Automatic control method and system for dredging robot

Abstract

According to the automatic control method and system for the desilting robot, comprehensive sludge resistance is calculated based on real-time detection data, optimal power is determined by combining power parameters of the robot, and due to dynamic change of the data, the optimal power can be accurately matched with the working environment, the sludge resistance is increased, and the power can be rapidly adjusted to prevent stagnation; when resistance is small, power is reduced, waste is avoided, and energy utilization rate is increased; in addition, according to the optimal power, the dredging frequency is calculated, the close relation between the frequency and the power is established, the frequency is dynamically adjusted along with the change of the optimal power, dredging is made to be practical, and flexible and accurate adjustment is achieved. And meanwhile, the moving path is dynamically planned according to real-time sludge thickness information, environmental data are fully utilized, the robot covers more dredging areas within limited time, the operation efficiency and comprehensiveness are improved, and the problem that repeated operation or key area omission easily occurs in traditional fixed path planning is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of dredging robot technology, and in particular to an automated control method and system for dredging robots. Background Technology

[0002] As a highly efficient and intelligent dredging device, dredging robots have been widely used in various dredging scenarios. They can operate in complex and harsh silt environments, replacing manual labor to complete heavy and dangerous dredging tasks, and significantly improving dredging efficiency and safety. However, the level of automation control of dredging robots still needs to be improved: (1) Traditional dredging robot control methods are often simple and fixed. In terms of power control, a preset fixed power mode is usually adopted, which cannot dynamically adjust the power output according to the real-time changes in silt resistance. When encountering a sudden increase in silt resistance, the fixed power may not be able to meet the dredging needs, resulting in dredging efficiency. (1) The robot may stop or even stagnate; when the silt resistance is small, it will cause energy waste; (2) In terms of dredging frequency control, most dredging robots adopt a constant dredging frequency and cannot be flexibly adjusted according to the actual power required. This makes it difficult to guarantee the dredging effect. Either the dredging is not thorough, or the excessive dredging causes unnecessary disturbance to the surrounding environment; (3) For the planning of the movement path, the traditional method is mostly based on the pre-set fixed route and lacks effective use of real-time silt thickness information. This may cause the robot to repeatedly pass through the dredged area during the dredging process, or miss the key area with thicker silt, and fail to achieve efficient and comprehensive dredging operation. Summary of the Invention

[0003] In view of this, the present invention proposes an automated control method and system for dredging robots, which can effectively solve the defects of existing technologies, such as the inability to dynamically adjust power output according to real-time changes in silt resistance, the inability to flexibly adjust dredging frequency according to actual power requirements, and the inability to dynamically plan movement paths.

[0004] The technical solution of this invention is implemented as follows:

[0005] An automated control method for a dredging robot includes:

[0006] Based on real-time detection data of the silt environment in which the dredging robot is located, the overall resistance generated by the silt to the dredging robot is calculated.

[0007] Based on the calculated comprehensive resistance and combined with the robot's own power parameters, the optimal power required by the robot is determined.

[0008] Based on the optimal power required by the dredging robot, the dredging frequency of the dredging robot is calculated;

[0009] Based on the real-time detected silt thickness information, the movement path of the dredging robot is planned;

[0010] The calculated optimal power, dredging frequency, and planned movement path are input into the control system of the dredging robot to achieve automated control of the dredging robot.

[0011] As a further optional solution to the automated control method for the dredging robot, the calculation of the comprehensive resistance exerted by the dredging robot on the dredging robot based on real-time detection data of the sludge environment in which the dredging robot is located specifically includes:

[0012] The data obtained include silt density, dredging robot speed, contact area between dredging robot and silt, silt friction coefficient, and depth of dredging robot penetration into silt.

[0013] Based on the silt density, the dredging robot's moving speed, the contact area between the dredging robot and the silt, the friction coefficient of the silt, and the depth to which the dredging robot penetrates the silt, the overall resistance generated by the silt on the dredging robot is calculated.

[0014] As a further optional solution to the automated control method for the dredging robot, the specific calculation formula for determining the optimal power required by the dredging robot is as follows:

[0015] ;

[0016] in, This represents the optimal power required by the dredging robot. This represents the overall resistance exerted by the silt on the dredging robot. This represents the movement speed of the dredging robot. This refers to the efficiency of the power transmission system of the dredging robot. This refers to the efficiency of the dredging execution agency. This represents the basic power consumption of the dredging robot when it is not engaged in dredging operations.

[0017] As a further optional embodiment of the automated control method for the dredging robot, the specific formula for calculating the dredging frequency of the dredging robot is as follows:

[0018] ;

[0019] in, This represents the dredging frequency of the dredging robot. This represents the initial dredging frequency of the dredging robot. This represents the optimal power required by the dredging robot. This represents the standard power demand at the initial dredging frequency.

[0020] As a further optional embodiment of the automated control method for the dredging robot, the step of planning the movement path of the dredging robot based on the real-time detected silt thickness information specifically includes:

[0021] Obtain the coordinates of the points in the path planning, as well as the thickness of the silt at those points;

[0022] The movement path of the dredging robot is calculated based on the coordinate points and the thickness of the silt at those points.

[0023] As a further optional solution to the automated control method for the dredging robot, the specific formula for calculating the movement path of the dredging robot is as follows:

[0024] ;

[0025] in, This represents the movement path of the dredging robot. Represented as coordinate points in path planning. Represented as coordinate points The thickness of the silt at that location, Represented as the thickness of the silt Related path weight functions, This is represented as the next coordinate point in the path planning.

[0026] As a further optional embodiment of the automated control method for the dredging robot, the path weight function The specific method for determining it is as follows:

[0027] when hour, This indicates that the area does not require dredging and the dredging robot will not pass through this area.

[0028] when hour, This indicates that the silt thickness in the area is moderate, and the dredging robot passes through and dredges the silt according to the preset priority.

[0029] when hour, This indicates that the silt layer in the area is relatively thick, and the dredging robot will prioritize passing through and dredging that area.

[0030] in, , , These are the preset minimum, intermediate, and maximum values ​​for silt thickness, respectively.

[0031] An automated control system for a dredging robot includes:

[0032] The data detection module is used to acquire real-time detection data of the silt environment in which the dredging robot is located;

[0033] The comprehensive resistance calculation module is used to calculate the comprehensive resistance of the silt to the dredging robot based on the real-time detection data of the silt environment in which the dredging robot is located.

[0034] The optimal power determination module is used to determine the optimal power required by the dredging robot based on the calculated comprehensive resistance and the robot's own power parameters.

[0035] The dredging frequency calculation module is used to calculate the dredging frequency of the dredging robot based on the optimal power required by the dredging robot.

[0036] The path planning module is used to plan the movement path of the dredging robot based on the real-time detected silt thickness information;

[0037] The control command output module is used to input the calculated optimal power, dredging frequency, and planned movement path to the control system of the dredging robot, so as to realize the automated control of the dredging robot.

[0038] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of any of the above-described automated control methods for a dredging robot.

[0039] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the above-described automated control methods for a dredging robot.

[0040] The beneficial effects of this invention are as follows: Based on real-time detection data of the silt environment in which the dredging robot is located, the comprehensive resistance exerted by the silt on the robot is calculated. Then, combined with the robot's own power parameters, the optimal power is determined. Since real-time detection data can promptly reflect changes in the silt environment, the comprehensive resistance calculated based on this dynamic data also changes accordingly. Therefore, the optimal power determined based on the comprehensive resistance can accurately match the needs of the current working environment. When encountering a sudden increase in silt resistance, the power output can be quickly adjusted to ensure the dredging robot has sufficient power to continue operating and avoid stagnation. Conversely, when the silt resistance is low, the power output can be reasonably reduced, effectively avoiding energy waste and improving energy utilization. Furthermore, based on the optimal power required by the dredging robot, the dredging frequency is calculated, and a dredging frequency... The close relationship between efficiency and actual operating power is crucial. In actual dredging processes, different silt environments and operating stages have different requirements for dredging frequency. When the optimal power changes, it means that the difficulty or demand of the operation has changed. At this time, the dredging frequency can be dynamically adjusted through a specific dredging frequency adjustment formula, making the dredging operation more in line with actual needs and achieving flexible and precise adjustment of the dredging frequency. In addition, the movement path of the dredging robot is planned based on the real-time detected silt thickness information, making full use of real-time environmental data. This dynamic path planning method ensures that the robot can cover more areas that need dredging within a limited operating time, improving the efficiency and comprehensiveness of dredging operations and solving the problems of repetitive work or omission of key areas that may occur in traditional fixed path planning methods. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of an automated control method for a dredging robot according to the present invention;

[0043] Figure 2 This is a schematic diagram of the composition of an automated control system for a dredging robot according to the present invention;

[0044] Figure 3 This is a schematic diagram of the composition of a computing device according to the present invention. Detailed Implementation

[0045] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] refer to Figures 1 to 3 An automated control method for a dredging robot, comprising:

[0047] Based on real-time monitoring data of the silt environment in which the dredging robot is located, the overall resistance exerted by the silt on the dredging robot is calculated, specifically including:

[0048] The data obtained include silt density, dredging robot speed, contact area between dredging robot and silt, silt friction coefficient, and depth of dredging robot penetration into silt.

[0049] Based on the silt density, the dredging robot's moving speed, the contact area between the dredging robot and the silt, the friction coefficient of the silt, and the depth to which the dredging robot penetrates the silt, the overall resistance generated by the silt on the dredging robot is calculated.

[0050] Specifically, by acquiring real-time detection data from multiple dimensions such as silt density, dredging robot speed, contact area with silt, friction coefficient of silt, and depth of penetration into silt, the comprehensive resistance can be calculated. This can comprehensively and meticulously reflect the actual resistance status of the dredging robot in the current silt environment. The influence of different factors on the resistance is taken into consideration, making the calculation results closer to the real situation.

[0051] Accurate calculation of the overall resistance lays the foundation for determining the optimal power required for the dredging robot. Since the overall resistance takes into account a variety of factors that affect the resistance, the optimal power determined based on it can more accurately match the actual operation requirements. When the silt environment changes and the overall resistance changes, the power output can be adjusted in a timely and reasonable manner based on this calculation result, so as to avoid insufficient power that would hinder the dredging operation or excessive power that would waste energy, thereby improving the rationality and efficiency of power utilization.

[0052] The appropriate setting of dredging frequency is closely related to the operational resistance. The comprehensive resistance calculated by this technical solution can serve as an important reference for adjusting the dredging frequency. For example, when the comprehensive resistance is high, it means that the difficulty of dredging increases, and the dredging frequency can be increased accordingly to enhance the dredging effect. Conversely, when the comprehensive resistance is low, the dredging frequency can be appropriately reduced to reduce unnecessary energy consumption and impact on the surrounding environment while ensuring the dredging quality, thereby achieving a dynamic match between the dredging frequency and the actual operational situation.

[0053] The overall resistance of silt to a dredging robot affects the ease of its movement. Understanding the overall resistance in different areas, combined with information such as silt thickness, allows for more rational planning of the robot's movement path. For example, areas with excessive overall resistance that may cause the robot to get stuck or have difficulty moving can be avoided, while areas with relatively low resistance and where silt needs to be cleared can be prioritized. This improves the efficiency and safety of dredging operations and ensures that the robot can operate smoothly in silt environments.

[0054] It should be noted that the calculation of the overall resistance exerted by the current silt on the dredging robot is as follows:

[0055] ;

[0056] in, The density of the silt, To improve the movement speed of the dredging robot, The contact area between the dredging robot and the silt. Let be the coefficient of friction of the silt. The dredging robot went deep into the silt. , These are correction coefficients pre-set according to different sludge types;

[0057] Correction coefficient , Determined in the following ways:

[0058] Data from various types of silt were collected in advance, including silt density. dredging robot movement speed Contact area with silt The coefficient of friction of silt And the depth to which the dredging robot penetrates the silt. And measure the actual combined resistance that each type of sludge exerts on the dredging robot;

[0059] Using the collected sample data, the least squares method is used to fit the data. , The value of .

[0060] The real-time detection data is acquired through a variety of sensors installed on the dredging robot, including but not limited to density sensors, speed sensors, area measurement sensors, friction coefficient sensors, depth sensors, and silt thickness sensors.

[0061] Based on the calculated overall resistance and combined with the robot's own power parameters, the optimal power required by the robot is determined; in some embodiments, the specific calculation formula for determining the optimal power required by the robot is as follows:

[0062] ;

[0063] in, This represents the optimal power required by the dredging robot. This represents the overall resistance exerted by the silt on the dredging robot. This represents the movement speed of the dredging robot. This refers to the efficiency of the power transmission system of the dredging robot. This refers to the efficiency of the dredging execution agency. This represents the basic power consumption of the dredging robot when it is not engaged in dredging operations.

[0064] Specifically, the overall resistance that the current silt poses to the dredging robot was comprehensively considered. dredging robot movement speed Efficiency of power transmission system Efficiency of dredging implementation agencies and basic power consumption in non-dredging operation state Several key factors, including those comprehensively reflecting the various working conditions and energy consumption of the dredging robot during actual operation, lead to the calculated optimal power... It can accurately match the actual operational needs at different times and in different silt environments, ensuring that the dredging robot always operates with appropriate power.

[0065] Due to overall resistance It is calculated based on real-time monitored silt environment data and changes with factors such as silt density, friction coefficient, and robot depth within the silt. The optimal driving force... The calculation is closely dependent on the overall resistance. Therefore, it can adjust in real time according to the dynamic changes of the silt environment. When encountering a sudden increase in silt resistance, the optimal power increases accordingly to ensure that the dredging robot has enough ability to overcome the resistance and continue to work, avoiding stagnation. When the silt resistance decreases, the optimal power also decreases, reducing unnecessary energy consumption and improving energy utilization efficiency.

[0066] Basic power consumption during non-dredging operations The inclusion of this power in the calculation ensures that the energy required for the robot to maintain basic operation is fully considered when calculating the optimal power. This allows the dredging robot to obtain a stable and appropriate power supply during operation, whether it is in a dredging state or in a non-dredging state such as movement or posture adjustment. This ensures the stability and reliability of dredging operations and reduces the occurrence of operation interruptions or abnormal situations caused by unreasonable power supply.

[0067] It should be noted that the efficiency of the power transmission system And the efficiency of dredging implementation agencies Obtain it through the following methods:

[0068] After the dredging robot is designed and manufactured, a special performance test experiment is conducted.

[0069] In the experiment, the input power and output power of the power transmission system, as well as the input power and effective dredging power of the dredging actuator, were measured respectively.

[0070] The efficiency of the power transmission system was calculated based on the measurement results. Efficiency of dredging implementation agencies ,in Input power to the power transmission system, For the output power of the power transmission system, Input power to the dredging actuator. To ensure the effective dredging power of the dredging execution agency.

[0071] Based on the optimal power required by the dredging robot, the dredging frequency of the robot is calculated; in some embodiments, the specific calculation formula for the dredging frequency of the robot is as follows:

[0072] ;

[0073] in, This represents the dredging frequency of the dredging robot. This represents the initial dredging frequency of the dredging robot. This represents the optimal power required by the dredging robot. This represents the standard power demand at the initial dredging frequency.

[0074] Specifically, the optimal power required for the dredging robot Standard power requirements at initial dredging frequency As a key variable, combined with the initial dredging frequency and frequency adjustment coefficient To calculate the dredging frequency Due to optimal dynamics The calculation frequency changes dynamically with the real-time changes in the silt environment, allowing the calculated dredging frequency to be adjusted according to actual operational needs. When encountering harder, thicker silt, the optimal power increases, and the dredging frequency increases accordingly, thereby enhancing the dredging force and ensuring effective silt removal. Conversely, when the silt is softer, the optimal power decreases, and the dredging frequency decreases, avoiding over-dredging and unnecessary disturbance to the surrounding environment.

[0075] By introducing the standard power requirements under the initial dredging frequency As a reference benchmark, it can more accurately measure the difference between the current optimal power and the standard condition, frequency adjustment coefficient. This allows for flexible settings based on the specific performance and dredging effect requirements of the dredging robot, further refining the adjustment precision of the dredging frequency. This calculation method enables the dredging frequency to better match the dredging operation needs under different working conditions, ensuring the quality and efficiency of the dredging operation.

[0076] It should be noted that the frequency adjustment coefficient in the dredging frequency adjustment formula... The value is set according to the type of dredging actuator and the dredging effect requirements of the dredging robot, and its range is 0.1-0.5.

[0077] Based on the real-time detected silt thickness information, the movement path of the dredging robot is planned, specifically including:

[0078] Obtain the coordinates of the points in the path planning, as well as the thickness of the silt at those points;

[0079] The movement path of the dredging robot is calculated based on the coordinate points and the thickness of the silt at those points.

[0080] In some embodiments, the calculation formula for the movement path of the dredging robot is as follows:

[0081] ;

[0082] in, This represents the movement path of the dredging robot. Represented as coordinate points in path planning. Represented as coordinate points The thickness of the silt at that location, Represented as the thickness of the silt Related path weight functions, This is represented as the next coordinate point in the path planning.

[0083] Specifically, the formula uses the silt thickness detected in real time at the coordinate points. Information enables the dredging robot to dynamically plan its movement path based on the actual distribution of the silt environment. The silt thickness is constantly changing in different areas, and this technical solution can capture these changes in a timely manner and reflect them in the path planning. This avoids the shortcomings of traditional fixed path planning methods that cannot adapt to dynamic environmental changes, and ensures that the robot always follows the optimal or better path for dredging operations.

[0084] Path weight function The setting is a major highlight of this technical solution. Different weight values ​​are assigned according to different silt thickness ranges, so that areas with thicker silt will be given higher weight during path planning. In this way, the dredging robot will give priority to passing through areas with thicker silt when planning the path, ensuring that the dredging work in key areas can be carried out in a timely manner, improving the targeting and effectiveness of dredging operations, and avoiding the situation of missing important dredging areas.

[0085] By comprehensively considering the distance between coordinate points and the weighted factors related to the thickness of the silt to calculate the movement path, the dredging robot can cover more areas that need dredging within a limited working time. The robot can move efficiently along the planned path, reducing unnecessary detours and repeated travel, shortening the overall dredging operation time, and significantly improving dredging efficiency.

[0086] In some embodiments, the path weight function The specific method for determining it is as follows:

[0087] when hour, This indicates that the area does not require dredging and the dredging robot will not pass through this area.

[0088] when hour, This indicates that the silt thickness in the area is moderate, and the dredging robot passes through and dredges the silt according to the preset priority.

[0089] when hour, This indicates that the silt layer in the area is relatively thick, and the dredging robot will prioritize passing through and dredging that area.

[0090] in, , , These are the preset minimum, intermediate, and maximum values ​​for silt thickness, respectively.

[0091] Specifically, by setting different silt thickness ranges and corresponding weight function values, it is possible to accurately divide each area into different dredging priorities based on the silt thickness. When the weight is 0, it clearly indicates that the area does not require dredging, and the dredging robot can bypass it directly, avoiding wasting time and energy in areas where no work is needed; when When the weight increases linearly, it indicates that the silt thickness in the area is moderate, and dredging should be carried out according to the preset priority; when At the same time, the weight changes in a specific way as the silt thickness increases, highlighting the area as a high-priority dredging area; this precise priority division ensures that the dredging robot can prioritize the areas that need dredging the most, improving the targeting and efficiency of dredging operations.

[0092] Weighting function and real-time detected silt thickness Closely related, this technology can dynamically adjust weight values ​​based on the actual silt thickness at different coordinate points. In actual dredging environments, silt thickness is complex and variable. This technology can respond to these changes in a timely manner, ensuring that path planning is always based on the latest silt thickness information, guaranteeing the accuracy and adaptability of path planning, and enabling the dredging robot to flexibly cope with various complex silt environments. The path planning method based on the weight function comprehensively considers the impact of silt thickness on dredging operations. When planning the movement path, the dredging robot tends to select areas with higher weights, i.e., areas with thicker silt and greater need for dredging. At the same time, it rationally connects various coordinate points, making the overall path more reasonable. This helps to reduce the robot's movement distance and number of turns, improves movement efficiency, and ensures that the dredging operation can cover the most key dredging areas with the shortest path.

[0093] Through precise prioritization and rational path planning, dredging robots can allocate more time and energy resources to high-priority dredging areas, avoiding resource dispersion and waste. Within a limited operating time, they can complete dredging tasks in more critical areas, improving the utilization efficiency of dredging resources and reducing the cost of dredging operations. Prioritizing areas with thicker silt can effectively prevent various problems caused by excessive silt accumulation, such as aggravated water pollution and obstructed flood flow. At the same time, rational path planning ensures the comprehensiveness and systematic nature of dredging operations, reducing the possibility of overlooking areas, thereby guaranteeing the overall quality of dredging operations and better achieving dredging objectives.

[0094] An automated control system for a dredging robot includes:

[0095] The data detection module is used to acquire real-time detection data of the silt environment in which the dredging robot is located;

[0096] The comprehensive resistance calculation module is used to calculate the comprehensive resistance of the silt to the dredging robot based on the real-time detection data of the silt environment in which the dredging robot is located.

[0097] The optimal power determination module is used to determine the optimal power required by the dredging robot based on the calculated comprehensive resistance and the robot's own power parameters.

[0098] The dredging frequency calculation module is used to calculate the dredging frequency of the dredging robot based on the optimal power required by the dredging robot.

[0099] The path planning module is used to plan the movement path of the dredging robot based on the real-time detected silt thickness information;

[0100] The control command output module is used to input the calculated optimal power, dredging frequency, and planned movement path to the control system of the dredging robot, so as to realize the automated control of the dredging robot.

[0101] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of any of the above-described automated control methods for a dredging robot.

[0102] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the above-described automated control methods for a dredging robot.

[0103] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automated control method for a dredging robot, characterized in that, The method comprises the following steps: Based on the real-time detection data of the silt environment where the dredging robot is located, the comprehensive resistance generated by the current silt to the dredging robot is calculated; According to the calculated comprehensive resistance, combined with the power parameters of the dredging robot itself, the optimal power required by the dredging robot is determined; According to the optimal power required by the dredging robot, the dredging frequency of the dredging robot is calculated; According to the real-time detection data of the silt thickness information, the moving path of the dredging robot is planned; The calculated optimal power, dredging frequency and planned moving path are input to the control system of the dredging robot to realize the automatic control of the dredging robot.

2. The method for automated control of a dredging robot according to claim 1, characterized in that, The method comprises the following steps: Obtain the silt density, the moving speed of the dredging robot, the contact area between the dredging robot and the silt, the friction coefficient of the silt, and the depth of the dredging robot into the silt; Based on the silt density, the moving speed of the dredging robot, the contact area between the dredging robot and the silt, the friction coefficient of the silt, and the depth of the dredging robot into the silt, the comprehensive resistance generated by the current silt to the dredging robot is calculated.

3. The method for automated control of a dredging robot according to claim 2, characterized in that, The specific calculation formula for determining the optimal power required by the dredging robot is: ； wherein, represents the optimal power required for the dredging robot, represents the combined resistance generated by the current sludge to the dredging robot, represents the moving speed of the dredging robot, represents the efficiency of the power transmission system of the dredging robot, represents the efficiency of the dredging actuator, represents the basic power consumption of the dredging robot in a non-dredging operation state.

4. The method for automated control of a dredging robot according to claim 3, characterized in that, The specific calculation formula for calculating the dredging frequency of the dredging robot is: ； wherein, represents a dredging frequency for the dredging robot, represents an initial dredging frequency for the dredging robot, represents an optimal power required for the dredging robot, represents a standard power requirement at the initial dredging frequency.

5. The method for automated control of a dredging robot according to claim 4, characterized in that, The method comprises the following steps: Obtain the coordinate points in the path planning and the silt thickness at the coordinate points; Based on the coordinate points and the silt thickness at the coordinate points, the moving path of the dredging robot is calculated.

6. The method for automated control of a dredging robot according to claim 5, characterized in that, The specific calculation formula for calculating the moving path of the dredging robot is: ； wherein, is a moving path of the dredging robot, is a coordinate point in the path planning, is a coordinate point is a silt thickness at the coordinate point, is a path weight function related to the silt thickness , is a next coordinate point in the path planning.

7. The method for automated control of a dredging robot according to claim 6, characterized in that, The path weight function The determination manner is specifically: When time, , indicates that the area does not need to be dredged and the dredging robot does not pass through this area; When , , indicates that the thickness of the silt in the area is moderate, and the dredging robot passes through and dredges according to the preset priority; When , , indicates that the area is thick in silt thickness, and the dredging robot is preferred to pass through and dredge; wherein, , , are respectively a pre-set minimum, intermediate and maximum value of the thickness of the sludge.

8. An automated control system for a dredging robot, characterized in that, The method comprises the following steps: A data detection module is configured to obtain real-time detection data of the silt environment where the dredging robot is located; A comprehensive resistance calculation module is configured to calculate the comprehensive resistance generated by the current silt to the dredging robot based on the obtained real-time detection data of the silt environment where the dredging robot is located; An optimal power determination module is configured to determine the optimal power required by the dredging robot according to the calculated comprehensive resistance and combined with the power parameters of the dredging robot itself; A dredging frequency calculation module is configured to calculate the dredging frequency of the dredging robot according to the optimal power required by the dredging robot; A path planning module is configured to plan the moving path of the dredging robot according to the real-time detection data of the silt thickness information; A control instruction output module is configured to input the calculated optimal power, dredging frequency and planned moving path to the control system of the dredging robot to realize the automatic control of the dredging robot.

9. A computing device, comprising: The storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the automatic control method for the dredging robot according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the automatic control method for the dredging robot according to any one of claims 1-7.

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