angle to 30 degrees. The hydrodynamic disturbance safety threshold is used to constrain the extreme critical point of secondary pollution of the water body ecosystem. It fully includes the maximum allowable suspended sediment concentration and the maximum allowable wading depth. In this embodiment, the maximum allowable suspended sediment concentration is limited to 50 mg / L, and the maximum allowable wading depth is 0.8 m. The slope geotechnical parameters characterize the three-dimensional bearing and shear resistance of the target strata, covering sediment cohesion, sediment internal friction angle, and sediment natural unit weight. In this embodiment, the sediment cohesion is taken as 15 kPa, the sediment internal friction angle is taken as 12 degrees, and the sediment natural unit weight is taken as 18 kN / m³.

[0018] In this embodiment, step 200, the pre-fusion and boundary extraction stage for constructing the topology map, employs a scale-invariant feature transformation algorithm to extract common corner points from the grayscale projection map corresponding to the 3D terrain data and the Spartina alterniflora distribution image data as corresponding ground feature points. Based on these corresponding ground feature points, spatial rigid body transformation registration is performed to generate fused image data containing vertical elevation coordinate information and horizontal spatial coordinate information. The fused image data refers to a 3D data matrix with absolute elevation dimension indented into a multispectral pixel array, which functions to give the 2D image accurate 3D spatial positioning capability. Based on the fused image data, this embodiment calculates the elevation change slope of all pixels by performing spatial differentiation on the 3D coordinate matrix, and extracts the elevation gradient abrupt change line in the target narrow habitat. The elevation gradient abrupt change line refers to a continuous physical edge with an elevation drop slope exceeding 35 percentage points. This physical edge directly reflects the location of the waterfall where the riverbed and bank meet. In this embodiment, the extracted elevation gradient abrupt change line is directly defined as the land-water boundary line, serving as a rigid constraint isolation zone that prohibits subsequent equipment from crossing the boundary.

[0019] After establishing the land-water boundary, this embodiment uses a multispectral vegetation index threshold segmentation method to extract the initial distribution area of ​​Spartina alterniflora from the fused image data. This process extracts the near-infrared and red reflectance from the fused image data, calculates the normalized difference between them to obtain a vegetation index. When the vegetation index is greater than 0.45, the corresponding pixel area is determined to be covered by Spartina alterniflora, thus obtaining the initial distribution area of ​​Spartina alterniflora. To eliminate the mesh fragmentation problem caused by low-level image noise, this embodiment removes isolated noise points with an actual physical area of ​​less than 5 square meters in the initial distribution area of ​​Spartina alterniflora, and uses morphological closing operations with a structuring element size of 3 pixels to fill internal holes and smooth physical edges, obtaining multiple independent patches. Subsequently, this embodiment calculates the weighted average of the spatial coordinates of all pixels within the contour of each independent patch, extracts the geometric centroid of each independent patch, and obtains the multiple patch nodes. These nodes represent the removal center location that subsequent equipment must reach.

[0020] This embodiment combines the land-water boundary line and the three-dimensional terrain data to calculate the obstacle avoidance geodesic distance between any two of the plurality of patch nodes, and establishes a distance attenuation matrix based on this distance. The obstacle avoidance geodesic distance refers to the shortest three-dimensional spatial ground-crawling path length that absolutely does not cross the land-water boundary line while adhering to the surface of the three-dimensional terrain data. This embodiment first converts the three-dimensional terrain data into a triangular mesh surface containing elevation undulations, and then uses a fast travel algorithm to expand outward on the triangular mesh surface with each of the plurality of patch nodes as the starting wavefront, avoiding the blocking mesh where the land-water boundary line is located, and calculates the obstacle avoidance geodesic distance between each pair of nodes. This embodiment traverses all of the plurality of patch nodes and generates the distance attenuation matrix based on the reciprocal of the calculated obstacle avoidance geodesic distance. This embodiment sets that when the obstacle avoidance geodesic distance exceeds 200 meters, the corresponding matrix element is forcibly reset to zero to cut off excessively long and inefficient operation transfer routes.

[0021] This embodiment, based on the distance attenuation matrix, introduces a preset propagation resistance coefficient for weighted calculation to generate a spatial connectivity matrix. The propagation resistance coefficient is a weighting factor characterizing the resistance attenuation when the equipment overcomes different sediment moisture contents during transfer. In this embodiment, the natural density of the sediment and the total weight of the machine are divided by the actual ground pressure generated by the track ground contact area, and the quotient is mapped to the propagation resistance coefficient. For the current high-moisture-content soft mud terrain, the propagation resistance coefficient is set to 1.5. This embodiment divides each element in the distance attenuation matrix by the propagation resistance coefficient to complete the weighted mapping, ultimately obtaining the spatial connectivity matrix characterizing the physical difficulty of actual operational transfer. Based on the spatial connectivity matrix, this embodiment establishes operational travel edges by bidirectionally connecting node pairs with connectivity values ​​greater than 0.6, thereby connecting the multiple patch nodes and finally constructing a discrete seed source patch topology map characterizing the spatial topological relationships of Spartina alterniflora. This topology map completely transforms the discrete plant distribution into a graph theory network model that the control system can directly track and execute.

[0022] The expression for the graph theory network model is: ; in, This refers to the graph theory network model; A set of vertices containing the plurality of patch nodes; and For set Any two patch nodes in the array; To establish a set of operation travel edges connecting the multiple patch nodes; For the corresponding node in the spatial connectivity matrix and The connectivity weights; For nodes and The distance between the obstacle avoidance geodesic lines; The preset propagation resistance coefficient; Furthermore, the specific implementation process of steps 300-400 is as follows: This embodiment performs the preliminary modeling stage in step 300. Based on the previously extracted land-water boundary line, a three-dimensional geological profile model of the target narrow habitat is constructed from the three-dimensional terrain data. The three-dimensional geological profile model of the slope refers to the geometric cross-sectional data representing the topographic undulations and underlying soil thickness, taken along the land and water sides perpendicular to the land-water boundary line as the reference axis. Its function is to provide accurate two-dimensional geometric boundary conditions for subsequent geotechnical stress calculations. In the specific data processing, this embodiment performs a vertical section along the normal direction of the land-water boundary line in the global coordinate system represented by the three-dimensional terrain data at a fixed geometric sampling interval of 0.5 meters, extending downwards to the bedrock layer or a set maximum exploration depth of 5.0 meters. All topographic nodes and stratigraphic boundary nodes within this section are extracted, thereby generating a set of two-dimensional spatial slices containing specific elevation and horizontal span coordinates, thus completing the three-dimensional geological profile model of the slope.

[0023] The expression for the three-dimensional geological profile model of the bank slope is: ; in, This is a three-dimensional geological profile model of the bank slope; and These are the horizontal spatial coordinates in the global coordinate system. This represents the elevation value at the corresponding horizontal coordinate. This represents the thickness of the bottom soil layer measured downwards at the corresponding horizontal coordinate. The set of cut line segments generated by perpendicularly cutting along the normal direction of the land-water boundary line at a fixed geometric sampling interval; This embodiment further uses the three-dimensional geological profile model of the bank slope and the soil and rock mechanics parameters of the bank slope to determine the potential sliding surface inside the bank slope and calculate the stable state using the limit equilibrium analysis algorithm. The specific data processing implementation process is as follows: In this embodiment, the potential sliding soil in the three-dimensional geological profile model of the bank slope is discretized into 20 vertical rigid soil strips; for each soil strip, its self-weight is calculated by calling the natural unit weight of the bottom mud in the soil and rock mechanics parameters of the bank slope, and the ultimate shear strength of the bottom of the soil strip is calculated by calling the cohesion of the bottom mud and the internal friction angle of the bottom mud; on this basis, in this embodiment, within the preset sliding circle center search grid extending from the top of the slope to the land side, the nodes are traversed and searched with a spatial step size of 0.2 meters to generate multiple arc-shaped potential sliding surfaces. For each potential sliding surface, this embodiment calculates the sum of the anti-sliding moments generated by the ultimate shear strength of all soil strips about the sliding center, preventing soil sliding. Simultaneously, it calculates the sum of the sliding moments generated by the tangential component of the self-weight of all soil strips about the sliding center, promoting soil sliding. The sum of the anti-sliding moments is then divided by the sum of the sliding moments to obtain a ratio. In this embodiment, the minimum ratio among all search traversal results is determined as the anti-sliding stability coefficient reflecting the slope's stability state. This coefficient directly quantifies the current slope's self-stability margin under conditions without external equipment overload. In this embodiment, the minimum ratio calculated and extracted is 1.15.

[0024] In this embodiment, step 400 constructs a safe working space. First, a preset critical value for slope safety is extracted, and a decay function is established to show the change in the anti-sliding stability coefficient with distance from the shore. Based on the decay function and the preset critical value for slope safety, the minimum soil and rock setback distance required to maintain slope stability is calculated to obtain the anti-collapse constraint boundary. The preset critical value for slope safety is the engineering baseline requirement to ensure that the water and soil structures do not suffer shear failure during continuous operation; in this embodiment, it is set to 1.25. The decay function characterizes the weakening and reduction mapping relationship of the original stability coefficient when the concentrated load of the working equipment is applied at different distances on the slope. In this embodiment, the distance from the shore is used as the independent variable, and the total weight of the equipment is used as an additional load in the limit equilibrium analysis algorithm to recalculate the stability coefficient and fit the continuous decay function. In this embodiment, the decay function is solved in reverse to find the value of the independent variable for distance from the shore when the calculated stability coefficient is exactly equal to the preset critical value for slope safety of 1.25, and this value is used as the minimum soil and rock setback distance. In this embodiment, the minimum soil and rock setback distance is calculated to be 1.5 meters. In this embodiment, the water-land boundary line is used as a reference, and the boundary line is strictly shifted 1.5 meters to the land side. The resulting spatial boundary line is the anti-collapse constraint boundary.

[0025] This embodiment further analyzes the equipment's characteristic parameters to obtain the total weight of the lightweight work equipment and the track ground contact area, and calculates the peak dynamic ground pressure of the lightweight work equipment under the maximum climbing condition. In this embodiment, the total weight is multiplied by the gravitational acceleration constant and then divided by the track ground contact area to calculate a static ground pressure of 12.5 kPa. To accurately reflect the load concentration phenomenon on steep slopes, this embodiment introduces an angular load amplification factor, which is obtained by mapping the inverse of the cosine function of the maximum climbing angle. In this embodiment, it is set to 1.48. The static ground pressure is multiplied by the angular load amplification factor to obtain a peak dynamic ground pressure of 18.5 kPa.

[0026] The expression for the peak value of the dynamic grounding specific voltage is: ; in, The dynamic grounding specific voltage peak value; The total weight of the lightweight work equipment is [the weight of the machine]. It is the gravitational acceleration constant; The track ground contact area; The maximum climbing angle; Subsequently, this embodiment combines the dynamic grounding pressure peak value with the local elevation gradient of the three-dimensional terrain data to establish a sediment bearing capacity attenuation model. The processing logic of the sediment bearing capacity attenuation model is to extract the benchmark bearing capacity of the geologically flat area and subtract the product of the elevation gradient value and the preset slope attenuation constant 0.3 as a penalty term. Based on the sediment bearing capacity attenuation model with this clear calculation logic, this embodiment performs traversal calculations across the entire region to extract weak areas where the actual sediment bearing capacity is less than the dynamic grounding pressure peak value of 18.5 kPa. A morphological dilation algorithm is then used to extend the physical edge of this weak area outward by a safety buffer of 0.5 meters, generating its outer closed contour as the anti-collapse constraint boundary.

[0027] The expression for the actual bottom sediment bearing capacity is: ; in, The actual bottom sediment bearing capacity after reduction due to the influence of elevation gradient; The benchmark bearing capacity of the extracted geologically flat area; The preset slope attenuation constant; and These are the elevation gradient values ​​of the corresponding three-dimensional spatial coordinate points in the horizontal orthogonal direction; This embodiment analyzes the hydrodynamic disturbance safety threshold to obtain the maximum permissible wading depth, and maps the corresponding contour lines in the three-dimensional terrain data to generate wading depth constraint boundaries. In this embodiment, the maximum permissible wading depth is extracted as 0.8 meters. This embodiment extracts the absolute elevation of the still water surface obtained by fitting the water surface specular reflection point cloud using lidar during the surveying stage. By calculating the difference between the absolute elevation of the still water surface and the elevation of the underwater surface within the nearshore waters of the three-dimensional terrain data, continuous spatial lines with a difference strictly equal to 0.8 meters are extracted to constitute the wading depth constraint boundaries. Finally, within the three-dimensional spatial coordinate system corresponding to the three-dimensional terrain data, this embodiment performs spatial geometric intersection operations on the anti-collapse constraint boundary, the anti-sinking constraint boundary, and the wading depth constraint boundary to construct a safe operating space model that defines the travel boundaries of the lightweight operating equipment. The safe operating space model is a multi-dimensional virtual electronic fence. In this embodiment, the Boolean intersection algorithm is used to eliminate areas prone to collapse near the water and shore, weak mudflats with insufficient bearing capacity, and deep water areas exceeding the depth limit, retaining only the geometrically overlapping internal area that meets all three conditions. This internal area is solidified and stored in the system's underlying data structure as a three-dimensional raster matrix with a spatial resolution of 0.05 meters. The final output is the safe operating space model, ensuring that lightweight operating equipment operating within this model can have absolute disaster resistance and low disturbance to the aquatic ecosystem.

[0028] The expression for the safe workspace model is: ; in, The set of three-dimensional effective spaces defined by the aforementioned safe working space model; , , These are the geometric coordinates within the three-dimensional spatial coordinate system; This represents the actual horizontal distance from the coordinate point to the said land-water boundary line; The minimum soil and rock setback distance required to maintain the stability of the bank slope; The actual bottom mud bearing capacity calculated based on the bottom bearing capacity attenuation model at this coordinate point; The dynamic grounding specific voltage peak value; This represents the actual water depth corresponding to this coordinate point; The maximum permissible wading depth; Furthermore, the specific implementation process of steps 500-600 is as follows: In step 500 of this embodiment, the minimum turning radius and maximum climbing angle constraints are first extracted from the equipment characteristic parameters. The minimum turning radius represents the chassis's limit mechanical steering capability without track derailment; in this embodiment, its absolute value is limited to 2.5 meters. The maximum climbing angle represents the physical limit elevation angle at which the equipment's center of gravity projection does not exceed the track ground contact polygon and does not experience longitudinal slippage or overturning; in this embodiment, its absolute value is limited to 30 degrees. Subsequently, in this embodiment, within the safe operating space model, a path planning model is established with the hard optimization constraint that all the multiple patch nodes in the discrete source patch topology graph must be traversed. This path planning model refers to a mathematical abstract architecture based on graph theory spatial state search, whose core function is to transform the disordered discrete removal task nodes into a coherent physical access sequence with a spatial execution order.

[0029] The expression for the path planning model is: ; in, The objective function for the path planning model is distance minimization. The total number of the plurality of patch nodes; For the first in the access sequence One patch node; The obstacle avoidance geodesic distance between adjacent access nodes; The spatial geometric equivalent radius of curvature formed by three consecutive access nodes; The minimum radius of gyration; This represents the actual spatial slope between adjacent access nodes. The maximum climbing angle; In solving the path planning model, this embodiment strictly incorporates the minimum turning radius and the maximum climbing angle constraints to perform pre-emptive physical boundary pruning on the search space. The specific data processing is as follows: When expanding the spatial node connections, this embodiment sequentially extracts the three-dimensional coordinates of any three consecutive search nodes, and fits a unique circumcircle passing through all three nodes in the three-dimensional coordinate system. The physical radius of this circumcircle is directly defined as the spatial geometric equivalent curvature radius. When this spatial geometric equivalent curvature radius is less than the minimum turning radius of 2.5 meters, the path is deemed likely to cause equipment dynamics loss of control, and the node connection combination is directly eliminated. Simultaneously, this embodiment calculates the arctangent of the elevation difference between adjacent nodes and the horizontal projection distance to obtain the actual spatial slope. When the actual spatial slope is greater than the maximum climbing angle of 30 degrees, the connection path is forcibly blocked. Through the above-mentioned dual geometric pruning operation, this embodiment accurately eliminates dangerous connection paths that do not meet the device characteristic parameters, and finally generates the global reference path that sequentially connects the multiple patch nodes. In this embodiment, the final extracted global reference path contains 15 task nodes, and its effective spatial extension total length is 450.5 meters.

[0030] In step 600 of this embodiment, based on the global reference path, a track kinematic slip model of the lightweight operating equipment is first established. The track kinematic slip model is a high-dimensional dynamic physical model that quantitatively describes the attenuation of forward displacement under soft mud conditions. This embodiment extracts the theoretical mechanical traction force output by the chassis motor and performs a ratio mapping calculation with the previously obtained ultimate shear strength of the mud, obtaining an actual slip rate of 0.15, characterizing the degree of slippage and idling of the tracks in this type of high-water-content soft mud. This embodiment inputs the theoretical straight-line speed of the bottom control system (1.2 m / s) and, combined with this actual slip rate, calculates the estimated operating time along the target trajectory, directly constructing this estimated operating time as an operating time penalty term. Next, this embodiment calculates the instantaneous rate of curvature change and the equipment heading angle deviation of the target trajectory by discretely sampling points along the trajectory. The severity of the steering operation is quantified by calculating the sum of the squares of these two values, thereby constructing a curvature smoothness penalty term. The function of this penalty term is to avoid the cutting damage to the underwater mud surface caused by frequent mechanical steering actions.

[0031] The expression for the track kinematic slip model (high-dimensional dynamic physical model) is as follows: ; in, The decayed actual velocity is calculated and output for the track kinematic slip model; The theoretical straight-line speed of the underlying control system; The actual slip ratio; To calibrate the system friction mapping coefficient for the sensitivity of sediment moisture content to slippage; This refers to the theoretical mechanical traction force output by the chassis motor. This refers to the ultimate shear strength of the bottom mud obtained in the previous stage; The track ground contact area; To completely eliminate the problem of secondary disturbance in the water body, this embodiment establishes a nonlinear hydrodynamic disturbance mapping equation that includes travel speed, track slip ratio, and steering angular velocity. This embodiment couples and multiplies these three dynamic state variables to calculate the mechanical shear dissipation energy per unit time generated by the track teeth in the sediment. This dissipation energy is then mapped to the mass concentration of suspended particulate matter in the water body through a preset empirical conversion constant, thereby calculating the predicted value of the sediment suspended concentration.

[0032] The expression for the predicted value of the sediment suspension concentration is: ; in, This is the predicted value of the suspended concentration of the sediment. The preset empirical transformation constant; This refers to the ultimate shear strength of the bottom mud obtained in the previous stage; The driving speed of the underlying control system; The actual slip ratio is calculated as follows; The physical density is the equivalent of the natural density of the sediment. The equivalent turning radius of track grounding for lightweight operational equipment; The steering angular velocity of the underlying control system; Subsequently, this embodiment compares the predicted value with the maximum allowable suspended sediment concentration of 50 mg / L in the hydrodynamic disturbance safety threshold. When the predicted value approaches this extreme value, an exponential dynamic surge weight with the natural base is generated. The dynamic surge weight is multiplied by the predicted value to construct the water disturbance penalty term. After completing the extraction of individual penalties, this embodiment divides the operation time penalty term, the curvature smoothness penalty term, and the water disturbance penalty term by the maximum endurance time of the equipment, the maximum physical turning acceleration, and the maximum allowable concentration extreme value, respectively, to unify and dimensionlessly map the three heterogeneous physical quantities to the standard range of 0 to 1. Subsequently, this embodiment assigns fixed weight parameters of 0.2, 0.3, and 0.5 to the three normalized indicators and performs a weighted summation operation, finally fusing them to construct the multi-objective cost functional.

[0033] The expression for the water disturbance penalty term is: ; in, The water body disturbance penalty item; The base is the natural number; This is the predicted value of the suspended concentration of the sediment. The maximum permissible suspended sediment concentration; To prevent the denominator from being zero, which could lead to a singular, extremely small positive real number in the system; After constructing the functional, this embodiment finally solves the multi-objective cost functional to generate the optimal operation trajectory. The specific data processing logic is as follows: This embodiment mathematically transforms the multi-objective cost functional into an objective function that needs to be minimized in the optimal control problem, and transforms the three-dimensional grid anti-collision boundary of the safe operation space model into state-space inequality constraints in the optimal control problem. This embodiment selects the driving speed and steering angular velocity of the lightweight operation equipment as the underlying control variables, strictly limiting the control boundary of the driving speed to the range of 0 to 1.5 meters per second, and the control boundary of the steering angular velocity to the range of -0.4 to +0.4 radians per second. Subsequently, this embodiment uses a model predictive control algorithm to iteratively solve the control variables within a finite prediction time domain of 5.0 seconds, with a fixed time step of 0.1 seconds. Under the premise of strictly adhering to the state-space inequality constraints, the optimal control sequence that minimizes the value of the objective function is obtained. Finally, based on the extracted optimal control sequence, this embodiment performs continuous spatiotemporal integral derivation in Cartesian three-dimensional space, completely mapping and translating the discrete low-level control commands into a smooth time-series point set containing continuous timestamps and high-precision three-dimensional spatial coordinates, thereby obtaining the optimal operation trajectory finally used for execution.

[0034] This embodiment also provides a trajectory optimization system for lightweight Spartina alterniflora operation equipment targeting narrow inland river habitats, including: The multi-source data acquisition module is used to acquire three-dimensional topographic data of the target narrow habitat, slope rock and soil mechanical parameters, Spartina alterniflora distribution image data, as well as equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operation equipment for control operations. The feature extraction and topology construction module is used to extract the land-water boundary line based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, and construct a discrete seed source patch topology map that represents the spatial topological relationship of Spartina alterniflora, wherein the discrete seed source patch topology map contains multiple patch nodes; The bank slope stability calculation module is used to calculate the anti-sliding stability coefficient, which reflects the stability state of the bank slope, based on the bank slope geotechnical parameters and the water-land boundary line. The safe operating space modeling module is used to construct a safe operating space model that defines the driving boundary of the lightweight operating equipment based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold. The global reference path generation module is used to construct a global reference path within the safe operation space model, using the multiple patch nodes as traversal nodes, that sequentially connects the multiple patch nodes and satisfies the device characteristic parameters. The optimal operation trajectory solution module is used to construct a multi-objective cost functional including a water disturbance penalty term based on the global reference path and the safe operation space model, and to solve the multi-objective cost functional to generate the optimal operation trajectory.

[0035] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0036] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for optimizing the trajectory of lightweight operational equipment for Spartina alterniflora in narrow inland river habitats, characterized in that, include: Acquire three-dimensional topographic data of the target narrow habitat, slope geomechanical parameters, Spartina alterniflora distribution image data, and equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operating equipment used for control operations; Based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, the water-land boundary line is extracted, and a discrete seed source patch topology map representing the spatial topological relationship of Spartina alterniflora is constructed, wherein the discrete seed source patch topology map contains multiple patch nodes. Based on the aforementioned slope geomechanical parameters and the water-land boundary line, the anti-sliding stability coefficient reflecting the slope's stability state is calculated. Based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold, a safe operating space model is constructed to define the driving boundary of the lightweight operating equipment. Within the safe operating space model, a global reference path is constructed by using the multiple patch nodes as traversal nodes, sequentially connecting the multiple patch nodes and satisfying the equipment characteristic parameters. Based on the global reference path, a multi-objective cost functional including a water disturbance penalty term is constructed in conjunction with the safe operation space model, and the multi-objective cost functional is solved to generate the optimal operation trajectory.

2. The trajectory optimization method for lightweight operation equipment of Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The device characteristic parameters include: The total weight of the lightweight work equipment, the track ground contact area, the minimum turning radius, and the maximum climbing angle; The hydrodynamic disturbance safety thresholds include: the maximum permissible sediment suspension concentration and the maximum permissible wading depth.

3. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The geomechanical parameters of the bank slope include: Sediment cohesion, sediment internal friction angle, and sediment natural density.

4. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The step of extracting the land-water boundary line based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, and constructing a discrete provenance patch topology map representing the spatial topological relationships of Spartina alterniflora, includes: Spatial feature registration is performed between the Spartina alterniflora distribution image data and the three-dimensional terrain data to generate fused image data containing three-dimensional coordinate information. Based on the fused image data, the elevation gradient abrupt change line in the target narrow habitat is extracted, and the elevation gradient abrupt change line is defined as the water-land boundary line; The initial distribution area of ​​Spartina alterniflora was extracted from the fused image data using the multispectral vegetation index threshold segmentation method. By removing isolated noise points in the initial distribution area of ​​Spartina alterniflora and performing morphological closing operations, multiple independent patches are obtained. Extract the geometric centroid of each of the individual patches to obtain the plurality of patch nodes; By combining the land-water boundary line with the three-dimensional terrain data, the obstacle avoidance geodesic distance between any two of the plurality of patch nodes is calculated, and a distance attenuation matrix is ​​established; A preset propagation resistance coefficient is introduced to weight the distance attenuation matrix to generate a spatial connectivity matrix. Based on the spatial connectivity matrix, the nodes of each of the multiple patches are connected to construct a discrete source patch topology map representing the spatial topological relationship of Spartina alterniflora.

5. The trajectory optimization method for lightweight operation equipment of Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The calculation of the anti-sliding stability coefficient, reflecting the stability state of the bank slope, based on the bank slope geomechanical parameters and the land-water boundary line, includes: Based on the water-land boundary line, a three-dimensional geological profile model of the bank slope of the target narrow habitat is constructed in the three-dimensional terrain data; Based on the three-dimensional geological profile model of the bank slope and the rock and soil mechanical parameters of the bank slope, the potential sliding surface inside the bank slope is determined by the limit equilibrium analysis algorithm. Calculate the ratio of the anti-slip moment to the sliding moment on the potential sliding surface, and determine the minimum calculated ratio as the anti-slip stability coefficient that reflects the stability state of the bank slope.

6. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The step of constructing a safe operating space model that defines the travel boundary of the lightweight operating equipment based on the anti-skid stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold includes: Extract the preset critical value for bank slope safety, establish the decay function of the anti-sliding stability coefficient as a function of distance from the bank, and solve the minimum soil and rock retreat distance required to maintain bank slope stability based on the decay function and the preset critical value for bank slope safety, so as to obtain the anti-collapse constraint boundary. The total weight and track grounding area of ​​the lightweight work equipment are obtained by analyzing the characteristic parameters of the equipment, and the peak value of the dynamic grounding specific voltage of the lightweight work equipment under the maximum climbing condition is calculated. By combining the dynamic grounding specific pressure peak value with the local elevation gradient of the three-dimensional terrain data, a sediment bearing capacity attenuation model is established. Based on the sediment bearing capacity attenuation model, regions with bearing capacity less than the peak value of the dynamic grounding specific pressure are extracted and offset outwards to obtain the anti-sinking constraint boundary. The maximum permissible wading depth is obtained by analyzing the hydrodynamic disturbance safety threshold, and the corresponding contour lines are mapped in the three-dimensional terrain data to generate wading depth constraint boundaries. Within the three-dimensional spatial coordinate system corresponding to the three-dimensional terrain data, a spatial intersection operation is performed on the anti-collapse constraint boundary, the anti-sinking constraint boundary, and the wading depth constraint boundary to construct a safe operating space model that defines the driving boundary of the lightweight operating equipment.

7. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, Within the safe operating space model, a global reference path is constructed, using the plurality of patch nodes as traversal nodes, that sequentially connects the plurality of patch nodes and satisfies the device characteristic parameters. This includes: Extract the minimum turning radius and maximum climbing angle constraints from the equipment's characteristic parameters; Within the safe operation space model, a path planning model is established with the constraint that all the multiple patch nodes in the discrete source patch topology map must be traversed; In the process of solving the path planning model, the minimum turning radius and the maximum climbing angle constraints are introduced to eliminate the connection paths between nodes that do not meet the equipment characteristic parameters, thereby obtaining the global reference path that sequentially connects the multiple patch nodes.

8. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, The construction of a multi-objective cost functional, which includes a water disturbance penalty term, based on the global reference path and combined with the safe operation space model, includes: Establish a track kinematics slip model for the lightweight work equipment, calculate the estimated operation time along the target trajectory based on the track kinematics slip model, and construct an operation time penalty term; Calculate the instantaneous rate of curvature change and heading angle deviation of the target trajectory, and construct a curvature smoothness penalty term; A nonlinear hydrodynamic disturbance mapping equation incorporating travel speed, track slip ratio, and steering angular velocity is established. The predicted value of sediment suspended concentration is calculated based on the aforementioned nonlinear hydrodynamic disturbance mapping equation; The predicted sediment suspension concentration is compared with the maximum allowable sediment suspension concentration in the hydrodynamic disturbance safety threshold. A dynamic surge weight is generated based on the comparison difference. The dynamic surge weight is multiplied by the predicted sediment suspension concentration to construct the water body disturbance penalty term. The global reference path is extracted as the initial planning benchmark. Under the boundary constraints of the safe operation space model, the operation time penalty, the curvature smoothness penalty, and the water disturbance penalty are normalized and weighted summed to construct the multi-objective cost functional.

9. The method for trajectory optimization of lightweight operation equipment for Spartina alterniflora in narrow inland river habitats according to claim 1, characterized in that, Solving the multi-objective cost functional to generate the optimal job trajectory includes: The multi-objective cost functional is transformed into an objective function in the optimal control problem, and the safe operation space model is transformed into a state-space inequality constraint in the optimal control problem. The driving speed and steering angular velocity of the lightweight work equipment are used as control variables; The model predictive control algorithm is used to perform rolling iterative solutions on the control variables in a finite time domain to obtain the optimal control sequence that minimizes the multi-objective cost functional. The optimal operation trajectory is obtained by performing spatiotemporal integration based on the optimal control sequence.

10. A trajectory optimization system for lightweight operational equipment of Spartina alterniflora targeting narrow inland river habitats, characterized in that, include: The multi-source data acquisition module is used to acquire three-dimensional topographic data of the target narrow habitat, slope rock and soil mechanical parameters, Spartina alterniflora distribution image data, as well as equipment characteristic parameters and hydrodynamic disturbance safety thresholds of lightweight operation equipment for control operations. The feature extraction and topology construction module is used to extract the land-water boundary line based on the three-dimensional terrain data and the Spartina alterniflora distribution image data, and construct a discrete seed source patch topology map that represents the spatial topological relationship of Spartina alterniflora, wherein the discrete seed source patch topology map contains multiple patch nodes; The bank slope stability calculation module is used to calculate the anti-sliding stability coefficient, which reflects the stability state of the bank slope, based on the bank slope geotechnical parameters and the water-land boundary line. The safe operating space modeling module is used to construct a safe operating space model that defines the driving boundary of the lightweight operating equipment based on the anti-slip stability coefficient, the equipment characteristic parameters, and the hydrodynamic disturbance safety threshold. The global reference path generation module is used to construct a global reference path within the safe operation space model, using the multiple patch nodes as traversal nodes, that sequentially connects the multiple patch nodes and satisfies the device characteristic parameters. The optimal operation trajectory solution module is used to construct a multi-objective cost functional including a water disturbance penalty term based on the global reference path and the safe operation space model, and to solve the multi-objective cost functional to generate the optimal operation trajectory.

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