A distributed robot cluster configuration method and system

Abstract

The present invention discloses a distributed robot cluster configuration method and system, belonging to the field of artificial intelligence technology. The key points of the technical solution include: obtaining the total feeding amount and feeding period of each first breeding pond according to the fish type, fish growth stage and environmental parameters in each first breeding pond in a preset area; determining the remaining feeding time of multiple second breeding ponds and each second breeding pond according to the current time and the feeding period; judging whether an intelligent feeding robot can complete the feeding work within the remaining feeding time; if not, calling an idle robot from an adjacent area of ​​the preset area to the preset area; configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond. The present invention configures the optimal feeding path for the intelligent feeding robot and the idle robot based on the remaining feeding time and the path length, so that the feeding work can be completed in the shortest time.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically to a distributed robot cluster configuration method and system. Background Art

[0002] With the development of aquaculture, the workload of feeders has gradually increased. In order to reduce the workload of feeders and improve the intelligence of feeding, feeders are usually fed to the aquaculture objects through feeding machines in the prior art.

[0003] However, the feeding method in the prior art is usually based on a fixed feeding machine, and each fixed feeding machine can only solve the feeding problem of a separate feeding water area. Therefore, if the farm is large and the number of feeding water areas is large, multiple feeding machines need to be configured, which requires a high cost, so the prior art has shortcomings. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the purpose of the present invention is to provide a distributed robot cluster configuration method and system, which plans the feeding path for the feeding robot according to the remaining feeding time of each second breeding pond and the path length between the second breeding ponds, and completes the feeding work by the mobile feeding robot, thereby reducing the feeding cost compared with the existing technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] This application provides a distributed robot cluster configuration method, including:

[0007] According to the fish species, fish species growth stage and environmental parameters in each first breeding pond in the preset area, the total feeding amount and feeding time period of each first breeding pond are obtained, and each preset area corresponds to an intelligent feeding robot;

[0008] determining, according to the current time and the feeding period, a plurality of second breeding ponds and a remaining feeding time of each of the second breeding ponds, wherein the second breeding pond is the first breeding pond that needs to be fed at the current time;

[0009] Determine whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time;

[0010] If not, calling an idle robot from an adjacent area of ​​the preset area to the preset area;

[0011] According to the remaining feeding time of each of the second breeding ponds, a feeding path is configured for the intelligent feeding robot and the idle robot.

[0012] As a further improvement of the present invention, configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond includes:

[0013] Dividing the plurality of second breeding ponds into a plurality of feeding areas according to the number of the intelligent feeding robots and the idle robots, each feeding area corresponding to one of the intelligent feeding robots or one of the idle robots;

[0014] In each feeding area, determining the objective function and constraint conditions of the feeding path according to the remaining feeding time of each second breeding pond and the distance between each second breeding pond;

[0015] According to the objective function and the constraint conditions, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained.

[0016] As a further improvement of the present invention, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained according to the objective function and the constraint conditions, including:

[0017] Taking the position of the intelligent feeding robot or the idle robot as a root node, selecting a first child node to an Nth child node for the root node according to the constraint condition to obtain multiple first feeding paths, where N is the number of the second breeding ponds in each feeding area;

[0018] The bait casting path is obtained according to the objective function and the plurality of first bait casting paths.

[0019] As a further improvement of the present invention, the first child node to the second child node are selected for the root node according to the constraint condition. Subnodes, including:

[0020] Establish the first child node to the Preset conditions corresponding to the child nodes;

[0021] According to the first sub-node to the The preset conditions corresponding to the child nodes are to select the first child node to the Child node.

[0022] As a further improvement of the present invention, the objective function is determined according to the distance between each child node.

[0023] As a further improvement of the present invention, the determining whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time includes:

[0024] Calculating the distance between each of the second breeding ponds and the intelligent feeding robot and the distance between each of the second breeding ponds according to the positions of the second breeding ponds and the intelligent feeding robot;

[0025] sorting each of the second aquaculture ponds according to the remaining feeding time of each of the second aquaculture ponds to obtain a feeding order;

[0026] Calculating the travel time required for the intelligent feeding robot to reach each of the second breeding ponds based on the distance between each of the second breeding ponds and the intelligent feeding robot, and the distance between each of the second breeding ponds;

[0027] According to the bait throwing sequence and the driving time, it is determined whether the intelligent bait throwing robot can complete the bait throwing task within the remaining bait throwing time.

[0028] As a further improvement of the present invention, obtaining the total feeding amount and feeding period of each first breeding pond according to the fish species type, fish species growth stage and environmental parameters in each first breeding pond in the preset area includes:

[0029] Calculating the total weight of the fish in each first breeding pond according to the growth stage of the fish, the breeding density and the breeding area of ​​each first breeding pond;

[0030] Obtaining a total feeding amount for each of the first breeding ponds based on the total weight of the fish species and the environmental parameters, wherein the environmental parameters include water temperature, pH value, and dissolved oxygen content;

[0031] According to the total feeding amount, the fish species type and the fish species growth stage, the feeding time period of each first breeding pond and the feeding amount corresponding to the feeding time period of each first breeding pond are obtained.

[0032] As a further improvement of the present invention, the total feed amount of each first breeding pond on that day is determined based on environmental parameters, feeding rate and the total weight of the fish species in each first breeding pond, wherein the environmental parameters are determined by water temperature, pH value and dissolved oxygen content, and the total weight of the fish species in each first breeding pond is determined based on the growth stage of the fish species in each first breeding pond, the breeding density of each first breeding pond and the breeding area of ​​each first breeding pond.

[0033] As a further improvement of the present invention, the intelligent feeding robot collects images of each second breeding pond through a camera while completing the feeding work to complete the inspection work.

[0034] The present invention provides a distributed robot cluster configuration system, comprising:

[0035] a calculation module for determining, based on the fish species type, fish species growth stage, and environmental parameters in each first breeding pond in a preset area, a total feeding amount and a feeding period for each first breeding pond, each of the preset areas corresponding to an intelligent feeding robot, and determining, based on a current time and the feeding period, a plurality of second breeding ponds and a remaining feeding time for each of the second breeding ponds, where the second breeding pond is the first breeding pond that needs to be fed at the current time;

[0036] A judgment module is used to judge whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time, and if not, call an idle robot from an adjacent area of ​​the preset area to the preset area;

[0037] A configuration module is used to configure a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond.

[0038] Through the bait-feeding algorithm and judgment logic, the present invention can quickly determine whether the intelligent bait-feeding robot can complete the bait-feeding task, and promptly call the idle robot to assist the intelligent bait-feeding robot when the intelligent bait-feeding robot cannot complete the bait-feeding task. Finally, through the objective function and constraint conditions, the optimal bait-feeding path is configured for the intelligent bait-feeding robot and the idle robot to quickly complete the bait-feeding task. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flow chart of the method steps provided by the present invention;

[0040] Figure 2 This is the initial baiting sequence of the intelligent bait-feeding robot;

[0041] Figure 3 The final bait throwing order of the intelligent bait throwing robot;

[0042] Figure 4 This is a schematic diagram of the baiting area;

[0043] Figure 5 Schematic diagram of the steps for selecting the bait casting path;

[0044] Figure 6 This is a schematic diagram of the system structure provided by the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations of the technical solution of the present invention.

[0046] The term "and / or" in the following text simply describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " generally indicates an "or" relationship between the related objects.

[0047] like Figure 1 As shown, the embodiment of the present application provides a distributed robot cluster configuration method, including:

[0048] According to the fish species, fish growth stage and environmental parameters in each first breeding pond in the preset area, the total feeding amount and feeding time period of each first breeding pond are obtained, and each preset area corresponds to an intelligent feeding robot;

[0049] Determining, according to the current time and the feeding period, a plurality of second breeding ponds and a remaining feeding time of each second breeding pond, wherein the second breeding pond is the first breeding pond that needs to be fed at the current time;

[0050] Determine whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time;

[0051] If not, call an idle robot from an adjacent area of ​​the preset area to the preset area;

[0052] According to the remaining feeding time of each second breeding pond, the feeding path is configured for the intelligent feeding robot and the idle robot.

[0053] The method provided in this embodiment can call on idle robots to jointly complete the feeding task when a single robot is unable to complete the feeding task, and configure the feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond, so that each robot can complete the feeding task under the optimal path.

[0054] Furthermore, this embodiment provides a step of determining whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time, including:

[0055] Calculate the distance between each second breeding pond and the intelligent feeding robot and the distance between each second breeding pond according to the positions of the second breeding pond and the intelligent feeding robot;

[0056] sorting each second aquaculture pond according to the remaining feeding time of each second aquaculture pond to obtain a feeding order;

[0057] Calculate the travel time for the intelligent feeding robot to reach each second breeding pond based on the distance between each second breeding pond and the intelligent feeding robot, and the distance between each second breeding pond;

[0058] According to the bait feeding sequence and driving time, it is judged whether the intelligent bait feeding robot can complete the bait feeding task within the remaining bait feeding time.

[0059] Specifically, first according to the current time and bait casting period, Determined in the first breeding pond The second breeding ponds are then calculated to obtain the remaining feeding time of each second breeding pond, and each second breeding pond is sorted in ascending order according to the remaining feeding time to obtain a preliminary feeding order.

[0060] Then the initial feeding sequence was tested for collinearity, and the feeding sequence of the second culture pond located on the same straight line was adjusted.

[0061] For example, it is assumed that there are six second breeding ponds, such as Figure 2-Figure 3 As shown, Figure 2 For the initial baiting order, Figure 3 This is the final adjusted feeding order. In the preliminary feeding order, breeding pond No. 1, which is in the third place, and breeding pond No. 2, which is in the first place, are located on the same straight line. Since the robot must pass through breeding pond No. 1 when going to breeding pond No. 2, in order to save driving time, the order of breeding pond No. 1 is updated to the first place, and the adjusted feeding order is obtained.

[0062] Assume that after the above adjustments, the final baiting order is , Indicates the location of the second breeding pond in the first place. Indicates that it is located at The location of the second breeding pond in sequence.

[0063] Then, according to the distance between each second breeding pond and the intelligent feeding robot, and the distance between each second breeding pond, the time required for the intelligent feeding robot to reach the first breeding pond is calculated. Travel time required for the second aquaculture pond for:

[0064]

[0065] in Indicates that from -1 in the second breeding pond to the first in the feeding order The time spent in the second breeding pond is , It is the time it takes for the intelligent feeding robot to travel from its initial position to the second breeding pond in the first place. Indicates the The total amount of feed added to the second breeding pond on that day, , Indicates the The number of times the second breeding pond is fed on the same day, , Indicates the amount of bait delivered by the intelligent bait-feeding robot per unit time.

[0066] Finally, the Remaining feeding time for the second culture pond and arrive at Travel time required for the second aquaculture pond For comparison, , if exists If the situation is , it means that the intelligent feeding robot cannot complete the feeding task within the remaining feeding time.

[0067] Since the feeding time needs to be strictly followed in aquaculture, this embodiment quickly determines whether a single intelligent feeding robot can complete the feeding work within the remaining feeding time through the remaining feeding time and the driving time. If not, it is necessary to call an idle robot from the adjacent area of ​​the preset area to the preset area to assist the intelligent feeding robot in completing the feeding work. Since the idle robot is called from the adjacent area, it needs to complete the assisting work in the shortest time and return to the adjacent area.

[0068] Furthermore, this embodiment provides a step of configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond, including:

[0069] Dividing the plurality of second breeding ponds into a plurality of feeding areas according to the number of intelligent feeding robots and idle robots, each feeding area corresponding to an intelligent feeding robot or an idle robot;

[0070] In each feeding area, determining the objective function and constraint conditions of the feeding path according to the remaining feeding time of each second breeding pond and the distance between each second breeding pond;

[0071] According to the objective function and constraints, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained.

[0072] Specifically, the method for dividing the feeding area can be cluster analysis, that is, assuming that the intelligent feeding robot and the idle robot have Then, it is necessary to divide the multiple second breeding ponds into For example, assuming that the number of intelligent bait-feeding robots and idle robots is one, then The number of the second breeding pond is 12, and the feeding area after division is as follows Figure 4 shown.

[0073] Furthermore, this embodiment provides a step of obtaining bait-feeding paths of the intelligent bait-feeding robot and the idle robot according to the objective function and the constraint conditions, including:

[0074] The position of the intelligent bait-feeding robot or the idle robot is taken as the root node, and the first child node to the second child node are selected for the root node according to the constraint conditions. Child nodes, get multiple first baiting paths, The number of second culture ponds in each feeding area;

[0075] A baiting path is obtained according to the objective function and the plurality of first baiting paths.

[0076] Furthermore, according to the constraint conditions, the first child node to the The steps of the child node include:

[0077] According to the constraints, establish the first child node to the Preset conditions corresponding to the child nodes;

[0078] According to the first child node to the The preset conditions corresponding to the child nodes are to select the first child node to the Child node.

[0079] Specifically, the objective function for:

[0080]

[0081] in, Indicates the number of second breeding ponds in each feeding area, Indicates the first Child nodes and The distance between child nodes, ,when hour, Represents the distance between the root node and the first child node. The purpose of establishing this objective function is to make the total length of the bait path as short as possible.

[0082] Constraints include:

[0083]

[0084] in:

[0085]

[0086] Indicates arrival The time required for the child node, Indicates the The remaining feeding time of the child node, Indicates the speed of the intelligent bait-feeding robot or idle robot. Indicates the The total amount of bait fed to the child node on that day, , Indicates the The number of times the child node is baited on the day, The purpose of this constraint is to enable each child node to complete feeding within the remaining feeding time, which is equivalent to enabling each second breeding pond to complete feeding within the remaining feeding time.

[0087] In addition to the above constraints, the intelligent bait-feeding robot and the idle robot must also meet the basic conditions for bait-feeding, that is, the remaining power and stored bait of the intelligent bait-feeding robot and the idle robot are sufficient to complete the bait-feeding task.

[0088] Based on the above conditions, we can get The preset conditions corresponding to the child nodes are: , that is, select The basis of the child node is that after completing the After the child node's baiting work, there is still enough time to complete the The baiting work of the child nodes is to select the first child node to the The first baiting path can be obtained by selecting the child node. There may be multiple first baiting paths.

[0089] Then calculate the objective function of each first feeding path. The first feeding path corresponding to the minimum function value is the feeding path. Repeat the above steps in each feeding area to obtain the feeding path of each intelligent feeding robot and idle robot.

[0090] For example, Figure 5 As shown in the figure, "0" represents the location of the intelligent feeding robot, and "1-6" represent the six secondary breeding ponds within the feeding area corresponding to the intelligent feeding robot. Taking the location of the intelligent feeding robot as the root node, the first to sixth child nodes are selected layer by layer according to the preset conditions. Three primary feeding paths are obtained: 2→3→1→6→4→5, 4→2→1→3→6→5, and 4→2→1→3→5→6. The objective functions of the three paths are then calculated, and the first feeding path with the minimum function value is the feeding path.

[0091] The method provided in this embodiment divides multiple second breeding ponds into multiple feeding areas through cluster analysis, dispatches a robot to each feeding area, and configures the feeding path of each robot according to the objective function and preset conditions, so that the feeding task can be completed in the shortest time within the remaining feeding time, thereby improving work efficiency.

[0092] Furthermore, this embodiment provides a step of obtaining the total feeding amount and feeding period of each first breeding pond according to the fish species type, fish species growth stage and environmental parameters in each first breeding pond in a preset area, including:

[0093] Calculating the total weight of the fingerlings in each first breeding pond based on the growth stage of the fingerlings, the breeding density and the breeding area of ​​each first breeding pond;

[0094] Determining the total feeding amount for each first culture pond based on the total weight of the fish and environmental parameters, including water temperature, pH value, and dissolved oxygen content;

[0095] According to the total feeding amount, the fish species type and the fish species growth stage, the feeding time period of each first breeding pond and the feeding amount corresponding to the feeding time period of each first breeding pond are obtained.

[0096] Specifically, Total weight of fish in the first breeding pond for:

[0097]

[0098] in, , is the number of the first breeding pond in the preset area, Indicates the The fish species in the first breeding pond are in the growth stage, Indicates the The fish species in the first breeding pond are The average weight of each growth stage, , corresponding to the four growth stages of larvae, juveniles, young fish and adults, and Respectively represent The stocking density and stocking area of ​​the first stocking pond.

[0099] No. The total amount of feed added to the first breeding pond on the day for:

[0100]

[0101] in Indicates environmental parameters, through The water temperature, pH value and dissolved oxygen content of the first aquaculture pond are determined. Specifically, different weights can be determined for different factors according to the type and growth stage of the fish species in the aquaculture pond, and finally the environmental parameters are obtained according to the weighted method. In addition, since the water temperature, pH value and dissolved oxygen content have different dimensions, normalization processing is required when calculating the weighted results; is the feeding rate, which means that without considering environmental factors, The total feeding amount of the first breeding pond on that day accounted for The proportion of the total weight of the fish in the first breeding pond.

[0102] Then, according to the fish type and growth stage of each first breeding pond, the number of feeding times of each first breeding pond on the day is determined, and according to the number of feeding times and the total feeding amount, the feeding time period and the feeding amount corresponding to each feeding time period are allocated to each first breeding pond.

[0103] For example, suppose The first breeding pond is used to raise juvenile crucian carp. According to the feeding standard of crucian carp, the number of feeding times per day in the first breeding pond is three. The three feeding times are evenly distributed, and the feeding time periods of the first breeding pond are 8:00-9:00, 13:00-14:00, and 17:00-18:00. The amount of feeding each time is .

[0104] Furthermore, while the intelligent feeding robot and the idle robot complete their feeding operations, they use cameras to capture images of each secondary aquaculture pond to complete their inspections. Furthermore, the images captured by the cameras can be used to determine the remaining bait rate for each aquaculture pond from the previous feeding. Specifically, image recognition technology can accurately identify remaining bait from the captured images, and the remaining amount of bait can be calculated based on the area of ​​the remaining bait in the image. This is then combined with the previous feeding amount to determine the remaining bait rate, which can be used to adjust the total amount of bait to be fed next time.

[0105] Specifically:

[0106]

[0107] in, is the total feeding amount after adjustment, is the bait residual rate, is the bait remaining rate threshold.

[0108] This embodiment can more accurately obtain the feeding rate of each breeding pond through the type of fish species, the growth stage of the fish species, the breeding density of each breeding pond, the breeding area and the environmental parameters. At the same time, the feeding amount can be adjusted through the breeding pond images collected during the inspection process to obtain the accurate feeding amount as the basis for subsequent feeding work.

[0109] The distributed robot cluster configuration method provided in the embodiment of the present application can accurately determine the amount of bait to be fed to each breeding pond through the feeding algorithm, which serves as the basis for subsequent feeding work. At the same time, through the judgment logic, it can quickly determine whether the intelligent feeding robot can complete the feeding work, and when the intelligent feeding robot cannot complete the feeding work, the idle robot can be called in time to assist the intelligent feeding robot. Finally, the optimal feeding path is configured for the intelligent feeding robot and the idle robot through the objective function and constraint conditions to quickly complete the feeding task.

[0110] Furthermore, if Figure 6 As shown, an embodiment of the present application provides a distributed robot cluster configuration system, including:

[0111] a calculation module for determining the total feeding amount and feeding time period for each first breeding pond in a preset area based on the fish species type, fish species growth stage, and environmental parameters in each first breeding pond, wherein each preset area corresponds to an intelligent feeding robot, and determining the remaining feeding time for each of the plurality of second breeding ponds based on the current time and the feeding time period, wherein the second breeding pond is the first breeding pond that needs to be fed at the current time;

[0112] A judgment module is used to judge whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time. If not, an idle robot is called from an adjacent area of ​​the preset area to the preset area;

[0113] The configuration module is used to configure feeding paths for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond.

[0114] The distributed robot cluster configuration method and system provided in the embodiments of the present application configure the feeding amount for the robot through an accurate feeding algorithm, and configure the optimal feeding route for the robot through an objective function and constraint conditions, which can ensure that the robot completes the feeding machine inspection work in the shortest time, thereby saving costs and improving work efficiency.

[0115] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0118] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A distributed robot cluster configuration method, characterized in that: include: According to the fish species, fish species growth stage and environmental parameters in each first breeding pond in the preset area, the total feeding amount and feeding time period of each first breeding pond are obtained, and each preset area corresponds to an intelligent feeding robot; determining, according to the current time and the feeding period, a plurality of second breeding ponds and a remaining feeding time of each of the second breeding ponds, wherein the second breeding pond is the first breeding pond that needs to be fed at the current time; Determine whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time; If not, calling an idle robot from an adjacent area of ​​the preset area to the preset area; configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond; The step of configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond includes: Dividing the plurality of second breeding ponds into a plurality of feeding areas according to the number of the intelligent feeding robots and the idle robots, each feeding area corresponding to one of the intelligent feeding robots or one of the idle robots; In each feeding area, determining the objective function and constraint conditions of the feeding path according to the remaining feeding time of each second breeding pond and the distance between each second breeding pond; According to the objective function and the constraint conditions, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained; Wherein, according to the objective function and the constraint conditions, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained, including: The position of the intelligent bait-feeding robot or the idle robot is used as the root node, and the first child node to the second child node are selected for the root node according to the constraint conditions. Child nodes, get multiple first baiting paths, is the number of the second breeding ponds in each feeding area; Obtaining the baiting path according to the objective function and the plurality of first baiting paths, wherein the objective function is determined according to the distance between each child node; Wherein, according to the constraint condition, the first child node to the second child node are selected for the root node. Subnodes, including: According to the constraint condition, the first sub-node to the The preset condition corresponding to the child node is that each child node has remaining time to complete the baiting work of the next adjacent child node after completing the baiting work of the current node; According to the first sub-node to the The preset conditions corresponding to the child nodes are to select the first child node to the Child node.

2. A distributed robot cluster configuration method according to claim 1, characterized in that: The determining whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time includes: Calculating the distance between each of the second breeding ponds and the intelligent feeding robot and the distance between each of the second breeding ponds according to the positions of the second breeding ponds and the intelligent feeding robot; sorting each of the second aquaculture ponds according to the remaining feeding time of each of the second aquaculture ponds to obtain a feeding order; Calculating the travel time required for the intelligent feeding robot to reach each of the second breeding ponds based on the distance between each of the second breeding ponds and the intelligent feeding robot, and the distance between each of the second breeding ponds; According to the bait throwing sequence and the driving time, it is determined whether the intelligent bait throwing robot can complete the bait throwing task within the remaining bait throwing time.

3. A distributed robot cluster configuration method according to claim 1, characterized in that: The method of obtaining the total feeding amount and feeding time period of each first breeding pond according to the fish species type, fish species growth stage and environmental parameters in each first breeding pond in the preset area includes: Calculating the total weight of the fish in each first breeding pond according to the growth stage of the fish, the breeding density and the breeding area of ​​each first breeding pond; Obtaining a total feeding amount for each of the first breeding ponds based on the total weight of the fish species and the environmental parameters, wherein the environmental parameters include water temperature, pH value, and dissolved oxygen content; According to the total feeding amount, the fish type and the fish growth stage, the feeding time period of each first breeding pond and the feeding amount corresponding to the feeding time period of each first breeding pond are obtained.

4. A distributed robot cluster configuration method according to claim 3, characterized in that: The total amount of feed fed to each first breeding pond on that day is determined based on environmental parameters, feeding rate, and the total weight of the fish species in each first breeding pond, wherein the environmental parameters are determined by water temperature, pH value, and dissolved oxygen content; and the total weight of the fish species in each first breeding pond is determined based on the growth stage of the fish species in each first breeding pond, the breeding density of each first breeding pond, and the breeding area of ​​each first breeding pond.

5. A distributed robot cluster configuration method according to claim 1, characterized in that: The intelligent feeding robot collects images of each second breeding pond through a camera while completing the feeding work to complete the inspection work.

6. A distributed robot cluster configuration system, characterized in that: include: a calculation module for determining, based on the fish species type, fish species growth stage, and environmental parameters in each first breeding pond in a preset area, a total feeding amount and a feeding period for each first breeding pond, each of the preset areas corresponding to an intelligent feeding robot, and determining, based on a current time and the feeding period, a plurality of second breeding ponds and a remaining feeding time for each of the second breeding ponds, where the second breeding pond is the first breeding pond that needs to be fed at the current time; A judgment module is used to judge whether the intelligent bait-feeding robot can complete the bait-feeding task within the remaining bait-feeding time, and if not, call an idle robot from an adjacent area of ​​the preset area to the preset area; a configuration module, configured to configure a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond; The step of configuring a feeding path for the intelligent feeding robot and the idle robot according to the remaining feeding time of each second breeding pond includes: Dividing the plurality of second breeding ponds into a plurality of feeding areas according to the number of the intelligent feeding robots and the idle robots, each feeding area corresponding to one of the intelligent feeding robots or one of the idle robots; In each feeding area, determining the objective function and constraint conditions of the feeding path according to the remaining feeding time of each second breeding pond and the distance between each second breeding pond; According to the objective function and the constraint conditions, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained; Wherein, according to the objective function and the constraint conditions, the bait-feeding paths of the intelligent bait-feeding robot and the idle robot are obtained, including: The position of the intelligent bait-feeding robot or the idle robot is used as the root node, and the first child node to the second child node are selected for the root node according to the constraint conditions. Child nodes, get multiple first baiting paths, is the number of the second breeding ponds in each feeding area; Obtaining the baiting path according to the objective function and the plurality of first baiting paths, wherein the objective function is determined according to the distance between each child node; Wherein, according to the constraint condition, the first child node to the second child node are selected for the root node. Subnodes, including: According to the constraint condition, the first sub-node to the The preset condition corresponding to the child node is that each child node has remaining time to complete the baiting work of the next adjacent child node after completing the baiting work of the current node; According to the first sub-node to the The preset conditions corresponding to the child nodes are to select the first child node to the Child node.

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