Unmanned cleaning ship for salvaging garbage and control method thereof

Abstract

The invention discloses an unmanned cleaning ship for salvaging garbage and a control method of the unmanned cleaning ship. The unmanned cleaning ship comprises a ship body, a garbage collecting device, a multi-mode sensing system, an intelligent control system and a water quality purifying device. The multi-mode sensing system senses the surrounding environment and transmits comprehensive environment information to the intelligent control system. The intelligent control system dynamically plans a navigation path according to the water surface garbage position, the obstacle data, the real-time ship body position, the historical cleaning efficiency and the energy storage state; according to the garbage type identification result, the distribution density and the storage cabin capacity state, the working state of the garbage collection device is adjusted in a self-adaptive mode; controlling the working state of the water purification device according to the water quality parameters, the flow velocity and the water temperature data. By integrating the multifunctional module and the intelligent control system, comprehensive perception, intelligent decision making and multifunctional treatment of the water area environment are achieved, the water area cleaning efficiency and quality are improved, and an innovative solution is provided for sustainable treatment of the water area environment.

Description

Technical Field

[0001] The present invention relates to the technical field of water environment protection, and in particular to an unmanned cleaning boat for salvaging garbage and a control method thereof. Background Art

[0002] With rapid economic development and increasing human activities, water pollution has become one of the major environmental challenges facing the world. Traditional manual cleaning methods are no longer sufficient when faced with large water areas and the increasing amount of pollutants.

[0003] Although existing water cleaning equipment has improved cleaning efficiency to a certain extent, it still has many shortcomings. First, most cleaning equipment has a single function, either focusing only on collecting surface garbage or only purifying water quality, and lacks comprehensive management capabilities. Secondly, existing equipment generally lacks intelligent control systems and is unable to adjust work strategies in real time according to the complex and changing water environment, resulting in low cleaning efficiency. Furthermore, many cleaning equipment has limited perception capabilities, making it difficult to accurately identify and locate surface garbage, and unable to effectively avoid surface and underwater obstacles, increasing operational risks. In addition, existing equipment often ignores energy management and efficiency optimization during the cleaning process, making it difficult to achieve long-term and large-scale autonomous operation. Finally, most cleaning equipment lacks real-time monitoring of water quality parameters and corresponding purification processing capabilities, and is unable to take appropriate purification measures for different water quality conditions.

[0004] These problems seriously restrict the effectiveness and efficiency of water environment management. The industry urgently needs an integrated, intelligent, and multifunctional unmanned cleaning ship to solve these problems. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides an unmanned cleaning boat for salvaging garbage and a control method thereof, which solves the problems of existing water area cleaning equipment such as single function, low intelligence, and incomplete cleaning effect.

[0006] To achieve the above objectives, in a first aspect, an unmanned cleaning vessel for salvaging garbage is provided, comprising a hull, and a garbage collection device disposed at the front end of the hull for collecting garbage on the water surface and transporting it to a garbage storage compartment within the hull; the vessel also comprises:

[0007] A multimodal sensing system provided on the hull, for sensing the surrounding environment and transmitting comprehensive environmental information to an intelligent control system provided inside the hull;

[0008] A water purification device provided at the bottom of the hull, for purifying the water during navigation;

[0009] The intelligent control system is used to:

[0010] Dynamically planning the navigation path of the vessel based on the surface garbage location data, surface obstacle data, underwater obstacle data, and real-time vessel location data in the comprehensive environmental information, combined with historical cleaning efficiency data and current energy reserve status;

[0011] Adaptively adjusting the working state of the garbage collection device based on the surface garbage type identification result and surface garbage distribution density in the comprehensive environmental information and the current capacity of the garbage storage compartment;

[0012] The working state of the water purification device is controlled according to the water quality parameter data, water flow rate data and water temperature data in the comprehensive environmental information.

[0013] In a second aspect, a control method for an unmanned cleaning vessel for salvaging garbage is provided, wherein the method is executed by an intelligent control system disposed in the vessel hull and comprises the following steps:

[0014] receiving comprehensive environmental information from a multimodal sensing system, the comprehensive environmental information including surface garbage location data, surface obstacle data, underwater obstacle data, real-time ship location data, surface garbage type identification results, surface garbage distribution density, water quality parameter data, water flow rate data, and water temperature data;

[0015] Obtain historical cleaning efficiency data, current energy reserve status and capacity status of waste storage compartments;

[0016] Dynamically planning the navigation path of the ship based on the surface garbage location data, surface obstacle data, underwater obstacle data, and real-time ship location data, combined with the historical cleaning efficiency data and current energy reserve status;

[0017] Adaptively adjusting the working state of the garbage collection device provided at the front end of the hull according to the surface garbage type identification result and the surface garbage distribution density, combined with the current capacity state of the garbage storage compartment;

[0018] The working state of the water purification device arranged at the bottom of the hull is controlled according to the water quality parameter data, water flow rate data and water temperature data.

[0019] The above technical solution has the following beneficial technical effects:

[0020] This unmanned cleaning boat achieves comprehensive perception, intelligent decision-making, and multifunctional management of the aquatic environment by integrating a multimodal sensing system, an intelligent control system, a garbage collection device, and a water purification device. The present invention can dynamically plan cleaning routes based on real-time environmental information, adaptively adjust garbage collection efficiency, and perform water purification, thereby significantly improving the efficiency and quality of water cleaning. At the same time, by comprehensively considering historical cleaning efficiency data and current energy reserve status, the cleaning boat can achieve long-term, highly efficient autonomous operation. Furthermore, the water purification function of the present invention provides a new means for the comprehensive management of aquatic environments, not only removing surface garbage but also improving water quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are provided for a better understanding of the present invention and are not intended to limit the present invention.

[0022] Figure 1 This is a functional block diagram of an unmanned cleaning vessel for salvaging garbage according to an embodiment of the present invention;

[0023] Figure 2 is a functional block diagram of a multimodal perception system according to an embodiment of the present invention;

[0024] Figure 3 is a functional block diagram of an intelligent control system according to an embodiment of the present invention;

[0025] Figure 4 is a functional block diagram of a water purification device according to an embodiment of the present invention;

[0026] Figure 5 This is a flow chart of a control method for an unmanned cleaning vessel for salvaging garbage according to an embodiment of the present invention;

[0027] Figure 6 is a specific flow chart of step S30 of an embodiment of the present invention;

[0028] Figure 7 is a specific flow chart of step S33 of an embodiment of the present invention;

[0029] Figure 8 Schematic diagram of the structure of a computer system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0031] Example 1

[0032] like Figure 1 As shown, an unmanned cleaning boat for salvaging garbage includes a hull, and a garbage collection device arranged at the front end of the hull, for collecting surface garbage and transporting it to a garbage storage compartment in the hull; it also includes: a multimodal perception system arranged on the hull, for sensing the surrounding environment and transmitting comprehensive environmental information to an intelligent control system arranged in the hull; a water purification device arranged at the bottom of the hull, for purifying the water during navigation; the intelligent control system is used to: dynamically plan the navigation path of the hull based on surface garbage location data, surface obstacle data, underwater obstacle data and real-time hull position data in the comprehensive environmental information, combined with historical cleaning efficiency data and current energy reserve status; adaptively adjust the working state of the garbage collection device based on the surface garbage type identification result and surface garbage distribution density in the comprehensive environmental information, combined with the current capacity status of the garbage storage compartment; and control the working state of the water purification device based on water quality parameter data, water flow rate data and water temperature data in the comprehensive environmental information.

[0033] The design of this unmanned cleaning vessel facilitates efficient waste removal and water purification. The hull is constructed of lightweight, high-strength composite materials with excellent corrosion and impact resistance. The front-mounted waste collection device features an adjustable multi-layer filter structure that can accommodate various sizes and types of surface debris. Trash is transported via a conveyor system to a modular waste storage compartment for easy cleaning and replacement. The multimodal perception system can include high-definition cameras, lidar, sonar, GPS positioning, and water quality sensors, working together to provide comprehensive environmental information to the intelligent control system. The water purification device, located on the bottom of the hull, can utilize a multi-stage purification system, including physical filtration, chemical adsorption, and biological purification, continuously purifying the surrounding water during navigation. The intelligent control system utilizes a deep learning algorithm to process the large amounts of data transmitted by the multimodal perception system in real time. Its functions include navigation path planning, waste collection regulation, and water purification control. The intelligent control system determines the optimal navigation path based on garbage distribution, obstacle locations, historical cleaning efficiency, and energy reserve status. It uses image recognition technology to identify garbage types and automatically adjusts the collection device's operating parameters based on garbage distribution density and storage compartment capacity. It also dynamically adjusts the purification device's operating parameters based on real-time water quality data, water temperature, and flow rate to ensure optimal purification results. Through this intelligent control strategy, the unmanned cleaning vessel can efficiently and comprehensively manage the water environment, achieving the dual functions of garbage removal and water purification, providing an innovative solution for improving the water ecosystem.

[0034] like Figure 2As shown, the multimodal perception system may include: a positioning module for obtaining real-time hull position data, the positioning module including a positioning signal receiver and an inertial measurement unit (IMU) for providing auxiliary positioning when the positioning signal is limited; a 360-degree panoramic camera for collecting image data of the surrounding environment including surface garbage; a millimeter-wave radar for detecting surface obstacle data, which includes the position, distance and relative speed of the surface obstacle data; an underwater sonar detector for obtaining position data and shape data of underwater obstacles, the underwater sonar detector having a multi-beam scanning function and being able to provide an underwater three-dimensional topographic map; a water quality detection sensor group for obtaining multiple water quality parameter data of the water body, including pH value, dissolved oxygen, turbidity, conductivity, ammonia nitrogen and total phosphorus; a flow rate sensor for obtaining water flow rate data, the flow rate sensor using an acoustic Doppler current meter (Acoustic Doppler Current Profiler (ADCP), capable of measuring the flow rate of different water layers; a water temperature sensor for obtaining water temperature data; a garbage storage compartment capacity sensor for real-time monitoring of the capacity status of the garbage storage compartment, including a weight sensor or a liquid level sensor; an energy management sensor for monitoring the remaining power, charge and discharge status and temperature of the battery pack on the hull.

[0035] Specifically, the multimodal perception system in this embodiment is the sensing unit of the unmanned cleaning vessel. It integrates a variety of advanced sensors to comprehensively perceive the vessel's surroundings and provide comprehensive data support for the intelligent control system. The positioning module can use a high-precision GNSS (Global Navigation Satellite System), and the receiver is combined with an IMU (Inertial Measurement Unit) to ensure accurate location information in all environments. The 360-degree panoramic camera uses a high-resolution image sensor and a wide-angle lens to capture all-round images of the surrounding environment, especially the distribution of surface debris. The millimeter-wave radar has strong penetration and high-precision ranging capabilities, allowing it to detect surface obstacles in all weather conditions. The underwater sonar detector uses multi-beam scanning technology to create accurate three-dimensional underwater terrain maps, effectively avoiding underwater obstacles. The water quality detection sensor group integrates a variety of electrochemical and optical sensors to simultaneously monitor multiple water quality parameters, providing a basis for water purification. The flow rate sensor can use ADCP technology to measure the flow rate of different water layers, which helps optimize the navigation path and purification efficiency. The water temperature sensor uses a high-precision thermistor to monitor water temperature changes in real time. The garbage storage compartment capacity sensor can use either a weight sensor or a liquid level sensor, depending on the specific design, to ensure timely and efficient garbage collection. The energy management sensor utilizes an intelligent Battery Management System (BMS) to comprehensively monitor battery status and ensure the reliability and safety of the ship's energy supply. Data from these sensors is transmitted in real time to the intelligent control system via a high-speed data bus. After fusion processing, it provides comprehensive environmental awareness capabilities for the ship's autonomous decision-making and control.

[0036] Alternative positioning modules include a variety of technical options. In addition to the combination of GNSS and IMU, a visual positioning system (VPS) can be used, which determines the position by analyzing the images captured by the camera. Another option is to use ultra-wideband (UWB) positioning technology, which provides high-precision positioning within a short distance. In certain specific environments, a positioning system based on wireless beacons, such as Bluetooth low energy (BLE) beacons or Wi-Fi signal strength indicator (RSSI) positioning, can be used. For large areas of water, a long baseline acoustic positioning system (LBL) can also be used.

[0037] The primary function of a GNSS receiver is to receive signals from multiple satellites and calculate the receiver's precise position through triangulation. It provides global positioning services, including longitude, latitude, and altitude information. In open waters, GNSS receivers can provide highly accurate position data.

[0038] The primary function of an inertial measurement unit (IMU) is to measure an object's acceleration, angular velocity, and orientation. It includes an accelerometer, gyroscope, and magnetometer. When GNSS signals are limited or lost, the IMU can estimate the position change of the UAV's hull through integration calculations, providing a short-term position estimate. The IMU also provides information about the vessel's attitude, such as pitch, roll, and heading, which is crucial for stable control and navigation.

[0039] Multibeam scanning technology is an advanced sonar detection method. It simultaneously transmits multiple acoustic beams, creating a fan-shaped coverage area. These sound waves reflect off underwater objects or the seabed and are captured by a receiver. By analyzing the time differences and intensity of these reflected signals, the system constructs a detailed three-dimensional underwater topographic map. This technology can quickly and efficiently scan large areas of water, providing high-resolution underwater topographic information, which is very effective for obstacle avoidance.

[0040] Alternatives to ADCP technology include several different flow rate measurement methods. Electromagnetic current meters use Faraday's electromagnetic induction principle to measure water flow velocity and are suitable for shallow water areas. Thermal current meters infer flow velocity by measuring the heat transfer rate and are suitable for small-scale, low-flow environments. Mechanical current meters, such as rotor current meters, measure flow velocity by the speed of the rotor driven by the water flow and have a simple structure. In addition, there is particle image velocimetry (PIV) based on image processing, which is suitable for flow velocity measurement in small water areas.

[0041] Fusion processing, as described above, involves comprehensive analysis and integration of data from multiple sensors. This involves data cleaning, time synchronization, spatial registration, and multi-source information fusion algorithms. For example, a Kalman filter can be used to fuse GNSS and IMU data for more accurate position estimates, or data from millimeter-wave radar and optical cameras can be combined to improve obstacle detection accuracy. The goal of fusion processing is to leverage the strengths of different sensors, complementing and validating each other to ultimately produce more comprehensive, accurate, and reliable environmental perception results, providing high-quality decision-making support for intelligent control systems.

[0042] like Figure 3 As shown, the intelligent control system in this embodiment is the decision-making and control unit of the unmanned cleaning vessel. It integrates multiple functional modules to achieve efficient and intelligent autonomous cleaning operations. The intelligent control system includes: an image recognition module, a data recording and analysis module, a path planning module, and an automatic obstacle avoidance module.

[0043] The image recognition module uses deep learning algorithms, such as convolutional neural networks (CNNs), to process images captured by the 360-degree panoramic camera in real time. This module can accurately identify different types of surface debris (such as plastic bottles and floating plants), as well as obstacles on the water (such as other ships and buoys). Furthermore, by analyzing the distribution of debris in the image, the module can estimate the density of surface debris, providing a valuable reference for subsequent cleaning path planning.

[0044] Specifically, the image recognition module estimates surface trash density through the following steps: First, a semantic segmentation algorithm (such as U-Net or Mask R-CNN) is used to accurately segment the 360-degree panoramic image into distinct regions: water surface, trash, and obstacles. Subsequently, an object detection algorithm (such as YOLO or SSD) is used to precisely locate and count trash. Based on the segmentation results, the system calculates the pixel area of ​​each trash object in the image and converts this into its actual physical area using camera parameters. The total area of ​​detected trash is divided by the total surface area to determine the trash coverage ratio, which serves as a density indicator. Simultaneously, a clustering algorithm (such as K-means or DBSCAN) is used to analyze the spatial distribution pattern of trash and identify high- and low-density areas. If equipped with a stereo camera or depth sensor, depth information of the trash can also be obtained, enabling more accurate three-dimensional spatial distribution estimation. The system tracks the movement of trash by analyzing consecutive frames to understand the dynamic changes in its distribution. Based on these analysis results, a heat map or density map is generated to visually demonstrate the density of trash distribution. The density estimation model is calibrated and validated by combining known water surface area with actual measurement data to improve estimation accuracy. Finally, the image analysis results are combined with data from other sensors (such as water quality sensors and sonar) to generate a comprehensive and accurate assessment of the density of trash on the water surface. This approach not only considers the amount and area of ​​trash, but also incorporates its spatial distribution characteristics and temporal dynamics, providing a detailed and accurate basis for cleaning route planning and efficiency optimization.

[0045] The Data Recording and Analysis module collects and processes key data from each cleaning task. It records the task's start and end times, the area cleaned, and the total amount of garbage collected. Using this data, the module can calculate historical cleaning efficiency, such as the area cleaned per unit time or the amount of garbage collected per unit area. This historical data helps to more accurately estimate the time and resources required for cleaning tasks.

[0046] The path planning module is used to develop the optimal navigation path for the unmanned cleaning ship. This module takes into account multiple factors: environmental data such as the location of surface garbage, surface obstacle information and underwater obstacle information obtained from the multimodal perception system, real-time hull position data and water quality parameter data, combined with historical cleaning efficiency data and the current energy reserve status of the hull. Through complex algorithms (such as A* algorithm or dynamic programming algorithm), the path planning module can dynamically generate an optimal path that balances cleaning efficiency, safety and energy consumption. Path planning will give priority to areas with higher garbage density, while avoiding known obstacles and ensuring that the task is completed within the energy allowed.

[0047] Historical cleaning efficiency data is obtained by recording and analyzing the performance of unmanned cleaning vessels during past missions. This includes information on the amount of garbage collected per unit time, the cleaning rate for different types of garbage, cleaning efficiency in different water conditions, the relationship between energy consumption and the amount of garbage cleaned, cleaning efficiency at different speeds, and the sustainability of cleaning results. This data is primarily collected automatically by the unmanned vessel's intelligent sensing system, which includes high-precision sensors, a real-time positioning system, an intelligent garbage identification and sorting system, and an onboard data processing unit. The system automatically records and analyzes various parameters to generate detailed efficiency reports. Furthermore, it integrates satellite remote sensing data and information from surrounding environmental monitoring stations to comprehensively evaluate cleaning effectiveness.

[0048] Energy reserve status is primarily monitored through the ship's onboard energy management system. This information includes the battery pack's current remaining charge, battery charge and discharge status, battery temperature, estimated remaining operating time (based on current charge and average energy consumption), and the real-time power generation of the solar panels. This information, monitored and calculated in real time by the ship's onboard battery management system (BMS) and related sensors, provides critical information for route planning and task scheduling, ensuring the vessel completes its cleaning mission within its energy constraints.

[0049] Path planning algorithms are used to achieve intelligent navigation for unmanned cleaning vessels. These include the A* algorithm, the RRT* algorithm, and the dynamic programming algorithm. The A* algorithm is a heuristic search algorithm for path planning in static environments, combining the greedy nature of best-first search with the completeness of Dijkstra's algorithm. The dynamic programming algorithm solves optimization problems by breaking down complex problems into subproblems and storing the solutions to these subproblems. It is suitable for path planning problems with time dependencies or multi-stage decision-making. The RRT* (Rapidly Expanding Random Trees) algorithm is a sampling-based path planning algorithm particularly well-suited for high-dimensional spaces and dynamic environments. In practical applications, the path planning module can combine these algorithms: using an improved A* algorithm for preliminary global path planning, the RRT* algorithm for handling dynamic obstacles and local path adjustments, and applying the dynamic programming algorithm to optimize the multi-stage cleaning task schedule. By combining these algorithms and data, the path planning module can generate an optimal path that balances cleaning efficiency, safety, and energy consumption, thereby enabling the intelligent operation of the unmanned cleaning vessel.

[0050] The automatic obstacle avoidance module is used to evaluate the collision risk during navigation in real time based on the navigation path planned by the path planning module and the surface obstacle data and underwater obstacle data in the comprehensive environmental information. When a potential collision risk is detected, the module dynamically calculates a local obstacle avoidance path. The local obstacle avoidance path is close to the originally planned navigation path while ensuring safety, and automatically returns to the originally planned navigation path after obstacle avoidance is completed.

[0051] Specifically, the automatic obstacle avoidance module, building on the path planning module, provides real-time obstacle avoidance capabilities to ensure the safe navigation of the unmanned cleaning vessel. This module continuously monitors surface and underwater obstacle data from a multimodal perception system and uses a collision risk assessment algorithm (such as a time-to-collision (TTC)-based method) to calculate potential collision risks in real time. When a potential collision risk is detected, the module immediately initiates a local path planning algorithm (such as the dynamic window approach) to calculate a safe obstacle avoidance path. This obstacle avoidance path ensures safety while remaining as close to the original route as possible to minimize the impact on cleaning efficiency. Once an obstacle is successfully avoided, the module automatically guides the vessel back to the original route, achieving smooth and continuous obstacle avoidance control. This dynamic obstacle avoidance capability enables the unmanned cleaning vessel to safely and efficiently complete cleaning tasks in complex and changing water environments. The dynamic window approach (DWA) is a local path planning algorithm used by mobile robots to avoid obstacles in dynamic environments. Based on the robot's motion model, this method calculates a safe path in real time, enabling the robot to avoid obstacles while remaining oriented toward its target.

[0052] like Figure 3 As shown, the intelligent control system may also include: a garbage collection adjustment module for adaptively adjusting the operating status of corresponding components in the garbage collection device based on the surface garbage type identification results and surface garbage distribution density in the comprehensive environmental information, combined with the current capacity of the garbage storage compartment; and a water purification control module for controlling the operating status of the water purification device based on the water quality parameter data, water flow rate data, and water temperature data in the comprehensive environmental information. The corresponding components include: an inlet mechanism with adjustable inlet width, a water pump with adjustable power, a filter with adjustable mesh size, and a drive mechanism with adjustable operating frequency for controlling the operating frequency of the garbage collection. The drive mechanism is at least one of a reciprocating mechanism, a rotary collector, or a conveyor belt.

[0053] Specifically, the garbage collection adjustment module is specifically used to: dynamically adjust the working parameters of the garbage collection device based on the surface garbage type identification results and surface garbage distribution density estimation in the comprehensive environmental information, combined with the current capacity status of the garbage storage compartment; wherein, the surface garbage type identification results include multiple types of plastic bottles, plastic bags, organic garbage, microplastic particles, fallen leaves, wood fragments and metal cans; the dynamic adjustment includes at least one of the following: when a plastic bottle or plastic bag is identified and the proportion of its area to the total area of ​​the image exceeds a preset threshold, the entrance width of the garbage collection device is increased to the maximum; The maximum value is set, and the power of the water pump in the garbage collection device is increased to a preset high power level; when microplastic particles are identified and their number per unit water area exceeds a preset density, the mesh size of the filter of the garbage collection device is increased to a preset high mesh size level, and the power of the water pump is reduced to a preset low power level; when the density of garbage distribution on the water surface exceeds a preset density threshold, the operating frequency of the garbage collection device is increased to a preset high frequency level; wherein, the capacity status of the garbage storage compartment is monitored in real time, and when the capacity reaches a preset high capacity level, the collection speed of the garbage collection device is reduced to a preset low speed level.

[0054] For larger items like plastic bottles and bags, when they are identified and their area in the image exceeds a preset threshold (e.g., 20%), the waste collection adjustment module instructs the waste collection device to increase its inlet width to its maximum value. Simultaneously, it also increases the pump power in the waste collection device to a preset high power level (e.g., 80% of rated power). This adjustment ensures efficient collection of large floating debris.

[0055] When microplastic particles are detected and their density exceeds a preset value (e.g., 100 particles per square meter), the waste collection adjustment module increases the mesh size of the waste collection device's filter to a preset high mesh size level (e.g., by 50%). At the same time, it reduces the power of the water pump to a preset low power level (e.g., 40% of the rated power). This adjustment helps to more effectively capture small particles of waste while preventing excessive water flow from washing away microplastics.

[0056] When the density of garbage on the water surface exceeds a preset density threshold (e.g., 5 pieces of garbage per square meter), the garbage collection adjustment module increases the operating frequency of the garbage collection device to a preset high frequency level (e.g., by 20%). This adjustment can improve cleaning efficiency in highly polluted areas.

[0057] In addition to adjusting for waste type and density, the waste collection control module also monitors the capacity of the waste storage chamber in real time. When the storage chamber reaches a preset high capacity level (e.g., 90% full), the module instructs the waste collection device to reduce the collection speed to a preset low speed level (e.g., 50% of normal speed). This mechanism prevents the storage chamber from overloading while providing sufficient time for the cleaning ship to find a waste transfer point or return to base.

[0058] Through this comprehensive and flexible adjustment mechanism, the unmanned cleaning vessel can automatically adjust its cleaning strategy according to different water surface pollution conditions and its own status. This not only improves cleaning efficiency, but also extends the continuous working time of the cleaning vessel and maximizes its cleaning capacity.

[0059] The water purification control module is responsible for optimizing the operation of the water purification device based on real-time environmental data. This module comprehensively analyzes the water quality parameters (such as pH value, dissolved oxygen, turbidity, etc.), water flow rate and water temperature data provided by the multimodal perception system, and dynamically adjusts the working mode of the purification device. For example, when it is detected that the water body is heavily polluted, the module will increase the treatment intensity of the purification device or start additional purification units; in areas with better water quality, the treatment intensity will be reduced to save energy. Water flow rate data is used to adjust the water inlet of the purification device to ensure treatment efficiency; water temperature data is used to optimize the biological purification process. Through this intelligent control, the water purification device can flexibly adjust the purification strategy according to the characteristics and pollution conditions of different waters to achieve efficient and accurate water quality improvement.

[0060] like Figure 3As shown, the path planning module may include: a data analysis unit, which is used to generate a garbage distribution map by clustering analysis of surface garbage location data, which includes garbage-dense area information, and generate an obstacle distribution map by spatial analysis of surface obstacle location data and underwater obstacle location data; generate a water quality status report including water pollution level based on water quality parameter data; the water pollution level is obtained based on a comprehensive comparative evaluation of multiple water quality parameter data and preset water quality standards; a path optimization unit, which is used to determine the optimal cleaning path based on the garbage distribution map and the obstacle distribution map, as well as the location and range of the garbage-dense area; a task priority determination unit, which is used to determine the priority of the cleaning task based on the following multiple factors: garbage-dense area information in the garbage distribution map; water pollution level in the water quality status report; current energy reserve status, which includes the remaining battery power and the estimated working time available for the cleaning task; an energy management unit, which is used to determine the energy usage strategy based on the remaining battery power, task requirements and weather forecast data; and according to the energy usage strategy, work in conjunction with the task priority determination unit to adjust the priority of the cleaning task to ensure maximum energy efficiency.

[0061] The path planning module is responsible for formulating efficient and reasonable cleaning strategies and paths. The data analysis unit first performs in-depth processing and analysis on the data collected by the multimodal perception system. For example, it can use clustering algorithms such as K-means or DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to analyze the location data of garbage on the water surface, generate an intuitive garbage distribution heat map, and clearly identify garbage-intensive areas. At the same time, spatial analysis techniques (such as Voronoi diagrams or rasterization methods) are used to process obstacle data to generate a detailed obstacle distribution map. For water quality data, the unit can use a multi-parameter weighted scoring model to compare multiple parameters such as pH, dissolved oxygen, and turbidity with national water quality standards to comprehensively evaluate the degree of water pollution.

[0062] Based on data analysis, the path optimization unit uses a pre-set algorithm to determine the optimal cleaning path. Specifically, the path optimization unit can use a modified A* algorithm or a rapidly-exploring random tree (RRT*) path planning algorithm, combined with garbage distribution maps and obstacle distribution maps, to generate a preliminary path. The path is then further optimized using a genetic algorithm or a particle swarm optimization algorithm. During this process, the algorithm considers multiple factors: first, prioritizing coverage of densely packed garbage areas to ensure efficient cleaning; second, avoiding obstacles to ensure vessel safety; third, considering water flow direction and speed to minimize energy consumption; and finally, maintaining the integrity of the cleaning area. For example, when encountering large areas of densely packed garbage, an S-shaped or spiral path is used to improve coverage efficiency; while in areas with more dispersed garbage, a straight path is chosen to save time and energy. Furthermore, the path optimization unit dynamically adjusts the path based on real-time conditions. For example, when new garbage accumulation points or moving obstacles are detected, the local path is rapidly recalculated to ensure the continuity and efficiency of the cleaning task.

[0063] Based on path optimization, the task prioritization unit further refines the cleaning strategy. It uses multi-criteria decision-making methods, such as the Analytic Hierarchy Process (AHP) or the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to comprehensively evaluate the priority of each cleaning area. Evaluation factors include: garbage density (calculated based on garbage distribution maps), water pollution level (derived from water quality status reports), energy status (including current power consumption and estimated working hours), and the ecological sensitivity of the area (such as whether it is close to important water sources or ecological protection areas). For example, areas with high garbage density, severe water pollution, and located in ecologically sensitive areas are given the highest priority; while areas with less garbage and good water quality are given a lower priority. In addition, the task prioritization unit also considers time factors, such as adjusting the cleaning plan in advance for regular garbage accumulation (for example, tourist attractions generate more garbage on weekends).

[0064] The energy management unit plays a key regulatory role throughout the cleaning process. It first analyzes historical energy consumption data to establish an accurate energy consumption prediction model. Then, it uses a dynamic programming algorithm to develop an optimal energy usage strategy, combining the current battery status, the expected task volume, and future weather forecasts (especially solar charging efficiency). For example, on days predicted to be sunny, more high-energy-consuming tasks are scheduled; on cloudy days or at night, low-energy-consuming tasks are prioritized. The energy management unit also monitors energy consumption in real time and triggers policy adjustments when actual energy consumption deviates significantly from expectations. Furthermore, it works closely with the task prioritization unit to temporarily adjust the order of tasks when energy is scarce, prioritizing important and less energy-intensive tasks. This ensures that critical areas are cleaned promptly while avoiding work interruptions due to energy depletion. Through this dynamic balance, the energy management unit not only maximizes energy efficiency but also improves the reliability and sustainability of the entire cleaning system.

[0065] like Figure 4 As shown, the water purification device includes at least one purification unit, and the purification unit is selected from one or more of a filtration system, an ultraviolet sterilization system, and a microbial degradation system; the water body is purified by passing through the at least one purification unit; the water purification control module is used to control the working state of the water purification device according to the water quality parameter data, water flow rate data, and water temperature data in the comprehensive environmental information. The water purification device can be simplified in certain application scenarios. For example, in areas with good water quality, only a filtration system is needed; in areas with more specific pollutants, the microbial degradation system is mainly relied upon; in scenarios where rapid sterilization is required, the ultraviolet sterilization system is mainly used. In one embodiment, the water purification device includes a filtration system, an ultraviolet sterilization system, and a microbial degradation system connected in sequence, and the water body is purified by passing through the filtration system, ultraviolet sterilization system, and microbial degradation system in sequence.

[0066] Water purification devices use multiple purification technologies to ensure comprehensive improvement in water quality. The filtration system can use multi-stage filtration, including primary mechanical filtration to remove large particles of impurities, activated carbon filtration to absorb organic pollutants, and precision membrane filtration to remove tiny particles and some bacteria. The ultraviolet sterilization system uses ultraviolet rays of a specific wavelength to destroy the DNA structure of microorganisms, achieving efficient sterilization. The microbial degradation system uses specific microbial communities to decompose organic pollutants in the water. The water purification control module dynamically adjusts the operating parameters of each purification unit by analyzing water quality parameters (pH, dissolved oxygen, turbidity, etc.), water flow rate, and water temperature in real time. For example, when a sudden increase in water turbidity is detected, the filtration system's operating intensity will be increased; when the water temperature is low, the ultraviolet irradiation time will be extended to compensate for the decrease in sterilization efficiency; and when the concentration of specific organic pollutants is detected to be elevated, the corresponding microbial community will be activated for targeted degradation.

[0067] like Figure 3 As shown, the water purification control module may specifically include: a first purification control submodule, which is used to increase the operating frequency of the filtration system when the turbidity exceeds a preset threshold; and dynamically adjust the working parameters of the filtration system according to the water flow rate data, which includes at least one of the following: increasing the filtration pressure and accelerating the filtration flow rate.

[0068] Specifically, the first purification control submodule is mainly responsible for the intelligent control of the filtration system. When the turbidity of the water body exceeds the preset threshold (for example, 5NTU), the submodule will immediately increase the operating frequency of the filtration system from 15 minutes per hour to continuous operation. At the same time, it will dynamically adjust the filtration parameters according to the real-time monitored water flow rate data. For example, when an increase in water flow rate is detected, the filtration pressure will be increased accordingly, from the standard 0.2MPa to 0.3MPa to ensure the filtration effect; or the filtration flow rate will be increased from 2m 3 / h increased to 3m 3 / h to match the increased water flow. This dynamic adjustment ensures that the filtration system always maintains optimal working condition under different hydrological conditions, effectively removing suspended solids while avoiding energy waste caused by over-filtration.

[0069] The water quality purification control module also includes: a second purification control submodule, which is used to: obtain real-time water quality parameter data including pH value, dissolved oxygen, turbidity, conductivity, ammonia nitrogen, and total phosphorus; obtain the influence weight of each real-time water quality parameter data on microbial growth; obtain current water temperature data, and determine the ultraviolet sterilization efficiency coefficient at the current water temperature based on a preset water temperature-ultraviolet sterilization efficiency correspondence; obtain a comprehensive evaluation result of the water quality parameters based on a multi-parameter weighted algorithm according to the real-time water quality parameter data, the influence weight and the ultraviolet sterilization efficiency coefficient; and dynamically adjust the working state of the ultraviolet sterilization system according to the comprehensive evaluation result by one of the following methods or a combination thereof: adjusting the power output of the ultraviolet lamp; adjusting the duration of ultraviolet irradiation; adjusting the frequency of ultraviolet irradiation.

[0070] Specifically, the second purification control submodule focuses on the intelligent control of the UV disinfection system. It first obtains comprehensive water quality parameter data, including pH (which can range from 6.5-8.5), dissolved oxygen (ideally 5-8 mg / L), turbidity (preferably below 5 NTU), conductivity (between 50-1500 μS / cm), ammonia nitrogen (below 0.5 mg / L), and total phosphorus (below 0.05 mg / L). These parameters are then assigned different weights based on their impact on microbial growth. For example, pH might be assigned a weight of 0.15, dissolved oxygen a weight of 0.25, turbidity a weight of 0.2, conductivity a weight of 0.1, ammonia nitrogen a weight of 0.15, and total phosphorus a weight of 0.15. These weights reflect the relative importance of each parameter to water quality and microbial growth. Simultaneously, based on the current water temperature (e.g., 20°C), it searches a preset table of water temperature-UV disinfection efficiency relationships to determine the corresponding efficiency coefficient (e.g., 0.9). This efficiency coefficient reflects the impact of water temperature on the effectiveness of UV sterilization. The higher the water temperature, the higher the sterilization efficiency. Next, a multi-parameter weighted algorithm is used to combine all factors to calculate a comprehensive evaluation score (for example, 75 points out of 100).

[0071] The calculation method is as follows: First, each water quality parameter is normalized to a scale of 0-100. For example, a pH of 7.5 (within the ideal range) would result in a score of 90; a dissolved oxygen of 6 mg / L (also within the ideal range) would result in a score of 85. Then, each parameter's normalized score is multiplied by its corresponding weight. For example, the weighted score for pH is 90 * 0.15 = 13.5. The weighted scores for all parameters are summed to obtain a preliminary comprehensive assessment score. Finally, this preliminary score is multiplied by the water temperature minus the UV disinfection efficiency factor (e.g., 0.9) to obtain the final comprehensive assessment score. A high comprehensive assessment score (e.g., above 80) indicates good water quality, effective microbial growth suppression, and the UV disinfection system is maintaining standard operating conditions. A low comprehensive assessment score (e.g., below 60) indicates poor water quality, the potential for microbial proliferation, and the need to increase the UV disinfection system's operating intensity.

[0072] Based on this evaluation result, the system will dynamically adjust the working status of the ultraviolet disinfection system. For example, when the score is low (for example, below 60 points), the power of the ultraviolet lamp will be increased from the standard 30W to 40W, or the irradiation time will be extended from 15 minutes per hour to 20 minutes, or the irradiation frequency will be increased from once every 2 hours to once every 1.5 hours. On the contrary, when the score is high (for example, above 80 points), the system will appropriately reduce the power of the ultraviolet lamp or reduce the irradiation time to save energy. This refined control ensures that the ultraviolet disinfection system can maintain the best sterilization effect under different water quality conditions while avoiding unnecessary energy consumption. Through real-time adjustments, the system can quickly respond to changes in water quality, maintain the cleanliness of the water body, and maximize energy efficiency.

[0073] The water purification control module also includes: a third purification control submodule, which is used to control the microbial community of the microbial degradation system according to water environment parameters, wherein the water environment parameters include pH value, water flow rate data and water temperature data. The control includes releasing corresponding acid-resistant or alkali-resistant microbial communities according to the pH value, adjusting the release rate of the microbial community according to the water flow rate data, and adjusting the temperature of the microbial culture chamber according to the water temperature data to maintain microbial activity.

[0074] Specifically, the third purification control submodule is used to: when the pH value is higher than a preset upper limit, release the acid-resistant microbial community in the microbial culture chamber of the microbial degradation system stored in the hull to the microbial reaction area of ​​the microbial degradation system, and the microbial reaction area is in direct contact with the water at the bottom of the hull; when the pH value is lower than a preset lower limit, release the alkali-resistant microbial community in the microbial culture chamber of the microbial degradation system stored in the hull to the microbial reaction area of ​​the microbial degradation system; according to the water flow rate data, dynamically adjust the concentration of the microbial community in the microbial reaction area by adjusting the release rate of the microbial community from the microbial culture chamber to the microbial reaction area of ​​the microbial degradation system; according to the water temperature data, adjust the temperature of the microbial culture chamber to maintain optimal microbial activity.

[0075] Specifically, the third purification control submodule is mainly responsible for the intelligent management of the microbial degradation system. When the pH value of the water body is detected to be outside the normal range (for example, higher than 8.5 or lower than 6.5), the module will respond immediately. If the pH value is higher than the preset upper limit, the system will release specific acid-resistant microbial communities (such as thiobacillus or nitrifying bacteria) from the microbial culture chamber to the microbial reaction area. These microorganisms can survive and function in acidic environments, helping to neutralize alkaline substances and adjust the pH value back to the normal range. On the contrary, when the pH value is lower than the preset lower limit, the system will release alkaline-resistant microbial communities (such as Pseudomonas or Bacillus). These microorganisms can survive in alkaline environments and help neutralize acidic substances through metabolic activities. The microbial reaction area is in direct contact with the water at the bottom of the hull, ensuring that the microorganisms can directly act on the water to be treated. In addition, the module also dynamically adjusts the release rate of microorganisms based on real-time monitored water flow rate data. For example, when the water flow is faster (over 0.5m / s), the release rate of microorganisms will be increased from the standard 100mL / min to 150mL / min to maintain an appropriate microbial concentration in the reaction area. At the same time, the system will adjust the temperature of the microbial culture chamber according to the water temperature data. The optimal growth temperature of most water treatment microorganisms is between 20-35°C. Therefore, when the water temperature is detected to be below 20°C, the system will start the heating device of the culture chamber to maintain the temperature within the ideal range to ensure that the microorganisms maintain optimal activity. This refined control not only improves the efficiency of the microbial degradation system, but also enhances its ability to adapt to different water quality conditions.

[0076] In a further embodiment, the filtration system may be composed of a multi-stage filtration device, including a primary filter, a secondary filter, and a precision filter. The primary filter uses a coarse grid and a fine grid to intercept larger floating objects and suspended matter. The secondary filter uses an activated carbon filter layer, which can effectively remove organic matter, odor, and some heavy metals in the water. The precision filter uses ultrafiltration membrane technology to filter out tiny particles and most bacteria. These three-stage filtration systems are connected in sequence to ensure that the water body is fully purified. In addition, the system is also equipped with a backwash device that can automatically clean the filter medium regularly to extend its service life.

[0077] In a further embodiment, the UV sterilization system primarily consists of UV lamps, quartz sleeves, a reactor, and a control unit. Multiple UV lamps are installed within a stainless steel reactor, each protected by a transparent quartz sleeve to ensure effective UV transmission. The reactor is designed with a spiral flow channel structure to increase the contact time between the water and UV rays. The control unit is responsible for adjusting the UV intensity and exposure time, and monitoring the lamp life. The system is also equipped with an automatic cleaning mechanism to regularly clean the quartz sleeve surface to maintain sterilization efficiency. Furthermore, a UV intensity sensor is provided to monitor the sterilization effect in real time to ensure that the desired disinfection standard is achieved.

[0078] In a further embodiment, the microbial degradation system can be composed of a bioreactor, a microbial culture chamber and a nutrient supply system. The bioreactor uses suspended bed technology and is filled with special biological carriers to provide a good growth environment for microorganisms. The microbial culture chamber is used to cultivate and reproduce high-efficiency degradation bacteria and regularly replenish active microorganisms to the bioreactor. The culture chamber is equipped with temperature control, pH adjustment and nutrient supply devices to ensure optimal growth conditions for microorganisms. The nutrient supply system is responsible for adding necessary nutrients, such as nitrogen and phosphorus, to the reactor and culture chamber to maintain the activity of microorganisms. The system is also equipped with a dissolved oxygen monitoring and regulation device to ensure that the reactor maintains an appropriate oxygen level. In addition, a pH and temperature control system is provided to create optimal living and working conditions for microorganisms. The entire system is automatically managed by an intelligent control unit to achieve continuous and efficient degradation of pollutants. The microbial reaction zone is the functional area inside the bioreactor for microbial degradation reactions. The microbial reaction zone is located inside the bioreactor and is the core functional area of ​​the bioreactor.

[0079] In a further embodiment, the unmanned cleaning vessel for salvaging garbage may further include: solar panels installed on the hull for providing power to the power system, intelligent control system, and multimodal sensing system; and a power system installed inside the hull for driving the hull.

[0080] The propulsion system is a hybrid power system, including: a battery pack installed in the hull for storing electrical energy; a solar charge controller connected to the solar panels and battery pack to manage the collection and storage of solar power; an electric propeller installed at the stern of the hull and connected to the battery pack to propel the hull; and an emergency diesel generator installed in the hull and connected to the battery pack to provide backup power in the event of a low battery. The battery pack is connected to the solar panels via the solar charge controller, prioritizing solar power to drive the electric propeller, and activating the emergency diesel generator to provide power in the event of a low battery.

[0081] The structure of the garbage collection device includes the following main parts:

[0082] The inclined deflector is located at the front of the hull and consists of two triangular plates arranged in a V shape, with the open end of the V facing the bow. Each triangular plate is angled at 30°-60° with the horizontal plane, and is used to guide floating garbage towards the conveyor belt.

[0083] The conveyor belt is located behind the inclined guide plate and connected to the lower end of the inclined guide plate. It is used to transport floating garbage to the garbage storage compartment. The adjustable inlet width mechanism is located at the connection between the inclined guide plate and the conveyor belt. It is used to adjust the width of the garbage entrance to the conveyor belt to accommodate garbage of different sizes and quantities.

[0084] An adjustable-power water pump, installed below or to the side of the conveyor belt, generates a water flow to help guide floating debris onto the conveyor belt. A filter with adjustable mesh size, installed above or integrated into the conveyor belt surface, filters waste of varying sizes, particularly fine particles. A drive mechanism with adjustable operating frequency, such as a reciprocating mechanism, a rotary collector, or a conveyor belt drive motor, is connected to the conveyor belt to control its speed and frequency, adjusting the frequency of waste collection. A waste storage compartment, located at the end of the conveyor belt, stores collected waste.

[0085] The lower end of the inclined guide plate is connected to the front end of the conveyor belt; the inlet mechanism is set at the connection between the inclined guide plate and the conveyor belt; the water pump is connected to the inlet mechanism or the front end of the conveyor belt through a pipeline; the filter screen is installed on the conveyor belt or integrated with the conveyor belt; the drive mechanism is mechanically connected to the conveyor belt to control its movement; the end of the conveyor belt is connected to the entrance of the garbage storage compartment.

[0086] The components are positioned from front to back as follows: inclined guide plate → inlet mechanism → conveyor belt (with filter screen above and pump below or to the side) → garbage storage compartment. The drive mechanism is located on the side or bottom of the conveyor belt.

[0087] The overall operating process is as follows: Surface waste is first guided by inclined guide plates to the inlet mechanism, which adjusts the entry width. A pump generates water flow to assist in the entry of waste into the system. The waste is then transported by a conveyor belt and filtered through a filter screen. A drive mechanism controls the frequency and speed of the conveyor belt, ultimately transporting the waste to the waste storage compartment. Throughout this process, the operating parameters of each component are adaptively adjusted based on environmental conditions and waste characteristics to ensure optimal waste collection.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0089] Example 2

[0090] like Figure 5 As shown, this embodiment provides a control method for an unmanned cleaning boat for salvaging garbage. The method is executed by an intelligent control system disposed in the hull, and includes the following steps:

[0091] S10: receiving comprehensive environmental information from the multimodal sensing system, the comprehensive environmental information including surface garbage location data, surface obstacle data, underwater obstacle data, real-time ship location data, surface garbage type identification results, surface garbage distribution density, water quality parameter data, water flow rate data, and water temperature data;

[0092] S20: Obtain historical cleaning efficiency data, current energy reserve status, and capacity status of the garbage storage compartment;

[0093] S30: dynamically planning the navigation path of the ship based on the surface garbage location data, surface obstacle data, underwater obstacle data, and real-time ship location data, combined with the historical cleaning efficiency data and current energy reserve status;

[0094] S40: Adaptively adjusting the working state of the garbage collection device provided at the front end of the hull according to the surface garbage type identification result and the surface garbage distribution density, combined with the current capacity state of the garbage storage compartment;

[0095] S50: Controlling the working state of the water purification device provided at the bottom of the hull according to the water quality parameter data, the water flow rate data and the water temperature data.

[0096] In a further embodiment, the multimodal perception system includes multiple functional modules: a positioning module for acquiring real-time ship position data; a 360-degree panoramic camera for capturing images of the surrounding environment; a millimeter-wave radar for detecting the position, distance, and relative speed of surface obstacles; an underwater sonar with multi-beam scanning capability for acquiring the position and shape of underwater obstacles, providing a three-dimensional underwater topographic map; a water quality sensor group for acquiring water quality parameters such as pH, dissolved oxygen, turbidity, conductivity, ammonia nitrogen, and total phosphorus; a flow rate sensor and a water temperature sensor for acquiring water flow rate and temperature data, respectively; a garbage storage compartment capacity sensor (including a weight or liquid level sensor) for real-time monitoring of the garbage storage compartment capacity; and an energy management sensor for monitoring the remaining charge, charge / discharge status, and temperature of the onboard battery pack. These modules work together to provide comprehensive environmental perception data for the intelligent control system.

[0097] like Figure 6 As shown, in a further embodiment, step S30 specifically includes the following steps:

[0098] S31: Processing the image data collected by the 360-degree panoramic camera based on an image recognition algorithm to identify the type of water surface garbage, identify water surface obstacles, and estimate the distribution density of water surface garbage;

[0099] S32: Calculate historical cleaning efficiency data by recording the time, cleaning area, and amount of garbage collected for each cleaning task;

[0100] S33: Dynamically planning the navigation path of the vessel based on the surface garbage location data, surface obstacle data, underwater obstacle data, real-time vessel location data, and water quality parameter data in the comprehensive environmental information, combined with historical cleaning efficiency data and current energy reserve status;

[0101] S34: On the basis of the dynamically planned navigation path, according to the surface obstacle data and underwater obstacle data in the comprehensive environmental information, the collision risk during navigation is evaluated in real time, and when a potential collision risk is detected, a local obstacle avoidance path is dynamically calculated. The local obstacle avoidance path is close to the originally planned navigation path while ensuring safety, and automatically returns to the originally planned navigation path after obstacle avoidance is completed, thereby realizing continuous obstacle avoidance control of the ship.

[0102] like Figure 7 As shown, in a further embodiment, the dynamic planning of the navigation path of the ship in step S33 includes the following specific steps:

[0103] S331: Generate a garbage distribution map by performing cluster analysis on the location data of garbage on the water surface, which includes information on garbage-intensive areas;

[0104] S332: Generate an obstacle distribution map by performing spatial analysis on the position data of surface obstacles and the position data of underwater obstacles;

[0105] S333: generating a water quality status report including a water pollution degree based on the water quality parameter data; the water pollution degree is determined based on a comprehensive comparative assessment of the multiple water quality parameter data and a preset water quality standard;

[0106] S334: Determine an optimal cleaning path based on the garbage distribution map, the obstacle distribution map, and the location and range of the garbage-dense area;

[0107] S335: Determine the priority of the cleaning task based on the following factors: information on garbage-dense areas in the garbage distribution map; the degree of water pollution in the water quality report; the current energy reserve status, including the remaining battery charge and the estimated working time available for cleaning tasks; and the historical cleaning efficiency data;

[0108] S336: Determine an energy usage strategy based on the remaining battery power, task requirements, and weather forecast data; and adjust the priority of the cleaning task based on the energy usage strategy to ensure maximum energy efficiency.

[0109] In a further embodiment, the water purification device includes at least one purification unit, and the purification unit is selected from one or more of a filtration system, an ultraviolet sterilization system, and a microbial degradation system; the water body is purified by passing through the at least one purification unit.

[0110] In a further embodiment, the working state of the control filtration system in step S50 specifically includes: when the turbidity exceeds a preset threshold, increasing the operating frequency of the filtration system; and dynamically adjusting the working parameters of the filtration system according to the water flow rate data, which includes at least one of the following: increasing the filtration pressure and accelerating the filtration flow rate.

[0111] In a further embodiment, controlling the working state of the ultraviolet sterilization system in step S50 specifically includes:

[0112] Obtain real-time water quality parameter data including pH, dissolved oxygen, turbidity, conductivity, ammonia nitrogen, and total phosphorus;

[0113] Obtain the influence weight of each real-time water quality parameter data on microbial growth;

[0114] Obtain the current water temperature data and determine the ultraviolet sterilization efficiency coefficient at the current water temperature based on the preset water temperature-ultraviolet sterilization efficiency correspondence;

[0115] Obtaining a comprehensive evaluation result of the water quality parameters based on a multi-parameter weighted algorithm according to the real-time water quality parameter data, the impact weights, and the ultraviolet sterilization efficiency coefficient;

[0116] According to the comprehensive evaluation result, the working state of the ultraviolet disinfection system is dynamically adjusted by one of the following methods or a combination thereof: adjusting the power output of the ultraviolet lamp; adjusting the duration of ultraviolet irradiation; adjusting the frequency of ultraviolet irradiation.

[0117] In a further embodiment, controlling the working state of the microbial degradation system in step S50 specifically includes:

[0118] When the pH value is higher than a preset upper limit, releasing the acid-resistant microbial community stored in the microbial culture chamber of the microbial degradation system in the hull to the microbial reaction zone of the microbial degradation system, wherein the microbial reaction zone is in direct contact with the water at the bottom of the hull;

[0119] When the pH value is lower than a preset lower limit, releasing the alkali-resistant microbial community stored in the microbial culture chamber of the microbial degradation system in the hull to the microbial reaction area of ​​the microbial degradation system;

[0120] According to the water flow rate data, the concentration of the microbial community in the microbial reaction zone is dynamically adjusted by adjusting the release rate of the microbial community from the microbial culture chamber to the microbial reaction zone of the microbial degradation system;

[0121] According to the water temperature data, the temperature of the microbial culture chamber is adjusted to maintain optimal microbial activity.

[0122] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the program implements any one of the above methods when executed by a processor.

[0123] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. Of course, there are other ways of readable storage media, such as quantum memory, graphene memory, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practices, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0124] The present invention also provides an electronic device. The electronic device in an embodiment of the present invention includes: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the control method of the unmanned cleaning vessel for salvaging garbage provided by the present invention.

[0125] Reference below Figure 8 , which shows a schematic structural diagram of a computer system 800 of an electronic device suitable for implementing an embodiment of the present invention. Figure 8 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0126] like Figure 8 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage unit 808 into a random access memory (RAM) 803. Various programs and data required for the operation of the computer system 800 are also stored in the RAM 803. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0127] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, and the like; an output section 807 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 808 including a hard disk; and a communication section 809 including a network interface card such as a LAN card or a modem. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 810 as needed, so that computer programs read therefrom can be installed in the storage section 808 as needed.

[0128] In particular, according to embodiments disclosed herein, the processes described in the main step diagrams above can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the methods shown in the main step diagrams. In the above embodiments, the computer program can be downloaded and installed from a network via the communication section 809 and / or installed from removable media 811. When the computer program is executed by the central processing unit 801, the above-described functions defined in the system of the present invention are performed.

[0129] It should be noted that the computer-readable medium described in the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical cable, RF, or any suitable combination thereof.

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0131] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. An unmanned cleaning boat for salvaging garbage, comprising a hull and a garbage collection device disposed at the front end of the hull, for collecting garbage on the water surface and transporting it to a garbage storage compartment inside the hull; characterized in that: Also includes: A multimodal sensing system provided on the hull, for sensing the surrounding environment and transmitting comprehensive environmental information to an intelligent control system provided inside the hull; A water purification device provided at the bottom of the hull, for purifying the water during navigation; The intelligent control system is used to: Dynamically planning the navigation path of the vessel based on the surface garbage location data, surface obstacle data, underwater obstacle data, and real-time vessel location data in the comprehensive environmental information, combined with historical cleaning efficiency data and current energy reserve status; Adaptively adjusting the working state of the garbage collection device based on the surface garbage type identification result and surface garbage distribution density in the comprehensive environmental information and the current capacity of the garbage storage compartment; The working state of the water purification device is controlled according to the water quality parameter data, water flow rate data and water temperature data in the comprehensive environmental information.

2. The unmanned cleaning ship according to claim 1, characterized in that: The multimodal perception system includes: Positioning module, used to obtain real-time hull position data; 360-degree panoramic camera, used to collect image data of the surrounding environment including water surface garbage, Millimeter-wave radar, used to detect surface obstacle data; Underwater sonar detector, used to obtain the location and shape data of underwater obstacles; Water quality detection sensor group, used to obtain multiple water quality parameter data of water bodies; Flow rate sensor, used to obtain water flow rate data; Water temperature sensor, used to obtain water temperature data; Garbage storage compartment capacity sensor, used to monitor the capacity status of the garbage storage compartment in real time; An energy management sensor is used to monitor the remaining power, charge and discharge status, and temperature of the battery pack on the hull.

3. The unmanned cleaning ship according to claim 2, characterized in that: The intelligent control system comprises: An image recognition module is used to process the image data collected by the 360-degree panoramic camera based on an image recognition algorithm to identify the type of water surface garbage, identify water surface obstacles, and estimate the distribution density of water surface garbage; The data recording and analysis module is used to calculate historical cleaning efficiency data by recording the time, cleaning area and amount of garbage collected for each cleaning task; A path planning module is used to dynamically plan the navigation path of the hull based on the surface garbage location data, surface obstacle data, underwater obstacle data, real-time hull location data and water quality parameter data in the comprehensive environmental information, combined with historical cleaning efficiency data and current energy reserve status.

4. The unmanned cleaning ship according to claim 3, characterized in that: The intelligent control system further comprises: a garbage collection adjustment module, configured to adaptively adjust the working states of corresponding components of the garbage collection device based on the surface garbage type identification result and the surface garbage distribution density in the comprehensive environmental information and the current capacity state of the garbage storage compartment; The water purification control module is used to control the working state of the water purification device according to the water quality parameter data, water flow rate data and water temperature data in the comprehensive environmental information.

5. The unmanned cleaning ship according to claim 3, characterized in that: The path planning module includes: A data analysis unit is configured to generate a garbage distribution map containing information on garbage-dense areas by clustering the location data of surface garbage, generate an obstacle distribution map by spatially analyzing the location data of surface obstacles and underwater obstacles, and generate a water quality status report including the degree of water pollution based on the water quality parameter data; a path optimization unit, configured to determine an optimal cleaning path based on the garbage distribution map and the obstacle distribution map, as well as the location and range of garbage-dense areas; a task priority determination unit, configured to determine the priority of the cleaning task based on the following factors: information on garbage-dense areas in the garbage distribution map; the degree of water pollution in the water quality report; the current energy reserve status, including the remaining battery charge and the estimated working time available for the cleaning task; and the historical cleaning efficiency data; The energy management unit is used to determine an energy usage strategy based on the remaining power of the battery pack, task requirements and weather forecast data; and work in conjunction with the task priority determination unit to adjust the priority of the cleaning task based on the energy usage strategy.

6. The unmanned cleaning ship according to claim 4, characterized in that: The corresponding components include at least one of the following: an inlet mechanism with adjustable inlet width, a water pump with adjustable power, a filter screen with adjustable mesh size, and a driving mechanism with adjustable working frequency.

7. The unmanned cleaning ship according to claim 6, characterized in that: The water purification control module specifically includes: The first purification control submodule is configured to increase the operating frequency of the filtration system when the turbidity exceeds a preset threshold; and dynamically adjust the operating parameters of the filtration system according to the water flow rate data.

8. The unmanned cleaning ship according to claim 7, characterized in that: The water purification control module also includes: The second purification control submodule is used to: Obtain real-time water quality parameter data including pH, dissolved oxygen, turbidity, conductivity, ammonia nitrogen, and total phosphorus; Obtain the influence weight of each real-time water quality parameter data on microbial growth; Obtain the current water temperature data and determine the ultraviolet sterilization efficiency coefficient at the current water temperature based on the preset water temperature-ultraviolet sterilization efficiency correspondence; Obtaining a comprehensive evaluation result of the water quality parameters based on a multi-parameter weighted algorithm according to the real-time water quality parameter data, the impact weights, and the ultraviolet sterilization efficiency coefficient; According to the comprehensive evaluation result, the working state of the ultraviolet disinfection system is dynamically adjusted.

9. The unmanned cleaning ship according to claim 8, characterized in that: The water purification control module also includes: The third purification control submodule is used to control the microbial community of the microbial degradation system according to water environment parameters, which include pH value, water flow rate data and water temperature data. The control includes releasing corresponding acid-resistant or alkali-resistant microbial communities according to pH value, adjusting the release rate of microbial communities according to water flow rate data, and adjusting the temperature of the microbial culture chamber according to water temperature data to maintain microbial activity.

10. A control method for an unmanned cleaning boat for salvaging garbage, characterized in that: The method is performed by an intelligent control system disposed in the hull, and comprises the following steps: receiving comprehensive environmental information from a multimodal sensing system, the comprehensive environmental information including surface garbage location data, surface obstacle data, underwater obstacle data, real-time ship location data, surface garbage type identification results, surface garbage distribution density, water quality parameter data, water flow rate data, and water temperature data; Obtain historical cleaning efficiency data, current energy reserve status and capacity status of waste storage compartments; Dynamically planning the navigation path of the ship based on the surface garbage location data, surface obstacle data, underwater obstacle data, and real-time ship location data, combined with the historical cleaning efficiency data and current energy reserve status; Adaptively adjusting the working state of the garbage collection device provided at the front end of the hull according to the surface garbage type identification result and the surface garbage distribution density, combined with the current capacity state of the garbage storage compartment; The working state of the water purification device arranged at the bottom of the hull is controlled according to the water quality parameter data, water flow rate data and water temperature data.

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