Unmanned ship and unmanned aerial vehicle cooperative feeding operation method

Abstract

The invention discloses an unmanned ship and unmanned aerial vehicle cooperative feeding operation method, which is characterized in that unmanned ship and unmanned aerial vehicle cooperative feeding operation is optimized by taking minimization of the total cost of unmanned aerial vehicle and unmanned ship cooperative feeding operation as an optimization target. The working time of the unmanned ship and the unmanned aerial vehicle, launching and recycling of the unmanned aerial vehicle and the cost of mutual waiting of the unmanned ship and the unmanned aerial vehicle during recycling are considered, constraint conditions are determined, then a solver is used for solving the target function, and the sequence of the unmanned ship and the unmanned aerial vehicle for accessing the breeding points is obtained; according to the method, the scheduling time and the feeding path of the unmanned ship and the unmanned aerial vehicle are generated according to the scheduling time and the feeding path of the unmanned ship and the unmanned aerial vehicle and the waiting time of the unmanned ship and the unmanned aerial vehicle at each culture point, so that the feeding cost can be reduced, and the problems that gravity type deepwater net cages used in a marine ranch are distributed dispersedly and the feeding efficiency is low can be solved. And the feeding efficiency is improved, and the situation that the feeding operation is easily influenced by the sea condition environment is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of path optimization, and particularly to a method for collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle. Background Art

[0002] "Marine ranch" refers to a specific sea area where large-scale fishery facilities and systematic management systems are adopted, and the natural marine ecological environment is utilized to artificially gather economic marine organisms and conduct planned and purposeful sea ranching.

[0003] Gravity-type deep-water cages are the most widely used aquaculture equipment in "marine ranches" at present. In the field of gravity-type deep-water cage aquaculture, with the help of advanced cage technology and deep-sea resources, the aquaculture density can be effectively increased, the aquaculture risk can be reduced, and the market demand for high-quality aquatic products can be met.

[0004] However, at the present stage, the gravity-type deep-water cages used in "marine ranches" are scattered and difficult to form centralized management. And the existing method is to only use an unmanned ship for manual feeding, which has problems such as low feeding efficiency, high feeding cost, and the feeding operation is easily affected by sea conditions. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle.

[0006] To achieve the above purpose, the technical solution provided by the present invention is as follows:

[0007] A method for collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle, comprising:

[0008] Equate each deep-water cage in the marine ranch to a breeding point, and assume that a departure base and n breeding points form a marine ranch; an unmanned ship carries multiple unmanned aerial vehicles and sufficient feed and departs from the base. The unmanned ship travels along the planned path for feeding. For the breeding points that the unmanned ship is difficult to reach, the unmanned aerial vehicles are launched and recovered for operation; when the unmanned ship arrives at the launching breeding point, the unmanned aerial vehicles are launched to go to other breeding points for feeding operation. After the unmanned ship completes the action of launching the unmanned aerial vehicles, it continues to operate for the remaining breeding points. Finally, the unmanned ship picks up the unmanned aerial vehicles that have completed the operation at the recovery breeding point to achieve collaborative operation; until all breeding points have been fed, the unmanned ship and the unmanned aerial vehicles return to the base.

[0009] Furthermore, the collaborative feeding operation of the unmanned ship and the unmanned aerial vehicle is optimized with the goal of minimizing the total cost of the collaborative feeding operation of the unmanned aerial vehicle and the unmanned ship, and an objective function is established;

[0010] Considering the operation time of the unmanned ship and the unmanned aerial vehicle, the launching, recovery of the unmanned aerial vehicle, and the cost of mutual waiting between the unmanned ship and the unmanned aerial vehicle during recovery, constraint conditions are established;

[0011] Use a solver to solve the objective function, obtain the order of the unmanned ship and the UAV to visit the aquaculture points, as well as the waiting time of the unmanned ship and the UAV at each aquaculture point, and generate the scheduling times and feeding paths of the unmanned ship and the UAV;

[0012] Carry out the feeding operation according to the scheduling times and feeding paths of the unmanned ship and the UAV.

[0013] Furthermore, the total cost of the collaborative feeding operation of the UAV and the unmanned ship includes the collaborative feeding operation cost and the waiting cost of the UAV and the unmanned ship;

[0014] The waiting cost includes the costs of two situations where the UAV may arrive at the recovery aquaculture point first and wait for the unmanned ship and the unmanned ship arrives at the recovery aquaculture point first and waits for the UAV;

[0015] The established objective function is as follows:

[0016]

[0017] Among them, C1 is the unit distance travel cost coefficient of the unmanned ship; C2 is the unit distance travel cost coefficient of the UAV; α is the unit time waiting cost of the unmanned ship; β is the unit time waiting cost of the UAV; V L ,V R : are respectively the sets of aquaculture points for the unmanned ship to launch and recover the UAV, V L ={0,1,2,…,n},V R =

[0018] {1,2,…,n + 1}; U D is the set of all UAVs; and respectively represent the driving and flying distances of the unmanned ship and the UAV from aquaculture point i to aquaculture point j, aquaculture point i ∈ V L , aquaculture point j ∈ V R , i ≠ j; is the flying distance of the UAV from aquaculture point j to aquaculture point k; L is the maximum endurance of the unmanned ship; W i is the waiting time of the unmanned ship at aquaculture point i ∈ V R ; is the waiting time of the UAV u ∈ U D at aquaculture point i ∈ V R ; V =

[0019] {0,1,…,n,n + 1} is the set of all nodes, including the departure base of the offshore ranch, 0 is the departure base of the offshore ranch, n + 1 is a virtual point representing the end point of the unmanned ship, and 1 to n are the aquaculture point set N; x ijis a binary variable. If the unmanned boat travels from aquaculture point \(i\in V\) L to aquaculture point \(j\in V\) R it is 1, otherwise it is 0; is a binary variable, indicating that the unmanned aerial vehicle carried by the unmanned boat \(u\in U\) D at aquaculture point \(i\in V\) L launches, visits aquaculture point \(j\in N\), and retrieves at aquaculture point \(k\in V\) R is 1, otherwise it is 0.

[0020] Furthermore, the constraint conditions include:

[0021] Constraint for the unmanned boat to depart from the base:

[0022]

[0023] \(x\) 0j is a binary variable. If the unmanned boat travels from the base to aquaculture point \(j\in V\) R it is 1, otherwise it is 0;

[0024] Constraint for the unmanned boat to return to the base:

[0025]

[0026] \(x\) i,n+1 is a binary variable. If the unmanned boat returns to the base, it is 1, otherwise it is 0;

[0027] Constraint for the flow conservation of the unmanned boat at the aquaculture point:

[0028]

[0029] \(x\) ij is a binary variable. If the unmanned boat travels from aquaculture point \(i\in V\) L to aquaculture point \(j\), it is 1, otherwise it is 0; \(x\) jk is a binary variable. If the unmanned boat travels from aquaculture point \(j\) to aquaculture point \(k\in V\) R it is 1, otherwise it is 0;

[0030] Constraint for the launch of the unmanned aerial vehicle at the launch aquaculture point and the retrieval at the retrieval aquaculture point:

[0031]

[0032] Constraints (4) and (5) limit that the same unmanned aerial vehicle can be launched and retrieved at most once at the same aquaculture point;

[0033] Each aquaculture point can only be served once by the unmanned boat or the unmanned aerial vehicle

[0034]

[0035] Time continuity constraint for unmanned vessels:

[0036]

[0037] is the time required for the unmanned vessel to travel from aquaculture point i ∈ V L to aquaculture point j ∈ V R ; M is an integer; x ik is a binary variable, which is 1 if the unmanned vessel travels from aquaculture point i to aquaculture point k, otherwise 0; t k is the time when the unmanned vessel arrives at aquaculture point k; l k is the time when the unmanned vessel leaves aquaculture point k; l i is the time when the unmanned vessel leaves aquaculture point i;

[0038] Path constraint for unmanned vessels:

[0039]

[0040] Constraints (9) and (10) ensure that the path of the unmanned vessel passes through the aquaculture point i for UAV launching and the aquaculture point j for recovery service;

[0041] x hi is a binary variable, which is 1 if the unmanned vessel travels from aquaculture point h ∈ V L to aquaculture point i, otherwise 0; x lk is a binary variable, which is 1 if the unmanned vessel travels from aquaculture point l ∈ N to aquaculture point k, otherwise 0; x hk is a binary variable, which is 1 if the unmanned vessel travels from aquaculture point h ∈ V L to aquaculture point k, otherwise 0; represents 1 if the UAV u ∈ U carried by the unmanned vessel D is launched at the base, visits aquaculture point j ∈ N, and is recovered at aquaculture point k ∈ V R otherwise 0;

[0042] The unmanned vessel can only launch the UAV after arriving at aquaculture point i:

[0043]

[0044] is the time when the UAV u ∈ U D leaves aquaculture point i;

[0045] After launching the UAV at aquaculture point i, the unmanned vessel goes to the next aquaculture point for operation:

[0046]

[0047] Time continuity constraint for the UAV to fly to aquaculture point j:

[0048]

[0049] For the drone \(u\in U\) D The moment of arriving at the aquaculture point; For the drone \(u\in U\) D From the aquaculture point \(i\in V\) L Traveling to the aquaculture point \(j\in V\) R The time required;

[0050] Time continuity constraint for the drone \(u\) leaving after operating at the aquaculture point \(j\):

[0051]

[0052] S d Is the time required for the drone to operate at the aquaculture point;

[0053] Time continuity constraint for the drone flying to the recovery aquaculture point \(k\):

[0054]

[0055]

[0056] For the drone \(u\in U\) D The moment of arriving at the aquaculture point \(k\);

[0057] Time constraint for the drone leaving the aquaculture point \(k\):

[0058]

[0059] For the drone \(u\in U\) D The moment of leaving the aquaculture point \(v\); S L ,S R Are the times required for the unmanned boat to launch and recover the drone respectively; Indicates that if the drone \(u\in U\) carried by the unmanned boat D At the aquaculture point \(k\in V\) L Launches, visits the aquaculture point \(l\in N\), and recovers at the aquaculture point \(m\in V\) R Then it is 1, otherwise it is 0;

[0060] Constraint related to the moment when the unmanned boat leaves the aquaculture point \(k\) and the drone:

[0061]

[0062] Constraint (22) indicates that the drone can be launched again only after being recovered; Indicates that if the drone \(u\in U\) carried by the unmanned boat D At the aquaculture point \(v\in V\)L Launch, access the aquaculture site \(m\in N\), and be at the aquaculture site \(n\in V\) R If retrieved, it is 1, otherwise it is 0; \(P\) iv Indicates that if the unmanned boat continuously visits the aquaculture sites \(i\in V\) in sequence L , \(v\in N\), then it is going, otherwise it is 0; \(S\) s Is the time required for the unmanned boat to operate at the aquaculture site;

[0063] Unmanned boat waiting time constraint:

[0064]

[0065] Drone waiting time constraint:

[0066]

[0067] Drone endurance constraint:

[0068]

[0069] Aquaculture site operation sequence constraint:

[0070]

[0071] \(\mu\) i , \(\mu\) j , \(\mu\) k Are all auxiliary variables used to eliminate sub - circuits;

[0072] Aquaculture site operation sequence symmetry constraint:

[0073]

[0074] Constraints (26)-(30) define the operation sequence of the aquaculture sites and eliminate sub - circuits;

[0075] \(P\) ij Indicates that if the unmanned boat continuously visits the aquaculture sites \(i\in V\) in sequence L , \(j\in N\), then it takes 1, otherwise it is 0. If the unmanned boat departs from the base, then \(P\) 0j = 1; \(P\) ji Indicates that the unmanned boat continuously visits the aquaculture sites \(j\in V\) in sequence L , \(i\in N\);

[0076] Unmanned boat and drone waiting time non - negative constraint:

[0077]

[0078] Unmanned boat travel decision variable value constraint:

[0079]

[0080] The auxiliary decision variables value constraints for the order of visiting breeding sites are:

[0081]

[0082] Decision variable constraints for unmanned boats serving aquaculture sites:

[0083]

[0084] Time variable non-negative constraint:

[0085]

[0086] t i is the time when the unmanned boat arrives at the breeding site i; For drone u∈U D The time of arrival at breeding point i;

[0087] Auxiliary variable value variable range constraints:

[0088]

[0089] Compared with the prior art, the principles and advantages of this technical solution are as follows:

[0090] 1. The feeding method of collaborative operation between drones and unmanned ships takes advantage of the large-scale feeding of unmanned ships and the flexible feeding of drones. It can not only solve the problem that the gravity-type deep-water cages used in "ocean ranches" are dispersed and difficult to form centralized management, but also improve feeding efficiency and avoid the feeding operation being easily affected by sea conditions.

[0091] 2. The collaborative feeding operation of unmanned ships and drones is optimized with the minimization of the total cost of the collaborative feeding operation of drones and unmanned ships as the optimization goal, and the operation time of unmanned ships and drones, the launch and recovery of drones, and the cost of waiting for each other during recovery are taken into account. Constraints are established, and then the solver is used to solve the objective function to obtain the order in which unmanned ships and drones visit the breeding points, as well as the waiting time of unmanned ships and drones at each breeding point. The scheduling time and feeding path of unmanned ships and drones are generated, and finally the feeding operation is carried out according to the scheduling time and feeding path of unmanned ships and drones to reduce the feeding cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0093] Figure 1 It is a process example of the collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle;

[0094] Figure 2 It is a principle flow chart for optimizing the collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle in a method for the collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle according to the present invention. Specific embodiments

[0095] The present invention will be further described below in conjunction with specific embodiments:

[0096] A method for the collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle described in this embodiment includes:

[0097] Equate each deep - sea cage in the marine ranch to a breeding point, and assume that a departure base and n breeding points form a marine ranch; an unmanned ship carries multiple unmanned aerial vehicles and sufficient feed and departs from the base. The unmanned ship travels along the planned path for feeding. For breeding points that the unmanned ship cannot reach, the unmanned aerial vehicle is launched and recovered for operation; when the unmanned ship arrives at the launching breeding point, it launches the unmanned aerial vehicle to go to other breeding points for feeding operation. After the unmanned ship completes the action of launching the unmanned aerial vehicle, it continues to operate for the remaining breeding points. Finally, the unmanned ship picks up the unmanned aerial vehicle that has completed the operation at the recovery breeding point to achieve collaborative operation; until all breeding points have been fed, the unmanned ship and the unmanned aerial vehicle return to the base.

[0098] An example of the feeding operation process is as Figure 1 shown.

[0099] According to the characteristics of the collaborative operation of the unmanned ship and the unmanned aerial vehicle, the following technical conditions are set:

[0100] The unmanned aerial vehicle travels at a constant speed during flight.

[0101] The unmanned aerial vehicle is limited by the endurance mileage.

[0102] It takes a certain amount of time for the unmanned ship to launch and recover the unmanned aerial vehicle.

[0103] The unmanned ship can only launch and recover the unmanned aerial vehicle at the breeding point

[0104] Each breeding point can only be operated once by the unmanned aerial vehicle and the unmanned ship.

[0105] The feed demand of each breeding point does not exceed the carrying capacity of the unmanned aerial vehicle.

[0106] In order to improve the effect of the collaborative operation of the unmanned ship and the unmanned aerial vehicle, as Figure 2 shown, taking the minimization of the total cost of the collaborative feeding operation of the unmanned aerial vehicle and the unmanned ship as the optimization goal for optimization, a target function is established;

[0107] Considering the operation time of the unmanned ship and the UAV, the launch and recovery of the UAV, and the cost of mutual waiting between the unmanned ship and the UAV during recovery, the constraint conditions are established.

[0108] Use the solver to solve the objective function, obtain the order of the unmanned ship and the UAV to visit the aquaculture points, and the waiting time of the unmanned ship and the UAV at each aquaculture point, and generate the scheduling times and feeding paths of the unmanned ship and the UAV.

[0109] Finally, carry out the feeding operation according to the scheduling times and feeding paths of the unmanned ship and the UAV.

[0110] In the above, the total cost of the collaborative feeding operation of the UAV and the unmanned ship includes the collaborative feeding operation cost and the waiting cost of the UAV and the unmanned ship.

[0111] The waiting cost includes the costs of two situations: the UAV may arrive at the recovery aquaculture point first and wait for the unmanned ship, and the unmanned ship may arrive at the recovery aquaculture point first and wait for the UAV.

[0112] The established objective function is as follows:

[0113]

[0114] Among them, C1 is the unit distance driving cost coefficient of the unmanned ship; C2 is the unit distance driving cost coefficient of the UAV; α is the unit time waiting cost of the unmanned ship; β is the unit time waiting cost of the UAV; V L ,V R : are respectively the sets of aquaculture points for the unmanned ship to launch and recover the UAV, V L ={0,1,2,…,n},V R =

[0115] {1,2,…,n + 1}; U D is the set of all UAVs; and respectively represent the driving and flying distances of the unmanned ship and the UAV from aquaculture point i to aquaculture point j, aquaculture point i ∈ V L , aquaculture point j ∈ V R , i ≠ j; is the flying distance of the UAV from aquaculture point j to aquaculture point k; L is the maximum endurance of the unmanned ship; W i is the waiting time of the unmanned ship at aquaculture point i ∈ V R ; is the waiting time of the UAV u ∈ U D at aquaculture point i ∈ V R ; V =

[0116] {0, 1, …, n, n + 1} is the set of all nodes, including the departure base of the marine ranch. 0 is the departure base of the marine ranch, n + 1 is a virtual point representing the end point of the unmanned ship, and 1 to n are the set of aquaculture points N; x ij is a binary variable. If the unmanned ship travels from aquaculture point i ∈ V L to aquaculture point j ∈ V R then it is 1, otherwise it is 0; is a binary variable, indicating that the unmanned aerial vehicle carried by the unmanned ship u ∈ U D is launched, visits aquaculture point j ∈ N, and is retrieved at aquaculture point k ∈ V L and is retrieved at aquaculture point k ∈ V is 1, otherwise it is 0. R is retrieved is 1, otherwise it is 0.

[0117] The constraint conditions include:

[0118] Constraint for the unmanned ship to depart from the base:

[0119]

[0120] x 0j is a binary variable. If the unmanned ship travels from the base to aquaculture point j ∈ V R then it is 1, otherwise it is 0;

[0121] Constraint for the unmanned ship to return to the base:

[0122]

[0123] x i,n+1 is a binary variable. If the unmanned ship returns to the base, it is 1, otherwise it is 0;

[0124] Constraint for the flow conservation of the unmanned ship at aquaculture points:

[0125]

[0126] x ij is a binary variable. If the unmanned ship travels from aquaculture point i ∈ V L to aquaculture point j, it is 1, otherwise it is 0; x jk is a binary variable. If the unmanned ship travels from aquaculture point j to aquaculture point k ∈ V R then it is 1, otherwise it is 0;

[0127] Constraint for the launch of the unmanned aerial vehicle at the launch aquaculture point and the retrieval at the retrieval aquaculture point:

[0128]

[0129] Constraints (4) and (5) limit that the same unmanned aerial vehicle can be launched and retrieved at most once at the same aquaculture point;

[0130] Each aquaculture site can only be served once by an unmanned boat or an unmanned aerial vehicle

[0131]

[0132] Time continuity constraint of the unmanned boat:

[0133]

[0134] For the unmanned boat traveling from aquaculture site i ∈ V L to aquaculture site j ∈ V R The required time; M is an integer; x ik Is a binary variable, which is 1 if the unmanned boat travels from aquaculture site i to aquaculture site k, otherwise 0; t k Is the moment when the unmanned boat arrives at aquaculture site k; l k Is the moment when the unmanned boat leaves aquaculture site k; l i Is the moment when the unmanned boat leaves aquaculture site i;

[0135] Path constraint of the unmanned boat:

[0136]

[0137] Constraints (9) and (10) ensure that the path of the unmanned boat passes through the drone launching aquaculture site i and the recovery service point j;

[0138] x hi Is a binary variable, which is 1 if the unmanned boat travels from aquaculture site h ∈ V L to aquaculture site i, otherwise 0;

[0139] x lk Is a binary variable, which is 1 if the unmanned boat travels from aquaculture site l ∈ N to aquaculture site k, otherwise 0; x hk Is a binary variable, which is 1 if the unmanned boat travels from aquaculture site h ∈ V L to aquaculture site k, otherwise 0; Indicates that if the drone u ∈ U carried by the unmanned boat D Is launched at the base, visits aquaculture site j ∈ N, and is recovered at aquaculture site k ∈ V R Then it is 1, otherwise 0;

[0140] The unmanned boat can only launch the drone after arriving at aquaculture site i:

[0141]

[0142] For the drone u ∈ U D The moment of leaving aquaculture site i;

[0143] The unmanned boat launches the UAV at aquaculture point i and then proceeds to the next aquaculture point for operation:

[0144]

[0145] Time continuity constraint for the UAV to fly to aquaculture point j:

[0146]

[0147]

[0148] For UAV u ∈ U D The moment of arrival at the aquaculture point; For UAV u ∈ U D From aquaculture point i ∈ V L Traveling to aquaculture point j ∈ V R The required time;

[0149] Time continuity constraint for the UAV u to leave after operating at aquaculture point j:

[0150]

[0151] S d Is the time required for the UAV to operate at the aquaculture point;

[0152] Time continuity constraint for the UAV to fly to the recovery aquaculture point k:

[0153]

[0154] For UAV u ∈ U D The moment of arrival at aquaculture point k;

[0155] Time constraint for the UAV to leave aquaculture point k:

[0156]

[0157] For UAV u ∈ U D The moment of leaving aquaculture point v; S L ,S R Are the time required for the unmanned boat to launch and recover the UAV respectively; Indicates that if the UAV u ∈ U carried by the unmanned boat D At aquaculture point k ∈ V L Launches, visits aquaculture point l ∈ N, and recovers at aquaculture point m ∈ V R Then it is 1, otherwise it is 0;

[0158] Constraint related to the moment when the unmanned boat leaves aquaculture point k and the UAV:

[0159]

[0160] Constraint (22) indicates that the UAV can only be launched for the second time after being recovered; Indicates that if the UAV carried by the unmanned boat u ∈ U D At the aquaculture point v ∈ V L Launches, visits the aquaculture point m ∈ N, and retrieves at the aquaculture point n ∈ V R Then it is 1, otherwise it is 0; P iv Indicates that if the unmanned boat continuously visits the aquaculture points i ∈ V in sequence L , v ∈ N, then it is "go", otherwise it is 0; S s Is the time required for the unmanned boat to operate at the aquaculture point;

[0161] Unmanned boat waiting time constraint:

[0162]

[0163] UAV waiting time constraint:

[0164]

[0165] UAV endurance constraint:

[0166]

[0167] Aquaculture point operation sequence constraint:

[0168]

[0169] μ i , μ j , μ k Are all auxiliary variables used to eliminate sub - circuits;

[0170] Aquaculture point operation sequence symmetry constraint:

[0171]

[0172] Constraints (26) - (30) define the operation sequence of the aquaculture points and eliminate sub - circuits;

[0173] P ij Indicates that if the unmanned boat continuously visits the aquaculture points i ∈ V in sequence L , j ∈ N, then it takes 1, otherwise it is 0. When the unmanned boat departs from the base, then P 0j = 1; P ji Indicates that the unmanned boat continuously visits the aquaculture points j ∈ V in sequence L , i ∈ N;

[0174] Unmanned boat and UAV waiting time non - negative constraint:

[0175]

[0176] Value constraints for decision variables of unmanned ship navigation

[0177]

[0178] Value constraints for auxiliary decision variables of the visiting order of aquaculture sites

[0179]

[0180] Constraints for decision variables of unmanned ship serving aquaculture sites

[0181]

[0182] Non - negative constraint for time variables

[0183]

[0184] t i is the time when the unmanned ship arrives at aquaculture site i; For the unmanned aerial vehicle u ∈ U D is the time when it arrives at aquaculture site i;

[0185] Constraints on the value range of auxiliary variables

[0186]

[0187] In this embodiment, the feeding method of the collaborative operation of the unmanned aerial vehicle and the unmanned ship gives full play to the characteristics of large - scale feeding of the unmanned ship and flexible feeding of the unmanned aerial vehicle. It can not only solve the problem that the gravity - type deep - water cages used in the "marine ranch" are scattered and difficult to form centralized management, but also improve the feeding efficiency and avoid the influence of sea conditions on the feeding operation.

[0188] The collaborative feeding operation of the unmanned ship and the unmanned aerial vehicle is optimized with the goal of minimizing the total cost of the collaborative feeding operation of the unmanned ship and the unmanned aerial vehicle. Considering the operation time of the unmanned ship and the unmanned aerial vehicle, the launch and recovery of the unmanned aerial vehicle, and the cost of mutual waiting between the unmanned ship and the unmanned aerial vehicle during recovery, constraint conditions are established. Then, a solver is used to solve the objective function to obtain the order of the unmanned ship and the unmanned aerial vehicle visiting the aquaculture sites, as well as the waiting time of the unmanned ship and the unmanned aerial vehicle at each aquaculture site, generate the scheduling times and feeding paths of the unmanned ship and the unmanned aerial vehicle, and finally carry out the feeding operation according to the scheduling times and feeding paths of the unmanned ship and the unmanned aerial vehicle, which can reduce the feeding cost.

[0189] The above - mentioned embodiments are only the preferred embodiments of the present invention, and do not limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A collaborative feeding operation method for an unmanned ship and an unmanned aerial vehicle, characterized in that, Including: Equivalent each deep - water cage in the marine ranch to a breeding point, and set up a departure base and n breeding points to form a marine ranch; An unmanned ship carries multiple drones and sufficient feed and departs from the base. The unmanned ship travels along the planned path for feeding. For breeding points that the unmanned ship cannot reach, drones are launched and recovered for operation. When the unmanned ship arrives at the launching breeding point, it launches drones to other breeding points for feeding operation. After the unmanned ship completes the action of launching drones, it continues to operate for the remaining breeding points. Finally, the unmanned ship picks up the drones that have completed the operation at the recovery breeding point to achieve collaborative operation; until all breeding points have been fed, the unmanned ship and drones return to the base.

2. The method for collaborative feeding operation of an unmanned boat and an unmanned aerial vehicle according to claim 1, characterized in that, The collaborative feeding operation of the unmanned ship and drones is optimized with the goal of minimizing the total cost of the collaborative feeding operation of the unmanned ship and drones, and an objective function is established; Considering the operation time of the unmanned ship and drones, the launching, recovery of drones, and the cost of mutual waiting between the unmanned ship and drones during recovery, constraint conditions are established; Use a solver to solve the objective function to obtain the order in which the unmanned ship and drones visit the breeding points, as well as the waiting time of the unmanned ship and drones at each breeding point, and generate the scheduling times and feeding paths of the unmanned ship and drones; Carry out feeding operations according to the scheduling times and feeding paths of the unmanned ship and drones.

3. The method for collaborative feeding operation of an unmanned ship and an unmanned aerial vehicle according to claim 2, wherein The total cost of the collaborative feeding operation of drones and the unmanned ship includes the cost of the collaborative feeding operation of drones and the unmanned ship and the waiting cost; The waiting cost includes the costs of two situations: the drone may arrive at the recovery breeding point first and wait for the unmanned ship, and the unmanned ship may arrive at the recovery breeding point first and wait for the drone; The established objective function is as follows: Among them, C1 is the unit distance travel cost coefficient of the unmanned ship; C2 is the unit distance travel cost coefficient of the unmanned aerial vehicle; α is the unit time waiting cost of the unmanned ship; β is the unit time waiting cost of the unmanned aerial vehicle; V L ,V R : are respectively the sets of aquaculture points for the unmanned ship to launch and recover the unmanned aerial vehicle, V L ={0, 1, 2, …, n}, V R ={1, 2, …, n + 1}; U D is the set of all unmanned aerial vehicles; and respectively represent the travel and flight distances of the unmanned ship and the unmanned aerial vehicle from aquaculture point i to aquaculture point j, where aquaculture point i ∈ V L , aquaculture point j ∈ V R , i ≠ j; is the flight distance of the unmanned aerial vehicle from aquaculture point j to aquaculture point k; L is the maximum endurance of the unmanned ship; W i is the waiting time of the unmanned ship at aquaculture point i ∈ V R ; is the waiting time of the unmanned aerial vehicle u ∈ U D at aquaculture point i ∈ V R ; V = {0, 1, …, n, n + 1} is the set of all nodes, including the departure base of the offshore ranch, 0 is the departure base of the offshore ranch, n + 1 is a virtual point representing the end point of the unmanned ship, and 1 to n are the set of aquaculture points N; x ij is a binary variable, which is 1 if the unmanned ship travels from aquaculture point i ∈ V L to aquaculture point j ∈ V R and 0 otherwise; is a binary variable, indicating that the unmanned aerial vehicle u ∈ U carried by the unmanned ship D is launched at aquaculture point i ∈ V L , visits aquaculture point j ∈ N, and is recovered at aquaculture point k ∈ V R and is 1 otherwise and 0 otherwise.

4. The method for collaborative feeding operation of an unmanned boat and an unmanned aerial vehicle according to claim 3, wherein, The constraint conditions include: Constraint for the unmanned ship departing from the base: x 0j is a binary variable. If the unmanned ship sails from the base to the aquaculture point j ∈ V R then it is 1, otherwise it is 0; Constraint for the unmanned ship returning to the base: x i,n+1 is a binary variable, which is 1 if the unmanned boat returns to the base, otherwise 0; Constraint for the conservation of flow of the unmanned ship at the breeding point: x ij is a binary variable. If the unmanned boat travels from aquaculture point \(i\in V\) L to aquaculture point \(j\), it is 1; otherwise it is 0. \(x\) jk is a binary variable. If the unmanned boat travels from aquaculture point \(j\) to aquaculture point \(k\in V\) R it is 1; otherwise it is 0. Constraints for launching at the launching breeding point and recovering at the recovery breeding point of the drone: Constraints (4) and (5) limit that the same drone can be launched and recovered at most once at the same breeding point; Each breeding point can only be served once by the unmanned ship or the drone Constraint for the time continuity of the unmanned ship: is the time required for the unmanned ship to travel from aquaculture point \(i\in C\) L to aquaculture point \(j\in V\) R ; \(M\) is an integer; \(x\) ik is a binary variable, which is 1 if the unmanned ship travels from aquaculture point \(i\) to aquaculture point \(k\), otherwise 0; \(t\) k is the time when the unmanned ship arrives at aquaculture point \(k\); \(l\) k is the time when the unmanned ship leaves aquaculture point \(k\); \(l\) i is the time when the unmanned ship leaves aquaculture point \(i\); Constraint for the path of the unmanned ship: x hi is a binary variable. If the unmanned boat travels from the aquaculture point h ∈ V L to the aquaculture point i, it is 1; otherwise, it is 0; x lk is a binary variable. If the unmanned boat travels from the aquaculture point l ∈ N to the aquaculture point k, it is 1; otherwise, it is 0; x hk is a binary variable. If the unmanned boat travels from the aquaculture point h ∈ V L to the aquaculture point k, it is 1; otherwise, it is 0; indicates that if the unmanned aerial vehicle u ∈ U carried by the unmanned boat D is launched at the base, visits the aquaculture point j ∈ N, and is retrieved at the aquaculture point k ∈ V R it is 1; otherwise, it is 0; Constraints (9) and (10) ensure that the path of the unmanned ship passes through the drone launching breeding point i and the recovery service point j; The unmanned ship can only launch the drone after arriving at the breeding point i: For the drone u ∈ U D The moment of leaving the aquaculture point i; After launching the drone at the breeding point i, the unmanned ship goes to the next breeding point for operation: Constraint for the time continuity of the drone flying to the breeding point j: For the drone \(u\in U\) D The moment of arrival at the aquaculture site; For the drone \(u\in U\) D From the aquaculture site \(i\in V\) L The time required to travel to the aquaculture site \(j\in V\) R The required time; Constraint for the time continuity of the drone u leaving after operating at the breeding point j: S d is the time required for the drone to operate at the breeding site; Constraint for the time continuity of the drone flying to the recovery breeding point k: For the UAV u ∈ U D The moment of arriving at the aquaculture point k; Time constraint for the drone leaving the breeding point k: For the drone \(u\in U\) D The moment when it leaves the aquaculture point \(v\); \(S\) L , \(S\) R are the times required for the unmanned boat to launch and recover the drone respectively; Indicates that if the drone \(u\in U\) carried by the unmanned boat D is at the aquaculture point \(k\in V\) L launches, visits the aquaculture point \(l\in N\), and is recovered at the aquaculture point \(m\in V\) R then it is 1, otherwise it is 0; Constraint related to the time when the unmanned ship leaves the breeding point k and the drone: Constraint (22) indicates that the drone can be launched again only after recovery; If the number of drones u∈U carried by the unmanned ship D At the breeding point v∈V L Launch, visit breeding point m∈N, and at breeding point n∈V R If it is recovered, it is 1, otherwise it is 0; iv If the unmanned boat visits the breeding point i∈V in sequence L , v∈N, then it is gone, otherwise it is 0; S s The time required for the unmanned boat to operate at the aquaculture site; Constraint for the waiting time of the unmanned ship: Constraint for the waiting time of the drone: Constraint for the endurance of the drone: Constraint for the operation order of the breeding point: μ i , μ j , μ k are all auxiliary variables for eliminating the sub-circuit; Symmetric constraint for the operation order of the breeding point: Constraints (26)-(30) define the operation order of the breeding point and eliminate sub - circuits; P ij Indicates that if the unmanned boat sequentially and continuously visits the aquaculture point \(i\in V\) L , \(j\in N\), then take 1, otherwise 0. When the unmanned boat departs from the base, then \(P\) 0j = 1; \(P\) ji Indicates that the unmanned boat sequentially and continuously visits the aquaculture point \(j\in V\) L , \(i\in N\); Non - negative constraint for the waiting time of the unmanned ship and the drone: Constraint for the value of the decision variable of the unmanned ship's travel decision: Constraint for the value of the auxiliary decision variable of the breeding point access order: Constraint for the decision variable of the unmanned ship serving the breeding point: Non - negative constraint of time variable: t i is the time when the unmanned ship arrives at the aquaculture point i; For the unmanned aerial vehicle u ∈ U D is the time when it arrives at the aquaculture point i; Constraint on the value range of auxiliary variable:

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