Marine robot energy optimization path planning method, program, device and storage medium considering spatiotemporal environmental changes

Abstract

The present application belongs to the technical field of path planning, and particularly relates to a marine robot energy optimization path planning method, program, device and storage medium considering space-time environment changes. In order to overcome the problem of low path planning efficiency and poor endurance of the marine robot in a long-time task due to the dynamic changes of the marine environment, the present application firstly constructs an energy evaluation function, and then utilizes the improved Lazy Theta* algorithm to dynamically expand and optimize the marine environment map, so as to ensure that the marine robot can maintain a relatively optimal energy utilization state in a complex environment, realize fast and efficient path planning, and thus improve the endurance performance and working efficiency of the marine robot.

Description

Technical Field

[0001] This invention belongs to the field of path planning technology, specifically relating to a method, program, device, and storage medium for energy optimization path planning of marine robots that takes into account changes in spatiotemporal environment. Background Technology

[0002] With the gradual maturation of marine energy technology, marine robots have shown broad application prospects in long-endurance missions such as resource exploration, environmental monitoring, and communication relay. However, due to the complexity and dynamism of the marine environment, especially the rapid changes in spatiotemporal environment, traditional path planning methods often struggle to adapt to these changes, resulting in low path planning efficiency, limited robot endurance, and severely impacting their mission execution capabilities. Therefore, to address these problems encountered by marine robots in long-endurance missions, there is an urgent need to develop a more efficient path planning method that adapts to dynamic environmental changes, in order to improve the endurance and energy utilization efficiency of marine robots in complex environments.

[0003] Currently, some path planning methods have achieved preliminary results in research. The paper "Energy optimal trajectory planning of an underwater robot using a genetic algorithm" utilizes BondGraph technology to model a marine robot and iteratively optimizes the trajectory through a genetic algorithm. This incorporates complex factors from the underwater environment into the computational model, ensuring path smoothness while significantly reducing energy consumption. However, this method does not comprehensively consider spatiotemporal environmental changes, and its real-time performance is difficult to guarantee in complex sea conditions.

[0004] The paper "Intelligent Path Planning of Underwater Robot Based on Reinforcement Learning" proposes an intelligent path planning method for underwater robots based on reinforcement learning. It utilizes an N-step Priority Double DQN (NPDDQN) algorithm for path planning, establishes a three-dimensional marine environment model, and proposes an empirical selection mechanism to improve the algorithm's stability in dynamic environments. However, this method has relatively high computational complexity and a long learning process.

[0005] Furthermore, other methods, such as classic path planning algorithms like A* and Dijkstra, while capable of relatively accurate path planning in static environments, lack the ability to quickly adapt to environmental changes and effectively update paths in real time when dealing with complex dynamic marine environments. This results in significant performance limitations when dealing with scenarios involving the balance of ocean energy conversion and consumption. Summary of the Invention

[0006] The purpose of this invention is to provide a method, program, device, and storage medium for energy-optimized path planning of marine robots that considers changes in the spatiotemporal environment. This invention fully integrates the dynamic characteristics of the marine environment with real-time calculations of marine energy conversion and consumption, constructs an energy evaluation function, and then utilizes an improved Lazy Theta* algorithm to dynamically search and optimize on a marine environment map. This ensures that the marine robot can maintain a relatively optimal energy utilization state in complex environments, achieving fast and efficient path planning, thereby improving the endurance and operational efficiency of the marine robot.

[0007] A method for energy optimization path planning of marine robots considering spatiotemporal environmental changes includes the following steps:

[0008] Step 1: Obtain the prior nautical chart of the target sea area and divide the prior nautical chart into a raster map;

[0009] Step 2: The marine robot obtains its current position and state information, and plans a path from the current position to the target point using the improved LazyTheta* algorithm;

[0010] Step 2.1: In the prior nautical chart's raster map, initialize the starting point and target point, setting the evaluation value of the starting point to 0; initialize both the OPEN and CLOSED sets to be empty sets, and add the starting point to the OPEN set;

[0011] Step 2.2: Determine if the OPEN set is empty; if it is empty, the search fails and the calculation stops.

[0012] Step 2.3: Remove the point with the smallest corresponding evaluation value from the OPEN set and add it to the CLOSED set, and use it as the current node. The evaluation value of a point is the energy consumption of the path from the starting point to that point;

[0013] Step 2.4: Determine the current node Is it the target point? If the current node... If the target point is found, the calculation ends, the CLOSED set is output, and the nodes are connected sequentially from the starting point to the target point in chronological order to complete the path planning; otherwise, proceed to step 2.5.

[0014] Step 2.5: Access the current node For each of the adjacent nodes, determine whether it can be expanded, and also determine whether it is in the CLOSED set. For each adjacent node that can be expanded but is not in the CLOSED set... After executing steps 2.6 to 2.7, return to step 2.2;

[0015] Step 2.6: Determine the current node parent node Straight line to expandable adjacent nodes Is the energy consumption less than that of the current node? To expandable adjacent nodes Energy consumption;

[0016] If yes, then for the node and Perform line-of-sight detection; if the detection passes, then proceed with the node... As a node Calculate the node from its parent node The evaluation value is calculated from the starting point to the node. The moment;

[0017] If no or the line-of-sight detection fails, proceed according to the node. For nodes Calculate the node from its parent node The evaluation value is calculated from the starting point to the node. The moment;

[0018] Step 2.7: If node If it is not in the OPEN set, then the node will be... Add to the OPEN set; if node In the OPEN set, the nodes are updated according to the calculation results of step 2.6. Evaluation value and from the starting point to the node The moment;

[0019] Step 3: After the ocean robot has traveled for a preset time according to the path planning results, if it has not reached the target point, it returns to Step 2.

[0020] Furthermore, the evaluation value of the point is the energy consumption of the path from the starting point to that point, specifically:

[0021]

[0022] in, Indicates the distance from the starting point to the point. The path points between them, the 0th path point is the starting point, and the 1st path point is the starting point. Path points are points ; Indicates from the first Path point moved to the The energy consumption power of the marine robot is predicted based on environmental information from prior nautical charts along the path of the waypoints. Indicates from the first Path point moved to the Path length of a path point; Indicates from the first Path point moved to the The speed of the marine robot is predicted based on environmental information from prior nautical charts along the path of the waypoints.

[0023] Furthermore, the prediction of the marine robot's energy consumption power based on prior environmental information from the nautical chart specifically involves:

[0024]

[0025] in, Indicates from the first Path point moved to the The wind energy conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points. Indicates the first Path point moved to the The solar power conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points. This indicates the energy consumption power of the marine robot itself, in relation to its speed. related.

[0026] Furthermore, the aforementioned from the first Path point moved to the Path length of a path point Specifically:

[0027]

[0028] in, Represents the radius of the Earth; Indicates the latitude of that point; This indicates the longitude of that point.

[0029] Furthermore, the aforementioned from the first Path point moved to the The speed of the marine robot is predicted based on environmental information from prior nautical charts along the path of the waypoints. Specifically:

[0030]

[0031] in, , , , From the first Path point moved to the During the waypoint process, the ocean robot's water velocity, land heading, latitudinal velocity of the ocean current, and meridional velocity of the ocean current are all obtained from prior nautical charts and are known items; , From the first Path point moved to the During the waypoint process, the ocean robot's ground speed and heading angle are unknowns, and a unique solution can be obtained through the above two equations.

[0032] Furthermore, the prediction of the marine robot's wind energy conversion power based on prior nautical chart environmental information specifically involves:

[0033]

[0034] in, , , The charging loss coefficient of the marine robot, the wind energy utilization coefficient, and the radius of the wind turbine blades are all fixed values. , From the first Path point moved to the The air density and airflow speed of the grid cells containing the waypoints are obtained from prior nautical charts.

[0035] The prediction of the marine robot's solar energy conversion power based on prior nautical chart environmental information specifically involves:

[0036]

[0037] in, , The photovoltaic panel area of ​​the marine robot and the light energy conversion coefficient considering battery charging losses are both fixed values. For from the first Path point moved to the The solar radiation intensity of the grid cell containing the path point is obtained from the prior nautical chart.

[0038] Furthermore, the energy consumption power of the marine robot itself. This includes the power consumption of its own intelligent control module, navigation and communication module, information fusion module, energy capture module, environmental perception module, and power execution module;

[0039] The intelligent control module is used to input task information and supports data processing for all functions of the marine robot;

[0040] The navigation and communication module is used to obtain the precise positioning of the marine robot according to the Beidou navigation system and is responsible for the real-time data transmission of other modules;

[0041] The information fusion module is used to acquire input information from the energy capture module, the environmental perception module, and the navigation and communication module, organize and form a priori nautical chart of the target sea area, rasterize the priori nautical chart, and mark the environmental data of each raster.

[0042] The planning algorithm module is used to execute the improved Lazy Theta* algorithm to plan the path of the marine robot from its current position to the target point;

[0043] The energy capture module is used to capture solar energy, wind energy and ocean energy, and convert them into electrical energy and power required for the normal operation of the marine robot.

[0044] The environmental perception module is used to acquire meteorological information about the sea area where the marine robot is located;

[0045] The power execution module is used to drive the movement and operation of the marine robot, ensuring that it performs tasks according to the planned path, and can adjust the power output in real time to adapt to changes in the environment.

[0046] A computer device / equipment / system includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method for energy optimization path planning of marine robots that takes into account changes in spatiotemporal environment.

[0047] A computer-readable storage medium storing a computer program / instructions that, when executed by a processor, implements the steps of the above-described method for energy-optimized path planning of marine robots that takes into account changes in the spatiotemporal environment.

[0048] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the above-described method for energy-optimized path planning of marine robots that takes into account changes in the spatiotemporal environment.

[0049] The beneficial effects of this invention are as follows:

[0050] This invention fully integrates the dynamic characteristics of the marine environment with the real-time calculation of marine energy conversion and consumption, constructs an energy evaluation function, and then uses an improved Lazy Theta* algorithm to perform dynamic search and optimization on the marine environment map. This enables marine robots to effectively adapt to the spatiotemporal environmental changes in different marine areas, maintain a relatively optimal energy utilization state, and thus achieve fast and efficient path planning, improving the endurance and working efficiency of marine robots. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the path detected by the line of sight.

[0052] Figure 2 This is a schematic diagram of paths where line-of-sight detection fails.

[0053] Figure 3 This is a flowchart illustrating the path planning from the current position to the target point using the improved Lazy Theta* algorithm in this invention.

[0054] Figure 4 This is a schematic diagram of the system structure of the marine robot in this invention. Detailed Implementation

[0055] The present invention will now be further described with reference to the accompanying drawings.

[0056] The purpose of this invention is to address the problems of low path planning efficiency and poor endurance of marine robots during long-endurance missions due to the dynamic changes in the marine environment. Traditional path planning methods cannot fully consider the dynamic changes in the spatiotemporal environment and the need to capture various natural energy sources (such as sea breeze, waves, solar energy, and ocean currents). To meet the planning requirements of marine robots during long-endurance missions, this invention proposes an energy-optimized path planning method for marine robots that considers spatiotemporal environmental changes. This method fully integrates the dynamic characteristics of the marine environment with real-time calculations of marine energy conversion and consumption, constructs an energy evaluation function, and then uses an improved Lazy Theta* algorithm to dynamically search and optimize on the marine environment map, ensuring that the marine robot can maintain a relatively optimal energy utilization state in complex environments, achieving fast and efficient path planning.

[0057] like Figure 4 As shown, the marine robot is equipped with an intelligent control module, an energy conversion module, a navigation and communication module, an information fusion module, a planning algorithm module, an environmental perception module, and a power execution module.

[0058] The intelligent control module is responsible for supporting data processing for all functions of the marine robot; the energy conversion module is responsible for capturing ocean energy and converting it into the electrical energy and power required for the normal operation of the marine robot; the navigation and communication module is responsible for achieving precise navigation and positioning of the marine robot and real-time data transmission with other modules, ensuring the acquisition of location information and environmental updates, and supporting the effectiveness and accuracy of path planning; the information fusion module is responsible for organizing and analyzing input information and normalizing it; the planning algorithm module is responsible for designing an energy-optimal evaluation function based on the Lazy Theta* algorithm principle, starting from the initial grid, continuously calculating the evaluation function value of the expansion direction, adding the grid with the minimum evaluation value to the path, until the target grid is reached, and completing the planning task; the power execution module is responsible for driving the robot's movement and operation, ensuring that the task is executed according to the planned path, and can adjust the power output in real time to adapt to changes in the environment; the environmental perception module is responsible for acquiring real-time meteorological information of the sea area where the marine robot is located, providing necessary data support, so that the path planning algorithm can help the marine robot dynamically adapt to environmental changes.

[0059] Furthermore, the environmental perception module of the marine robot mainly includes a weather station, a current meter, a wave sensor, and a solar radiation sensor. The weather station can monitor and collect sea breeze information in real time, specifically including wind speed and direction. The current meter can monitor and collect ocean wave information in real time, specifically including current velocity and direction. The wave sensor can monitor and collect ocean current information in real time, specifically including significant wave height, average wave period, and wave direction. The solar radiation sensor can monitor and collect solar radiation intensity information in real time. The energy conversion module of the marine robot mainly includes a wind turbine, a hydrofoil, and a photovoltaic panel. The wind turbine can convert wind energy into electrical energy required for the marine robot's operation. The photovoltaic panel can convert solar energy into electrical energy required for the marine robot's operation. The hydrofoil can convert wave energy into thrust for the marine robot's propulsion.

[0060] First, obtain a priori nautical chart of the target sea area and divide the priori chart into a raster map; such as Figure 1 and Figure 2 As shown, black represents land, and white represents navigable areas. When the black coverage area of ​​a grid is less than 10%, it is assigned a value of 0, indicating that the area is navigable. Figure 1 As shown, a straight line can cross the grid; otherwise, a value of 1 is assigned, indicating that the area is not navigable, as shown in the image. Figure 2 As shown, you need to navigate along the edge of the black grid.

[0061] The marine robot receives mission information, uses its current position as the starting point, and plans a path from its current position to the target point based on its own state information using an improved Lazy Theta* algorithm, such as... Figure 3 As shown, the specific steps include:

[0062] Step 1: In the prior nautical chart's raster map, initialize the starting point and target point, setting the evaluation value of the starting point to 0; initialize both the OPEN and CLOSED sets to be empty, and add the starting point to the OPEN set;

[0063] Step 2: Determine if the OPEN set is empty; if it is empty, the search fails and the calculation stops.

[0064] Step 3: Remove the point with the smallest corresponding evaluation value from the OPEN set and add it to the CLOSED set, and use it as the current node. ;

[0065] node Evaluation value The energy consumption along the path from the starting point to this point is calculated as follows:

[0066]

[0067] in, Indicates the distance from the starting point to the point. The path points between them, the 0th path point is the starting point, and the 1st path point is the starting point. Path points are points ;

[0068] Indicates from the first Path point moved to the The energy consumption power of the marine robot, predicted based on prior environmental information from the nautical chart, is calculated as follows:

[0069]

[0070] in, This indicates the energy consumption power of the marine robot itself, in relation to its speed. related; Indicates from the first Path point moved to the The wind energy conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points. Indicates the first Path point moved to the The solar power conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points.

[0071]

[0072] in, , , The charging loss coefficient of the marine robot, the wind energy utilization coefficient, and the radius of the wind turbine blades are all fixed values. , From the first Path point moved to the The air density and airflow speed of the grid cells containing the waypoints are obtained from prior nautical charts.

[0073]

[0074] in, , The photovoltaic panel area of ​​the marine robot and the light energy conversion coefficient considering battery charging losses are both fixed values. For from the first Path point moved to the The solar radiation intensity of the grid cell containing the path point is obtained from the prior nautical chart;

[0075] Indicates from the first Path point moved to the The path length of a path point is calculated as follows:

[0076]

[0077] in, Represents the radius of the Earth; Indicates the latitude of that point; Indicates the longitude of that point;

[0078] Indicates from the first Path point moved to the The speed of the marine robot, predicted from prior nautical chart environmental information along the path, is calculated as follows:

[0079]

[0080] in, , , , From the first Path point moved to the During the waypoint process, the ocean robot's water velocity, land heading, latitudinal velocity of the ocean current, and meridional velocity of the ocean current are all obtained from prior nautical charts and are known items; , From the first Path point moved to the During the waypoint process, the ocean robot's ground speed and heading angle are unknowns, and a unique solution can be obtained through the above two equations;

[0081] Step 4: Determine the current node Is it the target point? If the current node... If the target point is found, the calculation ends, and the CLOSED set is output. The nodes are connected sequentially from the starting point to the target point in chronological order to complete the path planning.

[0082] Step 5: Access the current node For all adjacent nodes (in the eight directions: up, down, left, right, top-left, bottom-left, top-right, and bottom-right), determine whether each adjacent node can be expanded, and also check if each adjacent node is in the CLOSED set. There are two specific cases where a node cannot be expanded in a certain direction: one is from the node... To node The ground speed of the marine robot obtained from the above formula There is no solution, meaning that due to weather limitations and excessively high ocean current speeds, the bow of the marine robot cannot be adjusted to the required position; another solution is to calculate the marine robot's ground-based speed. A value of zero indicates an obstacle in the search direction, making the ocean robot's path unreachable.

[0083] For each adjacent node that is expandable and not in the CLOSED set Perform the following judgment:

[0084] (1) Determine the current node parent node Straight line to expandable adjacent nodes Is the energy consumption less than that of the current node? To expandable adjacent nodes Energy consumption;

[0085] If yes, then for the node and Perform line-of-sight detection; if the detection passes, then proceed with the node... As a node Calculate the node from its parent node The evaluation value is calculated from the starting point to the node. The moment;

[0086] If no or the line-of-sight detection fails, proceed according to the node. For nodes Calculate the node from its parent node The evaluation value is calculated from the starting point to the node. The moment;

[0087] (2) If node If it is not in the OPEN set, then the node will be... Add to the OPEN set; if node In the OPEN set, the nodes are updated according to the calculation result of (1). Evaluation value and from the starting point to the node The moment;

[0088] Current node All expandable adjacent nodes that are not in the CLOSED set After executing (1) and (2), return to step 2.

[0089] This invention enables marine robots to effectively adapt to changes in the spatiotemporal environment of different marine areas, maintain optimal energy utilization, and thus achieve rapid and efficient path planning, thereby improving the endurance and working efficiency of marine robots.

[0090] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for energy-optimized path planning of marine robots considering spatiotemporal environmental changes, characterized in that, The method comprises the following steps: Step 1: obtaining a prior sea chart of a target sea area, and dividing the prior sea chart into a grid chart; Step 2: obtaining the position and state information of the marine robot at the current time, and planning a path from the current position to the target point by using the improved Lazy Theta* algorithm; Step 2.1: initializing the start point and the target point in the grid chart of the prior sea chart, setting the evaluation value of the start point to 0, initializing the OPEN set and the CLOSED set as empty sets, and adding the start point to the OPEN set; Step 2.2: judging whether the OPEN set is empty; if yes, determining that the search fails and stopping the calculation; Step 2.3: Remove the point with the lowest evaluation value from the OPEN set and add it to the CLOSED set and make it the current node ; the evaluation value of the point is the energy consumption of the path from the start point to the point Step 2.4: judge whether the current node is the target node; if the current node is the target node, end the calculation, output the CLOSED set, and connect the nodes in time sequence from the start node to the target node to complete the path planning. Step 2.4: judge whether the current node is the target node; if the current node is the target node, end the calculation, output the CLOSED set, and connect the nodes in time sequence from the start node to the target node to complete the path planning.​ Otherwise, step 2.5 is executed; Step 2.5: Visit the current node all of its neighboring nodes, determine whether each neighboring node can be expanded, and determine whether each neighboring node is in the CLOSED set, for each neighboring node that can be expanded and is not in the CLOSED set , perform steps 2.6 through 2.7, and return to step 2.2; Step 2.6: Determine the current node parent node Straight line to expandable adjacent nodes Is the energy consumption less than that of the current node? To expandable adjacent nodes Energy consumption; If yes, then for the node and Perform line-of-sight detection; if the detection passes, then proceed with the node... As a node Calculate the node from its parent node The evaluation value is calculated from the starting point to the node. The moment; If no or the line-of-sight detection fails, the evaluation value of the node is calculated as the parent node of the node , and the time from the start point to the node is calculated. ​ Step 2.7: If node is not in the OPEN set, then add node to the OPEN set; if node is in the OPEN set, then update the evaluation value of node and the time from the start node to node according to the result of step 2.

6. Step 3: after the marine robot moves for a preset time according to the path planning result, if the target point is not reached, returning to step 2.

2. The method of claim 1, wherein: The evaluation value of the point is the energy consumption of the path from the start point to the point, and specifically is: ； wherein, denotes the path point between the start point and point , the 0th path point is the start point, and the th path point is the point ; denotes the path between the th path point and the th path point, the energy consumption power of the marine robot is predicted according to the environmental information of the prior sea chart; denotes the path length from the th path point to the th path point; denotes the path between the th path point and the th path point, the sailing speed of the marine robot is predicted according to the environmental information of the prior sea chart.

3. The method of claim 2, wherein: The energy consumption power of the marine robot is predicted according to the environmental information of the prior sea chart, and specifically is: ； in, Indicates from the first Path point moved to the The wind energy conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points. Indicates the first Path point moved to the The solar power conversion power of the marine robot is predicted based on environmental information from prior nautical charts along the path points. This indicates the energy consumption power of the marine robot itself, in relation to its speed. related.

4. The method of claim 2, wherein: The path length from the first path point to the second path point The path length from the first path point to the second path point The path length from the first path point to the second path point , specifically: ； wherein, represents the radius of the Earth; represents the latitude at the point; represents the longitude at the point.

5. The method of claim 2, wherein: The first path point is determined according to the environmental information of the prior sea chart The path point moves to the first path point, and the sailing speed of the marine robot is predicted according to the environmental information of the prior sea chart The path point moves to the first path point, and the sailing speed of the marine robot is predicted according to the environmental information of the prior sea chart , Specifically: ； in, , , , From the first Path point moved to the During the waypoint process, the ocean robot's water velocity, land heading, latitudinal velocity of the ocean current, and meridional velocity of the ocean current are all obtained from prior nautical charts and are known items; , From the first Path point moved to the During the waypoint process, the ocean robot's ground speed and heading angle are unknowns, and a unique solution can be obtained through the above two equations.

6. The method of claim 3, wherein: The wind energy conversion power of the marine robot is predicted according to the environmental information of the prior sea chart, and specifically is: ； wherein, , , are the charging loss coefficient of the marine robot, the wind energy utilization coefficient and the radius of the wind turbine blade respectively, all of which are fixed values; , are the air density and the air flow velocity of the grid where the path from the path point moves to the path point, both of which are obtained from the prior map; The solar energy conversion power of the marine robot is predicted according to the environmental information of the prior sea chart, and specifically is: ； wherein, , are respectively the photovoltaic panel area of the marine robot, the light energy conversion coefficient considering the battery charging loss, both are fixed values; is the solar radiation intensity of the grid where the path from the path point moves to the path point, obtained from the prior map.

7. The method of claim 3, wherein: The energy consumption power of the marine robot itself The consumption power of the intelligent control module, the navigation communication module, the information fusion module, the planning algorithm module, the energy capture module, the environment perception module, and the power execution module carried by the marine robot itself The intelligent control module is used for inputting task information and supporting data operation of all functions of the marine robot; The navigation communication module is used for obtaining the accurate positioning of the marine robot according to the Beidou navigation system, and is responsible for real-time data transmission of other modules; The information fusion module is used for obtaining the input information of the energy capturing module, the environment perception module and the navigation communication module, sorting and forming the prior sea chart of the target sea area, rasterizing the prior sea chart, and marking the environmental data of each grid; The planning algorithm module is used for executing the improved Lazy Theta* algorithm to plan the path of the marine robot from the current position to the target point; The energy capturing module is used for capturing solar energy, wind energy and marine energy, and converting them into electric energy and power required for normal operation of the marine robot; The environment perception module is used for obtaining the meteorological information of the sea area where the marine robot is located; The power execution module is used for driving the movement and operation of the marine robot, ensuring the execution of the task according to the planned path, and being able to adjust the power output in real time to adapt to the changes of the environment.

8. A computer device comprising a memory, a processor, and a computer program stored on the memory, wherein: The processor executes the computer program to realize the steps of the method in any one of claims 1 to 7.

9. A computer readable storage medium having stored thereon computer programs / instructions, characterized in that: The computer program / instruction is executed by the processor to realize the steps of the method in any one of claims 1 to 7.

10. A computer program product comprising computer programs / instructions, characterized in that: The computer program / instruction is executed by the processor to realize the steps of the method in any one of claims 1 to 7.

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