Control method, control device, storage medium and computer device

Abstract

The application discloses a control method, a control device, a storage medium and a computer device. The control method comprises the following steps: acquiring the distance between a power supplement robot and a marine target object; calculating the residual power of the power supplement robot after the power supplement robot moves to the target object according to the current power of the power supplement robot, the photovoltaic charging power and the forward power consumption; and when the residual power is greater than a first preset power, controlling the power supplement robot to move to the marine target object to supplement the power of the marine target object. In this way, the charging gain of the photovoltaic device in the voyage of the power supplement robot is taken into account in the calculation of the residual power, so that the power judgment no longer depends on the static power value before departure, but considers the energy supplement in the process of movement, so that sufficient power is ensured when the power supplement robot arrives, and the effective power supplement window is avoided to be missed due to the neglect of the photovoltaic charging power, and the task success rate and the voyage safety are considered.

Description

Technical Field

[0001] This application relates to the field of marine robots, and more specifically, to a control method, control device, storage medium, and computer equipment. Background Technology

[0002] When offshore targets (such as yachts, sailboats, and work vessels) run out of power, they typically need to return to port or coastal base stations for charging. This round trip is time-consuming and affects the continuity and convenience of maritime activities. Related technologies include recharging robots that can proactively travel to the location of the target object to provide recharging services. However, the recharging strategies of these robots still need further refinement to better accomplish their recharging tasks. Summary of the Invention

[0003] This application provides a control method, control device, storage medium, and computer equipment to solve at least one technical problem in the related art.

[0004] This application provides a control method for a power replenishment robot. The control method includes: acquiring the distance between the power replenishment robot and a target object at sea; calculating the remaining power of the power replenishment robot after it reaches the target object based on the current power level, photovoltaic charging amount, and forward travel power consumption of the power replenishment robot, where photovoltaic charging amount is the amount of power used by the power replenishment robot to charge the target object during its journey, and forward travel power consumption is the amount of power required for the power replenishment robot to reach the target object; and controlling the power replenishment robot to move to the target object at sea when the remaining power level is greater than a first preset power level, so as to replenish the power of the target object at sea.

[0005] In the above implementation, the charging gain of the photovoltaic device during the recharge robot's journey is included in the calculation of the remaining power. This makes the power judgment no longer rely solely on the static power value before departure, but comprehensively considers the energy replenishment during the journey. This ensures that the recharge robot has sufficient power upon arrival, while avoiding missing effective recharge windows due to ignoring the photovoltaic charging amount, thus balancing mission success rate and journey safety.

[0006] In some implementations, the photovoltaic charging amount is determined based on the real-time light intensity, the effective light-receiving area of ​​the photovoltaic device, and the travel time during the robot's journey to the target object. In the above implementations, the estimation of photovoltaic charging amount is linked to real-time environmental conditions (light intensity) and the robot's own parameters (photovoltaic area, travel time), making the calculation closer to actual working conditions. This further improves the accuracy of remaining power prediction and reduces the risk of prediction deviations due to weather changes.

[0007] In some embodiments, the control method further includes: when the remaining power is not greater than a first preset power, controlling the power replenishment robot to switch to standby mode, and in standby mode using the power replenishment robot's fan and photovoltaic device to generate electricity and charge the robot, wherein the fan is the power device of the power replenishment robot and can drive the power replenishment robot to move.

[0008] In the above implementation, when the current power is insufficient to reach the target object, the recharge robot does not simply abandon the task or return to the base station. Instead, it simultaneously utilizes both a wind turbine and a photovoltaic device for dual-source charging while in standby mode. The wind turbine, as a power unit, is reused as a wind power generator in standby mode, achieving integrated propulsion and power generation functions. This reduces the additional weight and cost associated with dedicated power generation equipment. Simultaneously, the photovoltaic device continuously provides solar charging. This dual-source synergy accelerates power recovery and shortens the waiting time for the recharge robot to regain its task execution capability.

[0009] In some implementations, after the power replenishment robot generates electricity and charges using its wind turbine and photovoltaic device in standby mode, the control method further includes: updating the current power level of the power replenishment robot; recalculating the remaining power level of the power replenishment robot after it moves to the target object based on the updated current power level, photovoltaic charging amount and forward power consumption; and controlling the power replenishment robot to move to the target object at sea when the recalculated remaining power level is greater than a first preset power level.

[0010] In the above implementation, after the power replenishment robot completes the standby charging process, it re-executes the complete remaining power assessment process and recalculates using the updated current power. This ensures that the decision is based on the latest energy state, avoids outdated estimates caused by changes in environmental conditions (such as fluctuations in light intensity over time), and improves the dynamic adaptability of scheduling decisions.

[0011] In some implementations, the control method further includes: determining the real-time remaining power of the power replenishing robot during the process of the power replenishing robot replenishing power to the target object at sea; and controlling the power replenishing robot to stop replenishing power when the real-time remaining power is less than a second preset power, wherein the second preset power is less than a first preset power.

[0012] In the above implementation, by setting a second preset power level as a safe lower limit during the power replenishment process, the power replenishment robot continuously monitors its own power level while providing power to others. Once the power level drops to the safe lower limit, it actively stops power replenishment, thus preserving the minimum energy reserve required for returning to base or charging nearby. This effectively prevents the risk of the power replenishment robot losing its mobility due to over-discharge.

[0013] In some implementations, after controlling the recharge robot to stop recharging, the control method further includes: determining the first return power consumption of the recharge robot returning to the coastal base station, and the second return power consumption of the recharge robot heading to the nearest sea surface charging location; controlling the recharge robot to return to the coastal base station when the real-time remaining power meets the first return power consumption; and controlling the recharge robot to head to the nearest sea surface charging location when the real-time remaining power does not meet the first return power consumption but meets the second return power consumption.

[0014] In the above implementation, after the recharging robot stops, it does not mechanically choose a single return path. Instead, it compares the power consumption of the two optional paths (returning to the base station or charging on the nearby sea surface) based on the real-time remaining power and selects the optimal path that the power can support. This avoids the risk of running out of power midway due to a forced return to the base station, and also allows the recharging robot to return to the base station to access the complete charging and scheduling network as much as possible, thus achieving a balance between return safety and operational efficiency.

[0015] In some implementations, the target object at sea includes multiple power consumption areas; controlling the power replenishment robot to move to the target object at sea to replenish the power for the target object at sea includes: obtaining the power replenishment priority of each power consumption area among the multiple power consumption areas; and allocating power replenishment power to each power consumption area in descending order of power replenishment priority.

[0016] In the above implementation, the power output of the power replenishment robot is no longer evenly distributed to all power-consuming areas of the target object, but is distributed in an orderly manner according to the priority of each area, ensuring that critical systems (such as navigation equipment, communication equipment, and safety equipment) receive priority power replenishment, thereby improving the effectiveness of power replenishment services and the safety assurance capability in emergency scenarios.

[0017] This application provides a control device for a power replenishment robot. The control device includes: an acquisition module for acquiring the distance between the power replenishment robot and a target object at sea; a calculation module for calculating the remaining power of the power replenishment robot after it reaches the target object based on the current power level of the power replenishment robot, the photovoltaic charging amount, and the forward travel power consumption, wherein the photovoltaic charging amount is the amount of electricity charged by the power replenishment robot using a photovoltaic device during its journey to the target object, and the forward travel power consumption is the amount of electricity required for the power replenishment robot to reach the target object; and a control module for controlling the power replenishment robot to move to the target object at sea to replenish the power for the target object when the remaining power level is greater than a first preset power level.

[0018] This application provides a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the steps of any of the above control methods.

[0019] This application provides a computer device, including: a memory storing a computer program; and a processor communicatively connected to the memory, wherein the processor executes the computer program to implement the steps of any of the above control methods.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein: Figure 1 This is a schematic diagram of the energy replenishment robot according to an embodiment of this application; Figure 2 This is a schematic diagram of the application state of the energy replenishment robot according to the embodiments of this application; Figure 3 This is a schematic diagram of a scenario illustrating the control method of an embodiment of this application; Figure 4 This is a flowchart illustrating the control method according to an embodiment of this application; Figure 5 This is a schematic diagram of the control device according to an embodiment of this application; Figure 6 This is a schematic diagram of the computer device according to an embodiment of this application; Figure 7 This is another schematic flowchart of the control method according to the embodiments of this application; Figure 8 This is another flowchart illustrating the control method of the embodiments of this application.

[0022] Explanation of reference numerals in the attached figures: 100 - Energy replenishment robot; 10 - Photovoltaic device; 20 - Wind turbine; 30 - Energy storage unit; 200 - Maritime target object; 210 - Electricity consumption area; 300 - Coastal base station; 400 - Control device; 410 - Acquisition module; 420 - Computing module; 430 - Control module; 600 - Computer equipment; 610 - Memory; 620 - Processor. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0024] The following disclosure provides many different embodiments or examples for implementing different structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, various specific examples of processes and materials are provided in this application, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0025] Please see Figure 1-2 This application provides a control method. This method can be applied to a power replenishment robot 100. The power replenishment robot 100 may include a photovoltaic device 10, a wind turbine 20, and an energy storage unit 30.

[0026] like Figure 3 and Figure 4 As shown, in some embodiments, the control method of the power replenishment robot 100 includes: S1, obtain the distance between the power replenishment robot 100 and the target object 200 at sea; S2, based on the current power of the power replenishment robot 100, the photovoltaic charging amount and the power consumption for moving forward, calculate the remaining power of the power replenishment robot 100 after it moves forward to the target object 200. The photovoltaic charging amount is the amount of power that the power replenishment robot 100 uses to charge the target object 200 during its journey to the target object 200, and the power consumption for moving forward is the amount of power required for the power replenishment robot 100 to move to the target object 200. S3, when the remaining power is greater than the first preset power, control the power replenishment robot 100 to move to the target object 200 at sea, so as to replenish the power of the target object 200 at sea.

[0027] like Figure 5 As shown, the above control method can be implemented by a control device 400. Specifically, the control device 400 includes an acquisition module 410, a calculation module 420, and a control module 430. The acquisition module 410 is used to acquire the distance between the power replenishment robot 100 and the target object 200 at sea. The calculation module 420 is used to calculate the remaining power of the power replenishment robot 100 after it moves to the target object 200, based on the current power level of the power replenishment robot 100, the photovoltaic charging amount, and the power consumption for moving forward. The control module 430 is used to control the power replenishment robot 100 to move to the target object 200 at sea when the remaining power level is greater than a first preset power level, so as to replenish the power of the target object 200 at sea.

[0028] like Figure 6As shown, the above control method can be implemented by a computer device 600. Specifically, the computer device 600 includes a memory 610 and a processor 620. The memory 610 stores computer program instructions. When the computer program instructions are executed by the processor 620, the processor 620 executes the control method of the present application. Specifically, the processor 620 is used to obtain the distance between the energy replenishment robot 100 and the target object 200 at sea; and to calculate the remaining power of the energy replenishment robot 100 after it moves to the target object 200 based on the current power of the energy replenishment robot 100, the photovoltaic charging amount, and the power consumption for moving forward; and to control the energy replenishment robot 100 to move to the target object 200 at sea when the remaining power is greater than a first preset power, so as to replenish the power of the target object 200 at sea.

[0029] In the above implementation, the charging gain of the photovoltaic device 10 during the journey is included in the calculation of the remaining power, so that the power determination of the recharge robot 100 no longer depends solely on the static power value before departure, but comprehensively considers the energy replenishment during the journey. When there is only a small difference between the current power of the recharge robot 100 and the power consumption during the journey, the photovoltaic charging during the journey can make up for the difference, thereby avoiding missing an effective recharge window due to ignoring the photovoltaic charging. When the photovoltaic charging is insufficient, the task will be rejected prudently to ensure the safe return capability of the recharge robot 100.

[0030] During the implementation of the above control method, the power replenishment robot 100 may be equipped with one or more photovoltaic devices 10 (e.g., solar panels). The photovoltaic devices 10 can continuously convert solar energy into electrical energy and charge the energy storage unit 30 (e.g., lithium battery pack) during the movement of the power replenishment robot 100. The photovoltaic devices 10 may include flexible photovoltaic panels, which can be laid on the surface of the power replenishment robot 100.

[0031] The current position of the refueling robot 100 and the position of the target object 200 can be obtained through the Global Positioning System (GPS), the BeiDou Navigation Satellite System, or other maritime positioning methods. Distance can be calculated as a straight line distance based on the coordinates of both objects or by considering the actual sailing distance along the maritime route. The current battery level can be understood as the available battery power stored in the refueling robot 100's energy storage unit 30, and can be expressed as a percentage (State of Charge, SOC) or a numerical energy value (such as kilowatt-hours, kWh). The first preset battery level can be determined based on the minimum battery power required for the refueling robot 100 to safely return to the coastal base station 300 or a nearby charging location after completing its refueling task, or based on empirical values.

[0032] In one example, a yacht sends a power replenishment request approximately 15 nautical miles from a coastal base station, 300 meters away. The power replenishment robot 100 has a current State of Charge (SOC) of 65%, and its estimated power consumption to reach the yacht is 40%. Based on the current real-time sunlight intensity and the estimated 25-minute journey, the photovoltaic charging capacity is estimated to be 8%. Therefore, the estimated remaining power after the power replenishment robot 100 arrives is 65% - 40% + 8% = 33%, which is greater than the first preset power level of 25%. The power replenishment robot 100 then performs the power replenishment task. However, if the photovoltaic charging capacity is ignored, and only 65% ​​- 40% = 25% is used as the threshold, the decision will be at a critical point, increasing uncertainty.

[0033] In another example, a working vessel issued a power replenishment request at midday on a cloudy day. Approximately 25 nautical miles from the coastal base station (300 meters), the power replenishment robot 100 had a current State of Charge (SOC) of 80%. The estimated power consumption for traveling to the working vessel was 5%. Due to the cloudy weather and a solar irradiance of only 150 W / m², the estimated photovoltaic charging during the 25-minute journey was approximately 1%. The estimated remaining power after the power replenishment robot 100's arrival was 80% - 5% + 1% = 76%, exceeding the first preset power level of 60%. The power replenishment robot 100 then performed the power replenishment task. Upon arrival, the actual power consumption was 6% (slightly higher than estimated due to headwinds), but because the actual photovoltaic charging also reached 1.2%, the actual remaining power upon arrival was 80% - 6% + 1.2% = 75.2%, still exceeding the first preset power level of 60%, and the mission was completed safely.

[0034] In this embodiment, the energy replenishment robot 100 can be understood as a marine mobile device with autonomous navigation capabilities and energy storage and release capabilities, which may include a hull, a propulsion system (such as a wind turbine 20 or a propeller), an energy storage unit 30, and a photovoltaic device 10. The marine target object 200 can be understood as equipment or vehicles that need to replenish energy during marine activities, such as yachts, sailboats, work vessels, and offshore platforms. Distance can be understood as the path length required for the energy replenishment robot 100 to move from its current position to the location of the target object 200. The first preset energy level can be understood as a pre-set energy threshold used to determine whether the energy replenishment robot 100 still retains the minimum energy reserve required to complete the energy replenishment task and return safely after arriving at the target object 200. The first preset energy level can be any value between 30% and 100%. Energy replenishment mainly involves the energy replenishment robot 100 charging the marine target object 200 to replenish its electrical energy.

[0035] In some implementations, the photovoltaic charging amount is determined based on the real-time light intensity, the effective light-receiving area of ​​the photovoltaic device 10, and the travel time during which the power replenishment robot 100 travels to the target object 200.

[0036] In some embodiments, the acquisition module 410 is used to acquire the real-time illumination intensity and the effective light-receiving area of ​​the photovoltaic device 10 during the process of the power replenishment robot 100 moving towards the target object 200. The calculation module 420 is used to determine the photovoltaic charging amount based on the real-time illumination intensity, the effective light-receiving area, and the travel time.

[0037] In some implementations, the processor 620 is used to determine the amount of photovoltaic charging based on the real-time light intensity, the effective light-receiving area of ​​the photovoltaic device 10, and the travel time during the process of the charging robot 100 moving to the target object 200.

[0038] In the above implementation, the estimation of photovoltaic charging capacity is linked to three parameters: real-time light intensity, the light-receiving area of ​​the photovoltaic device 10, and the travel time. This upgrades the calculation of photovoltaic charging capacity from a fixed estimate to a dynamic estimate. When the weather is sunny and there is sufficient sunlight, the estimated value of photovoltaic charging capacity increases accordingly, enabling the charging robot 100 to cover charging tasks over longer distances. When the weather is overcast and there is insufficient sunlight, the estimated value of photovoltaic charging capacity decreases accordingly, and the system automatically narrows the task range to ensure safety.

[0039] In the process of determining the photovoltaic charging amount, the real-time light intensity can be collected in real time by the light sensor mounted on the energy replenishment robot 100. The effective light-receiving area is the area of ​​the photovoltaic device 10 that actually faces the sun (for the photovoltaic device 10 with an adjustable angle, the light-receiving area may vary with the solar altitude angle). The travel time can be estimated based on the distance and the average movement speed of the energy replenishment robot 100.

[0040] For example, under strong midday sunlight conditions, with a real-time illuminance of 800 W / m², an effective light-receiving area of ​​2 m² for photovoltaic device 10, and an estimated travel time of 20 minutes, the photovoltaic charging capacity would be approximately 800 × 2 × (20 / 60) ÷ 1000 ≈ 0.53 kWh. Under weak evening sunlight conditions, with a real-time illuminance reduced to 200 W / m², the photovoltaic charging capacity under the same conditions would be approximately 0.13 kWh.

[0041] For example, the estimated journey of the energy replenishment robot 100 to the target object 200 is 30 minutes. At the start of the journey, the real-time light intensity is 600W / m². After 15 minutes, a large area of ​​clouds appears on the sea surface, causing the light intensity to drop sharply to 100W / m² and remain there until arrival. The photovoltaic charging amount can be calculated in segments: 600×2×(15 / 60)÷1000=0.30kWh for the first 15 minutes, and 100×2×(15 / 60)÷1000=0.05kWh for the next 15 minutes, totaling approximately 0.35kWh, rather than the 0.60kWh estimated based on the initial 600W / m² light intensity.

[0042] In this embodiment, real-time light intensity can be understood as the solar radiation power received per unit area at the location of the power replenishment robot 100, expressed in watts per square meter (W / m²). Effective light-receiving area can be understood as the area of ​​the photovoltaic device 10 that actually participates in photoelectric conversion; this area may be smaller than the physical area of ​​the photovoltaic device 10 when partially shaded or not directly facing the sun. Travel time can be understood as the estimated time required for the power replenishment robot 100 to move from its starting position to the location of the target object 200.

[0043] In some implementations, the control method further includes: When the remaining power is not greater than the first preset power, the power replenishment robot 100 is controlled to switch to standby mode. In standby mode, the power replenishment robot 100 uses the fan 20 and photovoltaic device 10 to generate electricity and charge. The fan 20 is the power device of the power replenishment robot 100 and can drive the power replenishment robot 100 to move.

[0044] In some embodiments, the control module 430 is used to control the energy replenishment robot 100 to switch to standby mode when the remaining power is not greater than a first preset power, and to generate electricity and charge the robot using the fan 20 and photovoltaic device 10 in standby mode.

[0045] In some implementations, the processor 620 is used to control the power replenishment robot 100 to switch to standby mode when the remaining power is not greater than a first preset power, and to generate electricity and charge the robot using the fan 20 and photovoltaic device 10 in standby mode.

[0046] In the above embodiments, when the energy replenishment robot 100 determines that the current energy is insufficient to support task execution, it does not passively wait or turn back without power, but actively enters a standby charging mode. In this embodiment, the wind turbine 20 is reused as a wind power generation device in the standby state. The wind turbine 20 drives the energy replenishment robot 100 during normal navigation, and in the standby state, it receives sea breeze to drive rotation and converts wind energy into electrical energy, forming a wind-solar complementary dual-source charging system with the photovoltaic device 10. Dual-source coordinated charging significantly improves the charging rate during standby, shortens the waiting time for the energy replenishment robot 100 to regain task execution capability, and avoids the additional weight and cost added by carrying dedicated wind power generation equipment.

[0047] During the aforementioned standby charging process, the standby state can be understood as the working state in which the energy replenishment robot 100 maintains a low-speed drift or fixed-point anchorage on the water surface and does not move towards the target object 200. The drive circuit of the wind turbine 20 in propulsion mode can be switched to power generation mode. When the wind turbine 20 is blown by the sea breeze to rotate, it generates an induced electromotive force, which is rectified and charged into the energy storage unit 30.

[0048] The photovoltaic device 10 continuously receives sunlight and generates electricity in standby mode. For example, if the power replenishment robot 100 detects that the remaining power (after considering the photovoltaic charging) is only 22% at a distance of about 10 nautical miles from the target object 200, which is lower than the first preset power of 30%, it will switch to standby mode. The wind turbine 20 and the photovoltaic device 10 will charge the energy storage unit 30 at the same time. After the power is restored to a sufficient level, it will re-enter the task process.

[0049] For example, the energy replenishment robot 100 is located at an anchorage near an island. The local wind speed is about 8 m / s. The charging power of the photovoltaic device 10 is about 0.3 kW, and the power generation of the wind turbine 20 at a wind speed of 8 m / s is about 0.5 kW. The total charging power of the two sources is about 0.8 kW. If the available capacity of the energy storage unit 30 is 10 kWh, it only takes about 1.9 hours to charge from 20% SOC to 35%, which is significantly faster than the 5 hours required by photovoltaic charging alone.

[0050] In some embodiments, after the power generation and charging are performed by the fan 20 of the power replenishment robot 100 and the photovoltaic device 10 in the standby state, the control method further includes: Update the current battery level of the power replenishment robot 100; Based on the updated current power level, photovoltaic charging amount, and forward power consumption, recalculate the remaining power of the power replenishment robot 100 after it moves forward to the target object 200. When the recalculated remaining power is greater than the first preset power, the power replenishment robot 100 is controlled to move to the target object 200 at sea.

[0051] In some embodiments, the acquisition module 410 is used to update the current battery level of the recharge robot 100. The calculation module 420 is used to recalculate the remaining battery level of the recharge robot 100 after it has traveled to the target object 200, based on the updated current battery level, photovoltaic charging amount, and forward travel power consumption. The control module 430 is used to control the recharge robot 100 to move to the target object 200 at sea when the recalculated remaining battery level is greater than a first preset battery level.

[0052] In some embodiments, the processor 620 is used to update the current power level of the recharge robot 100; and to recalculate the remaining power level of the recharge robot 100 after it moves to the target object 200 based on the updated current power level, photovoltaic charging amount and forward power consumption; and to control the recharge robot 100 to move to the target object 200 at sea when the recalculated remaining power level is greater than a first preset power level.

[0053] In the above implementation, standby charging is not an isolated energy replenishment action, but rather forms a closed loop with the task evaluation process. After standby charging is completed, the energy replenishment robot 100 re-initiates a complete remaining power assessment, recalculating the remaining power using the updated current power level, ensuring that decisions are always based on the latest energy state. This closed-loop evaluation mechanism avoids the decision-making risks caused by using outdated estimates due to changes in environmental conditions during standby (such as fluctuations in light intensity over time, or the impact of wind power changes on the power generation rate of the wind turbine 20).

[0054] During the aforementioned reassessment process, the timing for updating the current battery level can be triggered periodically (e.g., every 5 minutes), by changes in battery level (e.g., every 5% increase in SOC), or by completion of charging (e.g., reaching the predetermined target battery level). When recalculating the photovoltaic charging amount, since standby charging consumes time, the illumination conditions at the start of the journey may differ from the initial calculation. Therefore, the latest real-time illumination intensity can be used to re-estimate the photovoltaic charging amount during the journey.

[0055] For example, when the power replenishment robot 100 initially assesses its battery at 8:00 AM, it enters standby charging mode due to insufficient power. After charging is completed by 9:30 AM, a reassessment is conducted. At this time, the solar intensity has increased from 200W / m² to 600W / m², resulting in a significantly higher recalculated photovoltaic charging amount, further increasing the probability of successful task execution. As another example, during the initial assessment, the power replenishment robot 100's current SOC is 28%, its forward power consumption is 30%, and the estimated photovoltaic charging amount under cloudy conditions is only 1%. The calculated remaining power is 28% - 30% + 1% = -1%, which does not meet the first preset power requirement of 30%, thus entering standby charging mode.

[0056] During standby, the weather cleared up and the wind speed increased. After one hour of dual-source charging by wind turbine 20 and photovoltaic device 10, the SOC rose to 42%. At this point, a reassessment was performed: the updated current power level was 42%, and due to the improved weather, the photovoltaic charging was estimated to increase to 4%. The recalculated remaining power was 42% - 30% + 4% = 16%, which still did not reach the first preset power level of 30%, so standby charging continued. After another 0.5 hours of charging to 50% SOC, a third assessment was performed: the remaining power was 50% - 30% + 4% = 24%, still insufficient. After the SOC reached 56%, a fourth assessment was performed: 56% - 30% + 4% = 30%, which exactly met the first preset power level, and the charging robot 100 performed the charging task.

[0057] Please see Figure 7 In some implementations, the control method further includes: S4, during the process of the energy replenishment robot 100 replenishing energy to the target object 200 at sea, the real-time remaining power of the energy replenishment robot 100 is determined in real time. S5, when the real-time remaining power is less than the second preset power, control the power replenishment robot 100 to stop replenishing power, and the second preset power is less than the first preset power.

[0058] In some embodiments, the acquisition module 410 is used to determine the real-time remaining power of the power replenishment robot 100 during the process of the power replenishment robot 100 replenishing power to the target object 200 at sea. The control module 430 is used to control the power replenishment robot 100 to stop replenishing power when the real-time remaining power is less than a second preset power.

[0059] In some embodiments, the processor 620 is used to determine the real-time remaining power of the power replenishment robot 100 during the process of the power replenishment robot 100 replenishing power to the target object 200 at sea; and to control the power replenishment robot 100 to stop replenishing power when the real-time remaining power is less than a second preset power.

[0060] In the above embodiment, the power replenishment robot 100 continuously monitors its own power level while outputting electrical energy. By setting a second preset power level below a first preset power level as a "stop red line" for the power replenishment process, the robot actively stops the power replenishment service when its own power level drops to this red line, preserving the minimum energy reserve required for returning or charging nearby. The first preset power level is used to determine whether the robot has the ability to perform its tasks before departure, and the second preset power level is used to prevent over-discharge during the power replenishment process. The two form a dual safety protection, which not only ensures the quality of the power replenishment service but also prevents the extreme situation where the power replenishment robot 100 loses its mobility due to deep discharge.

[0061] During the aforementioned recharging process termination, the real-time remaining power can be determined by reading the battery management system (BMS) of the energy storage unit 30. The second preset power can be set according to the minimum power required for the recharging robot 100 to return from the location of the target object 200 to the coastal base station 300 or a nearby sea surface charging location, and is usually less than the first preset power used for the departure decision.

[0062] For example, in a certain power replenishment scenario, the first preset power level is 30%, and the second preset power level is 15%. When the power replenishment robot 100 departs, it has 35% power remaining (greater than 30%) and performs the power replenishment task. During the power replenishment process, it outputs power to the yacht, and its own SOC gradually decreases. When it drops to 15%, it automatically stops replenishing power. At this time, the power replenishment robot 100 still has enough power to return to the base station or the charging point on the sea surface.

[0063] For example, when the power replenishment robot 100 is performing an emergency rescue power replenishment mission, the power demand of the target object 200 (the distressed vessel) far exceeds that of a regular power replenishment mission. Starting from a SOC of 38% at the start, the power replenishment robot 100 continuously supplies power to the distressed vessel at a maximum output power of 80kW, while its own SOC decreases at a rate of about 0.3% per minute.

[0064] After approximately 77 minutes of recharging, the State of Charge (SOC) dropped to 15% (the second preset power level), triggering the BMS to stop recharging. The recharging robot 100 immediately stopped supplying power to the outside world. At this point, the recharging robot 100 had actually delivered approximately 102 kWh of electrical energy to the distressed vessel, ensuring its communication and basic power needs. Meanwhile, the recharging robot 100 maintained its return capability with a 15% SOC.

[0065] Please see Figure 8 In some embodiments, after controlling the power replenishment robot 100 to stop replenishing power, the control method further includes: S6, determine the first return power consumption of the recharge robot 100 to the coastal base station 300, and the second return power consumption of the recharge robot 100 to the nearest sea surface charging location.

[0066] S7, when the real-time remaining power meets the power consumption for the first return trip, controls the power replenishment robot 100 to return to the coastal base station 300.

[0067] S8, when the real-time remaining power does not meet the first return power consumption but meets the second return power consumption, controls the charging robot 100 to go to the nearest sea surface charging location.

[0068] In some implementations, the calculation module 420 is used to determine the first return power consumption of the charging robot 100 to the coastal base station 300, and the second return power consumption of the charging robot 100 to the nearest sea surface charging location. The control module 430 is used to control the charging robot 100 to return to the coastal base station 300 when the real-time remaining power meets the first return power consumption; and to control the charging robot 100 to go to the nearest sea surface charging location when the real-time remaining power does not meet the first return power consumption but meets the second return power consumption.

[0069] In some implementations, the processor 620 is configured to determine the first return power consumption of the recharge robot 100 to the coastal base station 300, and the second return power consumption of the recharge robot 100 to the nearest sea surface charging location; and to control the recharge robot 100 to return to the coastal base station 300 when the real-time remaining power meets the first return power consumption; and to control the recharge robot 100 to the nearest sea surface charging location when the real-time remaining power does not meet the first return power consumption but meets the second return power consumption.

[0070] In the above implementation, after stopping recharging, the power replenishment robot 100 matches the power consumption of the two return paths (returning to the base station or charging at the nearest sea surface) based on the real-time remaining power, and selects the optimal path that can be supported by the available power. When the power is insufficient to return to the coastal base station 300, the power replenishment robot 100 will not force a return and run out of power midway, but will flexibly turn to the nearest sea surface charging location, and return to the base station after the power is restored or wait for the next task at sea, thus achieving a comprehensive optimization of safety and operational continuity.

[0071] During the implementation of the above-mentioned return-to-home decision, the first and second return-to-home power consumption can be estimated based on the corresponding distance, the power consumption per unit distance of the energy replenishment robot 100 in return-to-home mode, and the photovoltaic charging amount during the return-to-home process.

[0072] For example, if the remaining battery power of the refueling robot 100 is 12% when it stops refueling, the estimated power consumption for the first return trip (returning to the base station) is 20%, and the estimated power consumption for the second return trip (charging at the nearest sea surface) is 8%, then the remaining battery power only meets the power consumption for the second return trip. The refueling robot 100 will then proceed to the nearest sea surface charging location and return to the base station after charging is completed. If the remaining battery power is 25%, meeting the 20% power consumption for the first return trip, then it will directly return to the base station to access the complete shore-based charging facilities and dispatch network.

[0073] For example, when the power replenishment robot 100 stops replenishing power, its real-time remaining power is 18%. The target object 200 is about 12 nautical miles away from the coastal base station 300. The first return power consumption, after considering the return photovoltaic gain, is estimated to be 15%. The second return power consumption (the charging position on the sea surface) is only 2% (it can be moored near the target object 200). The real-time remaining power of 18% satisfies both power consumption requirements. The power replenishment robot 100 will prioritize returning to the base station in order to obtain complete shore-based charging services.

[0074] In this embodiment, the coastal base station 300 can be understood as a fixed charging infrastructure set up on the coastline, capable of providing high-power fast charging and scheduling commands for the charging robot 100. The nearest sea surface charging location can be understood as the nearest available location on the sea surface where the charging robot 100 can charge, such as any sea surface location where it can generate electricity and charge using its own wind turbine 20 and photovoltaic device 10.

[0075] In some embodiments, the maritime target object 200 includes multiple power-consuming areas; controlling the power replenishment robot 100 to move to the maritime target object 200 and replenish its power (S3) includes: Obtain the energy replenishment priority for each of multiple power consumption areas; According to the order of priority of energy replenishment for each power consumption area from high to low, the energy replenishment power is allocated to each power consumption area in turn.

[0076] In some implementations, the acquisition module 410 is used to acquire the energy replenishment priority of each power consumption area in multiple power consumption areas. The calculation module 420 is used to allocate energy replenishment power to each power consumption area in descending order of energy replenishment priority. The control module 430 is used to control the energy replenishment robot 100 to replenish the energy of the target object 200 at sea according to the energy replenishment power allocated by the calculation module 420.

[0077] In some implementations, the processor 620 is used to obtain the power replenishment priority of each power consumption area in a plurality of power consumption areas; and to allocate power replenishment to each power consumption area in descending order of power replenishment priority.

[0078] In the above implementation, the power output of the power replenishment robot 100 is not evenly distributed to all power-consuming areas of the target object 200, but rather prioritizes and orderly meets the energy needs of critical systems. In scenarios where the power replenishment robot 100 itself has limited power or needs to replenish multiple targets in a short period of time, the priority allocation mechanism ensures that critical power-consuming areas such as navigation equipment, communication equipment, and safety systems receive priority power guarantees, while non-critical power-consuming areas such as lighting and entertainment can have their allocation delayed or reduced, thus improving the effectiveness and safety of the power replenishment service under resource-constrained conditions.

[0079] During the implementation of the aforementioned priority allocation, the energy replenishment priority of each power consumption area can be pre-set and reported by the target object 200, or it can be automatically identified by the energy replenishment robot 100 based on the equipment type of the target object 200. For example, a yacht divides its power consumption areas into a navigation area (priority 1), a communication area (priority 2), a living area (priority 3), and an entertainment area (priority 4). After the energy replenishment robot 100 arrives, it will prioritize the available energy replenishment power to meet the energy needs of the navigation area and the communication area according to the priority order. After these areas are completed or if there is still residual power, it will then replenish the energy of the living area and the entertainment area in sequence.

[0080] When the power replenishment robot 100 is low on its own power, it can complete only the power replenishment tasks of priority 1 and 2, ensuring the basic navigation and communication safety of the target object 200. For example, a maritime rescue vessel may request power replenishment during a search and rescue mission. Its power consumption areas are divided into a search and rescue communication area (priority 1), a medical equipment area (priority 1), a navigation and power area (priority 2), a lighting area (priority 3), and a crew living area (priority 4), with the search and rescue communication area and the medical equipment area having the highest priority. Upon arrival, the power replenishment robot 100 simultaneously provides full power to the search and rescue communication area and the medical equipment area, ensuring uninterrupted operation of search and rescue command transmission and casualty treatment equipment. After replenishing power in the two priority 1 areas, the remaining power is then allocated to the navigation and power area (priority 2), ensuring the rescue vessel has sufficient power to return to port.

[0081] In this embodiment, the power consumption area can be the energy consumption area corresponding to different electrical devices or electrical systems on the target object 200, and each power consumption area can have an independent charging interface or power distribution circuit. The power replenishment priority can be understood as a pre-set level information that characterizes the priority order of each power consumption area in the power replenishment process. The higher the priority, the earlier the power allocation is obtained or the more power replenishment is obtained.

[0082] In this embodiment, the processor may include at least one of a Central Processing Unit (CPU), a Microcontroller Unit (MCU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or an Application Specific Integrated Circuit (ASIC). The operation of the computing module 420 may be performed by the processor's Arithmetic Logic Unit (ALU).

[0083] In this embodiment, the acquisition module 410 can be understood as a virtual functional unit in the control device 400 responsible for acquiring the required data from external sensors or communication interfaces, with its physical support being the processor executing data acquisition program instructions. The calculation module 420 can be understood as a virtual functional unit in the control device 400 responsible for performing arithmetic and logical operations to generate intermediate results required for decision-making, with its physical support being the processor's ALU or floating-point arithmetic unit. The control module 430 can be understood as a virtual functional unit in the control device 400 responsible for generating and outputting control instructions based on the calculation results, with its physical support being the processor executing control logic program instructions.

[0084] In some embodiments, the computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the steps of any of the control methods described above. The storage medium may include at least one of read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical disk storage media, flash memory, etc.

[0085] In some embodiments, the processor 620 is configured to read computer program instructions from a computer-readable storage medium and execute the computer program instructions to implement the steps of any of the control methods described above.

[0086] In the aforementioned application example of the storage medium, the manufacturer of the power replenishment robot 100 burns the firmware program containing the control method described above into a flash memory chip (as the storage medium) and solders the flash memory chip onto the main control board of the power replenishment robot 100. After the power replenishment robot 100 is powered on, the processor 620 loads the firmware program from the flash memory into RAM for execution, thus automatically running all control logic from distance acquisition to power replenishment decision. When the algorithm version of the control method needs to be upgraded, such as adding support for the BeiDou satellite positioning system or optimizing the calculation model of photovoltaic charging, it is only necessary to push the new firmware to the power replenishment robot 100 via the wireless communication link and write it into the flash memory. After the power replenishment robot 100 restarts, it can load the new control method without having to return it to the factory to replace the hardware.

[0087] In some embodiments, the computer device 600 includes a memory 610 and a processor 620. The memory 610 stores a computer program, and the processor 620 is communicatively connected to the memory 610. When the processor 620 executes the computer program, it implements the steps of any of the control methods described above.

[0088] The computer device 600 can be integrated into the onboard computing unit of the power replenishment robot 100, or it can be deployed on a remote server of the coastal base station 300 and send control commands to the power replenishment robot 100 via a wireless communication link. In the above embodiments, the control method is carried out by the standard hardware architecture of the memory 610 and the processor 620, which enables the control logic of this application to be reliably executed on general-purpose computer hardware, facilitating mass production and maintenance.

[0089] In the deployment example of the aforementioned computer device 600, the onboard computing unit of the refueling robot 100 uses an ARM-based embedded processor (as the processor), paired with DDR4 memory (as the storage device 610), and runs a Linux operating system. The computer program for the control method is compiled into an ARM executable file in C++ and stored in the solid-state drive of the onboard computing unit. After the refueling robot 100 is powered on, the processor 620 loads the executable file from the solid-state drive into the DDR4 memory and runs it, processing GPS data, light sensor data, and BMS data in real time. The control cycle is 100 milliseconds, enabling it to complete the entire process of calculation from distance acquisition to control command generation within 100 milliseconds, meeting the real-time control requirements of the refueling robot 100 in dynamic sea conditions.

[0090] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0091] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A control method for a power replenishment robot, characterized in that, The control method includes: Obtain the distance between the refueling robot and the target object at sea; Based on the current battery level, photovoltaic charging amount, and forward travel power consumption of the replenishing robot, the remaining battery level of the replenishing robot after it reaches the target object is calculated. The photovoltaic charging amount is the amount of electricity charged by the photovoltaic device during the process of the replenishing robot moving to the target object, and the forward travel power consumption is the amount of electricity required for the replenishing robot to move to the target object. When the remaining power is greater than a first preset power, the power replenishment robot is controlled to move to the target object at sea in order to replenish the power of the target object at sea.

2. The control method according to claim 1, characterized in that, The photovoltaic charging amount is determined based on the real-time light intensity, the effective light-receiving area of ​​the photovoltaic device, and the travel time during the process of the energy replenishment robot moving to the target object.

3. The control method according to claim 1, characterized in that, The control method further includes: When the remaining power is not greater than the first preset power, the power replenishment robot is controlled to switch to standby mode, and in the standby mode, the power replenishment robot's fan and the photovoltaic device are used to generate electricity and charge the robot. The fan is the power device of the power replenishment robot and can drive the power replenishment robot to move.

4. The control method according to claim 3, characterized in that, After the standby state is achieved by generating electricity and charging using the wind turbine of the energy replenishment robot and the photovoltaic device, the control method further includes: Update the current battery level of the recharge robot; Based on the updated current power level, the photovoltaic charging amount, and the forward power consumption, the remaining power of the energy replenishment robot after it moves to the target object is recalculated. When the recalculated remaining power is greater than the first preset power, the power replenishment robot is controlled to move to the target object at sea.

5. The control method according to claim 1, characterized in that, The control method further includes: During the process of the refueling robot refueling the target object at sea, the real-time remaining power of the refueling robot is determined in real time. When the real-time remaining power is less than a second preset power, the power replenishment robot is controlled to stop replenishing power, wherein the second preset power is less than the first preset power.

6. The control method according to claim 5, characterized in that, After the control method stops the power replenishment robot, it further includes: Determine the first return power consumption of the recharge robot to the coastal base station, and the second return power consumption of the recharge robot to the nearest sea surface charging location; When the real-time remaining power meets the first return power consumption, control the recharging robot to return to the coastal base station; When the real-time remaining power does not meet the first return-to-base power consumption but meets the second return-to-base power consumption, the recharging robot is controlled to proceed to the nearest sea surface charging location.

7. The control method according to claim 1, characterized in that, The target object at sea includes multiple power consumption areas; controlling the power replenishment robot to move to the target object at sea to replenish its power includes: Obtain the energy replenishment priority of each of the multiple power consumption areas; According to the order of energy replenishment priority from high to low for each power consumption area, the energy replenishment power is allocated to each power consumption area in sequence.

8. A control device for a power replenishment robot, characterized in that, The control device includes: The acquisition module is used to acquire the distance between the power replenishment robot and the target object at sea; The calculation module is used to calculate the remaining power of the power replenishment robot after it moves to the target object based on the current power of the power replenishment robot, the photovoltaic charging amount, and the power consumption for moving forward. The photovoltaic charging amount is the amount of power that the power replenishment robot uses to charge itself using a photovoltaic device during its journey to the target object, and the power consumption for moving forward is the amount of power required for the power replenishment robot to move to the target object. The control module is used to control the refueling robot to move to the target object at sea when the remaining power is greater than a first preset power, so as to refuel the target object at sea.

9. A computer-readable storage medium, characterized in that, The medium stores computer program instructions, which, when executed by a processor, implement the steps of the control method according to any one of claims 1 to 7.

10. A computer device, characterized in that, include: Memory, which stores computer programs; A processor, communicatively connected to the memory, which, when executing the computer program, implements the steps of the control method according to any one of claims 1 to 7.

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