Photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method and system, electronic equipment and storage medium

Abstract

The invention provides a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method and system, electronic equipment and a storage medium, and relates to the technical field of multi-machine task scheduling and collaborative operation, and the method comprises the steps: obtaining the position and speed information of each robot in a robot cluster, and constructing a dynamic adjacency graph model; controlling each robot to interact information through an ad hoc network communication relay node by using a time division multiple access protocol, controlling communication delay and broadcasting obstacle information in real time; dividing a to-be-cleaned area based on related information, determining task sub-areas, and realizing adaptive distribution of tasks according to models; and finally, in the cleaning process, by fusing the swarming control of the artificial potential field method, the adjacent robots synchronously clean the boundary and adjust the track, multi-machine efficient collaborative operation of the photovoltaic cleaning robot can be achieved, and the cleaning efficiency and flexibility are improved.

Description

Technical Field

[0001] The present application relates to the technical field of multi-machine task scheduling and collaborative operation, and in particular to a multi-machine task scheduling and collaborative operation method, system, electronic equipment and storage medium for photovoltaic cleaning robots. Background Art

[0002] In large-scale photovoltaic (PV) sites, numerous PV cleaning robots must collaborate to ensure panel cleanliness and improve power generation efficiency. PV panel sizes and layouts vary across different regions, and various obstacles may exist on-site. Furthermore, each robot's power reserve and cleaning capabilities vary. Therefore, an efficient multi-robot task scheduling and collaborative operation solution is urgently needed to ensure the rational allocation of cleaning tasks and orderly collaboration between robots, maximizing cleaning efficiency and energy utilization.

[0003] Currently, existing technologies for photovoltaic cleaning robots mostly rely on robots following pre-set, fixed cleaning routes. For communication, conventional communication networks are typically used, resulting in relatively independent information exchange between robots and a lack of real-time, efficient collaborative communication mechanisms. Task allocation is often based on experience or simple average allocation, without fully considering the actual status of the robots and the complex environment of the site.

[0004] However, existing technologies have numerous drawbacks. Fixed-route cleaning cannot cope with dynamic obstacles within the station, resulting in incomplete cleaning or an increased risk of robot collisions. Conventional communication networks are susceptible to environmental interference, leading to significant communication delays between robots, untimely information exchange, and difficulties in collaborative operations. Simple task allocation methods neither allow robots to flexibly adjust tasks based on their remaining battery power and cleaning capabilities, nor do they take into account the actual conditions of the area to be cleaned. This results in some robots being overloaded with tasks while others remain idle, resulting in low overall cleaning efficiency and an inability to meet the needs of efficient cleaning at large-scale photovoltaic stations. Summary of the Invention

[0005] The purpose of this application is to provide a method, system, electronic device and storage medium for multi-machine task scheduling and collaborative operation of photovoltaic cleaning robots to solve the problem of poor multi-machine task scheduling and collaborative operation effects in the prior art.

[0006] To solve the above technical problems, in the first aspect, the present application provides a method for multi-machine task scheduling and collaborative operation of photovoltaic cleaning robots, comprising:

[0007] Obtaining position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and constructing a dynamic adjacency graph model based on the position information and speed information of each photovoltaic cleaning robot;

[0008] Controlling each photovoltaic cleaning robot to exchange information using a time division multiple access protocol through a self-organizing network communication relay node, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time broadcasting obstacle information in real time in the robot cluster through the self-organizing network communication relay node;

[0009] Based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster to achieve dynamic distribution of task load according to the adaptability of the robot model;

[0010] When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, a swarming control method is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot. After the two adjacent photovoltaic cleaning robots reach the common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

[0011] Optionally, based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster, including the following steps:

[0012] Obtaining the remaining power, cleaned area, and energy consumption per unit area of ​​each photovoltaic cleaning robot, and grouping the photovoltaic cleaning robots whose distance values ​​are less than a preset distance threshold into the same collaborative group based on the connection relationship between each node in the dynamic adjacency graph model;

[0013] Calculating the duration of cleaning that can be continued based on the remaining power of each photovoltaic cleaning robot in the same collaborative group, converting the cleanable area of ​​each photovoltaic cleaning robot in the same collaborative group based on the energy consumption per unit area, and determining the unfinished cleaning ratio based on the cleaned area;

[0014] Divide the remaining area of ​​the photovoltaic station to be cleaned after removing the obstacle information into a number of continuous initial area blocks, wherein the area of ​​each initial area block is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot in a single time, and allocate at least two initial area blocks to each of the same collaborative groups. Based on the ratio of the cleanable area to the unfinished cleaning area, allocate sub-areas in the initial area blocks to each photovoltaic cleaning robot in the same collaborative group to form a preliminary task plan;

[0015] Sending the preliminary task plan to each photovoltaic cleaning robot in the same collaborative group to control each photovoltaic cleaning robot to feedback acceptance or adjustment request based on the straight-line distance between its current position and the sub-area;

[0016] In the event that any of the photovoltaic cleaning robots feedback an adjustment request, the sub-area is reallocated based on the acceptance or adjustment requests feedback from all photovoltaic cleaning robots, with the sub-area being preferentially allocated to the photovoltaic cleaning robot that is closer to the sub-area, until all photovoltaic cleaning robots in the same collaborative group accept the allocation result to form a task sub-area.

[0017] Optionally, the remaining area in the area to be cleaned in the photovoltaic station after removing the obstacle information is divided into a number of continuous initial area blocks, wherein the area of ​​each initial area block is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot in a single time, and at least two initial area blocks are allocated to each of the same collaborative groups. Based on the ratio of the cleanable area to the unfinished cleaning, a sub-area in the initial area block is allocated to each photovoltaic cleaning robot in the same collaborative group to form a preliminary task plan, which includes the following steps:

[0018] Divide the remaining area into several continuous strips along the direction parallel to the arrangement of the photovoltaic panels in the photovoltaic station, and divide each of the continuous strips into several initial area blocks along the direction perpendicular to the arrangement of the photovoltaic panels. The area of ​​each initial area block is not less than the maximum cleaning area that can be cleaned by a single photovoltaic cleaning robot in a single time, and the initial area block contains an integer number of photovoltaic panels.

[0019] Based on the position information of all photovoltaic cleaning robots in each collaborative group, the straight-line distance between each collaborative group and the center of each initial area block is calculated. Based on the allocation rule that the straight-line distance between the collaborative group and the corresponding initial area block does not exceed the maximum distance between any two photovoltaic cleaning robots in the collaborative group, at least two initial area blocks that are closer to each other are preferentially allocated to the corresponding collaborative group;

[0020] Counting the total cleanable area of ​​all photovoltaic cleaning robots in each collaborative group, calculating the ratio of the area of ​​the initial area block to the total cleanable area, and dividing the initial area block into sub-areas equal to the number of photovoltaic cleaning robots in the collaborative group according to the ratio;

[0021] Determining the area of ​​each sub-region according to the cleanable area of ​​each photovoltaic cleaning robot so that the ratio of the area of ​​the sub-region to the cleanable area of ​​the corresponding photovoltaic cleaning robot tends to be consistent;

[0022] Combined with the unfinished cleaning ratio of each photovoltaic cleaning robot, based on the principle that the straight-line distance between the edge of the sub-area corresponding to the photovoltaic cleaning robot with a higher unfinished cleaning ratio and the edge of the cleaned area is smaller, the sub-area is adjusted, and the adjusted sub-area is associated with the corresponding photovoltaic cleaning robot to form a preliminary task plan.

[0023] Optionally, when the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, the moving speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot is adjusted in a swarming control manner; after the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal, including the following steps:

[0024] When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, it sends a boundary synchronization request to the adjacent photovoltaic cleaning robot, so that the two adjacent photovoltaic cleaning robots exchange their current travel directions and distance information from the common boundary line based on the boundary synchronization request, and adjust their respective movement speeds using a swarming control method so that the time difference between the two adjacent photovoltaic cleaning robots reaching the common boundary line is within a preset range;

[0025] After the two adjacent photovoltaic cleaning robots reach the common boundary line, they move synchronously in a direction parallel to the common boundary line, maintaining a preset distance during the movement. When an obstacle is detected on the movement trajectory, based on the obstacle information and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot, so that the adjacent photovoltaic cleaning robot adjusts its own movement trajectory accordingly based on the trajectory adjustment signal, so as to maintain the collaborative distance of the two adjacent photovoltaic cleaning robots within the preset distance range;

[0026] After the adjacent photovoltaic cleaning robots avoid obstacles, they restore to the original cleaning path or replan the route to the next boundary section according to the boundary information of the task sub-area updated in real time until the cleaning operation of the common boundary line is completed.

[0027] Optionally, the synchronous movement in a direction parallel to the common boundary line, maintaining a preset distance during movement, and when an obstacle is detected on the movement trajectory, adjusting the steering angle to bypass the obstacle based on the obstacle information and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area, includes the following steps:

[0028] Collecting vertical distance information between the two adjacent photovoltaic cleaning robots and a common boundary line, exchanging the vertical distance information through a self-organizing network communication relay node, and adjusting the travel directions of the two adjacent photovoltaic cleaning robots so that the travel directions are both parallel to the common boundary line and the distance difference from the common boundary line is within a preset safety distance;

[0029] Calculating a straight-line distance between the two adjacent photovoltaic cleaning robots; when the straight-line distance between the two adjacent photovoltaic cleaning robots is greater than a preset distance, increasing the movement speed of the photovoltaic cleaning robot closer to the inner side of the common boundary and reducing the movement speed of the photovoltaic cleaning robot closer to the outer side, so that the straight-line distance is within the preset distance;

[0030] When an obstacle is detected in the travel path in front of the two adjacent photovoltaic cleaning robots, the coordinate information and lateral width of the obstacle are recorded, and based on the coordinate information of the obstacle, the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is calculated;

[0031] When the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is greater than the lateral width of the obstacle, the steering angle is adjusted in the direction away from the common boundary line based on the principle that the size of the steering angle is proportional to the lateral width, or when the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is less than or equal to the lateral width, the steering angle is adjusted in the direction close to the common boundary line, and a new travel trajectory is generated, and the minimum distance between the new travel trajectory and the common boundary line is not less than the preset safety distance.

[0032] Optionally, constructing a dynamic adjacency graph model according to the position information and speed information of each photovoltaic cleaning robot comprises the following steps:

[0033] Calculate the straight-line distance between every two photovoltaic cleaning robots in the robot cluster based on the position information, the moving rate and the moving direction in the speed information;

[0034] Taking the position point corresponding to the coordinate information of each photovoltaic cleaning robot as a node, when the straight-line distance between the two photovoltaic cleaning robots is within the preset adjacency judgment range and the angle between the moving direction and the boundary line of each current task sub-area meets the preset angle condition, a connecting edge is established between the position points of the two photovoltaic cleaning robots, the edge weight is determined based on the moving rate, and a dynamic adjacency graph model is constructed.

[0035] Optionally, controlling each photovoltaic cleaning robot to exchange information through a self-organizing network communication relay node using a time division multiple access protocol so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and simultaneously broadcasting obstacle information in the robot cluster in real time through the self-organizing network communication relay node, comprises the following steps:

[0036] According to the preset time segment division rules, each photovoltaic cleaning robot in the robot cluster is assigned a dedicated information sending time segment. The duration of the information sending time segment is set according to the amount of position information, speed information and task status information required for a single information interaction. The information to be exchanged includes obstacle information, coordinate information of the collection location and the time identifier of the collection moment;

[0037] Control each photovoltaic cleaning robot to send the information to be interacted to the ad hoc network communication relay node within its own dedicated information transmission time segment, so that the ad hoc network communication relay node adds a corresponding forwarding sequence number to each information to be interacted in the order of receipt, and broadcasts the information to be interacted to all other photovoltaic cleaning robots;

[0038] After receiving a delay exception signal sent by any other photovoltaic cleaning robot under preset conditions, the exclusive time segments corresponding to the two photovoltaic cleaning robots corresponding to the delay exception are readjusted, and the interval between the exclusive time segments is shortened. The preset condition is that the full time difference exceeds the preset delay range, and the full time difference is the time difference from the time the information to be interacted is sent from itself to the time it is received by the target photovoltaic cleaning robot.

[0039] In a second aspect, the present application provides a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system, comprising:

[0040] A construction module is used to obtain the position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and to construct a dynamic adjacency graph model based on the position information and speed information of each photovoltaic cleaning robot;

[0041] a control module for controlling each photovoltaic cleaning robot to exchange information through a self-organizing network communication relay node using a time division multiple access protocol, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time, broadcasting obstacle information in real time in the robot cluster through the self-organizing network communication relay node;

[0042] a partitioning module for partitioning the area to be cleaned in the photovoltaic station into segments based on the dynamic adjacency graph model and the obstacle information, in combination with the remaining power and cleaned area of ​​each photovoltaic cleaning robot, and determining the task sub-area of ​​each photovoltaic cleaning robot through the robot cluster to achieve dynamic allocation of task load according to the adaptability of the robot model;

[0043] An adjustment module is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot by using a swarming control method when the photovoltaic cleaning robot detects that the distance between itself and the adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold. After the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

[0044] In a third aspect, the present application provides an electronic device, comprising:

[0045] Memory for storing computer programs;

[0046] The processor is used to implement the steps of the photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method as described in the first aspect above when executing the computer program.

[0047] In a fourth aspect, the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method as described in the first aspect above can be implemented.

[0048] The present application provides a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method, which obtains the position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and constructs a dynamic adjacency graph model according to the position information and speed information of each photovoltaic cleaning robot; controls each photovoltaic cleaning robot to exchange information through the self-organizing network communication relay node using the time division multiple access protocol, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time broadcasts the obstacle information in the robot cluster in real time through the self-organizing network communication relay node; based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, The area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster to realize dynamic distribution of task load according to the adaptability of the model; when the photovoltaic cleaning robot detects that the distance to the adjacent photovoltaic cleaning robot is less than or equal to the preset collaborative distance threshold, the swarming control method is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot. After the two adjacent photovoltaic cleaning robots reach the common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

[0049] The technical solution of this application has the following beneficial effects:

[0050] This application integrates the position and speed information of each photovoltaic cleaning robot to clearly present the position relationship and motion status between the robots, providing a basic relationship basis for subsequent task allocation and collaborative work, and facilitating the rapid identification of collaborative robot combinations; using the time division multiple access protocol with the help of self-organizing network communication relay nodes to realize information interaction, which can effectively avoid information sending conflicts, control communication delays within a preset range, and ensure the timeliness of information transmission; at the same time, obstacle information is broadcast in real time, so that each robot knows the obstacle situation in advance and provides a reference for path planning; combining the dynamic adjacency graph model, obstacle information and the remaining power and cleaned area of ​​the robot, the area is reasonably divided and task sub-areas are allocated, realizing dynamic allocation of task load according to model adaptability, so that the task volume of each robot matches its capability, and improving the overall cleaning efficiency; using the swarm control method integrating the artificial potential field method, when adjacent robots enter the preset collaborative distance range, the synchronous cleaning of the area boundary is triggered, ensuring the consistency of the cleaning of the boundary area; adjusting the travel trajectory through the real-time updated task sub-area boundary information, it can flexibly respond to environmental changes and ensure the continuous progress of the cleaning operation.

[0051] Furthermore, the present application obtains the remaining power, cleaned area and energy consumption per unit area of ​​each photovoltaic cleaning robot, and classifies the robots whose distance is less than a preset threshold into the same collaborative group based on the connection relationship of the nodes in the dynamic adjacency graph model; then calculates the cleanable area based on the remaining power and energy consumption per unit area of ​​the robots in the collaborative group, and determines the proportion of unfinished cleaning based on the cleaned area; then divides the area to be cleaned to remove obstacles into initial area blocks and allocates them to each collaborative group, and allocates sub-areas to the robots in the group based on the cleanable area and the unfinished cleaning proportion to form a preliminary task plan; finally, reallocates the sub-areas based on the robot's feedback on the preliminary plan until all robots accept it to form a task sub-area.

[0052] This application forms a collaborative group, combines the robot's energy consumption, power consumption, cleaning progress and other parameters to accurately calculate the cleaning capacity, scientifically divides the area and allocates sub-areas, and optimizes task allocation with the help of a feedback adjustment mechanism to ensure that the task sub-area is compatible with the robot's position and capabilities, thereby achieving a reasonable distribution of task loads within the collaborative group and improving the coordination and efficiency of area cleaning.

[0053] Furthermore, when the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, it uses a swarming control method to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot. After the two adjacent photovoltaic cleaning robots reach a common boundary line, they move synchronously in a direction parallel to the common boundary line while maintaining a preset spacing. If an obstacle is detected during movement, the robot adjusts its steering angle to avoid the obstacle and simultaneously sends a trajectory adjustment signal to the adjacent photovoltaic cleaning robot to maintain the collaborative distance between the two adjacent photovoltaic cleaning robots within the preset distance range. The present application uses swarming control to adjust the movement speed, thereby preventing collisions between adjacent robots due to close proximity, laying a safe foundation for subsequent collaborative actions. After reaching the common boundary line, the robots move synchronously in parallel directions and at a preset spacing, which enables the robots to maintain a neat formation, ensure an orderly cleaning path, reduce overlap or omission of cleaning areas, and improve cleaning coverage. The synchronous travel mode ensures that adjacent robots clean the same area at a consistent rhythm, avoiding a decrease in cleaning efficiency due to disjointed movements (such as repeated cleaning of an area or blank areas). When encountering obstacles, the robots not only flexibly circumvent them but also synchronize with adjacent robots through trajectory adjustment signals, ensuring that the preset collaborative distance is maintained during the obstacle avoidance process. This prevents a single robot from disrupting the overall formation, ensuring the continuity of the cleaning process and minimizing cleaning interruptions or missed areas due to obstacles. From distance control and formation maintenance to collaborative obstacle avoidance, the full-process collaborative mechanism reduces coordination losses between robots, enabling multi-robot teams to efficiently cover the photovoltaic area and improve overall cleaning efficiency.

[0054] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0056] Figure 1 A flowchart of a multi-machine task scheduling and collaborative operation method for photovoltaic cleaning robots provided in an embodiment of the present application;

[0057] Figure 2 A scenario diagram of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method provided in an embodiment of the present application;

[0058] Figure 3 A schematic diagram of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system provided in an embodiment of the present application;

[0059] Figure 4 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] In order to solve the problem of poor multi-machine task scheduling and collaborative operation in the existing technology, the present application provides a multi-machine task scheduling and collaborative operation method for photovoltaic cleaning robots. The design idea of ​​this method is: by integrating the position and speed information of each photovoltaic cleaning robot, the position correlation and motion status between the robots are clearly presented, which provides a basic correlation basis for subsequent task allocation and collaborative operation, and facilitates the rapid identification of collaborative robot combinations; the time division multiple access protocol is used to realize information interaction with the help of self-organizing network communication relay nodes, which can effectively avoid information sending conflicts, control communication delays within a preset range, and ensure the timeliness of information transmission; at the same time, obstacle information is broadcast in real time. , so that each robot knows the obstacle situation in advance and provides a reference for path planning; combining the dynamic adjacency graph model, obstacle information and the robot's remaining power and cleaned area, the area is reasonably divided and task sub-areas are allocated, realizing dynamic allocation of task load according to model adaptability, so that the task volume of each robot matches its capability, and improving the overall cleaning efficiency; using the swarming control method that integrates the artificial potential field method, the synchronous cleaning of the area boundary is triggered when the adjacent robots enter the preset collaborative distance range, ensuring the consistency of the cleaning of the boundary area; adjusting the travel trajectory through the real-time updated task sub-area boundary information, it can flexibly respond to environmental changes and ensure the continuous progress of the cleaning operation.

[0061] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the embodiments described are only a part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making any creative efforts are within the scope of protection of the present application.

[0062] The core of this application is to provide a method for multi-machine task scheduling and collaborative operation of photovoltaic cleaning robots. The flow chart of a specific implementation method is as follows: Figure 1 As shown, the method includes:

[0063] S101. Obtain position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and construct a dynamic adjacency graph model according to the position information and speed information of each photovoltaic cleaning robot.

[0064] Optionally, the step S101 of constructing a dynamic adjacency graph model according to the position information and speed information of each photovoltaic cleaning robot includes:

[0065] Step 1011: Calculate the straight-line distance between every two photovoltaic cleaning robots in the robot cluster based on the position information, the moving rate and the moving direction in the speed information.

[0066] Step 1012: Taking the position point corresponding to the coordinate information of each photovoltaic cleaning robot as a node, when the straight-line distance between the two photovoltaic cleaning robots is within the preset adjacency determination range and the angle between the moving direction and the boundary line of each current task sub-area meets the preset angle condition, a connecting edge is established between the position points of the two photovoltaic cleaning robots, the edge weight is determined based on the moving rate, and a dynamic adjacency graph model is constructed.

[0067] In the above scheme, position information refers to the coordinate data collected by the photovoltaic cleaning robot through the onboard positioning module, which is used to identify its specific position in the photovoltaic station, including horizontal coordinates and vertical coordinates; speed information is the motion state data collected by the robot through the motion detection component, including movement rate and movement direction; the dynamic adjacency graph model is a graphical model used to describe the position association of each robot in the robot cluster; the preset adjacency judgment range is a pre-set distance threshold, which is used to determine whether two robots are within the spatial range where an association can be established; the boundary line of the current task sub-area refers to the edge boundary line of the cleaning area assigned to each robot; the preset angle condition is a pre-set angle threshold, which is used to determine whether the robot's movement direction meets the requirements for forming an association with the boundary line of its own task sub-area.

[0068] In this application example, first, step 1011 is used to calculate the straight-line distance between each two photovoltaic cleaning robots in the robot cluster based on the moving rate and moving direction in the position information and speed information. Specifically, the coordinates of the two robots are extracted from the position information collected by each robot and recorded as and , using the straight-line distance calculation formula Calculate, where d is the straight-line distance between the two robots, are the horizontal and vertical coordinates of the first robot, are the horizontal and vertical coordinates of the second robot; at the same time, the moving speeds of the two robots are recorded (respectively and ) and the included angle between the moving direction and the boundary line of each task sub-area (respectively denoted as and ).

[0069] Next, in step 1012, the straight-line distance d is compared with the preset adjacent determination range. If d is less than or equal to the preset adjacent determination range, the angle between the two robots is further checked. and Are both less than or equal to the preset angle condition? If the above two conditions are met at the same time, a connection edge is established between the position points (nodes) of the two robots. and Determine the weight of the connecting edge, for example, take the average of the two rates As edge weights, by repeating the above operations for all pairwise combinations in the robot cluster, a dynamic adjacency graph model containing nodes, connecting edges and edge weights is finally formed.

[0070] In actual applications, the robot cluster in the photovoltaic station includes three devices: robots R1, R2, and R3. Among them, the position coordinates of robot R1 are (20, 30), the moving speed is 0.4m / s, and the angle between the moving direction and the boundary line of its own task sub-area is 25 degrees; the position coordinates of robot R2 are (23, 32), the moving speed is 0.5m / s, and the angle between the moving direction and the boundary line of its own task sub-area is 28 degrees; the position coordinates of robot R3 are (30, 35), the moving speed is 0.3m / s, and the angle between the moving direction and the boundary line of its own task sub-area is 35 degrees. The preset adjacency judgment range is 6 meters, and the preset angle condition is 30 degrees. First, calculate the straight-line distance between the two robots: the distance between robots R1 and R2, substitute into the formula to get meters (less than 6 meters); the distance between robots R1 and R3 meters (greater than 6 meters); the distance between robots R2 and R3 Meters (greater than 6 meters). Then determine the angle condition: the angle of robot R1 (25 degrees) and the angle of robot R2 (28 degrees) are both less than 30 degrees, which meets the condition; at least one of the angles between robots R1 and R3, or between robots R2 and R3, does not meet the condition (for example, the angle of R3 (35 degrees) is greater than 30 degrees). Therefore, only connect edges between the nodes corresponding to R1 and R2, and the edge weight is the average of the two rates, that is, The final dynamic adjacency graph model contains three nodes: R1, R2, and R3. There is only one connecting edge with a weight of 0.45 between R1 and R2.

[0071] The above-mentioned S101 overall solution accurately collects the robot's position and speed information, combines it with quantitative distance calculation, angle judgment and weight setting, and constructs a dynamic adjacency graph model that can reflect the spatial association of robot clusters in real time. The precise calculation of straight-line distance ensures the accuracy of adjacency range judgment, the introduction of angle conditions avoids associations without collaborative meaning, and the setting of edge weights provides a quantitative basis for subsequent task allocation. This overall improves the accuracy of the model's description of the robot cluster status and lays a solid foundation for multi-machine scheduling and collaborative operations.

[0072] S102, controlling each photovoltaic cleaning robot to exchange information through the self-organizing network communication relay node using the time division multiple access protocol, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time broadcasting the obstacle information in the robot cluster in real time through the self-organizing network communication relay node.

[0073] Optionally, the step of controlling each photovoltaic cleaning robot to exchange information using a time division multiple access protocol through a self-organizing network communication relay node in S102, so that a communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and simultaneously broadcasting obstacle information in the robot cluster in real time through the self-organizing network communication relay node, includes:

[0074] Step 1021: According to the preset time segment division rules, an exclusive information sending time segment is allocated to each photovoltaic cleaning robot in the robot cluster. The duration of the information sending time segment is set according to the amount of position information, speed information and task status information required for a single information interaction. The information to be interacted includes obstacle information, coordinate information of the collection position and the time identifier of the collection moment.

[0075] Step 1022: Control each photovoltaic cleaning robot to send the information to be interacted to the self-organizing network communication relay node within its own exclusive information sending time segment, so that the self-organizing network communication relay node adds a corresponding forwarding sequence number to each of the information to be interacted in the order of reception, and broadcasts the information to be interacted to all other photovoltaic cleaning robots.

[0076] Step 1023: After receiving a delay exception signal sent by any other photovoltaic cleaning robot under preset conditions, readjust the exclusive time segments corresponding to the two photovoltaic cleaning robots corresponding to the delay exception, and shorten the interval between the exclusive time segments. The preset condition is that the full time difference exceeds the preset delay range, and the full time difference is the time difference from when the information to be interacted is sent from itself to when it is received by the target photovoltaic cleaning robot.

[0077] In the above scheme, the self-organizing network communication relay node refers to a device that enables multiple photovoltaic cleaning robots to connect to each other to form a network and forward information, which is used to realize information transmission between robots; the time division multiple access protocol refers to a rule that divides time into segments and allows different robots to send information within their own exclusive time segments to avoid information transmission conflicts; communication delay refers to the time it takes for information to be sent from one robot to another; the preset delay range refers to the pre-set maximum acceptable communication delay; obstacle information refers to the relevant data detected by the robot that hinders its progress; task status information refers to data such as the progress of the robot's current cleaning task; the forwarding sequence number refers to the number added in sequence by the self-organizing network communication relay node to the received information, which is used to identify the order in which the information is received; the delay abnormality signal refers to the prompt signal sent by the robot when the communication delay exceeds the preset delay range.

[0078] In this application example, first, in step 1021, each robot is assigned a dedicated information sending time segment. According to the preset time segment division rule, the amount of position information, speed information and task status information required for a single information interaction is first counted. Assuming that the time required for a unit of data volume is , then the duration of a single time segment , can be obtained by formula , calculated, where k is the redundancy coefficient (range 1.1-1.3), D in the formula is the amount of data for a single information interaction, and according to the calculated length of each time segment, the total time is sequentially allocated to each photovoltaic cleaning robot in the robot cluster to form their own exclusive information sending time segment.

[0079] Next, in step 1022, information transmission and broadcasting are implemented. Each robot transmits the information to be exchanged (including obstacle information, acquisition location coordinates, and acquisition time stamp) to the ad hoc network communication relay node within its dedicated information transmission time slot. The ad hoc network communication relay node assigns a forwarding sequence number to each message based on the time of receipt. The forwarding sequence number starts at 1 and increases sequentially. The relay node then broadcasts the information with the forwarding sequence number to all other photovoltaic cleaning robots, ensuring that each robot receives the complete information during the broadcast process.

[0080] Finally, step 1023 adjusts the time segment to control the communication delay. After any robot receives the information sent by other robots, it records the time when the information is sent. and receiving time , through the formula , calculate the total time difference .like Exceeding the preset delay range , the robot sends a delay exception signal to the information aggregation node, which contains the identifiers of the sender and receiver and After receiving the signal, the information aggregation node will and The difference , calculate the time interval length that needs to be shortened , The value is 1.2-1.5 times of the original time, and accordingly readjust the exclusive time segments of the two robots to reduce the interval between them. , to reduce communication delay.

[0081] In practical applications, the number of relay nodes can be 1, 2 or other values. Figure 2 As shown, this application sets up two relay nodes: relay node 1 and relay node 2. There are three photovoltaic cleaning robots R1, R2, and R3 in the photovoltaic station. The self-organizing network communication relay node is responsible for information forwarding. The preset delay range is 0.5 seconds, and the time required for unit data volume is =0.001 seconds / unit data, redundancy coefficient k=1.2, the data volume of a single information interaction D=100 units of data, through the formula seconds, calculate the length of each time segment to be 0.12 seconds, and according to this length, allocate 0-0.12 seconds to R1, 0.12-0.24 seconds to R2, and 0.24-0.36 seconds to R3 as exclusive information sending time segments. Robot R1 sends the detected obstacle information (such as there is an obstacle at coordinates (10, 20), and the collection time is 10:00:00) to relay node 1 within 0-0.12 seconds; after receiving, relay node 1 adds forwarding sequence 1, which can be broadcast directly to R2, and can be broadcast to R3 through relay node 2. Robot R2 sends its own position and other information between 0.12 and 0.24 seconds, and relay node 1 adds forwarding sequence 2 to broadcast; robot R3 sends information in the same way, and relay node 2 adds forwarding sequence 3 to broadcast. When robot R2 receives information from R1, it records the sending time as 10:00:00 and the receiving time as 10:00:00.6, and uses the formula The calculated total time difference is 0.6 seconds, which exceeds the preset delay range of 0.5 seconds. Seconds, take After receiving the signal, R21 and R2's time segments are adjusted, with R1 set to 0-0.12 seconds and R2 set to 0.12-0.13=-0.01 (adjusted to 0.01)-0.01+0.12=0.13 seconds, shortening the interval between the two and reducing communication delay.

[0082] The above-mentioned S102 overall solution effectively avoids information transmission conflicts and ensures the orderliness of information transmission by allocating exclusive information sending time segments to each robot and adopting the time division multiple access protocol for information exchange; forwards and broadcasts information through the self-organizing network communication relay node, so that each robot can obtain the required information in a timely manner, including obstacle information, etc.; when communication delay anomalies occur, by adjusting the time segment interval length, the communication delay can be controlled within the preset range, ensuring the timeliness and stability of robot cluster information exchange, and providing a good communication foundation for multi-machine task scheduling and collaborative operations.

[0083] S103. Based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined through the robot cluster to achieve dynamic distribution of task load according to the adaptability of the model.

[0084] Optionally, in S103, based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster, including:

[0085] Step 1031: Obtain the remaining power, cleaned area, and energy consumption per unit area of ​​each photovoltaic cleaning robot, and based on the connection relationship between each node in the dynamic adjacency graph model, classify the photovoltaic cleaning robots whose distance values ​​are less than a preset distance threshold into the same collaboration group.

[0086] Step 1032: Calculate the duration of continued cleaning based on the remaining power of each photovoltaic cleaning robot in the same collaborative group, convert the cleanable area of ​​each photovoltaic cleaning robot in the same collaborative group based on the energy consumption per unit area, and determine the proportion of incomplete cleaning based on the cleaned area.

[0087] Step 1033: Divide the remaining area of ​​the photovoltaic station to be cleaned area after removing the obstacle information into several continuous initial area blocks, wherein the area of ​​each initial area block is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot at a time, and allocate at least two initial area blocks to each of the same collaborative groups. Based on the cleanable area and the ratio of unfinished cleaning, allocate sub-areas in the initial area blocks to each photovoltaic cleaning robot in the same collaborative group to form a preliminary task plan.

[0088] Among them, step 1033 may specifically include the following processes: dividing the remaining area into several continuous strips along the arrangement direction parallel to the photovoltaic panels in the photovoltaic station, and dividing each of the continuous strips into several initial area blocks along the arrangement direction perpendicular to the photovoltaic panels, the area of ​​each of the initial area blocks is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot at a time and the initial area block contains an integer number of photovoltaic panels; based on the position information of all photovoltaic cleaning robots in each collaborative group, calculating the straight-line distance between each collaborative group and the center of each initial area block, based on the allocation rule that the straight-line distance between the collaborative group and the corresponding initial area block does not exceed the maximum distance between any two photovoltaic cleaning robots in the collaborative group, preferentially allocating at least two initial area blocks that are closer to the corresponding collaborative group; counting each The total cleanable areas of all photovoltaic cleaning robots in the collaborative group are calculated, the ratio of the area of ​​the initial area block to the total cleanable areas is calculated, and the initial area block is divided into sub-areas with the same number as the photovoltaic cleaning robots in the collaborative group according to the ratio; the area of ​​each sub-area is determined according to the cleanable area of ​​each photovoltaic cleaning robot, so that the ratio of the area of ​​the sub-area to the cleanable area of ​​the corresponding photovoltaic cleaning robot tends to be consistent; combined with the unfinished cleaning ratio of each photovoltaic cleaning robot, based on the principle that the straight-line distance between the edge of the sub-area corresponding to the photovoltaic cleaning robot with a higher unfinished cleaning ratio and the edge of the cleaned area is smaller, the sub-area is adjusted, and the adjusted sub-area is associated with the corresponding photovoltaic cleaning robot to form a preliminary task plan.

[0089] Step 1034: Send the preliminary task plan to each photovoltaic cleaning robot in the same collaborative group to control each photovoltaic cleaning robot to feedback acceptance or adjustment request based on the straight-line distance between its current position and the sub-area.

[0090] Step 1035: In the event that any of the photovoltaic cleaning robots feedbacks an adjustment request, the sub-area is reallocated based on the acceptance or adjustment requests feedbacked by all photovoltaic cleaning robots, with the sub-area being preferentially allocated to the photovoltaic cleaning robot that is closer to the sub-area, until all photovoltaic cleaning robots in the same collaborative group accept the allocation result to form a task sub-area.

[0091] In the above scheme, the dynamic adjacency graph model refers to a graphic model used to reflect the position association of each photovoltaic cleaning robot in the robot cluster; obstacle information refers to the position, size and other data of objects detected by the robot that hinder its movement; model adaptability refers to the allocation of suitable tasks based on the performance parameters of the robot; a collaborative group is a group of robots that are close to each other to facilitate collaborative work; the preset distance threshold refers to the distance standard for judging whether robots can be classified as the same collaborative group; a continuous strip is a long strip area divided along the direction parallel to the arrangement of the photovoltaic panels; a sub-area is an area assigned to a single robot after the initial area block is further divided; and a task sub-area is the cleaning area finally determined and assigned to each robot.

[0092] In this application example, first, a collaborative group is formed through step 1031 to obtain the remaining power, cleaned area and energy consumption per unit area of ​​each photovoltaic cleaning robot. According to the connection relationship of each node in the dynamic adjacency graph model, the position coordinates of any two robots are extracted, and the formula , (where d is the distance between the two robots, 、 are the position coordinates of the two robots respectively) to calculate the distance value, and the robots with distance values ​​less than the preset distance threshold are classified into the same collaboration group to form a collaboration group list.

[0093] Next, the cleanable area and the unfinished cleaning ratio are calculated in step 1032. For each robot in the same collaborative group, the remaining power E and the energy consumption per unit area e, as well as the cleaning area per unit time s, are calculated by the formula , calculate the duration of continuous cleaning, where t is the duration of continuous cleaning; then use the formula Get the cleanable area, where A is the cleanable area. At the same time, according to the cleaned area a and the total task area (the total area of ​​the collaborative group's responsibility area), through the formula Determine the unfinished cleaning ratio, and record the corresponding cleaning area and unfinished cleaning ratio of each robot, where r is the unfinished cleaning ratio.

[0094] Then, the area is divided and a preliminary task plan is formed through step 1033. First, the remaining area after removing the obstacle information from the area to be cleaned is divided into continuous strips parallel to the arrangement direction of the photovoltaic panels. The strip width is determined according to the width of the photovoltaic panels and the robot cleaning width. Then, the strip is divided into initial area blocks along the vertical direction. The area of ​​each initial area block is calculated by the formula (in is the initial area of ​​the block, n is the number of photovoltaic panels included, is the area of ​​a single photovoltaic panel), ensure that n is an integer and The maximum cleanable area of ​​a single robot is not less than the maximum cleanable area of ​​a single robot. The straight-line distance between the center of each collaborative group and the center of each initial area block is calculated. At least two initial area blocks are allocated to each collaborative group according to the rule that the distance is closer and does not exceed the maximum distance between any two robots in the collaborative group. The total cleanable area of ​​all robots in the collaborative group is calculated. ,(in is the cleanable area of ​​the i-th robot in the collaborative group), calculate the area of ​​each initial area block and proportion , divide the initial area block into sub-areas with the same number of robots in proportion, and the area of ​​each sub-area is ,make tend to be consistent; on this basis, combined with the proportion of unfinished cleaning , following the rule that "the straight-line distance between the edge of the sub-area corresponding to the photovoltaic cleaning robot with a higher unfinished cleaning ratio and the edge of the cleaned area is smaller", by comparing the If a robot's The value is greater than that of at least one other robot in the group If the value is too high, the robot has a high proportion of unfinished cleaning. Calculate the straight-line distance between the edge of the sub-area and the edge of the cleaned area. ,in is the distance of the corresponding sub-area of ​​the i-th robot, is the basic distance, is the unfinished cleaning ratio of the i-th robot, based on The larger the robot, the The smaller the value, the smaller the straight-line distance between the edge of the sub-area and the edge of the cleaned area. The position of each sub-area is adjusted. After the adjustment, the sub-area is associated with the corresponding robot to form a preliminary task plan.

[0095] Afterwards, the acceptance of the task plan is fed back through step 1034, and the preliminary task plan is sent to each robot in the collaborative group. Each robot extracts its current position coordinates and the coordinates of the center of the assigned sub-area, and uses the distance formula in step 1031 to calculate the straight-line distance. If the distance is less than or equal to the preset acceptable distance, the robot will feedback acceptance; otherwise, the robot will feedback an adjustment request and attach the distance value.

[0096] Finally, the final task sub-area is determined through step 1035, and feedback from all robots is collected. If there is an adjustment request, the straight-line distance between each robot and each sub-area is recalculated according to the distance value attached to the request. The sub-area is preferentially assigned to the robot with a closer distance in order of distance from small to large, and the association between the sub-area and the robot is updated. The adjusted plan is sent to each robot again. Here, closer means that within the same collaborative group, the straight-line distance between each photovoltaic cleaning robot and a sub-area is horizontally compared. The straight-line length is calculated by coordinates. If the distance value of a robot is smaller than the distance value of at least one other robot in the group, the sub-area is preferentially assigned to this robot, and the process of steps 1034 and 1035 is repeated until all photovoltaic cleaning robots have formed a task sub-area with the coordinate range, area size, edge position and other information of the task sub-area corresponding to themselves after reallocation.

[0097] In practical applications, the number of robots in a photovoltaic station can be 2, 3, 4 or other numbers. For example, there are robots R1, R2, R3, and R4 in a photovoltaic station. The dynamic adjacency graph model shows that their position coordinates are (10, 20) (15, 25) (20, 30) (25, 35) respectively, and the preset distance threshold is 10 meters. The distance between R1 and R2 is calculated by the formula Meters, the distance between R2 and R3 Meters, the distance between R3 and R4 The remaining power of each robot is: R1 is 150 units, R2 is 200 units, R3 is 180 units, and R4 is 120 units; the energy consumption per unit area e is 3 units / square meter, and the cleaning area per unit time s is 4 square meters / minute. So the continuous cleaning time of R1 is Minutes, can clean area Square meter; R2: Minutes, can clean area Square meter; R3: Minutes, can clean area Square meter; R4: Minutes, can clean area Based on the above cleanable area, the total task area of ​​the collaboration team is determined to be 50+66.68+60+40=216.68 square meters; then calculate the proportion of unfinished cleaning: R1 has cleaned an area of ​​30 square meters, the proportion of unfinished cleaning, the proportion of unfinished cleaning ; R2 has cleaned an area of ​​40 square meters, ; R3 has cleaned an area of ​​25 square meters, ; R4 has cleaned an area of ​​15 square meters, After removing the obstacles, the remaining area to be cleaned is 216.68 square meters. The area of ​​a single photovoltaic panel is square meters, divided into two continuous strips parallel to the photovoltaic panel direction, each of which is further divided into two initial area blocks vertically, each initial area block contains photovoltaic panels ( square meters, which is larger than the maximum cleanable area of ​​40 square meters for a single machine), calculate the distance between the center of the collaborative group (17.5, 27.5) and the center of each initial area block, and assign the 4 initial area blocks closest to the collaborative group. Square meters, initial area block area =60 square meters, ratio , then the sub-region area square meters, square meters, square meters, At this time, the sub-area is adjusted based on the unfinished cleaning ratio, and the basic distance m, according to the principle that "the straight-line distance between the edge of the sub-area corresponding to the robot with a higher proportion of unfinished cleaning and the edge of the cleaned area is smaller", the distance between the edge of each robot's sub-area is calculated. rice, rice, rice, The robot's distance to the assigned sub-area is 15 meters, with R4 being the smallest. This ensures that the edge of R4's sub-area is closest to the cleaned area, followed by R3, and so on, forming a preliminary task plan. After the preliminary task plan is sent, R4 reports that its distance to the assigned sub-area is 15 meters (greater than the preset acceptable distance of 10 meters). The robot recalculates the distance between each robot and the sub-area and finds that R3's distance is 8 meters. This sub-area is assigned to R3, and R4 is reassigned a sub-area 9 meters away. R4 accepts the plan, ultimately forming the task sub-area.

[0098] The 103 overall solution, described above, establishes collaborative teams and calculates the robot's remaining cleaning capacity and unfinished percentage based on parameters such as the robot's remaining battery life and the area already cleaned. This scientifically divides the area to be cleaned into initial blocks and sub-areas. A feedback adjustment mechanism determines the final task sub-areas, enabling dynamic allocation of task loads based on the robot's adaptability. This process fully considers the robots' actual capabilities and location relationships, ensuring rational and efficient task allocation, facilitating collaborative operation among robots and improving cleaning efficiency and coverage at the photovoltaic plant.

[0099] S104. When the photovoltaic cleaning robot detects that the distance between itself and an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, a swarming control method is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot. After the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

[0100] Optionally, S104, when the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot are adjusted in a swarming control manner. After the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal, including:

[0101] Step 1041: When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, it sends a boundary synchronization request to the adjacent photovoltaic cleaning robot, so that the two adjacent photovoltaic cleaning robots exchange their current travel directions and distance information from the common boundary line based on the boundary synchronization request, and adjust their respective movement speeds using a swarming control method so that the time difference between the two adjacent photovoltaic cleaning robots reaching the common boundary line is within a preset range.

[0102] Step 1042: After the two adjacent photovoltaic cleaning robots reach the common boundary line, they move synchronously in a direction parallel to the common boundary line, maintain a preset distance during the movement, and when an obstacle is detected on the movement trajectory, adjust the steering angle to bypass the obstacle based on the obstacle information and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area, and at the same time send a trajectory adjustment signal to the adjacent photovoltaic cleaning robot, so that the adjacent photovoltaic cleaning robot adjusts its own movement trajectory accordingly based on the trajectory adjustment signal to maintain the collaborative distance of the two adjacent photovoltaic cleaning robots within the preset distance range, wherein the task sub-area boundary refers to the edge line of the cleaning area that a single photovoltaic cleaning robot is responsible for, which is exclusive to the robot and is used to define its independent operating range, and the common boundary refers to the common edge line between two adjacent task sub-areas, which is jointly responsible by the two adjacent photovoltaic cleaning robots and is the intersection of their operating ranges. For example, the task sub-area boundary of robot A includes four edges: a, b, c, and d; the task sub-area boundary of robot B includes four edges: c, e, f, and g. Edge c is the common boundary of the two robots, and only edge c is shared by the two robots. The other edges are their own exclusive task sub-area boundaries.

[0103] Among them, step 1042 may specifically include the following processes: collecting vertical distance information between the two adjacent photovoltaic cleaning robots and the common boundary line, exchanging the vertical distance information through the self-organizing network communication relay node, and adjusting the moving directions of the two adjacent photovoltaic cleaning robots so that the moving directions are parallel to the common boundary line, and the distance difference from the common boundary line is within a preset safety distance; calculating the straight-line distance between the two adjacent photovoltaic cleaning robots, when the straight-line distance between the two adjacent photovoltaic cleaning robots is greater than the preset spacing, increasing the moving speed of the photovoltaic cleaning robot close to the inner side of the common boundary, and reducing the moving speed of the photovoltaic cleaning robot on the outer side, so that the straight-line distance is within the preset spacing; when it is detected that When there is an obstacle in the travel trajectory in front of the two adjacent photovoltaic cleaning robots, the coordinate information and lateral width of the obstacle are recorded, and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is calculated based on the coordinate information of the obstacle; when the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is greater than the lateral width of the obstacle, based on the principle that the size of the steering angle is proportional to the lateral width, the steering angle is adjusted in the direction away from the common boundary line, or when the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is less than or equal to the lateral width, the steering angle is adjusted in the direction close to the common boundary line, and a new travel trajectory is generated, and the minimum distance between the new travel trajectory and the common boundary line is not less than the preset safety distance.

[0104] Step 1043: After the adjacent photovoltaic cleaning robots avoid obstacles, they restore to the original cleaning path or re-plan the route to the next boundary section according to the boundary information of the task sub-area updated in real time until the cleaning operation of the common boundary line is completed.

[0105] In the above scheme, the swarm control method integrating the artificial potential field method refers to a control method that combines the simulated "potential field force" and the group collaborative motion rules to coordinate the movement of multiple robots; the synchronized cleaning of the area boundary refers to the coordinated cleaning of the common boundary by adjacent robots; the boundary information of the task sub-area refers to the edge position data of the area that each robot is responsible for cleaning; the preset collaborative distance threshold is the distance critical value that triggers the boundary synchronization request; the boundary synchronization request is the signal sent by the robot to the adjacent robot to collaboratively clean the boundary; the trajectory adjustment signal is the signal sent to the adjacent robot to adjust the motion trajectory when the robot bypasses the obstacle; the collaborative distance is the distance that should be maintained between adjacent robots; the vertical distance information is the distance from the robot to the common boundary line in the vertical direction; the lateral width of the obstacle is the width of the obstacle in the direction perpendicular to the robot's movement; the new movement trajectory is the new motion path planned when the robot bypasses the obstacle; the original cleaning path is the cleaning route of the robot before encountering the obstacle.

[0106] In this application example, first, step 1041 is used to trigger boundary synchronization, and each robot detects the distance to the adjacent robot in real time, using the distance formula ,) calculate the distance value, where d is the distance, The coordinates of the robot and the adjacent robot are respectively; when the distance is less than or equal to the preset collaborative distance threshold, a boundary synchronization request is sent to the adjacent robot. After receiving the request, the adjacent robots exchange their respective travel directions (such as the angle with the arrangement direction of the photovoltaic panels) and the distance information from the common boundary line (such as the vertical distance), and adopt the swarming control method. and current movement speed , through the formula Calculate the arrival time difference. If the time difference exceeds the preset range, adjust the speed (such as increasing the speed of the robot at a long distance). is within the preset range.

[0107] Secondly, synchronized movement and obstacle avoidance are achieved through step 1042. When adjacent robots reach the common boundary line, the vertical distance between each robot and the common boundary line is collected. 、 , after exchanging information, adjust the direction of travel so that the directions are parallel to the common boundary line, and , which is less than the preset safety distance, the straight-line distance d between the two is calculated in real time during movement. When d is greater than the preset distance, the robot closer to the inside increases its speed. , the outer reduction rate , It can be determined based on the difference between d and the preset distance, so that d is maintained within the preset distance. If an obstacle is detected in front, its coordinates and horizontal width W are recorded, and the straight-line distance S between itself and the boundary of the task sub-area is calculated. When S>W, the steering angle is adjusted. , (k is the proportional coefficient) adjust in the direction away from the common boundary line, when S≤W, adjust in the direction close to the common boundary line , ensuring that the minimum distance between the new trajectory and the common boundary line is not less than the preset safety distance, and at the same time sending a trajectory adjustment signal (including the new direction and adjustment amplitude) to the adjacent robots. The adjacent robots adjust their trajectories accordingly to maintain the collaborative distance within the preset range.

[0108] Finally, after restoring or replanning the path through step 1043 and avoiding obstacles, the robot obtains real-time updated task sub-area boundary information (such as changes in boundary line coordinates). If the original cleaning path is not affected, it is restored to the original path. If the original path is blocked, it replans the route to the next boundary section according to the new boundary information (such as along the extension direction of the new boundary line) and continues to clean synchronously until the cleaning operation of the common boundary line is completed.

[0109] In actual application, robots R1 and R2 are adjacent robots in the photovoltaic station, with a preset collaborative distance threshold of 5 meters, a preset time difference range of 2 seconds, a preset spacing of 2 meters, a preset safety distance of 0.5 meters, and a proportional coefficient k = 0.1 radians / meter. Robot R1 coordinates (10, 20), the direction of travel is parallel to the common boundary line, and the distance perpendicular to the common boundary line is ,rate m / s, robot R2 coordinates (14,23), calculated distance Meters, triggering a boundary synchronization request. The vertical distance between R2 and the common boundary line Meter, speed m / s, time difference of arrival seconds (within range). After reaching the common boundary line, Meters (meeting the safe distance), while moving synchronously at a distance d = 3 meters (greater than the preset spacing of 2 meters), R1 (inside) increases its speed to 0.6 m / s, while R2 reduces it to 0.4 m / s, restoring d to 2 meters. Then, when an obstacle is detected while moving forward, based on the lateral width W = 1 meter and the distance S = 1.5 meters between R1 and the boundary of the task subarea (S>W), the steering angle θ = 0.1 × 1 = 0.1 radians is adjusted in the direction away from the boundary, and a signal is sent to R2, which synchronizes the adjustment to maintain the coordinated distance. After avoiding the obstacle, R1 and R2 resume their original path based on the updated boundary information and continue to clear the common boundary line until completion.

[0110] The 104-robot overall solution, by integrating swarming control with the artificial potential field method, enables synchronized cleaning of boundaries between adjacent robots within a preset collaborative distance, ensuring stable distance during synchronized movement. When encountering obstacles, the robots can flexibly adjust their steering angle based on their distance from the boundary, while simultaneously achieving collaborative obstacle avoidance through trajectory adjustment signals, preventing collisions and maintaining collaborative relationships. After avoiding obstacles, they promptly resume or replan their paths, ensuring the continuity and integrity of cleaning operations and improving the efficiency and safety of collaborative robot swarm operations.

[0111] The following is a complete example of steps S101 to S104. First, in the photovoltaic station, there are three photovoltaic cleaning robots A, B, and C, which can correspond to Figure 2 R1, R2 and R3 in the equation. A's position coordinates are (5,10), moving at a speed of 0.3m / s, and heading east; B's coordinates are (8,12), moving at a speed of 0.4m / s, and heading east; C's coordinates are (15,18), moving at a speed of 0.35m / s, and heading east. , calculate the distance, where d is the straight-line distance between the two robots, The coordinates of the two robots are obtained, and the distance between A and B is approximately 3.61m, A and C is approximately 10.44m, and B and C is approximately 7.81m. Using the positions of these three robots as nodes, a dynamic adjacency graph model is constructed. In this model, there are edges connecting nodes A and B, and B and C, but not A and C. This distance data and connection relationships will be used to subsequently divide collaborative groups.

[0112] Next, based on the positional relationship between robots A, B, and C in the photovoltaic station, a time-division multiple access protocol is pre-set for information exchange. The information aggregation node divides one second into three dedicated time segments (the preset duration of each segment is 0.3 seconds based on the amount of information data): 0-0.3 seconds for robot A, 0.3-0.6 seconds for robot B, and 0.6-1 seconds for robot C. At 0.1 seconds between 0 and 0.3 seconds, robot A sends its own position (5, 10) to the relay node. The relay node forwards this to robots B and C, which receive it at 0.15 seconds. The time difference is calculated as: 0.15-0.1 = 0.05 seconds, which is within the preset delay range of 0.2 seconds. While traveling, robot B detects an obstacle at coordinates (10, 12) and sends it to the relay node with a timestamp of 10:00:00. The relay node then adds the forwarding sequence number 1 in the order of receipt and broadcasts it to robots A and C. This obstacle information is then used to divide the area to be cleaned.

[0113] Then, based on the dynamic adjacency graph model, a distance threshold of 10m and a cleaning area per unit time of 2m2 / s were preset. Since A, B, and C were all within this threshold, they were grouped together. Considering the information exchange state without delay anomalies, a fixed energy consumption per unit area was set. A had 120 units of remaining power and a unit area energy consumption of 2 units / m2. The remaining cleaning time was calculated as: 120 ÷ 2 ÷ 2 m2 / s = 30 seconds, and the cleaning area was: 30 × 2 = 60 m2. 30 m2 had been cleaned, and the total task area was 200 m2. The uncompleted cleaning percentage was: (200 - 30) ÷ 200 = 0.85. B had 150 units of remaining power, and the cleaning area was: (150 ÷ ​​2 ÷ 2) × 2 = 75 m2. 40 m2 had been cleaned, and the uncompleted cleaning percentage was: (200 - 40) ÷ 200 = 0.8. Unit C has 100 remaining battery units. Its cleanable area is (100 ÷ 2 ÷ 2) × 2 = 50 m2. It has already cleaned 25 m2, resulting in an uncompleted percentage of (200 - 25) ÷ 200 = 0.875. Referring to the obstacle (10, 12) broadcast in step 2, the area to be cleaned is removed and divided into four initial blocks of 50 m2 each (the area of ​​each initial block is assumed to be no less than the maximum cleanable area of ​​40 m2 per unit). These blocks are then assigned to the collaborative group. The sub-areas are divided based on the proportion of cleanable area: Unit A: 60 ÷ (60 + 75 + 50) × 50 ≈ 15.38 m2; Unit B: 75 ÷ 215 × 50 ≈ 19.23 m2; and Unit C: 50 ÷ 215 × 50 ≈ 15.38 m2. After fine-tuning the uncompleted percentage, a preliminary task plan is formed. Unit A's sub-area is closer to the cleaned area, and this task plan will be used for subsequent cleaning operations.

[0114] Finally, based on the task sub-area determined in step 3, the collaborative distance range is preset to 5m. The sub-areas of A and B are adjacent, and when the distance between them reaches 5m, synchronous cleaning is triggered. The vertical distance between A and the common boundary line is 1m, and that of B is 1.2m. After exchanging information, the direction is adjusted to be parallel to the boundary line, and the preset spacing is 2m. The obstacle (10,12) broadcast in step 2 is detected during the journey, and its horizontal width is measured to be 2m. The distance between A and the boundary of the task sub-area is 3m (greater than 2m). According to the preset steering angle formula (in is the steering angle, 0.1 is the preset scale factor, and W is the horizontal width). Calculate the steering angle: 0.1×2=0.2 radians, adjust in the direction away from the boundary, and send a trajectory adjustment signal to B. B synchronously adjusts to maintain the coordinated distance. After avoiding obstacles, it restores the original path according to the updated task sub-area boundary information and continues to clean synchronously until completion.

[0115] Figure 3 This is a structural diagram of a specific implementation of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system provided in an embodiment of the present application, with reference to Figure 3 , the system may include:

[0116] The construction module 31 is used to obtain the position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and to construct a dynamic adjacency graph model according to the position information and speed information of each photovoltaic cleaning robot.

[0117] The control module 32 is used to control each photovoltaic cleaning robot to exchange information through the self-organizing network communication relay node using the time division multiple access protocol, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time, the obstacle information is broadcast in real time in the robot cluster through the self-organizing network communication relay node.

[0118] The division module 33 is used to divide the area to be cleaned in the photovoltaic station into segments based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, and determine the task sub-area of ​​each photovoltaic cleaning robot through the robot cluster to achieve dynamic allocation of task load according to the adaptability of the model.

[0119] The adjustment module 34 is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot by using a swarming control method when the photovoltaic cleaning robot detects that the distance between itself and the adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold. After the two adjacent photovoltaic cleaning robots reach the common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

[0120] A photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system in an embodiment of the present application is used to implement the aforementioned photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method. Therefore, the specific implementation method of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system can be seen in the embodiment part of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method in the previous text. Its specific implementation method can refer to the description of the corresponding embodiments of each part, and will not be repeated here.

[0121] like Figure 4 As shown, the present application also provides an electronic device, including: a memory 41 for storing a computer program; a processor 42 for implementing any of the steps of the above-mentioned method for multi-machine task scheduling and collaborative operation of a photovoltaic cleaning robot when executing the computer program.

[0122] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of any one of the above-mentioned methods for multi-machine task scheduling and collaborative operation of photovoltaic cleaning robots are implemented.

[0123] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, a read-only memory, a random access memory, a mobile hard disk, a magnetic disk, or an optical disk.

[0124] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of any of the above-mentioned photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method embodiments.

[0125] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0126] The above is a detailed introduction to the photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method, system, electronic equipment and storage medium provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method of this application and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the scope of protection of this application.

Claims

1. A photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method, characterized in that: include: Obtaining position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and constructing a dynamic adjacency graph model based on the position information and speed information of each photovoltaic cleaning robot; Controlling each photovoltaic cleaning robot to exchange information using a time division multiple access protocol through a self-organizing network communication relay node, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time broadcasting obstacle information in real time in the robot cluster through the self-organizing network communication relay node; Based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster to achieve dynamic distribution of task load according to the adaptability of the robot model; When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, a swarming control method is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot. After the two adjacent photovoltaic cleaning robots reach the common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

2. The method according to claim 1, characterized in that Based on the dynamic adjacency graph model and the obstacle information, combined with the remaining power and the cleaned area of ​​each photovoltaic cleaning robot, the area to be cleaned in the photovoltaic station is divided into segments, and the task sub-area of ​​each photovoltaic cleaning robot is determined by the robot cluster, including the following steps: Obtaining the remaining power, cleaned area, and energy consumption per unit area of ​​each photovoltaic cleaning robot, and grouping the photovoltaic cleaning robots whose distance values ​​are less than a preset distance threshold into the same collaborative group based on the connection relationship between each node in the dynamic adjacency graph model; Calculating the duration of cleaning that can be continued based on the remaining power of each photovoltaic cleaning robot in the same collaborative group, converting the cleanable area of ​​each photovoltaic cleaning robot in the same collaborative group based on the energy consumption per unit area, and determining the unfinished cleaning ratio based on the cleaned area; Divide the remaining area of ​​the photovoltaic station to be cleaned after removing the obstacle information into a number of continuous initial area blocks, wherein the area of ​​each initial area block is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot in a single time, and allocate at least two initial area blocks to each of the same collaborative groups. Based on the ratio of the cleanable area to the unfinished cleaning area, allocate sub-areas in the initial area blocks to each photovoltaic cleaning robot in the same collaborative group to form a preliminary task plan; Sending the preliminary task plan to each photovoltaic cleaning robot in the same collaborative group to control each photovoltaic cleaning robot to feedback acceptance or adjustment request based on the straight-line distance between its current position and the sub-area; In the event that any of the photovoltaic cleaning robots feedback an adjustment request, the sub-area is reallocated based on the acceptance or adjustment requests feedback from all photovoltaic cleaning robots, with the sub-area being preferentially allocated to the photovoltaic cleaning robot that is closer to the sub-area, until all photovoltaic cleaning robots in the same collaborative group accept the allocation result to form a task sub-area.

3. The method according to claim 2, characterized in that The remaining area of ​​the photovoltaic station to be cleaned area, after removing the obstacle information, is divided into a number of continuous initial area blocks, wherein the area of ​​each initial area block is not less than the maximum area that can be cleaned by a single photovoltaic cleaning robot in a single time, and at least two initial area blocks are allocated to each of the same collaborative groups. Based on the ratio of the cleanable area to the unfinished cleaning area, sub-areas in the initial area blocks are allocated to each photovoltaic cleaning robot in the same collaborative group to form a preliminary task plan, including the following steps: Divide the remaining area into several continuous strips along the direction parallel to the arrangement of the photovoltaic panels in the photovoltaic station, and divide each of the continuous strips into several initial area blocks along the direction perpendicular to the arrangement of the photovoltaic panels. The area of ​​each initial area block is not less than the maximum cleaning area that can be cleaned by a single photovoltaic cleaning robot in a single time, and the initial area block contains an integer number of photovoltaic panels. Based on the position information of all photovoltaic cleaning robots in each collaborative group, the straight-line distance between each collaborative group and the center of each initial area block is calculated. Based on the allocation rule that the straight-line distance between the collaborative group and the corresponding initial area block does not exceed the maximum distance between any two photovoltaic cleaning robots in the collaborative group, at least two initial area blocks that are closer to each other are preferentially allocated to the corresponding collaborative group; Counting the total cleanable area of ​​all photovoltaic cleaning robots in each collaborative group, calculating the ratio of the area of ​​the initial area block to the total cleanable area, and dividing the initial area block into sub-areas equal to the number of photovoltaic cleaning robots in the collaborative group according to the ratio; Determining the area of ​​each sub-region according to the cleanable area of ​​each photovoltaic cleaning robot so that the ratio of the area of ​​the sub-region to the cleanable area of ​​the corresponding photovoltaic cleaning robot tends to be consistent; Combined with the unfinished cleaning ratio of each photovoltaic cleaning robot, the sub-area is adjusted based on the principle that the straight-line distance between the edge of the sub-area corresponding to the photovoltaic cleaning robot with a higher unfinished cleaning ratio and the edge of the cleaned area is smaller. The calculation formula of the straight-line distance is: , in the formula represents the distance of the corresponding sub-area of ​​the i-th photovoltaic cleaning robot, Indicates the base distance, It represents the unfinished cleaning ratio of the i-th photovoltaic cleaning robot. The adjusted sub-area is associated with the corresponding photovoltaic cleaning robot to form a preliminary task plan.

4. The method according to claim 1, wherein When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, the moving speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot is adjusted in a swarming control manner. After the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal, including the following steps: When the photovoltaic cleaning robot detects that the distance to an adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold, it sends a boundary synchronization request to the adjacent photovoltaic cleaning robot, so that the two adjacent photovoltaic cleaning robots exchange their current travel directions and distance information from the common boundary line based on the boundary synchronization request, and adjust their respective movement speeds using a swarming control method so that the time difference between the two adjacent photovoltaic cleaning robots reaching the common boundary line is within a preset range; After the two adjacent photovoltaic cleaning robots reach the common boundary line, they move synchronously in a direction parallel to the common boundary line, maintaining a preset distance during the movement. When an obstacle is detected on the movement trajectory, based on the obstacle information and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot, so that the adjacent photovoltaic cleaning robot adjusts its own movement trajectory accordingly based on the trajectory adjustment signal, so as to maintain the collaborative distance of the two adjacent photovoltaic cleaning robots within the preset distance range; After the adjacent photovoltaic cleaning robots avoid obstacles, they restore to the original cleaning path or replan the route to the next boundary section according to the boundary information of the task sub-area updated in real time until the cleaning operation of the common boundary line is completed.

5. The method according to claim 4, characterized in that The method of synchronously moving in a direction parallel to the common boundary line, maintaining a preset distance during movement, and adjusting the steering angle to avoid the obstacle based on the obstacle information and the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area when an obstacle is detected on the movement trajectory includes the following steps: Collecting vertical distance information between the two adjacent photovoltaic cleaning robots and a common boundary line, exchanging the vertical distance information through a self-organizing network communication relay node, and adjusting the travel directions of the two adjacent photovoltaic cleaning robots so that the travel directions are both parallel to the common boundary line and the distance difference from the common boundary line is within a preset safety distance; Calculating a straight-line distance between the two adjacent photovoltaic cleaning robots; when the straight-line distance between the two adjacent photovoltaic cleaning robots is greater than a preset distance, increasing the movement speed of the photovoltaic cleaning robot closer to the inner side of the common boundary and reducing the movement speed of the photovoltaic cleaning robot closer to the outer side, so that the straight-line distance is within the preset distance; When an obstacle is detected in the travel path in front of the two adjacent photovoltaic cleaning robots, the coordinate information and lateral width of the obstacle are recorded, and based on the coordinate information of the obstacle, the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is calculated; When the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is greater than the lateral width of the obstacle, the steering angle is adjusted in the direction away from the common boundary line based on the principle that the size of the steering angle is proportional to the lateral width, or when the straight-line distance between the photovoltaic cleaning robot itself and the boundary of the task sub-area is less than or equal to the lateral width, the steering angle is adjusted in the direction close to the common boundary line, and a new travel trajectory is generated, and the minimum distance between the new travel trajectory and the common boundary line is not less than the preset safety distance.

6. The method according to claim 1, characterized in that The step of constructing a dynamic adjacency graph model based on the position information and speed information of each photovoltaic cleaning robot comprises the following steps: Calculate the straight-line distance between every two photovoltaic cleaning robots in the robot cluster based on the position information, the moving rate and the moving direction in the speed information; Taking the position point corresponding to the coordinate information of each photovoltaic cleaning robot as a node, when the straight-line distance between the two photovoltaic cleaning robots is within the preset adjacency judgment range and the angle between the moving direction and the boundary line of each current task sub-area meets the preset angle condition, a connecting edge is established between the position points of the two photovoltaic cleaning robots, the edge weight is determined based on the moving rate, and a dynamic adjacency graph model is constructed.

7. The method according to claim 1, characterized in that The controlling of each photovoltaic cleaning robot to exchange information through a self-organizing network communication relay node using a time division multiple access protocol so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and simultaneously broadcasting obstacle information in the robot cluster in real time through the self-organizing network communication relay node, comprises the following steps: According to the preset time segment division rules, each photovoltaic cleaning robot in the robot cluster is assigned a dedicated information sending time segment, and the duration of the information sending time segment is set according to the amount of position information, speed information and task status information required for a single information interaction; Control each photovoltaic cleaning robot to send the information to be interacted with to the ad hoc network communication relay node within its own dedicated information transmission time segment, so that the ad hoc network communication relay node adds a corresponding forwarding sequence number to each of the information to be interacted with in the order of receipt, and broadcasts the information to be interacted with to all other photovoltaic cleaning robots, wherein the information to be interacted with includes obstacle information, coordinate information of the collection location, and a time identifier of the collection moment; After receiving a delay exception signal sent by any other photovoltaic cleaning robot under preset conditions, the exclusive time segments corresponding to the two photovoltaic cleaning robots corresponding to the delay exception are readjusted, and the interval between the exclusive time segments is shortened. The preset condition is that the full time difference exceeds the preset delay range, and the full time difference is the time difference from the time the information to be interacted is sent from itself to the time it is received by the target photovoltaic cleaning robot.

8. A photovoltaic cleaning robot multi-machine task scheduling and collaborative operation system, characterized in that: include: A construction module is used to obtain the position information and speed information of each photovoltaic cleaning robot in the robot cluster in the photovoltaic station, and to construct a dynamic adjacency graph model based on the position information and speed information of each photovoltaic cleaning robot; a control module for controlling each photovoltaic cleaning robot to exchange information through a self-organizing network communication relay node using a time division multiple access protocol, so that the communication delay between each photovoltaic cleaning robot in the robot cluster is within a preset delay range, and at the same time, broadcasting obstacle information in real time in the robot cluster through the self-organizing network communication relay node; a partitioning module for partitioning the area to be cleaned in the photovoltaic station into segments based on the dynamic adjacency graph model and the obstacle information, in combination with the remaining power and cleaned area of ​​each photovoltaic cleaning robot, and determining the task sub-area of ​​each photovoltaic cleaning robot through the robot cluster to achieve dynamic allocation of task load according to the adaptability of the robot model; An adjustment module is used to adjust the movement speed of the photovoltaic cleaning robot and the adjacent photovoltaic cleaning robot by using a swarming control method when the photovoltaic cleaning robot detects that the distance between itself and the adjacent photovoltaic cleaning robot is less than or equal to a preset collaborative distance threshold. After the two adjacent photovoltaic cleaning robots reach a common boundary line, when an obstacle is detected on the travel trajectory, the steering angle is adjusted to bypass the obstacle, and a trajectory adjustment signal is sent to the adjacent photovoltaic cleaning robot at the same time, so that the adjacent photovoltaic cleaning robot adjusts the corresponding travel trajectory accordingly based on the trajectory adjustment signal.

9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it can implement a photovoltaic cleaning robot multi-machine task scheduling and collaborative operation method according to any one of claims 1 to 7.

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