CN119756381A

CN119756381A - Path planning method, device, electronic device and computer-readable storage medium

Info

Publication number: CN119756381A
Application number: CN202411996114.6A
Authority: CN
Inventors: 牛三库; 周兆忠; 刘宇航; 申屠铖琛; 胡若冲; 厉安健
Original assignee: Quzhou University
Current assignee: Quzhou University
Priority date: 2024-12-31
Filing date: 2024-12-31
Publication date: 2025-04-04

Abstract

The application provides a path planning method, a path planning device, electronic equipment and a computer readable storage medium, wherein the method comprises the steps of obtaining boundary information in a target area; the method comprises the steps of determining a running path of target equipment according to boundary information, optimizing set position points in the running path through a local path planning algorithm, and enabling the target equipment to run in a target area according to the optimized running path. According to the embodiment of the application, the set position points in the driving path are optimized according to the local path algorithm, so that the set position points in the path can be dynamically adjusted and optimized according to the real-time environment information of the target area, and the safety and stability of the driving path are improved.

Description

Path planning method, path planning device, electronic equipment and computer readable storage medium

Technical Field

The present application relates to the field of path planning, and in particular, to a path planning method, apparatus, electronic device, and computer readable storage medium.

Background

In modern production and living environments, the driving route of the equipment is not constant, but needs to be dynamically adjusted according to actual working conditions. For example, in farm work, the farm machinery needs to flexibly move to the next designated location after completing different tasks. This requires that the path planning algorithm be able to respond in real time to the operating conditions and terrain changes to provide an optimal path.

However, the conventional reciprocating path planning method is difficult to cope with complex and changeable farmland environments due to the fixity, so that the efficiency of target equipment is low when tasks are executed, and even errors can occur, thereby affecting the working efficiency and accuracy.

Disclosure of Invention

In view of the above, an object of the embodiments of the present application is to provide a path planning method, apparatus, electronic device, and computer readable storage medium, which can improve the safety and stability of a driving path and improve the adaptability of a target device to a complex environment.

In a first aspect, an embodiment of the present application provides a path planning method, where boundary information in a target area is obtained, a driving path of a target device is determined according to the boundary information, a set position point in the driving path is optimized by a local path planning algorithm, and the target device is configured to drive in the target area according to the optimized driving path.

In the implementation process, the set position points in the driving path are optimized according to the local path algorithm, so that the set position points in the path can be dynamically adjusted and optimized according to the real-time environment information of the target area, the safety and stability of the driving path are improved, and the adaptability of the target equipment to complex environments is improved.

In one embodiment, the local path planning algorithm is a B-spline curve optimization algorithm, and the optimizing of the set position points in the running path through the local path planning algorithm comprises the steps of calculating the curvature of each point in the running path, traversing all position points in the running path, determining a point set which does not meet curvature constraint conditions, and optimizing paths adjacent to the point set through the B-spline curve optimization algorithm.

In the implementation process, the curvature of each point in the running path is calculated, and the point set which does not meet the curvature constraint condition is screened out through the curvature constraint condition, so that the point set which does not meet the curvature constraint condition is optimized, each position point in the optimized running path can meet the curvature constraint condition, the smoothness of the running path is improved, the loss of target equipment is reduced, the adaptability of the target equipment to complex environments is improved, and meanwhile, the accuracy and the stability of the running path are improved.

In one embodiment, the optimization of the paths adjacent to the point set through the B-spline curve optimization algorithm comprises the steps of establishing a non-uniform rational B-spline curve, constructing an objective function according to the non-uniform rational B-spline curve, wherein the objective function is configured to define the distance between a minimized path and an actual position point, and establishing an optimization model based on the objective function and the curvature constraint condition, wherein the optimization model is configured to optimize the paths adjacent to the point set.

In the implementation process, the running path is optimized by adopting the B spline curve optimization algorithm, so that the running path of the operation of the target equipment can be accurately optimized, and the running path has better smoothness while the efficient operation of the target equipment is ensured. Not only can the turning radius of the target equipment in the target area be reduced, thereby improving the working efficiency and reducing the energy consumption. In addition, in the case that the target area is farmland, the method has a remarkable effect of protecting farmland crops and soil. In the turning process of target equipment (such as an intelligent agricultural machine), the direct rolling and friction of the intelligent agricultural machine to crops are greatly reduced due to the smooth optimization of the paths, so that the risk of damaging the crops is effectively avoided. Meanwhile, the reduction of the turning radius also means that the compaction effect of the intelligent agricultural machinery on the soil is weakened, which is helpful for maintaining the porosity and air permeability of the soil and providing more favorable conditions for the root growth of crops.

In one embodiment, the boundary information comprises a boundary path, and before the driving path of the target device is determined according to the boundary information, the method further comprises the steps of constructing a nonlinear boundary area according to the boundary information, conducting boundary smoothing on the boundary of the nonlinear boundary area, determining an extreme point area in the nonlinear boundary area, and conducting nonlinear spiral path design on the nonlinear boundary area according to the extreme point area.

In the implementation process, by constructing the nonlinear boundary region and carrying out nonlinear spiral line design based on the extreme points in the nonlinear boundary region, the complex geometric region can be effectively covered, overlapping and gaps among paths are reduced, the utilization rate of the paths is improved, and the moving efficiency of the mobile equipment is further improved.

In one embodiment, the boundary information comprises a boundary path, the determining of the driving path of the target device according to the boundary information comprises the steps of constructing a contour equation according to the boundary information, obtaining a plurality of paths according to the contour equation, and combining the paths into one path, wherein the combined path is the driving path.

In the implementation process, the target area is divided into a plurality of paths, and the paths are combined into one path, so that the complex geometric area can be effectively covered, overlapping and gaps between the paths are reduced, the driving path can be optimized, the acting time of target equipment and the fuel required by operation can be saved, and the overall efficiency of the operation is improved.

In one embodiment, the extreme point region in the nonlinear boundary region is a monopolar value point region, the nonlinear spiral path design is performed on the nonlinear boundary region according to the extreme point region, the nonlinear spiral path design comprises the steps of constructing a plurality of nonlinear equidistant paths with a first set interval in the nonlinear boundary by taking the extreme point region as a center until the interval between adjacent paths is smaller than a second set interval, selecting a position point on any path as a first position point, determining a second position point adjacent to the first position point on the same path according to the body parameter of the target device, wherein the first position point is a starting point, determining a third position point closest to the second position point on the previous path on the subsequent path adjacent to the previous path according to the extreme point region, determining a second position point adjacent to the third position point on the same path according to the body parameter of the target device until the corresponding position point is found in each path, disconnecting the two adjacent positions on the same path, and obtaining a connection between the two nearest positions on the two paths.

In the implementation process, for the single extreme point region, the connection line between two adjacent position points on each path can be disconnected, and two position points closest to each other on the two adjacent paths are connected, so that the paths are combined into one path, and the whole implementation mode is simple and easy to implement. When adjacent paths are connected, the nearest position point is selected for connection, so that the whole path length of the running path can be reduced, the running distance of target equipment is reduced, and the working efficiency is improved.

In one embodiment, the extreme point region in the nonlinear boundary region is a multipole value point region, a plurality of nonlinear equidistant paths with first set pitches are built in the nonlinear boundary region by taking the extreme point as a center until the distance between the adjacent paths is smaller than a second set pitch, the nonlinear equidistant paths with the first set pitches are built in the nonlinear boundary region by taking each extreme point as a center respectively, the distance between the adjacent paths in each nonlinear boundary region is smaller than a second set pitch, whether the paths corresponding to the adjacent extreme points can be connected or not is judged, the adjacent paths are connected by conducting edge breaking reconnection operation on the boundary paths of the paths corresponding to the adjacent extreme points on the condition that the paths corresponding to the adjacent extreme points are determined, a position point is selected on any one of the integral paths formed after the adjacent paths are connected as a first position point, a second position point adjacent to the first position point on the same path is determined according to the shape parameter of the target device, the first position point is a starting point, the adjacent position point is determined on the same path, the first position point is the first position point, the two adjacent points are located on the same path, the first position point is located on the same path, and the nearest to the second position point is located on the first position, and the second position point is located on the same path, and the nearest to the first position point.

In the implementation process, for the multi-extreme point region, whether the paths corresponding to the adjacent extreme points can be connected is judged, and under the condition that the adjacent extreme points can be connected, the boundary paths corresponding to the adjacent extreme points are opened to form an integral path, and all paths in the integral path are combined into one path, so that the running path can cope even facing a complex terrain environment, and the use scene of the path planning method can be increased.

In one embodiment, the acquiring of the boundary information in the target area comprises preprocessing the acquired target image of the target area, initializing a level set function, calculating the image gradient of the target image, determining the boundary of the target area in the target image according to the image gradient, updating the level set function through a regularized level set evolution equation, and outputting the boundary information of the target image under the condition that the level set function approaches the boundary of the target area.

In the implementation process, the boundary information of the target area is determined by adopting the regularized level set evolution equation, so that the smoothness and the shape of the boundary can be controlled and adjusted, the accuracy of boundary information extraction is improved, and meanwhile, the smoothness and the stability of the boundary are improved.

In a second aspect, the embodiment of the application further provides a path planning device, which comprises an acquisition module, a determination module and an optimization module, wherein the acquisition module is used for acquiring boundary information in a target area, the determination module is used for determining a running path of target equipment according to the boundary information, the optimization module is used for optimizing set position points in the running path through a local path planning algorithm, and the target equipment is configured to run in the target area according to the optimized running path.

In a third aspect, embodiments of the present application also provide an electronic device comprising a processor, a memory storing machine-readable instructions executable by the processor, which when executed by the processor perform the steps of the method of the first aspect, or any of the possible implementations of the first aspect.

In a fourth aspect, embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of path planning of the first aspect, or any of the possible implementations of the first aspect.

In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic block diagram of an electronic device according to an embodiment of the present application;

Fig. 2 is a flowchart of a path planning method according to an embodiment of the present application;

Fig. 3 is a schematic diagram of comparison between the before and after the optimization of the driving path according to the embodiment of the present application;

FIG. 4 is a schematic diagram of a nonlinear boundary region provided by an embodiment of the present application;

FIG. 5 is a schematic diagram of a monopole value point area path planning according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a path planning for a multi-pole area according to an embodiment of the present application;

Fig. 7 is a process diagram of generating a driving path according to the path planning method provided by the embodiment of the present application;

fig. 8 is a schematic diagram of merging traveling paths in a single-pole value point region according to an embodiment of the present application;

fig. 9 is a schematic diagram of merging travel paths in a multi-polar point area according to an embodiment of the present application;

fig. 10 is a schematic diagram of a functional module of a path planning apparatus according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.

It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.

With advances in technology, production mechanization has become a key factor in improving agricultural and/or industrial productivity and competitiveness. The use of the automatic equipment can not only greatly reduce the labor intensity and improve the working efficiency, but also realize quantitative production in mass production, optimize the resource allocation and reduce the production cost. For example, in the course of agricultural modernization, the popularity and use of agricultural machinery has significantly increased crop yield and quality, and the shift in power-assisted agriculture from traditional labor-intensive to technology-intensive.

However, in areas with complex topography and wide distribution of hilly and mountainous areas, such as southern areas of China, numerous small crushed fields are formed because most farmlands in the areas are small and scattered. This topographical feature determines the particularities of southern agricultural production and also makes agricultural mechanization a unique challenge. Because small fragments Tian Dekuai of hilly and mountain areas are scattered, the topography fluctuates greatly, and the traditional large-scale agricultural machinery is difficult to flexibly operate in the areas and is easy to be limited by the topography, so that the operation efficiency is low. In addition, the farmland environment in hilly areas is complex, and obstacles are more, so that the operation difficulty of the agricultural machinery is further increased. When the agricultural machinery works in the areas, the path is often required to be planned manually, or only a few straight-in and straight-out paths can be planned, and the process consumes a great deal of time and labor, is easy to generate errors, and reduces the working efficiency and accuracy.

In view of this, the present application proposes a path planning method, by optimizing the set position points in the driving path according to the local path algorithm, the set position points in the path can be dynamically adjusted and optimized according to the real-time environment information of the target area, so as to improve the safety and stability of the driving path, and simultaneously improve the adaptability of the target device to the complex environment.

For the sake of understanding the present embodiment, first, an electronic device that executes the path planning method disclosed in the embodiment of the present application will be described in detail.

As shown in fig. 1, a block schematic diagram of an electronic device is provided. The electronic device 100 may include a memory 111, a processor 113. Those of ordinary skill in the art will appreciate that the configuration shown in fig. 1 is merely illustrative and is not limiting of the configuration of the electronic device 100. For example, electronic device 100 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

The memory 111 and the processor 113 are directly or indirectly electrically connected to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The processor 113 is used to execute executable modules stored in the memory.

The Memory 111 may be, but is not limited to, a random access Memory (Random Access Memory, RAM), a Read Only Memory (ROM), a programmable Read Only Memory (Programmable Read-Only Memory, PROM), an erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), an electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc. The memory 111 is configured to store a program, and the processor 113 executes the program after receiving an execution instruction, and a method executed by the electronic device 100 defined by the process disclosed in any embodiment of the present application may be applied to the processor 113 or implemented by the processor 113.

The processor 113 may be an integrated circuit chip having signal processing capabilities. The processor 113 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), a digital signal processor (DIGITAL SIGNAL processor, DSP), an Application-specific integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a discrete gate or transistor logic device, or a discrete hardware component. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The electronic device 100 in this embodiment may be used to perform each step in each method provided in the embodiment of the present application. The implementation of the path planning method is described in detail below by means of several embodiments.

Fig. 2 is a flowchart of a path planning method according to an embodiment of the present application. The specific flow shown in fig. 2 will be described in detail.

In step 201, boundary information in a target area is acquired.

The target area here is an area where the target device performs work, for example, a field, a mine sweeping area, a cleaning area, or the like. The target area may be selected according to the actual situation.

Optionally, the target device may be a sweeping robot, an intelligent agricultural machine, a mine sweeping robot, a reconnaissance unmanned aerial vehicle, etc., and the target device may be selected according to actual situations.

In one embodiment, prior to step 201, the method further comprises acquiring an image of the target area.

The target area image can be acquired through image acquisition devices such as an aerial survey unmanned aerial vehicle, a camera and a sky eye, and the image acquisition device for acquiring the target area image can be selected according to actual conditions.

It can be appreciated that after the target area image of the target area is acquired, boundary information in the target area image can be extracted by an edge detection operator, a morphological algorithm, a chain code boundary extraction, and the like.

The boundary information may include information of edge pixels, edge directions, edge intensities, edge curvatures, boundary paths, etc., and the boundary information may be selected according to practical situations.

Step 202, determining a driving path of the target equipment according to the boundary information.

The driving path may be determined by a global planning method, a local planning method, or the like, and the determining method of the driving path may be selected according to actual situations.

Wherein the travel path is configured to be determined according to the start point and the end point of the target device and the boundary information of the target area.

And 203, optimizing the set position points in the driving path through a local path planning algorithm.

It can be appreciated that the travel path determined directly according to the starting point and the ending point of the target device and the boundary information of the target area may have discontinuous curvature, and may easily cause sudden changes of the front wheel steering angle when the agricultural machinery turns, and there is a certain risk. Based on the method, after the running path is determined, the set position points in the running path can be further optimized through a local path planning algorithm, so that the curvature of the optimized running path is continuous, the transition is smooth, and the working accuracy of the target equipment is improved.

The local path planning algorithm can be the shortest tangent method, the Bezier curve method, the B-spline curve optimization algorithm and the like, and can be selected according to actual conditions.

The shortest tangent method is a method for finding a path as short as possible by calculating a tangent path to avoid an obstacle, and has the advantages of high path generation speed and simple realization.

The Bezier curve method is a method for defining and generating a smooth curve through control points, and has the advantages of improving the continuity of a path and reducing steering load.

The B spline curve optimization algorithm is a parameterized curve based on control points and is used for generating a smooth track, and the B spline curve optimization algorithm has the advantages that the control points are reasonably arranged, so that the curvature of a path is continuous and smooth, the abrupt change of target equipment in turning is obviously reduced, the accuracy and stability of path tracking are ensured, and complex terrain environments can be flexibly coped with.

The set position point refers to any position point in the travel path, and the set position point can be selected according to actual conditions.

In one embodiment, the target device is configured to travel in the target area according to the optimized travel path.

In the implementation process, the set position points in the driving path are optimized according to the local path algorithm, so that the set position points in the path can be dynamically adjusted and optimized according to the real-time environment information of the target area, the safety and stability of the driving path are improved, and meanwhile, the adaptability of the target equipment to complex environments is improved.

In one possible implementation, step 203 includes calculating curvature of each point in the driving path, traversing all position points in the driving path, determining a point set which does not meet curvature constraint conditions, and optimizing paths adjacent to the point set through a B-spline curve optimization algorithm.

The curvature calculation here may be achieved by a three-point method. That is, the method of traversing 3 points to form an approximate arc performs a solution analysis on the curvature of points on the travel path.

For example, if there are i+1 original path points p _i, each path point has a corresponding radius of curvature r _i, the solution formula may be:

the curvature k _i may be:

In order to satisfy the curvature constraint condition, the following constraint may be set:

r_i≥r_min;

Wherein, Is a straight line between the i-th original path point and the i+1th original path point,R _min is the minimum radius of curvature, which is the straight line between the i-th original path point and the i-1 th original path point.

It will be appreciated that when a location point in the travel path satisfies a curvature constraint, determining the curvature at that location point may allow the target device to transition smoothly. Thus, no optimization is required for the location points that meet the curvature constraint. When a position point in the travel path does not satisfy the curvature constraint condition, determining the curvature at the position point does not smoothly transition the target device, and may affect the travel stability of the target device. Therefore, for the position points which do not meet the curvature constraint condition, further optimization is needed, so that the optimized curvature meets the curvature constraint condition.

In one possible implementation, the path adjacent to the point set is optimized by a B-spline curve optimization algorithm, which comprises the steps of establishing a non-uniform rational B-spline curve, establishing an objective function according to the non-uniform rational B-spline curve, and establishing an optimization model based on the objective function and curvature constraint conditions.

Wherein the non-uniform rational B-spline curve can be expressed by the following formula:

Wherein, C (u) is a non-uniform rational B-spline curve, N _i, P (u) is a B-spline curve basis function, P _i is a path control point, and ω _i is a weight coefficient.

The objective function is here configured to define a distance between the minimization path and the actual location point, which objective function fulfils the curvature constraint.

In one embodiment, the objective function may be expressed as:

Wherein J is an objective function, D _j is the actual point of the path, and m is the number of the path points.

The optimization model is configured to optimize paths adjacent to the point set. The optimization model may be expressed as:

It will be appreciated that, as shown in fig. 3, comparison before and after the travel path optimization is shown in fig. 3 (wherein, the travel path before the optimization shown in (a) in fig. 3, the travel path before the optimization shown in (b) in fig. 3). As can be seen from fig. 3, the B-spline curve optimization algorithm under the curvature constraint condition is set, so that the running path of the operation of the target equipment can be accurately optimized, and the running path has better smoothness while the efficient operation of the target equipment is ensured. Not only can the turning radius of the target equipment in the target area be reduced, thereby improving the working efficiency and reducing the energy consumption. Moreover, in the case that the target area is farmland, the method has a remarkable effect of protecting farmland crops and soil. In the turning process of target equipment (such as an intelligent agricultural machine), the direct rolling and friction of the intelligent agricultural machine to crops are greatly reduced due to the smooth optimization of the paths, so that the risk of damaging the crops is effectively avoided. Meanwhile, the reduction of the turning radius also means that the compaction effect of the intelligent agricultural machinery on the soil is weakened, which is helpful for maintaining the porosity and air permeability of the soil and providing more favorable conditions for the root growth of crops.

In a possible implementation, before step 202, the method further includes constructing a nonlinear boundary region according to the boundary information, performing boundary smoothing on a boundary of the nonlinear boundary region, determining an extreme point region in the nonlinear boundary region, and performing nonlinear spiral path design on the nonlinear boundary region according to the extreme point region.

As shown in fig. 4, the nonlinear boundary region is configured to include a plurality of straight lines and/or curves connected end to end, and is a closed region. Wherein the nonlinear boundary region may be expressed as:

Wherein L is a nonlinear boundary region, L _i is an ith curve, and n is the total number of curves constituting the nonlinear boundary region.

For each curve in the nonlinear boundary region, it can be assumed that each segment of curve L _i (where i=1, 2,..n-1, n) is a continuous and differentiable path in the plane. These paths may be parameterized, such as L _i＝_i (), where t is a parameter and r _i () is a two-dimensional vector function representing points on the curve.

Further, the endpoints of these curves may be defined. For example, assume that the starting point of L _i is P _i and the end point is P _i+1 (where P _n+1＝₁ may be ordered to represent a closure). Thus, each segment of curve L _i connects points P _i and P _i+1. A closed planar region R can be formed, which is enclosed by the curved sections L _i described above. The planar region R can express:

t _1,2,…,t_n holds for i in the region and all t _i,t_i+1 such that x is located on the path from r _i(_i) to r _i+1(_i+1).

Wherein, to ensure the closure of the region, it may be required that the end point of r _n(_n) coincides with the start point of r ₁(₁), i.e. P _n+1＝₁, to ensure the closure of the region.

The boundary smoothing of the nonlinear boundary described above may be performed by an arc.

For example, if the boundary L is smoothed with an arc having a radius r such that the minimum radius of curvature of the smoothed curve is greater than r, the curvature of the curve needs to be constrained. Where curvature is a measure of the degree of curvature of a curve at a point.

For a two-dimensional curve y=f (x), its curvature can be expressed as:

for the parameterized curve r (t) = (x (t), y (t)), its curvature can be expressed as:

the extreme point region determination herein may be classified into a single-pole value region determination and a multi-pole value region determination.

Wherein, as shown in FIG. 5, the monopole value point area can be determined by constructing an inscribed circle O-O ₁ and an circumscribed circle O-O ₂ based on a nonlinear boundary L ₁-L₂-…L_n-1-L_n, and a plurality of intermediate circles O-O _x interposed between the inscribed circle and the circumscribed circle, the origin of which constitute an origin area having a radius not exceeding r _L. This O-r _L region is taken as the pole region of the nonlinear region and as the inscribed circle radius r _o1, the circumscribed circle radius r _o2 and the intermediate circle radius r _ox.

As shown in FIG. 6, the multipole point region may be determined by constructing an inscribed circle O ₃-O₃、O₅-O₅, an circumscribed circle O ₃-O₄、O₅-O₆, and a plurality of intermediate circles O ₃-O_x、O₅-O_x interposed between the inscribed circle and the circumscribed circle on the basis of the nonlinear boundary, the origin of the plurality of intermediate circles, the inscribed circle, and the circumscribed circle constituting an origin region having a radius not exceeding r _L3、r_L2.

The criterion for judging whether the areas O ₃-r_L3、O₅-r_L5 are coincident is as follows:

0<r_L3<D,0<r_L5<D,r_L3+r_L5<D;

i.e., the distance between the two poles is greater than the sum of the radii of the two poles, the nonlinear region can be considered to have two poles.

In one possible implementation, step 202 includes constructing a contour equation based on boundary information, obtaining a plurality of paths based on the contour equation, and merging the plurality of paths into one path.

Wherein the contour equation can be expressed as:

S_Q=k*d;

Where k is the number of path layers generated by the target and d is the track width of the target device or the path row width in the target area.

The contour equations herein are configured to divide the target area into a plurality of spiral paths.

In one embodiment, the travel path may be generated based on archimedes equidistant spirals.

Among them, archimedes' spiral is an equidistant spiral, and in some special situations, an equidistant constant-speed environment (for example, when intelligent agricultural machinery works in farmland) is needed. The Archimedes spiral line can effectively cover complex geometric areas, overlap and gaps among paths are reduced, and filling efficiency is improved. And only one sharp turn is arranged in the center, and other parts are relatively smooth, so that the generated path is smoother in practical application, and continuity and quality in the operation process are facilitated.

The archimedes spiral is characterized herein by a radius proportional to the angle, and the polar equation for the archimedes spiral can be expressed as:

r_f＝a+bθ_f;

where r _f is the distance from the origin to the point f on the curve, a, b are constants, and θ _f is the angle from the starting axis to the point f. a is used to control the shape of the spiral and b is used to control the tightness of the spiral.

It will be appreciated that archimedes' spiral exhibits many advantageous properties in the path planning of a target device. Advantages of archimedes' spiral may include:

(1) Equidistant constant speed coverage, that is, the radius of the Archimedes spiral linearly increases with angle, so that the Archimedes spiral has uniform spacing in a two-dimensional space. The characteristic is very suitable for planning the path of special environment operation (such as farmland operation), can ensure that the target equipment keeps equidistant constant-speed movement during operation, improves the coverage efficiency and reduces the resource waste.

(2) Reducing path overlap and gaps the archimedes spiral can effectively cover complex geometric areas, reducing overlap and gaps between paths. Therefore, the working path is optimized, time and fuel can be saved, and the overall efficiency of the operation is improved.

(3) Smooth path, in the course of path generation, the Archimedes spiral has only one sharp turn in the centre, and other parts are relatively smooth. The path planning ensures that the target equipment moves more smoothly during operation, is beneficial to improving the continuity and quality of the operation process and reduces the mechanical abrasion and operation error.

In practical agricultural application, the Archimedes spiral path planning method can be widely used for seeding, fertilizing, spraying and other operations. The intelligent agricultural machinery can accurately move along a preset Archimedes spiral track, so that the full coverage of farmlands is ensured. Through optimizing the travel path, not only can the quality and the efficiency of operation be promoted, but also the small crushed field land utilization efficiency can be promoted.

In one embodiment, in order to enable the target device to continuously travel in the target area, after dividing the target area into multiple paths, the multiple paths are further required to be opened and combined, so as to obtain a completed travel path. The combined path is a driving path.

As described above, the target area may include one or more extreme points, and the extreme points of the target area may be selected according to the actual situation.

It will be appreciated that in order to integrate the travel path with the actual scene, it is also necessary to project the waypoints on the path to the actual exact location of the target area after optimizing the travel path.

Illustratively, if the target area is a farm field, the target device is an intelligent agricultural machine. Then before selecting the farmland operation path, the original two longitude and latitude points of the actual map boundary may be obtained first, as shown in fig. 7 (two points A, B are shown in fig. 7), and after path planning, the projection coefficient k is calculated:

Wherein lat _A is the A-point dimensional coordinate point, lon _A is the A-point precision coordinate point, X _A is the A-point path transverse point position, and Y _A is the A-point path longitudinal point position.

After the projection coefficient is acquired, the complete actual path point information can be acquired through a projection function:

M_i＝N_i+k·P_i;

Where N _i is the longitude and latitude coordinates of the path start point, and P _i is the control point coordinates.

In one possible implementation, as shown in fig. 8, the nonlinear spiral path design is performed on the nonlinear boundary area according to the extremum point area, and the nonlinear spiral path design comprises the steps of constructing a plurality of nonlinear equidistant paths with a first set interval inside the nonlinear boundary by taking the extremum point as the center until the interval between adjacent paths is smaller than a second set interval, selecting a position point on any path as the first position point, determining a second position point adjacent to the first position point on the same path according to the body parameters of target equipment, wherein the first position point is the starting point, determining a third position point closest to the second position point on the former path on the latter path adjacent to the former path for each path, determining a second position point adjacent to the third position point on the same path according to the body parameters of the target equipment until the corresponding position point is found in each path, disconnecting the connection line between the two adjacent position points on each path, and connecting the two position points closest to the adjacent two paths to each other to obtain one path.

The first set interval can be determined according to the number of paths in the nonlinear boundary region, can be set in advance according to actual requirements, and can be set according to actual conditions.

The second set pitch may be a multiple of the first device pitch, for example, 2 times.

In one embodiment, after constructing a plurality of nonlinear equidistant paths with a first set pitch inside the nonlinear boundary, obtaining a nonlinear spiral path, further searching a maximum curvature area in the nonlinear spiral path, determining a first position point, a second position point and a third position point in the maximum curvature area, and communicating adjacent paths through the first position point, the second position point and the third position point.

As indicated above, this region of maximum curvature may be determined by the following equation:

The region corresponding to the minimum value of k is the maximum curvature region.

The first location point here is the starting point.

It will be appreciated that in order to reduce the invalid travel path of the target device, the first location point may select a location point of the plurality of paths that is closest to the target device.

The shape parameter herein refers to the shape parameter of the target device. Such as the length of the target device, the width of the target device, the height of the target device, etc. The shape parameter may be selected according to what is the case.

It should be appreciated that in order to ensure that the target device reaches as far as possible each region in each path during travel, the distance between the first location point and the second location point may be determined according to the width of the target device in the direction perpendicular to the movement direction of the target device. That is, the distance between the first position point and the second position point is equal to or greater than the width of the target device in the direction perpendicular to the movement direction of the target device.

After determining the first and second location points on the previous path, it is necessary to continue determining the two location points on the next path. When the third position point on the next path is determined, the third position point can be determined according to the second position point on the previous path, and the distance of the target device moving from the next path to the next path can be reduced by setting the third position point as the position point closest to the second position point on the next path, so that the ineffective movement of the target device is reduced. Similarly, after the third location point is determined on the next path, the second location point on the next path may be further determined according to the width of the target device along the direction perpendicular to the direction of movement of the target device. The iteration is continued in this manner until a respective second location point and third location point is found in each of the plurality of paths.

After the second position point and the third position point in each path are determined, the paths can be combined into one path by disconnecting the connecting line between two adjacent position points on each path and connecting two position points which are closest to each other on the two adjacent paths.

Illustratively, as shown in fig. 8, a point P ₁ is first selected as a starting point (i.e., a first position point) of the connection curve on the boundary, then a point P ₂ in the same layer path is found according to the shape parameter, and a point P ₃ is found based on the track-withdrawal value d of the point P ₂. Subsequently, by removing the curve in between P ₁ and P ₂, connecting points P ₂ and P ₃, a layer of contours from P ₁ to P ₃ can be generated. And the same is repeated, the point P ₄、P₅、P₆ is found in sequence, and finally the spiral line end point P _f is found.

Optionally, an outlet line may be further introduced, the Q layer gradient is square downward 2n layer is used as an inlet layer, the Q layer gradient is square downward 2n-1 layer is used as an outlet layer, and the above iterative process is performed, so as to finally generate a monopole value point equidistant archimedes spiral line as shown in (d) of fig. 4.

The pitch of the outlet lines may be set to half the first set pitch.

In a possible implementation manner, a plurality of nonlinear equidistant paths with first set pitches are built in nonlinear boundaries by taking extreme points as centers until the pitches of adjacent paths are smaller than second set pitches, the method comprises the steps of building a plurality of nonlinear equidistant paths with first set pitches in each nonlinear boundary by taking each extreme point as a center until the pitches of adjacent paths in each nonlinear boundary are smaller than second set pitches, judging whether paths corresponding to the adjacent extreme points can be connected, connecting the adjacent paths by conducting edge breaking reconnection operation on boundary paths of the paths corresponding to the adjacent extreme points under the condition that the paths corresponding to the adjacent extreme points are determined to be connectable, selecting a position point on any one path in the whole paths formed after the adjacent paths are connected as a first position point, determining a second position point adjacent to the first position point on the same path according to body parameters of target equipment, determining a third position point closest to the second position point on the previous path on the latter path adjacent to the former path, determining a body parameter of the latter path on the former path according to the body parameters of each path, and finding a connection between two adjacent points on the second position point on the same path until the two paths are disconnected, and finding a connection between two adjacent positions on the two paths.

It can be appreciated that when the nonlinear boundary includes a plurality of extreme points, a plurality of nonlinear equidistant paths with a first set pitch may be constructed for each extreme point, so as to obtain a plurality of nonlinear spiral paths. For adjacent nonlinear spiral paths, whether the adjacent nonlinear spiral paths can be connected can be judged, and if the adjacent nonlinear spiral paths can be connected, the adjacent nonlinear spiral paths are combined.

Optionally, before judging whether the paths corresponding to the adjacent extreme points are connectable, the method further comprises marking each path. For example, Q _i,j represents each path, i is the distance from the path line to the boundary of the target area, j is the distance from the boundary to i, and all paths are stored in the set M.

Here, the direct communication edges of two adjacent paths can be expressed as:

O_i,j,j'＝{p∈Q_i,j|d(p,Q_i+1,j')<d(p,Q_i+1,k),k≠j’};

Where O _i,j,j' is the connected edge, d (p, Q _i+1,j,) represents the closest distance value of the p-point to the point on path Q _i+1,j,, and d (p, Q _i+1,k) represents the closest distance value of the p-point to the point on path Q _i+1,k.

The above-mentioned judgment whether the paths corresponding to the adjacent extreme points are connectable can be achieved by the following means:

If O _i,j,j' is not null, two adjacent edge paths can be connected, an outer boundary is subjected to primary broken edge reconnection operation, a boundary is added between nodes corresponding to Q _i+1,j, and Q _i+1,k, and the weight of an edge is defined as the length value of a connected edge.

If O _i,j,j' is empty, it indicates that two adjacent edge paths cannot be connected, and multiple paths determined according to adjacent extreme points which cannot be connected are combined into one path.

In one embodiment, selecting a location point on any one path as a first location point and determining a second location point adjacent to the first location point on the same path according to a shape parameter of the target device includes selecting a location point on any one path of an overall path formed after connecting adjacent paths as the first location point and determining a second location point adjacent to the first location point on the same path according to the shape parameter of the target device.

As can be understood, for the multiple extreme point region, when the paths corresponding to the adjacent extreme points can be opened before combining the multiple paths into one path, the paths corresponding to the adjacent extreme points are opened first, and the entire path including the multiple extreme points is obtained (as shown in fig. 9, fig. 9 (a) shows the combined travel path, and fig. 9 (b) shows the combined travel path in which the return path is added). Then, the area where the overall path is located can be regarded as a single-pole value point area, and each path in the overall path is merged into one path according to the merging mode of the single-extreme point area.

In one possible implementation, step 201 includes preprocessing a captured target image of a target region, initializing a level set function, calculating an image gradient of the target image, determining a boundary of the target region in the target image according to the image gradient, updating the level set function by regularizing a level set evolution equation, and outputting boundary information of the target image in a case where the level set function approaches the boundary of the target region.

The regularized level set evolution is a method for image segmentation, which combines a level set method and a regularization technology, and the level set method is a numerical technology for tracking the evolution of a shape boundary along with time. The method represents the boundary by an implicit function and treats the boundary as a zero level set for the function. The core idea is to evolve the level set function by solving the partial differential equation so that it gradually approaches the target boundary. Regularization techniques stabilize and optimize problem solving by introducing a priori information or constraints. Regularization can help handle noise and incomplete data, prevent overfitting, and improve the generalization ability of the model in image processing and computer vision.

Regularized level set evolution combines the advantages of both methods described above by introducing regularization terms during level set evolution to control and adjust the smoothness and shape of the boundaries. The method represents the target boundary by evolving an implicit function, and ensures the smoothness and stability of the boundary by utilizing regularization terms, so that the target object in the image is effectively segmented.

The regularization level set evolution technology is widely applied to the fields of medical image segmentation, target tracking, object recognition and the like, and can be suitable for processing complex shape and topology changes, providing smooth and continuous segmentation boundaries, processing targets with complex and various shapes and processing images with more noise or blurred boundaries.

In the agricultural field, the extraction of farmland boundaries is a great difficulty in agricultural unmanned. Farms often have a non-standardized, complex background that includes different types of plants, weeds, etc., which increase the complexity of the image. In addition, there are a lot of noise and varying obstacles in the farmland environment, such as farm tools, animals, shadows, etc., and complicated and varied topography of the pits, which makes boundary extraction more difficult. By adopting regularized level set evolution technology to extract boundary information, the accuracy of boundary extraction can be improved, and the efficiency of unmanned agricultural operation can be obviously improved.

The preprocessing here may include gaussian filtering to remove noise from the target image. The formula of the gaussian filtering process may be:

where x is a distance variable of the gaussian function in the horizontal direction, y is a distance variable of the gaussian function in the vertical direction, and σ is a standard deviation of the gaussian function, for controlling the width of the gaussian distribution. The larger the σ, the larger the width of the gaussian function, and the more pronounced the blurring effect.

The image gradient described above can be calculated by the following formula:

Wherein I _X represents a gradient value in the horizontal direction, I _y represents a gradient value in the vertical direction, and img is a set of pixel points in the target image.

It should be appreciated that, when the image gradient of the target image is calculated, the boundary of the target region may be further determined according to the image gradient.

In one embodiment, the boundary of the target region may highlight the edge of the target image by constructing an edge indicating function. Wherein the edge indication function can be expressed as:

Where f is the intensity of the image gradient, and g represents the edge that is emphasized by suppressing the region where the gradient intensity is high.

The level set evolution equation here can be expressed as:

wherein delta (phi) is a dirac function, For the curvature term, F (F, phi) is the external force term. The dirac function is used to ensure that evolution only occurs at zero level of the level set, the curvature term is used to control the smoothness of the level set, and the external force term is used to drive the level set to evolve.

It should be understood that the regularized level set evolution equation is based on the level set evolution equation, so that the regularized level set evolution equation can capture important edges in the target image and maintain the smoothness and stability of the level set function, thereby improving the effects of image segmentation and edge detection.

The regularized level set evolution equation described above can be expressed as:

Where μ is a parameter controlling regularization term for smoothing the level set function phi, λ is a parameter controlling internal energy term, typically related to image features, and ν is a parameter controlling external energy term for driving level set evolution.

It can be appreciated that in the process of acquiring the boundary information of the target image, the regularized level set evolution equation can be iteratively solved by continuously updating the level set function, so that the boundary information of the target image is output under the condition of the regularized level set evolution equation.

Based on the same application conception, the embodiment of the present application further provides a path planning device corresponding to the path planning method, and since the principle of the device in the embodiment of the present application for solving the problem is similar to that of the foregoing path planning method embodiment, the implementation of the device in the embodiment of the present application may refer to the description in the foregoing method embodiment, and the repetition is omitted.

Fig. 10 is a schematic functional block diagram of a path planning apparatus according to an embodiment of the present application. Each module in the path planning apparatus in this embodiment is configured to perform each step in the above-described method embodiment. The path planning device comprises an acquisition module 301, a determination module 302 and an optimization module 303;

Wherein,

The acquisition module 301 is configured to acquire boundary information in a target area.

The determining module 302 is configured to determine a driving path of the target device according to the boundary information.

The optimizing module 303 is configured to optimize a set position point in the driving path through a local path planning algorithm, where the target device is configured to drive in the target area according to the optimized driving path.

In a possible implementation manner, the optimization module 303 is further configured to calculate curvature of each point in the running path, traverse all the position points in the running path, determine a point set that does not meet curvature constraint conditions, and perform optimization processing on paths adjacent to the point set through the B-spline curve optimization algorithm.

In a possible implementation manner, the optimization module 303 is specifically configured to establish a non-uniform rational B-spline curve, construct an objective function according to the non-uniform rational B-spline curve, wherein the objective function is configured to define a distance between a minimized path and an actual position point, and establish an optimization model based on the objective function and the curvature constraint condition, wherein the optimization model is configured to perform optimization processing on paths adjacent to the point set.

In a possible implementation manner, the path planning device further comprises a design module, wherein the design module is used for constructing a nonlinear boundary area according to the boundary information, conducting boundary smoothing on the boundary of the nonlinear boundary area, determining an extreme point area in the nonlinear boundary area, and conducting nonlinear spiral path design on the nonlinear boundary area according to the extreme point area.

In a possible implementation manner, the determining module 302 is further configured to construct a contour equation according to the boundary information, obtain a plurality of paths according to the contour equation, and combine the paths into one path, where the combined path is the driving path.

In a possible implementation manner, a design module is specifically configured to construct a plurality of nonlinear equidistant paths with a first set pitch inside the nonlinear boundary with the extreme point as a center until the distance between adjacent paths is smaller than a second set pitch, select a position point on any one path as a first position point, determine a second position point adjacent to the first position point on the same path according to a shape parameter of the target device, wherein the first position point is a starting point, determine, for each path, a third position point closest to the second position point on the previous path on a subsequent path adjacent to the previous path, and determine, according to a shape parameter of the target device, a second position point adjacent to the third position point on the same path until a corresponding position point is found in each path of the plurality of paths, disconnect a connection line between two adjacent position points on each path, and connect the two position points closest to each path to each other to obtain one path.

In a possible implementation manner, a design module is specifically configured to construct a plurality of nonlinear equidistant paths with a first set pitch inside each nonlinear boundary by taking each extreme point as a center until the distance between adjacent paths inside each nonlinear boundary is smaller than a second set pitch, determine whether paths corresponding to adjacent extreme points are connectable, connect adjacent paths by performing a broken edge reconnection operation on boundary paths of paths corresponding to adjacent extreme points when the paths corresponding to adjacent extreme points are determined to be connectable, select a position point on any one of the whole paths formed after connecting the adjacent paths as a first position point, determine a second position point adjacent to the first position point on the same path according to a body parameter of the target device, wherein the first position point is a starting point, determine a third position point closest to the second position point on the previous path on a later path adjacent to the previous path, determine a position point closest to the third position point on the same path according to a body parameter of the target device, and determine a connection between two adjacent positions on the same path and the two adjacent paths according to the body parameter of the target device.

In a possible implementation manner, the determining module 302 is specifically configured to select a location point as a first location point on any one of the overall paths formed after connecting adjacent paths, and determine, according to the shape parameter of the target device, a second location point adjacent to the first location point on the same path, where the first location point is a starting point.

In a possible implementation manner, the obtaining module 301 is further configured to pre-process the acquired target image of the target area, initialize a level set function, calculate an image gradient of the target image, determine a boundary of the target area in the target image according to the image gradient, update the level set function by regularizing a level set evolution equation, and output the boundary information of the target image if the level set function approaches the boundary of the target area.

Furthermore, the embodiment of the present application also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor performs the steps of the path planning method described in the above method embodiment.

The computer program product of the path planning method provided by the embodiment of the present application includes a computer readable storage medium storing program codes, where the instructions included in the program codes may be used to execute the steps of the path planning method described in the above method embodiment, and specifically, reference may be made to the above method embodiment, which is not described herein.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes. It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that comprises the element.

The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application. It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. A method of path planning, comprising:

Acquiring boundary information in a target area;

determining a driving path of the target equipment according to the boundary information;

optimizing set position points in the driving path through a local path planning algorithm;

Wherein the target device is configured to travel in the target area according to the optimized travel path.

2. The method according to claim 1, wherein the local path planning algorithm is a B-spline optimization algorithm, and the optimizing the set position points in the driving path by the local path planning algorithm includes:

calculating the curvature of each point in the running path;

traversing all the position points in the driving path, and determining a point set which does not meet curvature constraint conditions;

and optimizing the paths adjacent to the point set through the B spline curve optimization algorithm.

3. The method of claim 2, wherein optimizing paths adjacent to the set of points by the B-spline curve optimization algorithm comprises:

Establishing a non-uniform rational B spline curve;

Constructing an objective function according to the non-uniform rational B-spline curve, wherein the objective function is configured to define a distance between a minimized path and an actual position point;

establishing an optimization model based on the objective function and the curvature constraint condition;

Wherein the optimization model is configured to optimize paths adjacent to the set of points.

4. The method of claim 1, wherein the boundary information comprises a boundary path;

Before the driving path of the target device is determined according to the boundary information, the method further comprises:

Constructing a nonlinear boundary region according to the boundary information;

Performing boundary smoothing on the boundary of the nonlinear boundary region;

determining an extreme point region in the nonlinear boundary region;

And designing a nonlinear spiral path according to the extreme point region.

5. The method of claim 4, wherein the extreme point region in the nonlinear boundary region is a monopolar value point region;

the step of designing the nonlinear spiral path according to the extreme point region, includes:

Constructing a plurality of nonlinear equidistant paths with first set spacing inside the nonlinear boundary by taking the extreme point as a center until the spacing between adjacent paths is smaller than the second set spacing;

Selecting a position point on any path as a first position point, and determining a second position point adjacent to the first position point on the same path according to the shape parameter of the target equipment, wherein the first position point is a starting point;

determining a third position point which is closest to a second position point on a previous path on a next path adjacent to the previous path for each path, and determining the second position point adjacent to the third position point on the same path according to the shape parameters of the target equipment until the corresponding position point is found in each path in the plurality of paths;

And disconnecting the connecting line between two adjacent position points on each path, and connecting two position points closest to the two adjacent paths to obtain one path.

6. The method of claim 4, wherein the extreme point region in the nonlinear boundary region is a multipole point region, wherein the constructing a plurality of nonlinear equidistant paths of a first set pitch inside the nonlinear boundary centered on the extreme point until adjacent path pitches are less than a second set pitch comprises:

respectively taking each extreme point as a center, and constructing a plurality of nonlinear equidistant paths with a first set interval in each nonlinear boundary until the interval between adjacent paths in each nonlinear boundary is smaller than a second set interval;

judging whether paths corresponding to adjacent extreme points can be connected or not;

Under the condition that the paths corresponding to the adjacent extreme points are determined to be connectable, connecting the adjacent paths by performing broken edge reconnection operation on the boundary paths of the paths corresponding to the adjacent extreme points;

Selecting a position point on any one of the integral paths formed after connecting adjacent paths as a first position point, and determining a second position point adjacent to the first position point on the same path according to the shape parameter of the target equipment, wherein the first position point is a starting point;

7. The method of claim 1, wherein the acquiring boundary information in the target area comprises:

Preprocessing the acquired target image of the target area;

initializing a level set function and calculating an image gradient of the target image;

Determining the boundary of the target area in the target image according to the image gradient;

updating the level set function by regularizing a level set evolution equation;

The boundary information of the target image is output in a case where the level set function approaches a boundary of the target region.

8. A path planning apparatus, comprising:

The acquisition module is used for acquiring boundary information in the target area;

The determining module is used for determining the driving path of the target equipment according to the boundary information;

The optimizing module is used for optimizing the set position points in the driving path through a local path planning algorithm;

9. An electronic device comprising a processor, a memory storing machine-readable instructions executable by the processor, which when executed by the processor perform the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any of claims 1 to 7.