Intelligent path planning method and system for pure electric shellfish harvesting machine

Abstract

The present invention discloses an intelligent path planning method and system for a pure electric shellfish collecting machine. The present invention performs grid processing on the shellfish collecting area, and performs trial picking and dotting on each grid area to form a matrix diagram capable of displaying the density distribution of each grid area; when the shellfish collecting machine is in the grid area, it has eight travel directions, and the grid area with the shortest path and the largest shellfish distribution density is selected from the eight travel directions as the starting point of the shellfish collecting machine, and when the shellfish collecting machine is in the grid area where the starting point is located, the grid area with the shortest path and the largest shellfish density distribution is also found from the eight travel directions around it as the next node of the shellfish collecting machine, and so on, until the entire tidal flat shellfish collecting area is traversed; finally, a shellfish collecting path is formed through the shellfish collecting nodes determined previously, and the shellfish collecting machine moves to each grid area in turn according to the shellfish collecting path and performs shellfish collecting and excavation, so as to realize traversal and shellfish collecting and excavation from the high-density breeding area to the low-density breeding area in the shortest time.

Description

Technical Field

[0001] The present invention relates to the technical field of electric shellfish collecting machines, and in particular to path planning of pure electric shellfish collecting machines, and specifically to an intelligent path planning method and system for pure electric shellfish collecting machines. Background Art

[0002] my country has vast sea areas, long coastlines and extensive coastal tidal flats. Vigorously developing tidal flat shellfish farming not only effectively develops and utilizes land resources, but also provides an effective way for fishermen to change their jobs and production. However, at present, the harvesting of shellfish and seafood mostly adopts the method of manual excavation, which is labor-intensive and takes a long time to harvest. In addition, sand and other debris must be removed manually, which directly affects the speed and efficiency of harvesting, and thus affects the development of tidal flat shellfish farming.

[0003] In order to solve the above problems, the prior art has studied some shellfish harvesting devices to replace manual shellfish harvesting, such as a multifunctional shallow sea mudflat shellfish harvesting vehicle disclosed in Chinese patent publication number CN107018964A on August 8, 2017, and a shellfish harvesting device disclosed in Chinese patent publication number CN205547051U on September 7, 2016. Although these harvesting devices reduce the labor intensity of manual shellfish harvesting, due to the lack of scientific shellfish harvesting path planning, there are still problems of long harvesting time and low harvesting efficiency.

[0004] With the rise of automation, intelligent navigation and path planning have become research hotspots. Existing path planning generally includes shortest path planning and traversal path planning. Among them, the shortest path planning usually constructs all the path points of the entire map into a graph, and then searches for the shortest path based on the graph to obtain the best path, such as depth or breadth first algorithm, Floyd algorithm, Dijkstra algorithm, Bellman-Ford algorithm, etc. The methods of traversal path planning include ant colony algorithm, behavior coverage method, region segmentation method, neural network method, etc.

[0005] The path for collecting shellfish on the beach is an obstacle-free path. Its path planning must not only meet the shortest path between the starting point and the end point, but also meet the requirements of traversing and collecting from high-density breeding areas to low-density breeding areas. The Chinese patent with publication number CN112805647A disclosed a path planning method on October 2, 2019. The method can determine an obstacle-free path between the starting point and the target point, but it cannot meet the requirements of traversing and collecting from high-density breeding areas to low-density breeding areas. Summary of the invention

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides an intelligent path planning method and system for a pure electric shellfish collecting machine, which can complete the shellfish collecting process in the shortest time without missing or repeating the collection, thereby achieving the effect of short collection time and high collection efficiency.

[0007] According to one aspect of the present invention, there is provided an intelligent path planning method for a pure electric shellfish collecting machine, comprising:

[0008] Discretize the environmental map of the shellfish collection area and construct a grid map of the shellfish collection area according to preset intervals;

[0009] Trial picking and marking are performed on each grid area in the grid map of the shellfish collection area to obtain the density distribution of shellfish in each grid area and generate a density distribution map of the entire shellfish collection area;

[0010] Taking the current position of the shell collecting machine as the center, from the grid areas involved in the eight directions of the shell collecting machine, the grid area with the shortest path and the highest density is selected as the starting point of the shell collecting machine; then taking the grid area where the starting point is as the center, from the grid areas involved in the eight directions of the shell collecting machine, the grid area with the shortest path and the highest density is selected as the next shell collecting node of the shell collecting machine; and so on, until the entire shell collecting area is traversed, and a shell collecting path formed by several shell collecting nodes is obtained;

[0011] The shell collecting machine moves to each grid area in sequence along the shell collecting path, and collects and excavates shells in the grid area according to the preset excavation path.

[0012] The above technical scheme first processes the tidal flat shellfish collection area with grids, and performs trial picking and dotting on each grid area to form a matrix diagram that can display the density distribution of each grid area, so as to take into account both the optimal path and the optimal shellfish distribution density when planning the path; when the shellfish collection machine is in the grid area, it has eight travel directions, and the grid area with the shortest path and the largest shellfish distribution density is selected from the eight travel directions as the starting point of the shellfish collection machine. When the shellfish collection machine is in the grid area where the starting point is located, there are also eight travel directions around it, and the grid area with the shortest path and the largest shellfish density distribution is found from the eight travel directions around it as the next node of the shellfish collection machine, and so on, until the entire tidal flat shellfish collection area is traversed, ensuring that one or more grid areas will not be missed or repeatedly collected during the shellfish collection process; finally, a shellfish collection path is formed through the shellfish collection nodes determined previously, and the shellfish collection machine moves to each grid area in turn according to the shellfish collection path and performs shellfish collection and excavation, thereby realizing traversal and shellfish collection and excavation from high-density breeding areas to low-density breeding areas in the shortest time.

[0013] As a further technical solution, when each grid area is trial-picked and marked one by one, the number of trial-picked and marked points in each grid area is distinguished by color, and a density distribution matrix diagram is generated in which the density of shellfish in the grid area is represented by color.

[0014] As a further technical solution, the preset excavation path is set as a U-shaped path, and the shellfish collecting machine excavates from the outer periphery of the grid area to the inside along the U-shaped path. When the shellfish collecting machine moves to the grid area, it enters from the boundary of the grid area and excavates the grid area along the U-shaped path, thereby avoiding missed or repeated collection in the current grid area to the greatest extent.

[0015] As a further technical solution, the preset excavation path is set to a zigzag path, and the shellfish collecting machine excavates shellfish from one side of the grid area to the other side according to the zigzag path. When the shellfish collecting machine advances to the grid area, it enters from the boundary of the grid area, and excavates shellfish from one side of the grid area to the other side according to the zigzag path, thereby avoiding missed collection or repeated collection in the current grid area to the greatest extent. The collection density of the zigzag path can be set according to the shellfish density distribution. For the grid area with a larger shellfish density distribution, a denser zigzag path is set, and for the grid area with a smaller shellfish density distribution, a sparser zigzag path is set, which not only avoids missed collection or repeated collection in the grid area, but also avoids excessive collection in the area with a smaller density distribution, resulting in waste of shellfish collecting machine resources.

[0016] As a further technical solution, the method further includes: performing secondary shellfish collection and excavation on the grid area where the shellfish distribution density is greater than a preset value. Because the density distribution of shellfish on the beach varies greatly, and the shellfish density in some areas is very high, it is difficult to collect all the shellfish in one collection. Secondary collection is required to avoid missing shellfish in this area and causing waste. Therefore, after completing a traversal shellfish collection process, for some grid areas with a large shellfish density distribution, the path can be re-planned for secondary collection.

[0017] In the above technical solution, the preset value of the shellfish distribution density can be determined by experience. Once it is greater than the preset value, it is considered that the shellfish in the area are difficult to be collected in one go, and a second collection is required in the area.

[0018] As a further technical solution, the method adopts the A* algorithm to find the shortest path, and the objective function adopted is f(n)=g(n)+h(n), wherein g(n) is the actual cost value from the starting point of the shellfish collection path to the shellfish collection node n, h(n) is the heuristic function and is in a two-dimensional normal distribution, and the independent variable of h(n) is the shellfish distribution density. While finding the optimal path, the shellfish distribution density factor is considered, and the area with the best path and the highest density is selected as the target area, so as to realize the traversal and collection of the entire tidal flat shellfish collection area from the high-density area to the low-density area in the shortest time.

[0019] According to another aspect of the present invention, there is provided an intelligent path planning system for a pure electric shellfish collecting machine, comprising:

[0020] A grid map generation module is used to discretize the environmental map of the shellfish collection area and construct a grid map of the shellfish collection area according to preset intervals;

[0021] The dotting statistics module is used to count the number of trial pickings in each grid area when trial picking and dotting are performed on each grid area in the grid map of the beetle area;

[0022] A density distribution map generating module is used to determine the density distribution of shellfish in each grid area according to the number of trial picks in each grid area, and generate a density distribution map of the entire shellfish picking area;

[0023] The shell picking path generation module is used to select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine, with the current location of the shell picking machine as the center; then, with the grid area where the starting point is located as the center, select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine as the next shell picking node of the shell picking machine; and so on, until the entire shell picking area is traversed, and a shell picking path formed by several shell picking nodes is obtained;

[0024] The shellfish collecting and excavation module is used to enable the shellfish collecting machine to move to each grid area in sequence according to the shellfish collecting path, and to collect and excavate the grid area according to the preset excavation path.

[0025] The above technical scheme obtains the environmental map of the shellfish collection area, discretizes and intervals the environmental map, and forms a shellfish collection area grid map composed of grid areas. Since the shellfish density in each grid area is different, each grid area is firstly tested for picking and marking to obtain the shellfish density distribution of each grid area and merge the density distribution into the grid map to form a shellfish collection area grid map with shellfish density display; on this basis, the path planning of the shellfish collection machine is carried out, and the grid area with the shortest path and the largest density in the direction of travel of the shellfish collection machine is selected as the starting point. Point, and with the area where the shellfish collecting machine is currently located as the center, select the grid area with the closest path and the largest density from the direction of travel of the shellfish collecting machine as the next node, and so on until the entire shellfish collecting area is traversed, and a shellfish collecting path formed by several shellfish collecting nodes is obtained. This shellfish collecting path takes into account the optimal path and the collection strategy from high-density breeding areas to low-density breeding areas, which not only avoids missed collection or repeated collection in the grid area, but also improves the overall collection efficiency; shellfish excavation is carried out according to the shellfish collecting path, so as to complete the shellfish collecting process from high-density breeding areas to low-density breeding areas in the shortest time.

[0026] As a further technical solution, the system also includes an excavation path setting module, which is used to set the excavation path of the shellfish collecting machine in each grid area, including a zigzag path and a zigzag path. When the shellfish collecting machine advances to the grid area, it enters from the boundary of the grid area and excavates shellfish in a zigzag or zigzag path, thereby avoiding missed collection or repeated collection in the current grid area to the greatest extent. The collection density of the zigzag or zigzag path can be set according to the shellfish density distribution. A denser collection path is set for the grid area with a larger shellfish density distribution, and a sparser collection path is set for the grid area with a smaller shellfish density distribution, thereby avoiding missed collection or repeated collection in the grid area, and avoiding excessive collection in the area with a smaller density distribution, which leads to waste of shellfish collecting machine resources.

[0027] As a further technical solution, the system also includes a screening module for screening out grid areas where the density of shellfish distribution is greater than a preset value, and sending the screened grid areas to the shellfish collection path generation module to generate a secondary shellfish collection path based on these grid areas. Since the density distribution of shellfish on the tidal flats varies greatly, the shellfish density in some areas is very high, and it is difficult to collect them all in one collection. Secondary collection is required to avoid missing shellfish in this area and causing waste. Therefore, after completing a traversal shellfish collection process, for some grid areas with a large shellfish density distribution, it is necessary to re-plan the path for secondary collection to ensure the collection effect.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] (1) The present invention firstly performs grid processing on the tidal flat shellfish collection area, and performs trial picking and marking on each grid area to form a matrix diagram that can display the density distribution of each grid area, so as to take into account both the optimal path and the optimal shellfish distribution density when planning the path; when the shellfish collection machine is in the grid area, it has eight travel directions, and the grid area with the shortest path and the largest shellfish distribution density is selected from the eight travel directions as the starting point of the shellfish collection machine; when the shellfish collection machine is in the grid area where the starting point is located, there are also eight travel directions around it, and the grid area with the shortest path and the largest shellfish density distribution is found from the eight travel directions around it as the next node of the shellfish collection machine, and so on, until the entire tidal flat shellfish collection area is traversed, ensuring that one or more grid areas will not be missed or repeatedly collected during the shellfish collection process; finally, a shellfish collection path is formed through the shellfish collection nodes determined previously, and the shellfish collection machine moves to each grid area in turn according to the shellfish collection path and performs shellfish collection and excavation, thereby realizing traversal and shellfish excavation from high-density breeding areas to low-density breeding areas in the shortest time.

[0030] (2) When the shellfish collecting machine of the present invention is in operation, it gradually works from the area with the highest breeding density to the area with the lowest breeding density, and follows the strategy of the shortest path during the traversal process, so as to complete the traversal and collection of the entire shellfish collecting area in the shortest time, avoid missed collection or repeated collection in the grid area, and reduce the missed collection rate in a single grid area through multiple traversals, thereby further improving the economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of a flow chart of an intelligent path planning method for a pure electric shellfish collecting machine according to an embodiment of the present invention.

[0032] Figure 2 Schematic diagram of a grid map of a sampling area according to an embodiment of the present invention.

[0033] Figure 3 Schematic diagram of a shellfish density distribution diagram according to an embodiment of the present invention.

[0034] Figure 4 The figure is a schematic diagram of the secondary collection process of the intelligent path planning method for a pure electric shellfish collecting machine according to an embodiment of the present invention.

[0035] Figure 5 FIG. 4 is a schematic diagram of multiple grid regions according to an embodiment of the present invention.

[0036] Figure 6 FIG. 4 is a schematic diagram of path planning for multiple grid areas according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions of various embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0038] On the one hand, the present invention provides an intelligent path planning method for a pure electric shellfish collecting machine, such as Figure 1 As shown, including:

[0039] Step 1: Draw a grid map. First, use the scanning polygon filling method to discretize and quantify the map information, discretize the environmental map into independent grids according to the preset intervals, generate connecting lines at the same intervals, and divide the electric shellfish harvesting machine into grids. The constructed grid map consists of rectangular areas, such as Figure 2 The preset interval can be set according to the actual situation. For example, if it is set to 10m, a grid area of ​​10m×10m is formed.

[0040] Since the sampling area is not a standard rectangle or ellipse, the raster map constructed based on the environmental map is not necessarily a standard matrix map. There may be omissions in some locations or prominent areas in some locations.

[0041] Step 2: Trial picking and dotting of the grid area. Trial picking and dotting are performed at the center of each grid area, and the dotting data of each grid area is counted.

[0042] Step 3, obtain the shellfish density distribution map. According to the statistical dot situation of each grid area, obtain the shellfish density distribution in each grid area, and generate the density distribution grid map of the entire shellfish collection area, such as Figure 3 shown.

[0043] As an implementation method, when trial picking and marking each grid area one by one, the number of trial picking and marking in each grid area is distinguished by color, and a density distribution matrix diagram is generated in which the density of shellfish in the grid area is represented by color. This makes it easier for staff to intuitively see whether the generated density distribution grid diagram is consistent with the actual situation, and use the staff's shellfish picking experience to help improve the accuracy of the density distribution grid diagram.

[0044] Step 4, generate a shell picking path. With the current position of the shell picking machine as the center, select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine as the starting point of the shell picking machine; then, with the grid area where the starting point is located as the center, select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine as the next shell picking node of the shell picking machine; and so on, until the entire shell picking area is traversed and a shell picking path formed by several shell picking nodes is obtained.

[0045] In step 4, the A* algorithm is used to find the shortest path, that is, based on the heuristic search method of the A* algorithm, the objective function used is f(n)=g(n)+h(n), where g(n) is the actual cost value from the starting point of the shellfish collection path to the shellfish collection node n, h(n) is the heuristic function and is in a two-dimensional normal distribution, and the independent variable of h(n) is the shellfish distribution density. While looking for the optimal path, the shellfish distribution density factor is considered, and the area with the best path and the highest density is selected as the target area, so as to realize the traversal and collection of the entire tidal flat shellfish collection area from the high-density area to the low-density area in the shortest time.

[0046] Step 5: shellfish collection and excavation. The shellfish collection machine moves to each grid area in sequence along the shellfish collection path, and collects shellfish and excavates the grid area according to the preset excavation path.

[0047] As an embodiment, the preset excavation path is set as a U-shaped path. When the shellfish collecting machine moves to the grid area, it enters from the boundary of the grid area and excavates shellfish in the grid area using the U-shaped path, thereby avoiding missed or repeated collection in the current grid area to the greatest extent.

[0048] As an embodiment, the preset excavation path is set as a zigzag path. When the shellfish collecting machine moves to the grid area, it enters from the boundary of the grid area and performs shellfish collecting and excavation from one side of the grid area to the other side in a zigzag path, thereby avoiding missed or repeated collection in the current grid area to the greatest extent.

[0049] The collection density of the U-shaped or zigzag path can be set according to the shellfish density distribution. A denser path is set for the grid area with a larger shellfish density distribution, and a sparser path is set for the grid area with a smaller shellfish density distribution. This can avoid missed collection or repeated collection in the grid area, and avoid excessive collection in the area with smaller density distribution, which will lead to waste of shellfish collection machine resources.

[0050] As an embodiment, the method of the present invention also performs secondary shellfish mining in the grid area where the shellfish distribution density is greater than a preset value, such as Figure 4As shown. Because the density distribution of shellfish on the tidal flats varies greatly, the density of shellfish in some areas is very high and it is difficult to collect them all in one collection. Secondary collection is required to avoid missing shellfish in this area and causing waste. Therefore, after completing a traversal of the shellfish collection process, for some grid areas with large shellfish density distribution, the shellfish density distribution matrix diagram can be regenerated and the path planning can be re-performed to achieve secondary collection. The preset value of the shellfish distribution density can be determined by experience. Once it is greater than the preset value, it is considered that the shellfish in this area are difficult to be collected in one collection, and secondary collection is required for this area.

[0051] As an implementation method, a raster map of the shellfish collection area is constructed based on the shellfish collection area environmental map, and a shellfish density distribution map is formed by trial picking and marking each grid area, such as Figure 5 As shown, the shellfish density decreases from 1 to 7, the shellfish density in area 1 is the largest, and the shellfish density in area 7 is the smallest.

[0052] The path planning process for these 7 areas is as follows: Figure 6 As shown, after determining that area 1 is the starting point of the shellfish collecting machine, with area 1 as the center, search in eight directions of travel around area 1, and find area 2 as the grid area with the shortest path and the highest density. Then, with area 2 as the center, search in eight directions of travel around area 2, and find area 5 as the grid area with the shortest path and the highest density. And so on, the order of the 7 areas is determined, and finally the shellfish collecting path formed by area 1, area 2, area 5, area 4, area 3, area 7, and area 6 is output.

[0053] According to another aspect of the present invention, there is provided an intelligent path planning system for a pure electric shellfish collecting machine, comprising: a grid map generation module, a dot statistics module, a density distribution map generation module, a shellfish collecting path generation module and a shellfish collecting mining module.

[0054] Among them, the grid map generation module discretizes the environmental map of the shellfish collection area and constructs a grid map of the shellfish collection area according to preset intervals.

[0055] Based on the grid diagram, the dot counting module performs trial dot picking on the center of each grid area and counts the number of trial picks in each grid area.

[0056] The density distribution map generation module determines the shellfish density distribution in each grid area according to the number of trial picks in each grid area, and generates a density distribution map of the entire shellfish collection area.

[0057] The shell picking path generation module takes the current position of the shell picking machine as the center, and selects the grid area with the shortest path and the highest density from the grid areas involved in the eight travel directions of the shell picking machine as the starting point of the shell picking machine; then, taking the grid area where the starting point is as the center, the grid area with the shortest path and the highest density is selected from the grid areas involved in the eight travel directions of the shell picking machine as the next shell picking node of the shell picking machine; and so on, until the entire shell picking area is traversed, and a shell picking path formed by several shell picking nodes is obtained.

[0058] The shellfish collecting and excavation module enables the shellfish collecting machine to move to each grid area in sequence along the shellfish collecting path, and to collect and excavate the grid area according to the preset excavation path.

[0059] The system also includes an excavation path setting module, which sets the excavation path of the shellfish collecting machine in each grid area, including a zigzag path and a zigzag path. When the shellfish collecting machine advances to the grid area, it enters from the boundary of the grid area and excavates shellfish in a zigzag or zigzag path, thereby avoiding missed or repeated collection in the current grid area to the greatest extent. The collection density of the zigzag or zigzag path can be set according to the shellfish density distribution. For the grid area with a larger shellfish density distribution, a denser collection path is set, and for the grid area with a smaller shellfish density distribution, a sparser collection path is set, which not only avoids missed or repeated collection in the grid area, but also avoids excessive collection in the area with a smaller density distribution, resulting in waste of shellfish collecting machine resources.

[0060] The system also includes a screening module, which screens out grid areas where the density of shellfish distribution is greater than a preset value, and sends the screened grid areas to the shellfish collection path generation module to generate a secondary shellfish collection path based on these grid areas. Since the density distribution of shellfish on the tidal flats varies greatly, the shellfish density in some areas is very high, and it is difficult to collect them all in one collection. Secondary collection is required to avoid missing shellfish in this area and causing waste. Therefore, after completing a traversal shellfish collection process, for some grid areas with a large shellfish density distribution, it is necessary to re-plan the path for secondary collection to ensure the collection effect.

[0061] The system of the present invention obtains an environmental map of the shellfish collection area, discretizes and intervals the environmental map, and forms a shellfish collection area grid map composed of grid areas. Since the shellfish density in each grid area is different, each grid area is firstly tested for picking and marking to obtain the shellfish density distribution of each grid area and merge the density distribution into the grid map to form a shellfish collection area grid map with shellfish density display; on this basis, the path planning of the shellfish collection machine is carried out, and the grid area with the shortest path and the largest density is selected as the starting point from the direction of travel of the shellfish collection machine. Point, and with the area where the shellfish collecting machine is currently located as the center, select the grid area with the closest path and the largest density from the direction of travel of the shellfish collecting machine as the next node, and so on until the entire shellfish collecting area is traversed, and a shellfish collecting path formed by several shellfish collecting nodes is obtained. This shellfish collecting path takes into account the optimal path and the collection strategy from high-density breeding areas to low-density breeding areas, which not only avoids missed collection or repeated collection in the grid area, but also improves the overall collection efficiency; shellfish excavation is carried out according to the shellfish collecting path, so as to complete the shellfish collecting process from high-density breeding areas to low-density breeding areas in the shortest time.

[0062] In the description of this specification, the description with reference to the terms "one embodiment", "certain embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent path planning method for a pure electric shellfish collecting machine, characterized in that: include: Discretize the environmental map of the shellfish collection area and construct a grid map of the shellfish collection area according to preset intervals; Trial picking and marking are performed on each grid area in the grid map of the shellfish collection area to obtain the density distribution of shellfish in each grid area and generate a density distribution map of the entire shellfish collection area; Taking the current position of the shell collecting machine as the center, from the grid areas involved in the eight directions of the shell collecting machine, the grid area with the shortest path and the highest density is selected as the starting point of the shell collecting machine; then taking the grid area where the starting point is as the center, from the grid areas involved in the eight directions of the shell collecting machine, the grid area with the shortest path and the highest density is selected as the next shell collecting node of the shell collecting machine; and so on, until the entire shell collecting area is traversed, and a shell collecting path formed by several shell collecting nodes is obtained; The shell collecting machine moves to each grid area in sequence along the shell collecting path, and collects and excavates shells in the grid area according to the preset excavation path.

2. The intelligent path planning method for a pure electric shellfish collecting machine according to claim 1, characterized in that: When trial picking and marking each grid area one by one, the number of trial picking and marking in each grid area is distinguished by color, and a density distribution matrix diagram is generated in which the density of shellfish in the grid area is represented by color.

3. The intelligent path planning method for a pure electric shellfish collecting machine according to claim 1, characterized in that: The preset excavation path is set as a U-shaped path, and the shellfish collecting machine excavates from the outer periphery of the grid area to the inside along the U-shaped path.

4. The intelligent path planning method for a pure electric shellfish collecting machine according to claim 1, characterized in that: The preset excavation path is set as a zigzag path, and the shellfish collecting machine performs shellfish collecting and excavation from one side of the grid area to the other side along the zigzag path.

5. The intelligent path planning method for a pure electric shellfish collecting machine according to claim 1, characterized in that: The method further comprises: performing secondary shellfish harvesting excavation on the grid area where the shellfish distribution density is greater than a preset value.

6. The intelligent path planning method for a pure electric shellfish collecting machine according to claim 1, characterized in that: The method adopts the A* algorithm to find the shortest path, and the objective function adopted is f(n)=g(n)+h(n), wherein g(n) is the actual cost value from the starting point of the shellfish collection path to the shellfish collection node n, h(n) is the heuristic function and has a two-dimensional normal distribution, and the independent variable of h(n) is the shellfish distribution density.

7. An intelligent path planning system for a pure electric shellfish collecting machine, characterized in that: include: A grid map generation module is used to discretize the environmental map of the shellfish collection area and construct a grid map of the shellfish collection area according to preset intervals; The dotting statistics module is used to count the number of trial pickings in each grid area when trial picking and dotting are performed on each grid area in the grid map of the beetle area; A density distribution map generating module is used to determine the density distribution of shellfish in each grid area according to the number of trial picks in each grid area, and generate a density distribution map of the entire shellfish picking area; The shell picking path generation module is used to select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine, with the current location of the shell picking machine as the center; then, with the grid area where the starting point is located as the center, select the grid area with the shortest path and the highest density from the grid areas involved in the eight directions of travel of the shell picking machine as the next shell picking node of the shell picking machine; and so on, until the entire shell picking area is traversed, and a shell picking path formed by several shell picking nodes is obtained; The shellfish collecting and excavation module is used to enable the shellfish collecting machine to move to each grid area in sequence according to the shellfish collecting path, and to collect and excavate the grid area according to the preset excavation path.

8. The intelligent path planning system for a pure electric shellfish collecting machine according to claim 7, characterized in that: The system also includes an excavation path setting module for setting the excavation path of the shellfish collecting machine in each grid area, including a zigzag path and a zigzag path.

9. The intelligent path planning system for a pure electric shellfish collecting machine according to claim 7, characterized in that: The system also includes a screening module for screening out grid areas where the shellfish distribution density is greater than a preset value, and sending the screened grid areas to the shellfish collection path generation module to generate secondary shellfish collection paths based on these grid areas.

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