Marine robot line-reeling control method, system, device and storage medium

Abstract

The application relates to a water robot take-up and pay-off line control method, which comprises the following steps: in the process of taking up and paying off the line of the water robot, position information of a tensioning wheel is acquired in real time through a position sensor arranged on a sliding rail of the tensioning wheel of the water robot; a current tensioning state of a cable is determined based on the position information of the tensioning wheel; a tensioning state signal corresponding to the current tensioning state is generated; the tensioning state signal is input into a predictive control model, and an adjustment control sequence of a motor speed difference is determined based on the output of the predictive control model; and a control instruction is generated based on the adjustment control sequence; the control instruction is used for driving the guide wheel motor and the line wheel motor to rotate respectively.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device control, and in particular to a water robot line winding and unwinding control method, system, device and storage medium. BACKGROUND

[0002] In underwater detection scenes such as fishing, underwater environment observation, underwater object salvage and the like, image transmission of a water robot underwater detector can be used. Exemplarily, in the fishing scene, the user can observe the underwater bait nest during the fishing waiting time. Meanwhile, by introducing a control system, the user can conveniently reach the fishing point for observation, increase the line winding and unwinding control, enable the user to explore deeper underwater environment, and make fishing more interesting, thereby providing a new entertainment way for fishing enthusiasts.

[0003] However, when the water robot underwater detector is lowered into the water, if the line winding wheel fails to stop winding in time after the water robot underwater detector touches the bottom, the cable loses the pulling force of the water robot underwater detector and becomes slack. In this case, if the winding motor continues to wind, the cable in the abdomen of the machine will accumulate in the abdomen of the machine, causing the cable to block and jam, which is called line explosion. Line explosion can cause cable winding and cause problems in lowering and retrieving the water robot underwater detector.

[0004] Therefore, it is necessary to provide a water robot line winding and unwinding control method, system, device and storage medium, which controls the rotation speed of the driving motor of the guide wheel and the winding wheel in the water robot, to prevent line explosion during the lowering and retrieving process of the water robot. SUMMARY

[0005] The present application provides a water robot line winding and unwinding control method, system and storage medium, which controls the rotation speed of the driving motor of the guide wheel and the winding wheel in the water robot, to prevent line explosion during the lowering and retrieving process of the water robot.

[0006] In a first aspect, the present application provides a water robot line winding and unwinding control method, which comprises:

[0007] During the process of winding and unwinding the line of the water robot, the position sensor arranged on the tensioner slide rail of the water robot is used to acquire the position information of the tensioner in real time;

[0008] Based on the position information of the tensioner, the current tensioning state of the cable is determined;

[0009] A tensioning state signal corresponding to the current tensioning state is generated;

[0010] input the tension state signal into a predictive control model, and determine an adjustment control sequence of the motor speed difference based on an output of the predictive control model;

[0011] generate a control instruction based on the adjustment control sequence; the control instruction is used to respectively drive the guide wheel motor and the winding wheel motor to rotate.

[0012] In some embodiments, the method further comprises:

[0013] predict a predicted change trajectory of the cable in a future preset period by the predictive control model, taking the tension state signal as an initial state;

[0014] construct a target function based on the predicted change trajectory and an ideal change trajectory of the cable;

[0015] introduce a constraint condition related to the motor speed and the motor speed change rate in the target function, and solve the target function with the objective of minimizing the target function;

[0016] determine the adjustment control sequence of the motor speed difference based on parameter information of the solving process.

[0017] In some embodiments, the method further comprises:

[0018] monitor a motion state of the underwater detector of the water surface robot in real time by a gyroscope during the unwinding process;

[0019] determine whether the underwater detector of the water surface robot contacts the water bottom according to the motion state of the underwater detector;

[0020] generate a bottom contact signal in response to the underwater detector of the water surface robot contacting the water bottom;

[0021] stop the winding wheel motor from rotating and terminate the unwinding operation based on the bottom contact signal.

[0022] In some embodiments, when the underwater detector of the water surface robot contacts the water bottom, the method further comprises:

[0023] obtain a propeller control signal of the water surface robot;

[0024] predict a motion trajectory of the underwater detector on the water bottom by a trajectory prediction model based on the propeller control signal;

[0025] generate a predicted tension state signal based on the motion trajectory;

[0026] inputting the predicted tension state signal into the prediction control model, and determining a water-bottom adjustment control sequence based on an output of the prediction control model;

[0027] generating a water-bottom control instruction based on the water-bottom adjustment control sequence.

[0028] In some embodiments, the method further comprises:

[0029] monitoring, by a power management module, a current power of the water robot;

[0030] determining whether the current power is lower than a first safety threshold;

[0031] generating a low-power return signal when it is determined that the current power is lower than the first safety threshold;

[0032] generating a take-up control instruction in response to the low-power return signal.

[0033] In some embodiments, the position sensor comprises a Hall sensor, and the position information of the tensioning wheel is obtained in real time by the position sensor arranged on the tensioning wheel slide rail of the water robot, comprising:

[0034] generating a pulse signal by sensing a magnetic field change of a magnet arranged on the water robot by the Hall sensor;

[0035] counting the pulse signal and determining a displacement amount of the tensioning wheel on the slide rail according to the counting result;

[0036] determining the position information of the tensioning wheel based on the displacement amount.

[0037] In some embodiments, the current tension state of the cable is determined based on the position information of the tensioning wheel, comprising:

[0038] determining a position change rate of the tensioning wheel within a preset time period based on the position information of the tensioning wheel;

[0039] comparing the position change rate with a preset rate change threshold;

[0040] determining the current tension state of the cable based on the comparison result.

[0041] In a second aspect, the present application provides a water robot take-up and pay-out control system, comprising:

[0042] an acquisition module configured to acquire, in a process of taking up and paying out a cable of a water robot, position information of a tensioning wheel of the water robot by a position sensor arranged on a tensioning wheel slide rail of the water robot;

[0043] A determining module is configured to determine a current tensioning state of the cable based on the position information of the tensioning wheel;

[0044] A first generating module is configured to generate a tensioning state signal corresponding to the current tensioning state;

[0045] A predicting module is configured to input the tensioning state signal into a prediction control model, and determine an adjustment control sequence of the motor speed difference based on an output of the prediction control model;

[0046] A second generating module is configured to generate a control instruction based on the adjustment control sequence; the control instruction is used to drive the guide wheel motor and the winding wheel motor to rotate respectively.

[0047] In a third aspect, an electronic device is provided, which includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;

[0048] The memory is configured to store a computer program;

[0049] The processor is configured to execute the program stored in the memory, and implement the steps of the underwater robot cable winding and unwinding control method according to any one of the embodiments of the first aspect.

[0050] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program; the computer program is executed by a processor to implement the steps of the underwater robot cable winding and unwinding control method according to any one of the embodiments of the first aspect.

[0051] Compared with the prior art, the above technical solution provided by the embodiment of the present application has the following advantages: (1) in the process of winding and unwinding the cable of the water robot, the position sensor arranged on the tensioning wheel sliding rail of the water robot is used to obtain the position information of the tensioning wheel in real time; based on the position information of the tensioning wheel, the current tensioning state of the cable is determined; the tensioning state signal corresponding to the current tensioning state is generated; the tensioning state signal is input into the predictive control model, and the adjustment control sequence of the motor speed difference is determined based on the output of the predictive control model, so that the optimized motor speed difference adjustment sequence is calculated and output in advance, so that the guide wheel speed is always slightly higher than the winding wheel speed, and the cable is always kept in a tensioning state during the unwinding process, thereby fundamentally avoiding the cable explosion caused by the cable relaxation and accumulation; (2) the gyroscope is used to monitor whether the underwater detector of the water robot contacts the water bottom in real time, and the unwinding is stopped immediately after the water bottom is contacted. Furthermore, the trajectory of the equipment moving on the water bottom and the change of the tensioning degree caused by the trajectory can be predicted, and the motor control is adjusted in advance to prevent the cable from being suddenly loosened and tightened due to the movement of the equipment, thereby causing the cable explosion; (3) the low-power automatic return control improves the reliability from the system level. When the power is insufficient, the winding is automatically performed, thereby avoiding the risk of cable disorder caused by the equipment staying in the water and subsequent salvage operation due to sudden power failure. BRIEF DESCRIPTION OF DRAWINGS

[0052] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the application.

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, other drawings can also be obtained by those skilled in the art without creative labor.

[0054] Figure 1 The flowchart of the water robot winding and unwinding control method provided by the embodiment of the present application is shown in the figure;

[0055] Figure 2 The flowchart of the water robot winding and unwinding control method provided by the embodiment of the present application is shown in the figure;

[0056] Figure 3 The flowchart of the water robot winding and unwinding control method provided by the embodiment of the present application is shown in the figure;

[0057] Figure 4 The flowchart of the water robot winding and unwinding control method provided by the embodiment of the present application is shown in the figure;

[0058] Figure 5 The structure diagram of the electronic device provided by the embodiment of the present application is shown in the figure;

[0059] Figure 6 is a structural schematic diagram of a water robot provided by an embodiment of the present application. DETAILED DESCRIPTION

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in a clear and complete manner with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0061] Figure 1 A flowchart of a water robot take-up and pay-off line control method provided by an embodiment of the present application is shown in some embodiments, as shown in Figure 1 The flowchart includes the following operations:

[0062] In step 101, during the process of taking up and paying off the line of the water robot, the position information of the tensioning wheel is acquired in real time by a position sensor arranged on the tensioning wheel slide rail of the water robot.

[0063] A water robot is a device capable of moving on water, which can observe the underwater environment through an underwater detector. The water robot can include a take-up and pay-off line system, a control system, and a power supply system, etc. An exemplary water robot is shown in Figure 6 which includes a winding wheel 601, a guide wheel 602, a motor 603, a tensioning wheel 604, a sensor 605, a battery 606, a propeller 607, an underwater detector 608, a control bin 609, and a slide rail 610, and other components (such as switches, LEDs, antennas, sealing covers, towed bait structures, etc., not marked in the figure).

[0064] The winding wheel 601 is a wheel structure for winding and storing a cable connected between the underwater detector and the water surface control end. The depth of the underwater detector in water is controlled by winding or paying off the line. For example, similar to the fishing reel on a fishing rod, the depth of the fishhook is controlled by winding or paying off the line.

[0065] The guide wheel 602 is a wheel structure for guiding the movement of the cable during the winding and paying off process.

[0066] The motor 603 is a driving structure for driving the winding wheel and the guide wheel to rotate. For example, a brushless motor, a servo motor, etc.

[0067] The tensioner 604 is used to maintain the tension of the cable, preventing the cable from slackening. The tensioner is usually mounted on the slide rail and can move with the change of the tension of the cable. For example, in the take-up and pay-off system, the tensioner applies pressure on the cable through a spring or gravity mechanism to ensure that the cable is taut.

[0068] The sensor 605 is a sensor for detecting the position of the tensioner. It can include a Hall sensor or other types of sensors.

[0069] The battery 606 is an energy storage device that provides power for all electronic devices of the water robot, such as motors, controllers, sensors, underwater detectors, and LED lights. For example, like a lithium battery of a mobile phone, it is the power source of the device.

[0070] The propeller 607 is a device that provides forward thrust for the water robot, usually consisting of an underwater motor driving a propeller. It enables the water robot to move forward, backward, or turn on the water surface.

[0071] The underwater detector 608 is a sensing device for collecting information about the underwater environment. For example, a camera that can capture images or videos of the underwater environment. For example, a sonar, which is a technical device that uses sound waves for detection, positioning, navigation, and communication underwater. Sonar can emit sound wave pulses into the water and receive echoes reflected from underwater objects such as fish, seabed topography, sunken ships, submarines, etc. For example, a radar, which is a device that uses electromagnetic waves (radio waves) to detect and measure the distance of a target. Radar can emit electromagnetic waves into space and receive the echoes reflected by the target, thereby obtaining information such as the distance, direction, and height of the target from the point of electromagnetic wave emission.

[0072] The control compartment 609 is a sealed cabin that contains the core control circuit board (main controller, also known as control system) of the water robot, which is responsible for processing sensor information, executing control algorithms, driving motors, and coordinating the work of various parts.

[0073] The slide rail 610 is a guide rail or track with high precision straightness that is fixedly installed inside the device. Its core function is to provide a limited and low-friction straight movement path for the tensioner. The tensioner is mounted on the slide rail through a mechanism such as a slider or bearing, allowing the tensioner to freely slide in the specified direction (usually straight) of the slide rail, but not in other directions.

[0074] The take-up and pay-off process refers to the process of winding or releasing the cable when the water robot performs the take-up or pay-off operation to control the depth of the underwater detector. For example, the user sends instructions through the mobile app to make the water robot take up the cable to lift the underwater detector or pay off the cable to lower the underwater detector.

[0075] The slide rail is a guide rail or track structure, on which the tensioner is installed, allowing the tensioner to move along the track in response to changes in cable tension. For example, a linear slide rail made of metal or plastic, through which the tensioner slides by sliding the slider on the slide rail.

[0076] The position sensor is a sensor device that detects the specific position of the tensioner on the slide rail and converts the position information into an electrical signal. For example, a Hall sensor outputs a position signal by detecting a magnet attached to the tensioner; or a potentiometer sensor measures the position by resistance change.

[0077] Position information refers to the coordinate or displacement data of the tensioner on the slide rail, usually represented in the form of digital or analog signals. For example, the voltage value (such as 0-5V) or digital code (such as 0-1023) output by the position sensor corresponds to the specific position of the tensioner on the slide rail.

[0078] When the AUV is performing a take-up or pay-out operation, the position sensor continuously monitors the position of the tensioner on the slide rail. The sensor reads the movement of the tensioner in real time and converts the position data into an electrical or digital signal, which is transmitted to the control system (such as a microcontroller). For example, when paying out, the cable tension decreases, and the tensioner moves towards one end of the slide rail. The position sensor detects this movement and outputs corresponding position information (such as an increase in voltage), and the control system samples this information multiple times per second to ensure real-time performance.

[0079] In some embodiments, the position sensor includes a Hall sensor, which acquires real-time position information of the tensioner on the AUV by setting a position sensor on the tensioner slide rail of the AUV, including:

[0080] S10, generating a pulse signal by sensing the magnetic field change of the magnet set on the AUV through the Hall sensor.

[0081] The Hall sensor is a semiconductor device based on the Hall effect, which can convert the changing magnetic field signal into a corresponding electrical signal. When a magnetic field approaches or moves away, the output voltage level changes.

[0082] Magnetic field change refers to the change in relative distance or angle between the magnet and the Hall sensor, resulting in a change in magnetic field strength or direction at the location of the Hall sensor. For example, the magnet moves from 10mm to 5mm from the Hall sensor, and the sensor senses an increase in magnetic field strength during this process.

[0083] The pulse signal is a digital electrical signal whose voltage rapidly jumps between high level (such as 5V) and low level (such as 0V), forming a square wave form pulse. Each pulse usually represents a specific event (such as the magnet passing once). For example, a square wave signal with a frequency of 100Hz and an amplitude of 5V.

[0084] The magnet is fixedly installed on the tensioner wheel or its linkage mechanism. The Hall sensor is fixedly installed near the slide rail. When the tensioner wheel moves on the slide rail due to the change of cable tension, the magnet on it moves together, thereby changing the relative position between the magnet and the Hall sensor, resulting in the change of the magnetic field perceived by the Hall sensor. The circuit of the Hall sensor will sense this change of magnetic field and convert it into a voltage jump, thereby generating a digital pulse signal. Usually, the magnet generates a pulse every time it passes the Hall sensor (or every time the magnetic pole changes polarity).

[0085] For example, the tensioner wheel moves, driving the magnet to sweep in front of the Hall sensor. When the south pole of the magnet approaches, the output of the Hall sensor changes from high to low; when the south pole moves away and the north pole approaches, the output jumps from low to high again. In this way, a complete square wave pulse signal is generated.

[0086] S11, count the pulse signal, and determine the displacement of the tensioner wheel on the slide rail according to the counting result.

[0087] Counting refers to a mathematical operation of accumulating or subtracting the number of electronic pulse signals.

[0088] The counting result refers to the cumulative pulse number value obtained after the counting operation. For example, the value in the counter register, such as 255.

[0089] The displacement refers to the linear distance that the tensioner wheel moves on the slide rail from a certain reference point. For example, the tensioner wheel moves 15 mm to the left.

[0090] The pulse signal generated by the Hall sensor is connected to the capture / counter pin of the microcontroller (MCU). The counter peripheral inside the MCU counts the input pulse signal (usually the rising edge or the falling edge) and stores the cumulative value in the register to obtain the counting result. The system knows the conversion relationship between the counting result and the displacement (for example, 1 pulse corresponds to a 0.1 mm movement of the tensioner wheel) through calibration in advance. Therefore, the system can determine the displacement of the tensioner wheel on the slide rail according to the current counting result through simple multiplication operation.

[0091] S12, determine the position information of the tensioner wheel based on the displacement.

[0092] This step converts the displacement amount (relative movement amount) into the required position information (absolute position). For example, when the system is powered on or receives a reset signal, it controls the tensioning wheel to move to the mechanical zero point of the slide rail (the far left end), and sets the position information at this time to 0 mm. Thereafter, the displacement amount obtained by counting the Hall pulses is the absolute position relative to the zero point. For example, if the calculated displacement amount is 85 mm, it is determined that the current position information is 85 mm. This 85 mm is the final position information of the tensioning wheel to be obtained.

[0093] Step 102, based on the position information of the tensioning wheel, determine the current tensioning state of the cable.

[0094] The cable refers to the cable connecting the water robot main body and the underwater detector, used for transmitting power, control signals and image data. For example, a multi-core shielded cable, including copper conductors and insulation layers, has a certain tensile strength.

[0095] The tensioning state refers to the tightness of the cable, including tight, loose or medium tensioning states, which affects the stability and anti-burst performance of the cable. For example, when the cable is completely tight, the tensioning wheel is located at the far right end of the slide rail; when the cable is loose, the tensioning wheel is located at the far left end of the slide rail.

[0096] The control system receives the position information of the tensioning wheel and determines the current tensioning state of the cable according to predefined rules or algorithms. For example, the control system compares the position information with a threshold value: if the position value is higher than a certain threshold value (such as a digital signal value of 800), it is determined to be in a tight state; if it is lower than another threshold value (such as a digital signal value of 200), it is determined to be in a loose state; the intermediate value is in a medium tensioning state. The judgment is based on the physical relationship between the position of the tensioning wheel and the tensioning degree of the cable. The greater the movement distance of the tensioning wheel, the looser the cable. For example, if the position sensor output value is 300, the control system compares it and determines that it is in a loose state because the value is lower than the threshold value 400.

[0097] Step 103, generate a tensioning state signal corresponding to the current tensioning state.

[0098] The tensioning state signal is an electrical signal or a digital signal used to represent the current tensioning state of the cable for subsequent processing and control. For example, a digital signal such as a binary code (such as 00 for loose, 01 for medium, and 10 for tight), or an analog signal such as a specific voltage level (such as 0V for loose, 2.5V for medium, and 5V for tight).

[0099] Based on the determined tension state, the control system generates a corresponding tension state signal. This signal can be generated through a digital output pin, serial communication, or analog voltage output, etc. For example, if the tension state is tight, the control system generates a high-level signal (such as 5V); if it is loose, it generates a low-level signal (such as 0V). After the signal is generated, it is transmitted to the next control module. For example, the control system determines that the tension state is tight, and then outputs a digital signal "1" (high level) through the GPI pin, indicating the tight state.

[0100] In some embodiments, the determination of the current tension state of the cable based on the position information of the tension wheel includes:

[0101] S20, based on the position information of the tension wheel, determining the position change rate of the tension wheel in a preset time period.

[0102] The preset time period is a pre-set time interval length for calculating the change rate. The selection of this time period needs to balance the response speed and smoothness (avoid noise interference). For example, 100 milliseconds (ms) or 0.5 seconds (s).

[0103] The position change rate refers to the moving speed of the tension wheel on the slide rail, that is, the change amount of position information per unit time. It reflects the speed of the tension wheel moving and is a key indicator for judging the dynamic characteristics of the cable tensioning process. For example, 10 millimeters per second (mm / s), indicating that the tension wheel moves 10 millimeters per second.

[0104] The control system samples and records the position information of the tension wheel once every fixed period (such as every 10ms). When the rate needs to be determined, the system obtains the position information (P2) at the current time (t2) and the historical position information (P1) at the time (t1=t2-Δt) before the preset time period (Δt). Then, by calculating the difference and dividing by the time interval, the position change rate (V) is determined, that is, V=(P2-P1) / Δt.

[0105] For example, the preset time period Δt=0.1s. At time t=1.0s, the position information P1=50mm is recorded; at time t=1.1s, the position information P2=52mm is recorded. Then the position change rate V=(52-50) / 0.1=20mm / s.

[0106] S21, comparing the position change rate with a preset rate change threshold.

[0107] The preset rate change threshold is one or more pre-set critical values for judging whether the position change rate belongs to a certain state. These thresholds are obtained based on a large number of experiments or theoretical analysis, and are used to distinguish different tension dynamics.

[0108] The comparison refers to a mathematical comparison operation (such as greater than, less than, equal to) between the calculated position change rate and the preset rate change threshold.

[0109] S22, based on the comparison result, determine the current tension state of the cable.

[0110] The comparison result is the logical conclusion obtained after comparing the position change rate with the preset rate change threshold. For example, the conclusion can be "the rate is higher than the high threshold", "the rate is lower than the low threshold" or "the rate is between the two thresholds".

[0111] In some embodiments, the current tension state of the cable can be determined according to a preset mapping rule. The movement rate of the tension wheel is closely related to the tension change process of the cable. For example, too fast rate can mean that the cable is suddenly relaxed (premonition of wire explosion) or suddenly tightened; too slow rate can indicate a stable state or fine-tuning state.

[0112] Step 104, input the tension state signal into the predictive control model, and determine the adjustment control sequence of the motor speed difference based on the output of the predictive control model.

[0113] The predictive control model is a control algorithm or mathematical model that predicts future behavior based on current system state and generates optimized control instructions to maintain system stability. For example, the model predictive control (MPC) algorithm uses state space equations to predict the change in cable tension and calculates the motor speed adjustment sequence.

[0114] The motor speed difference refers to the difference between the guide wheel motor and the winding wheel motor, which is used to control the tension of the cable; usually the guide wheel speed is slightly higher than the winding wheel speed to maintain tension. For example, the guide wheel motor speed is 100 RPM and the winding wheel motor speed is 90 RPM, the speed difference is 10 RPM.

[0115] The adjustment control sequence is a series of control instructions arranged in chronological order, used to gradually adjust the motor speed difference to achieve smooth control.

[0116] The tension state signal is input into the predictive control model, which predicts the future change in tension state based on the current tension state and system dynamics (such as motor response time, cable elasticity). The model calculates the adjustment control sequence, which specifies the adjustment value and timing of the motor speed difference in the future.

[0117] In some embodiments, the input of the tension state signal into the predictive control model and the determination of the adjustment control sequence of the motor speed difference based on the output of the predictive control model include the following operations:

[0118] S30, predicting a predicted change trajectory of the cable in a preset period in the future by the predictive control model, taking the tension state signal as an initial state;

[0119] The initial state is the state of the system at the beginning of prediction, which specifically refers to the tension state of the cable, represented by the tension state signal. For example, at a certain time t0, the tension state signal is "relaxed", and this "relaxed" state is taken as the starting point of prediction.

[0120] The preset period is a pre-set time length in the future, within which prediction and control are carried out. For example, the future 2 seconds, that is, the behavior of the system in the future 2 seconds from the current time.

[0121] The predicted change trajectory is a sequence or curve of the predicted value of the system state (here referring to the tension state of the cable) changing with time within the preset period. It describes how the system state will evolve if the current control strategy continues. For example, the algorithm predicts that in the future 2 seconds, the tension state will gradually change from "relaxed" to "moderate tension" and finally reach "tight", and this predicted state sequence is the predicted change trajectory.

[0122] The predictive control model takes the initial state represented by the tension state signal input at the current time as the starting point. The internal mathematical model (such as differential equation) included in the model describes the dynamic characteristics of the cable (for example, how the motor speed affects the position of the tension pulley, and then affects the tension). The model uses this internal model to simulate and calculate the value of the cable tension state at each time point in the future preset period, thereby generating a continuous or discrete predicted change trajectory.

[0123] S31, constructing a target function based on the predicted change trajectory and the ideal change trajectory of the cable.

[0124] The ideal change trajectory is a pre-set trajectory of how the system state (cable tension state) is expected to change in the future. It represents the ultimate goal of control. For example, it is hoped that the cable tension can be smoothly and quickly transitioned from the current "relaxed" state to the "moderate tension" state. This expected "moderate tension" state changing with time is the ideal change trajectory.

[0125] The target function is a mathematical function that measures the gap (error) between the actual predicted system behavior (predicted change trajectory) and the expected behavior (ideal change trajectory), and can also include the consideration of the control action itself (such as motor speed). The goal of the control algorithm is to find the control strategy that minimizes the value of this function. For example, a common target function is the sum of the squares of the prediction errors in the future period.

[0126] The control system compares the predicted trajectory with a pre-stored or generated ideal trajectory. The objective function is constructed by defining a mathematical expression that calculates the difference (error) between the two trajectories. The larger the value of this function, the further the predicted future state is from the desired state, and the worse the control performance.

[0127] S32, introduce constraints on motor speed and motor speed change rate in the objective function, and solve for the purpose of minimizing the objective function;

[0128] The motor speed change rate refers to the speed of the motor speed change, i.e. the change amount of the speed per unit time.

[0129] The constraint is a limit on the system control variable (here referring to the motor speed and its change rate) or state variable.

[0130] Based on the constructed objective function, constraints on motor speed and motor speed change rate are added. These constraints limit the search space of the optimization problem. Then, an optimization algorithm is used to solve it, the core of which is to find a set of optimal motor control sequences.

[0131] S33, determine the adjustment control sequence of the motor speed difference based on the parameter information of the solving process.

[0132] The parameter information of the solving process refers to the direct result obtained in the optimization solving process of the objective function, i.e. the optimal future control sequence found to minimize the objective function. This sequence includes the motor speed value that should be applied in each control period (such as every 0.1 seconds) within the future preset period.

[0133] The adjustment control sequence of the motor speed difference is a series of time-ordered instructions that indicate how to adjust the speed difference (ΔRPM) between the guide wheel motor and the winding wheel motor within a future period of time.

[0134] Step 105, generate control instructions based on the adjustment control sequence; the control instructions are used to drive the guide wheel motor and the winding wheel motor to rotate, respectively.

[0135] The control instruction is a specific electronic command used to control the operation of the motor, such as starting, stopping, and speed adjustment. For example, a PWM (Pulse Width Modulation) signal controls the motor speed through duty cycle control; or a CAN bus message including the target speed value.

[0136] The guide wheel motor is a motor that drives the guide wheel, which is used to guide the cable path and maintain tension. For example, a brushless DC motor drives the guide wheel to rotate through a gear set.

[0137] The winding wheel motor is a motor that drives the line wheel (i.e., the winding wheel) to wind or release the cable. For example, a stepper motor can accurately control the rotation angle and speed of the winding wheel.

[0138] According to the adjustment control sequence, the control system generates specific control instructions, which are sent to the guide wheel motor and the winding wheel motor, respectively. These instructions drive the motors to rotate at a specific speed to achieve the required speed difference. For example, the control instructions can adjust the duty cycle of the PWM signal: for the guide wheel motor, increase the duty cycle to increase the speed; for the winding wheel motor, reduce the duty cycle to reduce the speed. After the instructions are generated, they are executed through the motor driver or controller.

[0139] Figure 2 is a flowchart of the process of suspending the pay-out operation provided by the embodiments of the present application. In some embodiments, as shown in Figure 2 the flowchart can include the following operations:

[0140] Step 201: During the pay-out process, the motion state of the underwater probe of the water robot is monitored in real time by the gyroscope.

[0141] The pay-out process refers to the operation process in which the winding wheel motor of the water robot rotates to release the cable, causing the underwater probe to move downward. For example, the user issues a pay-out instruction through the mobile phone APP, the winding wheel motor reverses, the cable is paid out, and the underwater probe gradually sinks.

[0142] Real-time monitoring refers to continuous and uninterrupted measurement and judgment at a sufficiently high frequency to respond to changes in system state in a timely manner.

[0143] The motion state of the underwater probe refers to the dynamic characteristics of the underwater probe in space, including changes in position, velocity, acceleration, etc.

[0144] Step 202: According to the motion state of the underwater probe, it is determined whether the underwater probe of the water robot contacts the water bottom.

[0145] During the judgment process, the motion state data is used to analyze whether the underwater probe encounters an abnormal situation. For example, when the underwater probe is descending, the motion state may change from uniform speed to stop, indicating that the underwater probe may have touched the bottom. For example, when it is detected that the underwater probe is not moving, it can be considered that the underwater probe has touched the bottom.

[0146] In some embodiments, a depth gauge can also be used to monitor the state of the underwater probe of the water robot being lowered, and when it is detected that the underwater probe is not moving, it can be considered that the underwater probe has touched the bottom.

[0147] Step 203: In response to the underwater probe contacting the water bottom, a bottom touch signal is generated.

[0148] In response to a representation of a cause-effect relationship, when a certain event or state (here, the underwater probe contacting the water bottom) is detected, the corresponding operation is triggered.

[0149] The bottom-touching signal is an electrical signal or an internal flag in software generated by the control system to represent that a bottom-touching event has occurred. For example, a TTL signal at high level, or a Boolean variable set to True.

[0150] Once the system determines that the underwater probe of the surface robot has contacted the water bottom, it can generate a special bottom-touching signal in response to this event. This signal can be a hardware interrupt signal or an internal message or event flag in software to notify other control modules.

[0151] Step 204, based on the bottom-touching signal, controlling the winding wheel motor to stop rotating and suspending the paying-out operation.

[0152] Suspending the paying-out operation means stopping the ongoing paying-out process.

[0153] After receiving or generating the bottom-touching signal, the control system will immediately send a command to the driving circuit (such as the H-bridge driver) of the winding wheel motor to stop rotating. This is usually achieved by setting the PWM signal duty cycle to zero or sending a specific stop command to control the motor. After the motor stops, the paying-out operation is naturally suspended, preventing the cable from relaxing and accumulating (blowing out) due to continued paying-out.

[0154] For example, the bottom-touching signal triggers an interrupt service routine that immediately sends a "brake" or "free stop" command to the motor driver, causing the winding wheel motor to quickly stop rotating and no longer pay out the cable.

[0155] Figure 3 is a flowchart of the underwater probe water bottom control provided by the embodiments of the present application. In some embodiments, as shown in Figure 3 the flowchart can include the following operations:

[0156] Step 301, obtaining the propeller control signal of the surface robot.

[0157] The propeller of the surface robot refers to a device installed on the surface robot for providing thrust to make it move forward, backward, or turn in water, usually consisting of a motor-driven propeller.

[0158] The propeller control signal refers to the command signal sent by the control system to the propeller driving circuit (such as the electronic speed controller) for controlling the thrust size and direction. For example, a PWM (Pulse Width Modulation) signal, whose duty cycle determines the speed of the propeller motor and the direction of the thrust.

[0159] After the underwater probe of the surface robot touches the water bottom, the control system performs an acquisition operation. It reads the real-time pressure data of the pressure sensor through the ADC channel. At the same time, it reads the thruster control signal (e.g., the duty cycle value of the current PWM signal) that is currently being output from the control system (the module responsible for generating the thruster control signal).

[0160] At step 302, based on the thruster control signal, the trajectory prediction model predicts the motion trajectory of the underwater probe on the water bottom.

[0161] The motion trajectory refers to the expected path of the underwater probe's position (which can include three-dimensional coordinates and attitude) over time in the future. For example, it is predicted that the underwater probe will move 0.5 meters east along the water bottom in the next 3 seconds, with a slight tilt in attitude due to the uneven bottom.

[0162] The control system inputs the acquired thruster control signal into the trajectory prediction model. The thruster control signal indicates the size and direction of the upcoming thrust. The model integrates this information and performs calculations based on Newton's laws of motion (considering thrust, gravity, buoyancy, water bottom friction, etc.) to predict the expected position of the underwater probe at each step in the future, thereby forming a motion trajectory.

[0163] At step 303, based on the motion trajectory, a predicted tension state signal is generated.

[0164] The predicted tension state signal represents the signal of the inferred future cable tension state based on the predicted motion trajectory.

[0165] The control system analyzes the motion trajectory. The motion of the surface robot will cause changes in its relative position to the water surface, thereby changing the length and angle of the cable being dragged, affecting its tension state. The system calculates the theoretical cable tension change corresponding to each point on the trajectory based on geometric relationships (e.g., cable length, surface robot displacement vector), and maps it to the tension state. Finally, the system generates a signal representing this future expected state, i.e., the predicted tension state signal.

[0166] For example, the predicted motion trajectory shows that the underwater probe will move away from the pay-off point. The system infers that the cable will be pulled tighter and tighter, and the tension state will change from "moderate" to "tight". Therefore, it generates a predicted tension state signal whose value increases over time, indicating that the tightness is increasing.

[0167] At step 304, the predicted tension state signal is input into the predictive control model, and based on the output of the predictive control model, a water bottom adjustment control sequence is determined.

[0168] The underwater adjustment control sequence refers to a series of control instructions output by the predictive control model for adjusting the motor speed difference when the underwater probe is located on the water bottom. The purpose is to cope with the change in cable tension caused by underwater movement.

[0169] The control system takes the predicted tension state signal as the input of the predictive control model. Based on this predicted future state sequence, the model performs optimization calculation (which can include processes such as objective function construction and solution), and finally outputs the optimized underwater adjustment control sequence. This sequence indicates how to adjust the motor speed difference in the future to cope with the predicted tension change.

[0170] Step 305, based on the underwater adjustment control sequence, generate underwater control instructions.

[0171] The underwater control instruction refers to the control command generated according to the underwater adjustment control sequence to specifically drive the guide wheel motor and the winding wheel motor to rotate. For example, specific PWM duty cycle adjustment instructions are sent to the motor driver through the CAN bus or PWM interface.

[0172] The control system generates specific underwater control instructions that can be executed by the motor driver according to the speed difference adjustment requirements specified by the underwater adjustment control sequence. These instructions are sent to the drivers of the guide wheel motor and the winding wheel motor to control them to rotate at a specific speed to achieve the required speed difference in the sequence.

[0173] For example, the underwater adjustment control sequence requires the speed difference to be linearly reduced from +10 RPM to +5 RPM within 1 second. The control system generates the corresponding PWM signal instructions accordingly: gradually reduce the PWM duty cycle of the guide wheel motor, while slightly increasing or maintaining the PWM duty cycle of the winding wheel motor, and outputs these underwater control instructions through the motor drive interface.

[0174] Figure 4 is a flowchart of the underwater robot take-up control provided by an embodiment of the present application. In some embodiments, as shown in Figure 4 the flowchart can include the following operations:

[0175] Step 401, monitor the current battery power of the water robot in real time through the power management module.

[0176] The power management module refers to an electronic circuit or software module in the hardware system of the water robot that is specifically responsible for managing battery power supply, monitoring battery status, and performing related control. It usually includes voltage detection, current detection, power calculation, and other functional units. For example, a power management integrated circuit (PMIC) based on an MCU, or a power management unit composed of discrete components (such as operational amplifiers, ADCs) and software algorithms.

[0177] Battery of the water robot refers to the energy storage device that provides power for the entire water robot equipment (including motors, control systems, sensors, etc.).

[0178] Current battery level refers to the remaining available capacity of the battery at a certain moment, usually expressed in percentage, voltage value or ampere-hour number.

[0179] Real-time monitoring refers to continuous and uninterrupted measurement and update of battery level information at a certain frequency. For example, the power management module measures the battery voltage every second and calculates the remaining power.

[0180] The power management module is started and continuously works. It measures the relevant parameters (such as voltage, current) of the water robot battery in real time through its internal voltage sampling circuit (such as voltage dividing resistor and ADC) or coulomb meter (for measuring charge and discharge current integration). Then, the module calculates the current battery level through the built-in algorithm (such as voltage-battery level correspondence curve lookup table method or coulomb integration method). The battery level data is stored in a specific register or variable for other modules to read.

[0181] Step 402, determine whether the current battery level is lower than the first safety threshold.

[0182] The first safety threshold is a pre-set low battery warning value related to the battery level. When the battery level is lower than this value, the system considers that safety measures (such as return) need to be triggered to avoid loss of equipment or loss of data due to complete power loss.

[0183] The control system reads the current battery level value monitored by the power management module. Then compare this value with the first safety threshold pre-stored in the memory.

[0184] Step 403, when the current battery level is determined to be lower than the first safety threshold, generate a low battery return signal.

[0185] The low battery return signal is an electrical signal or internal instruction signal in software generated by the control system, indicating the need to immediately execute the low battery automatic return program. For example, a specific high / low level signal, or a software interrupt request (IRQ), or a flag variable set to a specific value.

[0186] When the conclusion of the judgment is that the current battery level is lower than the first safety threshold (i.e. the condition is true), the control system will generate a special low battery return signal.

[0187] Step 404, in response to the low battery return signal, generate a winding control instruction.

[0188] The take-up control instruction refers to a command specifically controlling the motor of the winding wheel to perform the take-up cable operation. For example, a PWM signal sent to the motor driver, whose duty ratio and direction control bit are set to make the motor perform the take-up operation.

[0189] After detecting the low power return signal to be valid, the control system starts to generate the take-up control instruction for take-up in response to the signal. The instruction includes information such as the motor rotation direction (take-up direction) and initial rotation speed / torque, and is sent to the driver of the winding wheel motor.

[0190] Based on the same inventive concept, the embodiments of the present application also provide a water robot take-up and pay-off control system, which comprises:

[0191] The acquisition module is configured to acquire, in real time, position information of the tensioner during take-up and pay-off of the water robot, by using a position sensor arranged on a sliding rail of the tensioner of the water robot.

[0192] The determination module is configured to determine a current tensioning state of the cable based on the position information of the tensioner.

[0193] The first generation module is configured to generate a tensioning state signal corresponding to the current tensioning state.

[0194] The prediction module is configured to input the tensioning state signal into a prediction control model, and determine an adjustment control sequence of a motor speed difference based on an output of the prediction control model.

[0195] The second generation module is configured to generate a control instruction based on the adjustment control sequence, and the control instruction is used to drive the guide wheel motor and the winding wheel motor to rotate, respectively.

[0196] As shown in Figure 5 The embodiments of the present application provide an electronic device, which comprises a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 complete mutual communication through the communication bus 114,

[0197] The memory 113 is used to store a computer program.

[0198] In the embodiments of the present application, the processor 111 is used to execute the program stored in the memory 113, and the method for controlling take-up and pay-off of a water robot provided by any of the preceding method embodiments is implemented, which comprises:

[0199] In the embodiments of the present application, the processor 111 is used to execute the program stored in the memory 113, and the method for controlling take-up and pay-off of a water robot provided by any of the preceding method embodiments is implemented, which comprises:

[0200] determine a current tension state of the cable based on the position information of the tensioning wheel;

[0201] generate a tension state signal corresponding to the current tension state;

[0202] input the tension state signal into a predictive control model, and determine an adjustment control sequence of a motor speed difference based on an output of the predictive control model;

[0203] generate a control instruction based on the adjustment control sequence; the control instruction is used to drive the guide wheel motor and the winding wheel motor to rotate respectively.

[0204] The embodiment of the present application further provides a computer readable storage medium, which has a computer program stored thereon, and the computer program is executed by a processor to realize steps of the water robot take-up and pay-off control method provided by any method embodiment.

[0205] It should be noted that, in this document, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without limitation, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0206] The above description is merely one specific implementation of the application. Many modifications and variations will be apparent to those skilled in the art. Embodiments may be utilized in various ways, and the application can be used in embodiments in combination with other technologies. It is intended that the subject application cover all such modifications and variations as fall within the scope of the application. Thus, it is intended that the application cover the modifications and variations of this application provided such are within the scope of the application.

Claims

1. A method for controlling a water robot, characterized by, The method comprises: During the process of the water robot paying out the cable, the position information of the tension pulley is acquired in real time by a position sensor arranged on the tension pulley slide rail of the water robot; Based on the position information of the tension pulley, the current tension state of the cable is determined; A tension state signal corresponding to the current tension state is generated; The tension state signal is input into a predictive control model, and an adjustment control sequence of the motor speed difference is determined based on the output of the predictive control model; Based on the adjustment control sequence, a control instruction is generated; the control instruction is used to drive the guide wheel motor and the winding wheel motor to rotate respectively; The method further comprises: During the process of paying out the cable, the motion state of the underwater detector of the water robot is monitored in real time by a gyroscope; Whether the underwater detector of the water robot contacts the water bottom is determined according to the motion state of the underwater detector; In response to the underwater detector of the water robot contacting the water bottom, a bottom contact signal is generated; Based on the bottom contact signal, the winding wheel motor is controlled to stop rotating, and the cable paying out operation is terminated.

2. The method of claim 1, wherein, When the underwater detector of the water robot contacts the water bottom, the method further comprises: The propeller control signal of the water robot is acquired; Based on the propeller control signal, the motion trajectory of the water robot on the water bottom is predicted by a trajectory prediction model; Based on the motion trajectory, a predicted tension state signal is generated; The predicted tension state signal is input into the predictive control model, and a water bottom adjustment control sequence is determined based on the output of the predictive control model; 3. The method of claim 2, wherein, Based on the water bottom adjustment control sequence, a water bottom control instruction is generated. The method further comprises: The current power of the battery of the water robot is monitored in real time by a power management module; Whether the current power is lower than a first safety threshold is determined; When it is determined that the current power is lower than the first safety threshold, a low power return signal is generated; In response to the low power return signal, a cable winding control instruction is generated.

4. The method of claim 3, wherein, The position sensor comprises a Hall sensor, and the position information of the tension pulley is acquired in real time by the position sensor arranged on the tension pulley slide rail of the water robot, which comprises: The Hall sensor senses the magnetic field change of the magnet arranged on the water robot, generates a pulse signal; The pulse signal is counted, and the displacement of the tension pulley on the slide rail is determined according to the counting result; Based on the displacement, the position information of the tension pulley is determined. ​ 5. The method of claim 1, wherein, ​ ​ ​ ​ 6. The method of claim 5, wherein, The current tension state of the cable is determined based on the position information of the tensioning wheel, including: The position change rate of the tensioning wheel in a preset time period is determined based on the position information of the tensioning wheel; The position change rate is compared with a preset rate change threshold; The current tension state of the cable is determined based on the comparison result.

7. An underwater robotic winch control system, comprising: The system comprises: An acquisition module is configured to acquire, in a process of paying out or winding up a cable of an aquatic robot, position information of a tensioning wheel of the aquatic robot in real time by using a position sensor arranged on a tensioning wheel slide rail of the aquatic robot; A determination module is configured to determine a current tension state of the cable based on the position information of the tensioning wheel; A first generation module is configured to generate a tension state signal corresponding to the current tension state; A prediction module is configured to input the tension state signal into a prediction control model, and determine an adjustment control sequence of a motor speed difference based on an output of the prediction control model; A second generation module is configured to generate a control instruction based on the adjustment control sequence; the control instruction is used to drive a guide wheel motor and a winding wheel motor to rotate, respectively. The inputting of the tension state signal into the prediction control model and the determination of the adjustment control sequence of the motor speed difference based on the output of the prediction control model include: The prediction control model is used to predict a predicted change trajectory of the cable in a future preset period with the tension state signal as an initial state; A target function is constructed based on the predicted change trajectory and an ideal change trajectory of the cable; A constraint condition about a motor speed and a motor speed change rate is introduced into the target function, and the target function is solved with the minimization of the target function as a target; The adjustment control sequence of the motor speed difference is determined based on parameter information of the solving process.

8. An electronic device, comprising: The system comprises a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete mutual communication through the communication bus; The memory is used to store a computer program; The processor is used to execute the program stored on the memory, and implement the steps of the aquatic robot cable paying-in and paying-out control method in any one of claims 1-6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the aquatic robot cable paying-in and paying-out control method in any one of claims 1-6.

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