A large intelligent unmanned feeding ship with a trimaran structure

Abstract

The present invention discloses a large-scale intelligent unmanned feeding vessel with a trimaran structure. The vessel comprises a hull and two buoys fixed on either side of the hull by a fixed frame. The hull is equipped with a diesel generator at the front, a feeding structure at the rear, and propeller propulsion mechanisms symmetrically arranged on both sides near the rear. The fixed frame is equipped with a feed silo with a weight sensor above the feeding structure. The lower opening of the silo transmits bait to the feeding structure. An electric control compartment is provided in the middle of the hull, which contains a main control chip and a positioning module. A server receives the position information of the positioning module, calculates and generates a path plan, uses an improved ILOS algorithm to guide the vessel along the route, and calculates the optimal speed of the vessel and the feeding speed based on the data from the weight sensors. The calculation results are sent to the main control chip, which controls the operating status of each motor to achieve uniform feeding according to the path plan. The present invention can intelligently complete uniform feeding operations with daily changes in feeding amount.

Description

Technical Field

[0001] The invention belongs to the technical field of feeding ships, and in particular relates to a large intelligent unmanned feeding ship with a trimaran structure. Background Art

[0002] Currently, my country's fishery and aquaculture still relies heavily on manual labor, including manual feed spreading or shore-based fixed-point feeding devices. These methods suffer from low efficiency, heavy workloads, and inability to promptly mitigate water pollution. Using unmanned surface-feeding boats for aquaculture is an inevitable trend, replacing traditional manual labor.

[0003] Among existing intelligent feed delivery technologies in aquaculture, the first involves using drones equipped with feeding devices. For example, Chinese patent publication CN110447584A discloses a feeding device and method for aquaculture, which uses drones to automatically refill feeders. However, this method only delivers a small amount of feed, making it difficult to meet the needs of large-scale aquaculture. Furthermore, it consumes significant costs and energy.

[0004] The second method uses an unmanned feeding boat powered by paddle wheels. For example, Chinese patent publication CN211167319U discloses a novel unmanned aquaculture boat with dual paddle wheels. This boat offers flexible maneuvers and can cruise and feed within a pond, expanding the feeding range. However, this approach still struggles to meet the demands of environments requiring high feed volumes. Summary of the Invention

[0005] The present invention provides a large-scale intelligent unmanned feeding ship with a trimaran structure, which enables the unmanned ship to automatically determine the feeding speed and driving speed according to an autonomously planned trajectory, and intelligently complete the uniform feeding operation with daily changes in the feeding amount.

[0006] A large intelligent unmanned feeding ship with a trimaran structure, comprising a hull and two floats fixed on both sides of the hull by a fixed frame;

[0007] The hull is provided with a diesel generator at the front, a material spreading structure at the rear, and propeller propulsion mechanisms symmetrically provided on both sides near the rear; a GPS antenna and a radar are provided on the diesel engine;

[0008] The fixed frame is provided with a silo above the spreading structure, and a weight sensor is provided in the silo; the lower opening of the silo transmits the bait to the spreading structure through a winch mechanism;

[0009] The middle part of the hull is provided with an electric control compartment, which is equipped with a battery, a main control chip, a communication module, a positioning module and a drive module. The positioning module receives satellite signals through a GPS antenna to determine the current position and orientation of the hull. The communication module is used to realize message communication between the mobile phone app, the server and the unmanned bait throwing boat.

[0010] The server receives the position information of the positioning module through the communication module, calculates and generates the path planning, uses the improved ILOS algorithm to make the ship perform the task along the route, and calculates the optimal driving speed and optimal material spreading speed of the ship in real time based on the data of the weight sensor; at the same time, the calculation results are sent to the main control chip, and the main control chip outputs the PWM signal to the drive module, which controls the operating status of the motors on the propeller propulsion mechanism, the cage mechanism and the material spreading structure to achieve uniform material spreading according to the path planning.

[0011] Furthermore, a camera is provided at the front of the diesel engine and the rear of the silo for real-time monitoring of the situation in front and behind the unmanned feeding ship.

[0012] Furthermore, a warning light is provided on the upper part of the diesel engine for warning the position of the ship, and the light flashes when a problem occurs on the ship to warn the ship of the problem.

[0013] Furthermore, the silo is a sealed inverted cone structure, and weight sensors are arranged at the four corners of the lower part of the silo.

[0014] Furthermore, the calculation and generation of the path planning includes generating a coastal driving path and a cruising path covering the area; wherein the process of generating the coastal driving path is as follows:

[0015] Mark the points on the mobile app to get the four shore points in the form of longitude and latitude, and connect the four shore points to get the working area;

[0016] Convert the four shore points in the form of longitude and latitude into a rectangular coordinate system, take the first shore point P1 as the origin, and calculate the straight line equations of the four sides as the four shore edges;

[0017] Calculate the equations of four straight lines inside the work area, parallel to the shore and at a distance d from the shore. The intersection of two adjacent straight lines is the desired path point;

[0018] The four obtained path points are converted from rectangular coordinates to longitude and latitude, and the return point is added to the end of the converted path to obtain the coastal driving path.

[0019] The process of generating a coverage cruise path within an area is as follows:

[0020] In the determined rectangular coordinate system, let the minimum distance between the ship and the shore during the journey be d1, and let the distance between two adjacent parallel path segments be d2;

[0021] By using the method of generating a coastal driving path, four new boundary lines d1 away from the shore are obtained to form the boundary G'. The boundary points are C1, C2, C3, and C4. The boundary G' is the working area covering the cruising path;

[0022] Select the longest boundary line as the starting edge, and calculate the distance from each boundary point to the starting edge, and take the maximum value of the four distances as D max , calculate the number of path segments parallel to the starting edge in the covered cruise path n is an integer;

[0023] Calculate the equation of the straight line l of the n-segment path parallel to the starting edge in the working area i , the distance between two adjacent paths is d2;

[0024] Find l i The intersection point with each boundary line of the boundary G' and whether the intersection point is inside G' or on the boundary;

[0025] Take the 2n intersection points inside and on the boundary of G', sort them in a bow shape, add the two endpoints of the starting edge at the beginning to obtain the coverage cruise path in the rectangular coordinate system, convert it into longitude and latitude, and add the return point at the end of the path to obtain the coverage cruise path in the area.

[0026] In the improved ILOS algorithm, the formula of the ILOS guidance law is as follows:

[0027]

[0028]

[0029] Where χ represents the heading angle, and α represents the angle y between the ship's forward direction and the vertical direction. e Indicates the distance between the center of the ship and the target route, indicating the deviation of the current ship in the forward direction, y int The integral term introduced in the ILOS algorithm is the accumulation of deviations in the ship's forward direction. Δ represents the forward distance of the ship along a given path. It is the distance between the desired heading point and the projection of the controlled ship's current position on the desired track, and is generally 2 to 5 times the ship's length. The parameter k satisfies the following conditions:

[0030]

[0031] Where k1 and k2 are the intermediate parameters required to determine the parameter k, k1 is a fixed parameter, k2 is a variable parameter related to the ship deviation, and U d is the expected speed. In order to further improve the integration effect, the variable parameter k2 is taken as follows:

[0032]

[0033] Where k max and k min are the maximum and minimum values of k2 respectively; ρ is the convergence rate; when the lateral deviation y e When the lateral deviation y is larger, k2 is smaller and the integral effect is weaker; e When it is smaller, k2 is larger and the integral effect is stronger.

[0034] The specific process of real-time calculation of the optimal ship speed and optimal spreading speed is as follows:

[0035] Step 1: Convert the path from longitude and latitude to rectangular coordinates. The converted path is [[x1,y1],[x2,y2],......[x n ,y n ]];

[0036] Step 2: Calculate the distance per week required to spread the material

[0037]

[0038] Step 3: Calculate the mass per meter of material required to spread the material just after the ship has finished traveling the path.

[0039]

[0040] The default speed of the ship is the maximum speed v=v max , multiplying the two together gives the mass of material spread per second q s =q m *v;

[0041] Step 4: Calculate the minimum number of circles n and the total distance s that the ship needs to travel to complete the mission

[0042]

[0043] s=s1*n

[0044] Step 5: Recalculate the mass of material spread per meter and the mass of material spread per second q s ′=q′m*v, if q s ' max , then the ship speed is determined to be v = v max , go to step 7; if q s >q max , then go to step 6;

[0045] Step 6: Reduce the ship speed by Δv; let the ship speed after the reduction be v, and calculate the mass of material spread per second q at this time s ​, if q s max &q s >q min , then determine the ship speed v, otherwise repeat step 6 until q s max ;

[0046] Step 7, calculate the forward speed of the ship; let the forward direction of the ship be θ1, the forward direction of the ship's speed be θ2, and the ship's speed v, then the forward speed

[0047] v heading =v*cos(θ2-θ1)

[0048] Step 8: Record the amount of material discharged per second as q s , the duty cycle of the blanking motor is DR, then the relationship between the two is: DR=a*q s , where a is a constant coefficient related to the structure; in this case,

[0049] q s =v heading *q m

[0050] DR=a*v heading *q m

[0051] Obtain the duty cycle DR of the spreading motor and output DR;

[0052] Step 9: Update the coefficient a in step 8 every 10 seconds by reading and recording the data from the mass sensor. The mass difference read by the mass sensor within 10 seconds is recorded as Δm, and the theoretical mass of the material spread in the past 10 seconds is m1. dm = m1 - Δm. Let the previous coefficient be a0 and the updated coefficient be a1, then a1=a0+da;

[0053] Step 10: Update the ship speed and feed spreading speed for the remaining distance every 20 seconds; calculate the total distance S from the current position to the destination, read the remaining feed mass m' through the mass sensor, proceed to Step 5 and Step 6, and after obtaining the ship's forward speed for the remaining distance and the feed spreading mass per second, skip Step 7 to Step 10 and proceed to Step 11;

[0054] Step 11: Using the ship speed and material spreading speed calculated in step 10, repeat steps 7 to 11 until the material spreading task is completed.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] ​​1. The present invention has two working modes. One is to use the corresponding remote control to control the boat, including controlling the forward, backward, left and right driving direction of the boat, turning on the spinning plate, feeding, and automatically starting the built-in route to work. The other is to generate a path by marking points while the boat is traveling in the working waters by remote control, or to use the built-in algorithm to automatically generate a coastal driving route or a cruising route covering the area and work along the route.

[0057] 2. After determining the travel route, the present invention can utilize the improved ILOS algorithm to enable the vessel to perform the mission along the route.

[0058] 3. The present invention has the function of automatically adjusting the driving speed and feeding speed. It uses a dynamic calculation method to combine the driving route and the weight of bait to be thrown. It recalculates the subsequent ship speed required to complete the task at regular intervals, and determines the subsequent feeding speed by calculating the remaining working distance and the remaining feed amount in the silo. It automatically adjusts the duty cycle of the feed spreading motor in combination with the current real-time travel speed of the ship, and can perform real-time calculations based on the distance traveled and the amount of feed spread during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is an overall structural diagram of a large-scale intelligent unmanned feeding ship with a trimaran structure according to the present invention;

[0060] Figure 2 This is a front view of a large intelligent unmanned feeding ship with a trimaran structure according to the present invention;

[0061] Figure 3 This is a rear view of a large intelligent unmanned feeding ship with a trimaran structure according to the present invention;

[0062] Figure 4 This is a side view of a large intelligent unmanned feeding ship with a trimaran structure according to the present invention;

[0063] Figure 5 This is a top view of a large intelligent unmanned feeding ship with a trimaran structure according to the present invention;

[0064] Figure 6 Marking points to determine the schematic diagram of the working area when generating the driving route along the coast;

[0065] Figure 7 Calculate the schematic diagram of two parallel lines along the shore when generating the driving path along the shore;

[0066] Figure 8 A schematic diagram showing the required straight line from two parallel lines when generating a coastal driving path;

[0067] Figure 9 A schematic diagram of the path points obtained when generating a coastal driving path;

[0068] Figure 10 Schematic diagram for selecting path boundaries and starting edges when generating covered cruise paths in the area;

[0069] Figure 11 This is a schematic diagram of the path obtained when generating a covered cruise path in the area;

[0070] Figure 12 Schematic diagram of the LOS guidance law for a straight path. DETAILED DESCRIPTION

[0071] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It should be noted that the embodiments described below are intended to facilitate understanding of the present invention and do not have any limiting effect on the present invention.

[0072] like Figures 1 to 5 As shown, a large, intelligent, unmanned feeding vessel with a trimaran structure comprises a hull 1 and two buoys 2 secured to either side of the hull via fixed frames 12. This structure provides exceptional stability and balance, making the vessel smoother and faster during travel. Its waterline design allows for better control of the vessel's posture at high speeds and maintains stability in all water depths and wave conditions. Its rigid structure prevents it from losing stability even under severe impact.

[0073] The hull 1 is provided with a diesel generator 11 at the front, a material spreading structure 3 at the rear, and propeller propulsion mechanisms 10 symmetrically provided on both sides near the rear; a GPS antenna 6 and a radar 7 are provided on the diesel engine 11.

[0074] The fixed frame 12 is provided with a silo 4 above the spreading structure 3, and a weight sensor is provided in the silo 4; the silo 4 is a sealed inverted cone structure, with a cover on the top to prevent rainwater and other factors from contaminating the feed, and it is more convenient to discharge the feed when it is open; the lower opening is connected to the winch mechanism, which is driven to rotate by the winch shaft motor to convey the feed to the spreading structure 3; weight sensors are provided at the four corners below the silo 4 to detect the weight of the feed in the silo 4, and then determine the real-time data of the feed.

[0075] The spreading mechanism 3, located behind the boat and below the winch mechanism, consists of a motor and dual nozzles. It utilizes centrifugal force to evenly distribute the feed behind the boat. Its simple structure, flexible operation, and high spraying accuracy make it suitable for a wide range of applications, including various sizes of feed for different crops.

[0076] The diesel generator 11 is located in the front of the hull and can ensure a stable output voltage for 10 hours. It works in conjunction with the propeller propulsion structure to provide stable and efficient power to meet the ship's cruising requirements.

[0077] The propeller propulsion mechanism is symmetrically located on either side of the central hull, behind the fixed frame 12. The propeller is a crucial component of the ship's propulsion system. Its structure consists of propeller blades and a propeller shaft. When the diesel generator 11 is running, the rotational shaft is transmitted to the propeller shaft, and the propeller blades create a small vortex in the water, propelling the ship forward.

[0078] An electric control compartment 5 is provided in the middle of the hull 1, and a battery, a main control chip, a communication module, a positioning module and a drive module are installed in the electric control compartment 8; among them, the positioning module receives satellite signals through the GPS antenna 9 to determine the current position and orientation information of the hull; the communication module is used to realize the message exchange between the mobile phone app-server-unmanned bait-casting boat; the control chip is used to receive sensor information and control the hull movement and bait-casting operation.

[0079] In an embodiment of the present invention, a GPS antenna 9 is fixed at a side angle above the diesel generator 11 for receiving GPS satellite signals; a radar 7 is fixed above the diesel generator 11 and below the camera 8 for detecting obstacles ahead to avoid collision with the hull; one camera 8 is located above the radar 7 and the other is located behind the silo 4, making it easy for users to observe the situation in front and behind the hull on the app.

[0080] The warning light is located above the radar and in the middle of the GPS antenna. It is mainly used to warn the ship's position in weather conditions with low visibility, and flashes frequently when a problem occurs on the ship to warn the ship of the problem.

[0081] Before using this system for feeding, manual path planning is required. Using a remote control or mobile app, the boat is directed to the four corners of the aquaculture pond (if the pond is irregularly shaped, all corners can be determined sequentially). Then, based on the spread width and the requirement for full coverage of the pond, the boat's trajectory is automatically generated. This trajectory remains unchanged throughout the operation unless the spread width or pond surface changes.

[0082] During operation, workers manually pour feed into the inverted conical silo and start the process with a single click using a remote control or mobile app. The intelligent unmanned bait-casting boat's communication module receives the control command and determines the speed of travel and feeding based on the volume of bait in the silo, ensuring that the bait is properly distributed after the entire trajectory is completed. Based on the required speed, the main control board sends commands to the propellers on both sides to control the boat's forward motion. When steering is required, the main control chip controls the two propellers through differential control.

[0083] During the operation of the ship, the cage mechanism will transport the feed in the silo 4 to the spreading structure 3, and the spreading structure 3 will start to rotate at the same time. The feeding distance can be controlled by the rotation speed of the spinning disc, and the feeding amount is controlled by the speed of the cage mechanism. The spreading structure 3 of the present invention can achieve the purpose of evenly spreading the bait in the pond by spreading the bait in a fan shape on the water surface. During this operation, the propeller propeller propels the hull forward, and the spreading structure 3 and the cage mechanism work together to evenly spread the feed along the planned route, and adjust the ship speed and the spreading speed in real time according to the detection data of the remaining material volume, so that when the trajectory is completed, the bait is also spread.

[0084] After completing the scheduled route, the present invention will return to the designated location on the shore and send a message of completion of the operation through the communication module, waiting for the next operation.

[0085] The following describes the algorithms used in the present invention to generate path planning and calculate the optimal traveling speed and optimal spreading speed of the ship in real time.

[0086] The calculation and generation of path planning includes generating coastal driving paths and regional coverage cruising paths.

[0087] The process of generating a coastal driving path is as follows:

[0088] Step 1: Determine the work area.

[0089] Mark points on the app to get a string of shore points in the form of longitude and latitude, and connect these points to get the working area. Figure 6 As shown, P1 to P4 are the four shore points.

[0090] Convert these shore points in the form of latitude and longitude into a rectangular coordinate system, with the first shore point P1 as the origin, the due east direction as the positive half-axis direction of the x-axis, and the due north direction as the positive half-axis direction of the y-axis, to facilitate subsequent calculations.

[0091] Conversion method: Assume that the radius of the earth is R = 6371000m, the latitude of the point to be converted is N, the longitude is E, and the latitude and longitude of the point set as the origin are the reference latitude and longitude, the reference latitude is refN, and the reference longitude is refE.

[0092]

[0093]

[0094]

[0095]

[0096] d lon =cos(E rad -refErad ) #(5)

[0097] arg=sin(refN rad )*sin(N rad )+cos(refN rad )*cos(N rad )*d lon #(6)

[0098] c=cos -1 arg,c>0 #(7)

[0099]

[0100] x=k*(cosrefN rad *sinN rad -sinrefN rad *cosN rad *d lon )*R #(9)

[0101] y=k*cosN rad *sin(E rad -refE rad )*R #(10)

[0102] At this time, the obtained x and y are the coordinates of the point to be converted in the current rectangular coordinate system.

[0103] Step 2: Convert the shore points from longitude and latitude to rectangular coordinates, and reorder the shore points in a counterclockwise direction to facilitate subsequent calculations. At this time, the order of the shore points is [P1, P4, P3, P2].

[0104] Step 3: Based on the rectangular coordinates of each shore point converted into a rectangular coordinate system, calculate the general straight line equation of each side, with P1P4 as the first side, P2P1 as the last side, and the next side of P2P1 as P1P4.

[0105] The general method for finding the equation of a straight line: Let two points (x1, y1), (x2, y2)

[0106] a=x1-x2 #(11)

[0107] b=y2-y1 #(12)

[0108] c=x1*y2-x2*y1 #(13)

[0109] Equation of a line: ax+by+c=0 #(14)

[0110] Step 4, calculate the general straight line equation corresponding to each bank, which is parallel to the bank and at a distance d from the bank.

[0111] Take the line where the first side P1P4 is located as an example: Let the general equation of the line where P1P4 is located be

[0112] ax+by+c=0 #(15)

[0113] The equations of the two lines parallel to this line and at a distance d from each other are

[0114] l1:ax+by+m1=0 #(16)

[0115] l2:ax+by+m2=0 #(17)

[0116] in, like Figure 7 In step 5 shown, it is determined which straight line is the desired straight line.

[0117] Suppose that the straight line of the next bank intersects the two straight lines found in step 4 at points Q1 and Q2. Q1, Q2 and the end point of the current edge and the starting point of the current edge form three vectors, which are calculate and Of the two vectors obtained, the one with the direction along the negative z-axis is the one we are looking for. Continuing with the example of the P1P4 edge, Figure 8 As shown,

[0118]

[0119]

[0120]

[0121] The direction is along the positive z-axis, The direction is along the negative z-axis, so the straight line l2 is the required straight line.

[0122] Step 6: After calculating the correct straight lines corresponding to all the shores according to steps 4 and 5, find the intersection of two adjacent straight lines. The intersection is the path point you are looking for, such as Figure 9 As shown, C1~C4 are the desired path points, and the path is C1→C4→C3→C2.

[0123] Step 7: Convert the path points obtained in step 6 from rectangular coordinates to longitude and latitude, and add the return point to the end of the converted path to obtain the desired path. Let the return point be P return , then the path is C1→C4→C3→C2→C1→P return .

[0124] The method of converting longitude and latitude from rectangular coordinates is as follows:

[0125] Assume that the radius of the earth is R = 6371000m, the horizontal coordinate of the point to be converted is x, the vertical coordinate is y, and the reference longitude and latitude are refE and refN.

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135] At this time, the obtained latitude N and longitude E are the converted longitude and latitude of the mission path point.

[0136] Determination of the return point: There is a button to determine the return point on the APP. Press it to record the current position of the ship and use it as the return point.

[0137] The process of generating a coverage cruise path within an area is as follows:

[0138] S01, in the determined rectangular coordinate system, let the minimum distance from the ship to the shore during the journey be d1, and let the distance between two adjacent parallel path segments be d2.

[0139] S02, based on the shore points P1, P2, P3, P4 and the minimum distance to the shore d1, follow steps 1 to 6 in generating the coastal path to generate a new boundary C1C2C3C4. This is the working area covering the cruise path. This boundary is denoted as G', and the shore P1P2P3P4 is denoted as G. Figure 10 shown.

[0140] S03: Calculate the lengths of each side of boundary G' and the general equations of the lines on which each side of G' lies. To minimize the number of turns during the ship's mission, the longest side of G' is selected as the starting edge. The blue line demarcates the shore, and the yellow-green lines C1C2C3C4 are the boundary G' covering the cruising path. The longest side of G' is C4C3, meaning the ship begins its mission at C4C3.

[0141] S04, find the distance D from each vertex of the boundary G' to the starting edge, and take the maximum value D in D max , calculate the number of path segments parallel to the starting edge in the covered cruise path n is an integer.

[0142] S05: Follow the method of steps 4 and 5 in generating the coastal path to obtain the equation of the first straight line within the boundary G' that is parallel to the starting edge, denoted as l1:ax+by+m1=0. The equation of the straight line of the starting edge is denoted as l:ax+by+c=0, and the equations of the remaining n-1 straight lines are obtained.

[0143] l i :ax+by+m i =0,i=2,3,......n#(30)

[0144] Where m i Determined by: m i =c+i*(m1-c),i=2,3,......n

[0145] S06, find l i The intersection with the straight lines of each side of G' is determined by the ray method to determine whether the intersection is inside G' (it is also considered to be inside if it is on the boundary of G').

[0146] Ray method: Draw a ray from the point to the right and determine the number of intersections with the polygon. If the number of intersections is odd, the point is inside the polygon, otherwise it is outside.

[0147] S07, take the 2n points in the interior in step S06, sort them in the bow shape, add the two endpoints of the starting edge at the beginning, and obtain the covered cruise path in the rectangular coordinate system. Convert it to longitude and latitude according to the method in step 7 of generating the coastal path, and add the return point at the end of the path to obtain the following: Figure 11 The full path shown.

[0148] The present invention uses an improved ILOS algorithm to determine a route and then direct the vessel to execute its mission along that route. Conventional LOS algorithms, when used in conjunction with windy and choppy conditions, can cause a fixed lateral deviation in the vessel. This deviation can be mitigated by integrating the algorithm.

[0149] The principle of the improved ILOS guidance law is as follows:

[0150] like Figure 12 As shown, the right-hand coordinate system X pp Y pp X pp The axis coincides with the straight line trajectory and moves in the direction of the straight line path. (Xp ,Y p ) is the coordinate system X pp Y pp Origin, (x,y) is the origin of the hull coordinate system.

[0151] In coordinate system X pp Y pp The position of the ship can be expressed as

[0152]

[0153] Since the coordinate system X pp Y pp Origin (X p ,Y p ) moves on a straight line, so

[0154]

[0155] where arctan2 is the generalized form of the arctan function, and α∈(-π,π]

[0156] Rewrite Equation (31) into the following general form:

[0157] 0=(xx p )cosα+(yy p )sinα #(33)

[0158]

[0159] The kinematic equation of the ship can be expressed as:

[0160]

[0161]

[0162] Derivative (34) and substitute (32), (33), (35), (36) into the equation to obtain

[0163]

[0164] In formula (37), χ = ψ + β is the heading angle; And β=arctan2(u,v) is the drift angle. Generally, the heading angle can be taken as

[0165]

[0166] Substituting equation (38) into equation (37) yields

[0167]

[0168] In order to eliminate the influence of drift angle, an integral operation can be directly added to the heading angle. The more direct ILOS guidance law can be written as

[0169] χ=α-arctan(k p y e +k i y int )#(40)

[0170]

[0171] In formula (40), k p and k i is greater than zero, and k i The selection of should be appropriate to avoid excessive integration operation causing large overshoot and long convergence time.

[0172] In order to make the selection of ILOS guidance law parameters more convenient and flexible, the following ILOS guidance law is proposed

[0173]

[0174]

[0175] In formula (43), the parameter k satisfies the following conditions:

[0176]

[0177] In formula (44), U d To further improve the integration effect and avoid large overshoot, the following time-varying parameter k2 can be taken as the desired speed:

[0178] k2(y e )=(k max -k min )e -ρ|ye| +k min #(45)

[0179] In formula (45), k max and k min are the maximum and minimum values of k2 respectively; ρ is the convergence rate. e When the lateral deviation y is larger, k2 is smaller and the integral effect is weaker; e When it is smaller, k2 is larger and the integral effect is stronger.

[0180] The system features a route storage function. After initially defining the work area, subsequent feeding tasks can be performed directly from the recorded route, eliminating the need for multiple setups and significantly reducing operational burdens and complexity. The system automatically saves all information from the previous task in the onboard main engine. When the user does not need to change the route or feed quality, they can simply activate the system with a single click using the remote control.

[0181] The present invention has the function of automatically adjusting the driving speed and feeding speed. It uses a dynamic calculation method to combine the driving route and the weight of bait to be dropped. It recalculates the subsequent ship speed required to complete the task at regular intervals. It determines the subsequent feeding speed by calculating the remaining working distance and the amount of feed remaining in the silo. It also automatically adjusts the duty cycle of the feed spreading motor based on the current real-time travel speed of the ship. It can also perform real-time calculations based on the distance traveled and the amount of feed spread during the driving process. Since the present invention can carry a large amount of feed, in order to ensure that all the feed is evenly spread, the route may have to be traveled for multiple rounds. This calculation method takes this into account. The specific implementation principle is as follows:

[0182] In order to achieve the goal of spreading the feed just at the end of the path execution and completing the task as quickly as possible, the maximum speed of the ship is set to v max , the maximum feeding speed is q max , the feed amount is m, and the task path is [P1, P2, ..., Pn], in the format [[lat, lon], [lat, lon] ... [lat, lon]], where P1, P2, ..., Pn are path points. Use the following steps to calculate the optimal ship speed (in m / s) and the optimal feed rate (in g / s).

[0183] Step 1: Convert the path from longitude and latitude to rectangular coordinates. According to equations (1) to (10), the converted path is [[x1, y1], [x2, y2], ... [x n ,y n ]].

[0184] Step 2: Find the distance per week that needs to be spread

[0185]

[0186] Step 3: Calculate the mass per meter of material required to spread the material just after the boat has finished traveling the path

[0187]

[0188] The default speed of the ship is the maximum speed v=v max , multiplying the two together gives the mass of material spread per second qs =q m *v.

[0189] Step 4: Calculate the minimum number of laps the ship needs to travel to complete the task.

[0190]

[0191] Total distance s = s1*n.

[0192] Step 5: Recalculate the mass of material per meter and the mass of material spread per second q′ s =q′ m *v, if q′ s max , then the ship speed is determined to be v = v max , go to step 7. If q s >q max , then go to step six.

[0193] Step 6: Reduce the ship speed by Δv. Let the ship speed after the reduction be v, and calculate the mass of material spread per second q at this time. s , if q s max &q s >q min , then determine the ship speed v, otherwise repeat step 6 until q s max .

[0194] Step 7: Calculate the forward speed of the ship. Let the forward direction of the ship be θ1, the forward direction of the ship's speed be θ2, and the speed of the ship be v. Then the forward speed is

[0195] v headi =v*cos(θ2-θ1) #(43)

[0196] Step 8: Record the amount of material discharged per second as q s , the duty cycle of the blanking motor is DR, then the relationship between the two is: DR=a*q s , where a is a constant coefficient related to the structure. At this time,

[0197] q s =v heading *q m #(44)

[0198] DR=a*v heading *q m #(45)

[0199] Obtain the duty cycle DR of the spreading motor and output DR.

[0200] ​​​Step 9: Update the coefficient a in step 8 every 10 seconds by reading and recording the data from the mass sensor. The mass difference read by the mass sensor within 10 seconds is recorded as Δm, and the theoretical mass of the material spread in the past 10 seconds is m1. dm = m1 - Δm. Let the previous coefficient be a0 and the updated coefficient be a1, then a1=a0+da.

[0201] Step 10: Update the remaining distance and feed spreading rate every 20 seconds. Calculate the total distance S from the ship's current position to the destination. Read the remaining feed mass m' from the mass sensor. Then proceed to Steps 5 and 6. Once you have determined the remaining distance and feed spreading mass per second, skip Steps 7 through 10 and proceed to Step 11.

[0202] Step 11: Using the ship speed and material spreading speed calculated in step 10, repeat steps 7 to 11 until the material spreading task is completed.

[0203] When using the present invention to work, the user only needs to pour the feed into the bin and input the mass of the feed to be spread in the APP. The present invention can automatically calculate the corresponding feeding speed. If the feed poured into the silo is more than the required feeding amount input, the excess feed will remain in the silo and wait for the next operation. If the feed poured into the silo is less than the required feeding amount input in the APP, the present invention will automatically spread all the feed in the silo. In addition, the present invention has a residual material detection function, which can detect the quality of the remaining bait in the silo in real time and feedback it in the APP, so that the user can check the working status of the ship. And the trimaran structural design is adopted to provide super stability and balance, which can truly replace manual labor in an intelligent and reliable way to achieve autonomous and efficient feeding.

[0204] The embodiments described above provide a detailed description of the technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements and equivalent substitutions made within the scope of the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A large intelligent unmanned feeding ship with a trimaran structure, characterized in that: It comprises a hull (1) and two floating bodies (2) fixed on both sides of the hull (1) via a fixed frame (12); The hull (1) is provided with a diesel generator (11) at the front, a material spreading structure (3) at the rear, and propeller propulsion mechanisms (10) symmetrically provided on both sides near the rear; a GPS antenna (6) and a radar (7) are provided on the diesel generator (11); The fixed frame (12) is provided with a silo (4) above the material spreading structure (3), and a weight sensor is provided in the silo (4); the lower opening of the silo (4) transmits the bait to the material spreading structure (3) through an auger mechanism; An electric control compartment (5) is provided in the middle of the hull (1), and a battery, a main control chip, a communication module, a positioning module and a drive module are provided in the electric control compartment (5); wherein the positioning module receives satellite signals through a GPS antenna (6) to determine the current position and orientation information of the hull; and the communication module is used to realize message communication between a mobile phone app, a server and an unmanned bait-casting boat; The server receives the position information of the positioning module through the communication module, calculates and generates a path plan, uses the improved ILOS algorithm to make the ship perform the task along the path plan, and calculates the optimal driving speed and the optimal material spreading speed of the ship in real time in combination with the data of the weight sensor; at the same time, the calculation result is sent to the main control chip, and the main control chip outputs a PWM signal to the drive module, and realizes uniform material spreading according to the path plan by controlling the operating status of the motors on the propeller propulsion mechanism (10), the auger mechanism and the material spreading structure (3); The specific process of real-time calculation of the optimal ship speed and optimal spreading speed is as follows: Step 1: Convert the path from longitude and latitude to rectangular coordinates. The converted path is [[x1,y1],[x2,y2],…[x n ,y n ]]; Step 2: Calculate the distance per week required to spread the material Step 3: Calculate the mass per meter of material required to spread the material just after the ship has finished traveling the path. The default speed of the ship is the maximum speed v=v max , multiplying the two together is the mass of material spread per second q s =q m *v; Step 4: Calculate the minimum number of circles n and the total distance s that the ship needs to travel to complete the mission s=s1*n Step 5: Recalculate the mass of material spread per meter and the mass of material spread per second q′ s =q′ m *v, if q′ s max , then the ship speed is determined to be v = v max , go to step 7; if q s >q max , then go to step 6;​ Step 6: Reduce the ship speed by Δv; let the ship speed after the reduction be v, and calculate the mass of material spread per second q at this time s , if q s max &q s >q min , then determine the ship speed v, otherwise repeat step 6 until q s max ;​​ Step 7, calculate the forward speed of the ship; let the forward direction of the ship be θ1, the forward direction of the ship's speed be θ2, and the ship's speed v, then the forward speed v heading =v*cos(θ2-θ1) Step 8: Record the amount of material discharged per second as q s , the duty cycle of the blanking motor is DR, then the relationship between the two is: DR=a*q s , where a is a constant coefficient related to the structure; in this case, q s =v heading *q m DR=a*v heading *q m Obtain the duty cycle DR of the spreading motor and output DR; Step 9: Update the coefficient a in step 8 every 10 seconds by reading and recording the data from the mass sensor. The mass difference read by the mass sensor within 10 seconds is recorded as Δm. The theoretical mass of the material spread in the past 10 seconds is m1. dm = m1 - Δm. Let the previous coefficient be a0 and the updated coefficient be a1, then a1=a0+da; Step 10: Update the remaining distance of the ship and the feeding speed every 20 seconds; calculate the total distance S from the current position to the end point, and read the remaining feed mass m through the mass sensor. ′ , proceed to step 5 to step 6, after obtaining the ship's forward speed and the mass of material spread per second for the remaining distance, skip steps 7 to 10 and proceed to step 11; Step 11: Using the ship speed and material spreading speed calculated in step 10, repeat steps 7 to 11 until the material spreading task is completed.

2. The large intelligent unmanned feeding ship with a trimaran structure according to claim 1 is characterized in that: A camera is provided at the front of the diesel generator and the rear of the silo for real-time monitoring of the situation in front and behind the unmanned feeding ship.

3. The large intelligent unmanned feeding ship with a trimaran structure according to claim 1 is characterized in that: A warning light is provided on the upper part of the diesel generator to warn the position of the ship and to flash when a problem occurs on the ship to warn the ship of the problem.

4. The large intelligent unmanned feeding ship with a trimaran structure according to claim 1 is characterized in that: The silo (4) is a sealed inverted cone structure, and weight sensors are arranged at the four corners of the lower part of the silo (4).

5. The large intelligent unmanned feeding ship with a trimaran structure according to claim 1 is characterized in that: The calculation and generation of path planning includes generating a coastal driving path and a cruising path covering the area. The process of generating a coastal driving path is as follows: Mark the points on the mobile app to get the four shore points in the form of longitude and latitude, and connect the four shore points to get the working area; Convert the four shore points in the form of longitude and latitude into a rectangular coordinate system, take the first shore point P1 as the origin, and calculate the straight line equations of the four sides as the four shore edges; Calculate the equations of four straight lines inside the work area, parallel to the shore and at a distance d from the shore. The intersection of two adjacent straight lines is the desired path point; The four obtained path points are converted from rectangular coordinates to longitude and latitude, and the return point is added to the end of the converted path to obtain the coastal driving path.

6. The large intelligent unmanned feeding ship with a trimaran structure according to claim 5, characterized in that: The process of generating a coverage cruise path within an area is as follows: In the determined rectangular coordinate system, let the minimum distance between the ship and the shore during the journey be d1, and let the distance between two adjacent parallel path segments be d2; By using the method of generating a coastal driving path, four new boundary lines d1 away from the shore are obtained to form the boundary G'. The boundary points are C1, C2, C3, and C4. The boundary G' is the working area covering the cruising path; Select the longest boundary line as the starting edge, and calculate the distance from each boundary point to the starting edge, and take the maximum value of the four distances as D max , calculate the number of path segments parallel to the starting edge in the covered cruise path n is an integer; Calculate the equation of the straight line l of the n-segment path parallel to the starting edge in the working area i , the distance between two adjacent paths is d2; Find l i The intersection point with each boundary line of the boundary G' and whether the intersection point is inside G' or on the boundary; Take the 2n intersection points inside and on the boundary of G', sort them in a bow shape, add the two endpoints of the starting edge at the beginning to obtain the coverage cruise path in the rectangular coordinate system, convert it into longitude and latitude, and add the return point at the end of the path to obtain the coverage cruise path in the area.

7. The large intelligent unmanned feeding ship with a trimaran structure according to claim 1 is characterized in that: In the improved ILOS algorithm, the formula of the ILOS guidance law is as follows: Where, χ represents the heading angle, α represents the angle between the ship's forward direction and the vertical direction; y e Indicates the distance between the center of the ship and the target route, indicating the deviation of the current ship in the forward direction; y int represents the integral term introduced in the ILOS algorithm, which is the accumulation of deviations in the ship's forward direction; Δ represents the forward distance of the ship along a given path, which is the distance between the desired heading point and the projection of the controlled ship's current position on the desired track; the parameter k satisfies the following conditions: Where k1 and k2 are the intermediate parameters required to determine the parameter k, k1 is a fixed parameter, k2 is a variable parameter related to the ship deviation, and U d is the expected speed. In order to further improve the integration effect, the variable parameter k2 is taken as follows: Where k max and k min are the maximum and minimum values of k2 respectively; ρ is the convergence rate; when the lateral deviation y e When the lateral deviation y is larger, k2 is smaller and the integral effect is weaker; e When it is smaller, k2 is larger and the integral effect is stronger.

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