A Method for Pond Full-Coverage Operation Trajectory Planning and Efficient Autonomous Return Navigation Endurance of an Aquaculture Feeding and Medicating Boat

Abstract

The present invention discloses a method for trajectory planning of full-pond coverage operation and efficient autonomous return voyage endurance of an aquaculture bait and medicine application ship. In the present invention, the larger value of the ship width and the ship length is used as the basic grid size, and the operation width is used as the operation grid size. The grid map is traversed using an optimized coverage range turning-back method. When encountering a dead zone, an improved A* algorithm is used to break away from the dead zone to complete the planning of the full-pond coverage traversal operation route. An improved A* algorithm is used to plan a shortest return voyage trajectory with fewer turns and larger turning angles between the return point and the dock. When refueling and continuing the voyage, the operation ship does not directly return to the previous return point, but calculates and selects the optimal return point according to the optimal energy consumption strategy to generate a continuous operation trajectory for the operation ship to continue the operation, and loops in turn until the operation of the entire pond is completed. The present invention can improve the operation efficiency of the bait and medicine application ship and reduce the energy consumption of the operation ship.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent agricultural machinery, and particularly relates to a method for planning the operation trajectory of a full-coverage of a pond by an aquaculture bait and medicine application ship and an efficient autonomous return voyage and endurance. Background Art

[0002] An aquaculture bait and medicine application ship is an automated equipment with autonomous cruise bait and medicine application. Compared with the traditional manual bait and medicine application operation mode, the operation ship can significantly improve the operation efficiency, reduce the manual labor intensity, and improve the aquaculture benefit. Therefore, more and more people begin to research aquaculture operation ships. Since ponds often contain obstacles, most of the current conventional full-coverage path planning algorithms use the ship body size or the operation width as the minimum resolution of the grid map. If the grid is too small, it will lead to a large amount of path planning calculation and it is difficult to find a full-coverage operation route; if the grid is too large, it will lead to problems such as obstacles occupying a large grid and low coverage rate of bait and medicine application operations. Since the required bait (medicine) density in different areas of the pond is different, it is necessary to plan the operation trajectory of variable bait (medicine) application for full coverage, while it is relatively difficult to implement the traditional pond operation path planning algorithm, and it is difficult for the traversal path planned by it to achieve the expected effect.

[0003] At the same time, with the increasing intensification of aquaculture, the water area of large-scale aquaculture is also large, and the bait (liquid medicine) loaded by the operation ship at one time cannot meet the needs of the entire aquaculture pond water area. Therefore, the operation ship needs to return to the dock multiple times to supplement the bait (liquid medicine) or recharge and then continue the operation. The existing full-coverage path planning method for operation ships does not fully consider this point. After each voyage operation is completed, whether the system can plan a shortest feasible return path and whether the subsequent voyage trajectory is efficient and energy-saving after supplementing the bait (liquid medicine) or charging directly determines the working efficiency of the operation ship. Summary of the Invention

[0004] To solve the above problems of the prior art, the present invention designs a method for planning the operation trajectory of a full-coverage of a pond by an aquaculture bait and medicine application ship and an efficient autonomous return voyage and endurance.

[0005] The technical solution of the present invention is: a method for planning the operation trajectory of a full-coverage of a pond by an aquaculture bait and medicine application ship and an efficient autonomous return voyage and endurance, the method comprising the following steps:

[0006] A. Collect the longitude and latitude coordinates of the pond vertices and obstacles, and convert the longitude and latitude coordinates into plane coordinates;

[0007] B. Separate the traversal coverage range and collision detection, determine the basic grid size according to the hull size, safety distance, and operation width, determine the operation grid size according to the operation width, establish a pond grid map, and use the full-coverage return traversal method of optimizing the traversal range to generate a variable operation trajectory of full-coverage bait and medicine application for the bait and medicine application ship;

[0008] C. During the operation of the feeding and medicine application boat according to the set trajectory, the remaining amounts of bait (liquid medicine) and battery power of the aquaculture feeding and medicine application boat are detected in real time. First, it is judged whether all the operation tasks have been completed. If so, it is necessary to automatically plan the optimal return route and return to the pond dock autonomously, and the operation ends. If all the operations have not been completed, then it is judged whether the remaining bait (liquid medicine) and battery power are insufficient and it is necessary to return to the pond dock for replenishment. If sufficient, the normal operation continues. If insufficient, it is necessary to record the return point, automatically plan the optimal return route, return to the dock autonomously, and carry out the corresponding replenishment;

[0009] D. After the operation boat is replenished, it automatically plans the optimal endurance route and operation trajectory, continues the feeding and medicine application operation, and jumps to step C.

[0010] Further, in the step B, the basic grid size is determined by the hull size, safety distance, and operation width, and the operation grid size is determined by the operation width. The method includes the following steps:

[0011] Step S21: First, take the larger value d1 of the ship length and ship width as the side length of the basic grid;

[0012] Step S22: Calculate the ratio of the operation width w to d1, and take the value after rounding down as a. Judge that if a is an odd number, the ratio b of the operation grid to the basic grid side length is a; if a is an even number, the ratio b of the operation grid to the basic grid side length is a - 1. Then, adjust the basic grid side length to d = w / b in combination with the safety distance.

[0013] Further, in the step B, the full - coverage return traversal method with an optimized traversal range is used. The method includes the following steps:

[0014] Step S31: Starting from the starting point, determine the traversal direction, start traversing in the direction parallel to the long side of the grid map, and start traversing at a distance of c unit grids from the boundary, where c = (b - 1) / 2;

[0015] Step S32: Count the covered area. The covered area is perpendicular to the traversal direction. Add the c grids on the left and right of the operation boat and the grid where it is located to the traversed list HLIST;

[0016] Step S33: Detect the obstacle or boundary situation in front of the current operation direction of the operation boat. If there is an obstacle, boundary, or traversed grid in one of the c grids in front along the current traversal direction, execute the turning strategy according to the algorithm rules. The turning priority rule of the traversal algorithm is up, left, right, down. The specific method for searching the next grid is to query the grids above, below, left, and right of the current point in turn, remove the obstacles and traversed points, and take the first qualified grid as the next waypoint of the operation boat;

[0017] Step S34: If no point meets the turning condition in step S33, it means that the traversal algorithm has fallen into a dead zone. At this time, it is necessary to use the improved A* algorithm to search for the nearest unvisited feasible point, obtain the trajectory from the dead zone point to the nearest feasible point, and then the workboat reaches the target feasible point along the trajectory. During this process, the workboat does not perform operations.

[0018] Further, in step S34, using the improved A* algorithm includes the following steps:

[0019] Step S41: First, store the points searched by the traditional A* algorithm into the LIST list.

[0020] Step S42: Take the first node as the starting point and connect the starting point with the next node. If the connection does not pass through an obstacle, this node is used as an alternative node, and continue to judge whether the next one meets the alternative node until a node that does not meet the condition is encountered.

[0021] Step S43: Set the nearest alternative node as the next node of the starting point, delete the intermediate nodes, and update the LIST list.

[0022] Step S44: Move the starting point backward by one node, and repeat steps S42, S43, and S44 until all nodes complete this optimization calculation.

[0023] Further, in step C, judging whether the remaining bait (liquid medicine) and battery power are insufficient and need to return to the pond dock for resupply includes the following steps:

[0024] Step S51: Through the planned operation trajectory, according to the weight of the bait (liquid medicine) actually loaded this time and the consumption of bait (liquid medicine) for each unit grid operation, calculate the remaining weight of the bait (liquid medicine) after each step of operation. The calculation method is:

[0025]

[0026] Among them, G is the total weight of the bait (liquid medicine) loaded this time, l i is the consumption of bait (liquid medicine) for each unit grid operation, G r (k) is the remaining weight of the bait (liquid medicine) after the k-th step of operation. Let G r (k)=0, and calculate the total number of operation steps n when the bait (liquid medicine) of the workboat is exhausted.

[0027] Step S52: During the operation of the bait and medicine application boat, use the improved A* algorithm to calculate the return route with the current point as the return point for each step, and calculate the power safety value E s , E s The calculation method is:

[0028]

[0029] Among them is the single-step energy consumption of straight-line driving at the j-th step during the return journey, L cj is the single-step energy consumption coefficient of straight-line driving at the j-th step during the return journey, v is the speed of the ship at this moment, G0 is the weight of the hull is the weight of the remaining bait (liquid medicine) at the k-th step of the operation; is the single-step energy consumption of turning driving at the j-th step during the return journey, T cj is the single-step energy consumption coefficient of turning driving at the j-th step during the return journey, v t is the speed of the ship when entering the bend, θ is the turning angle of the ship, p is the safety power margin coefficient, m is the maximum number of steps during the return journey;

[0030] Step S53: Determine whether the weight of the remaining bait (liquid medicine) is zero at this time or whether the current remaining power is less than or equal to the power safety value E s , if satisfied, mark this point as the return point G1 and return to the dock for resupply; if not satisfied, continue the operation.

[0031] Furthermore, in the said step D, after the operation ship completes resupply, it automatically plans the optimal endurance route and operation trajectory, including the following steps:

[0032] Step S61: Through the method described in step S51, calculate the total number of steps of this operation, predict the return point G2 of this operation according to the full-coverage traversal trajectory, and use G1 and G2 recorded in step S53 as the endurance points of this operation respectively, and calculate the energy consumption E cG1 、E cG2 for the loaded bait (liquid medicine) to endure to this operation endurance point. The calculation method is:

[0033]

[0034] Among them, L ci is the single-step energy consumption coefficient of straight-line driving at the i-th step during endurance, v is the speed of the ship at this moment, G0 is the weight of the hull, G is the weight of the loaded bait (liquid medicine), T ci is the single-step energy consumption coefficient of turning driving at the i-th step during endurance, v t is the speed of the ship when entering the bend, θ is the turning angle, q is the maximum number of steps during endurance;

[0035] Then, use G1 and G2 as the endurance points of this operation respectively, and calculate the energy consumption E mG1 、E mG2 when the bait and medicine application ship returns after completing this operation. The calculation method is:

[0036]

[0037] Among them, L cj is the single-step energy consumption coefficient of straight-line driving at the j-th step during the return journey after the end of this operation. v is the current speed of the ship, G0 is the weight of the hull, and T cj is the single-step energy consumption coefficient of turning driving at the j-th step during the return journey. v t is the speed of the ship when entering the bend, θ is the turning angle of the ship, and r is the maximum number of steps during the return journey;

[0038] Step S62: Calculate the sum of the return journey endurance energy consumptions E cG1 +E mG1 and E cG2 +E mG2 respectively with G1 and G2 as the endurance points of this operation, and select the point with the smaller energy consumption as the endurance point;

[0039] Step S63: If G1 is selected as the endurance point of this operation, then use G2 as the preset end point of this operation to generate the operation trajectory of this operation; if G2 is selected as the endurance point of this operation, then use G1 as the preset end point of this operation to generate the operation trajectory of this operation.

[0040] is a schematic diagram of converting longitude and latitude coordinates to plane coordinates according to the present invention

[0041] Figure 1 is a schematic diagram of the full-coverage algorithm rule according to the present invention

[0042] Figure 2 is the principle diagram of the improved A* algorithm according to the present invention

[0043] Figure 3 is a schematic diagram of the optimized endurance strategy according to the present invention

[0044] Figure 4 ​​

[0045] Figure 5 Flow chart of the method of the present invention Specific embodiments

[0046] A method for trajectory planning and efficient autonomous return and endurance of an aquaculture feeding and medicating ship for full pond coverage operation. The specific implementation of the present invention will be further described below with reference to the accompanying drawings.

[0047] This system is divided into two major modules: a full coverage path planning module and a return and endurance planning module.

[0048] Environmental modeling: Use the on-board GPS / BEIDOU positioning system to mark points, record the water area boundary and obstacle position information, convert this longitude and latitude position information into plane coordinates, and specify the starting point and dock supply point positions by the operator of the operation ship on the map.

[0049] The specific method for converting longitude and latitude coordinates into plane coordinates X and Y is as follows:[[]]

[0050]

[0051] Y = (lat - lat0) * R * π / 180

[0052] In the formula, lat and long are longitude and latitude coordinates, lat0 and long0 are the longitude and latitude coordinates of the origin of the plane X and Y axes (specified by the user), R is the radius of the earth, in this example, R is taken as 63713930 dm, and π is taken as 3.14159265358979323846. As Figure 1 shown, the positive and negative of the converted plane coordinate X correspond to the east and west of the geographical location, and the positive and negative of the Y axis correspond to the north and south of the geographical location.

[0053] As Figure 5 , separate the traversal coverage range and collision detection. Determine the basic grid size based on the hull size, safety distance, and operation width of the ship, and determine the operation grid size based on the operation width. The method includes the following steps:

[0054] Step S21: First, take the larger value d1 of the ship length and ship width as the side length of the basic grid;

[0055] Step S22: Calculate the ratio of the operation width w to d1, and take the rounded-down value as a. Determine that if a is odd, the ratio b of the operation grid to the basic grid side length is b = a; if a is even, the ratio b of the operation grid to the basic grid side length is b = a - 1; then adjust the basic grid side length to d = w / b in combination with the safety distance to establish a grid map.

[0056] The present invention separates the traversal coverage and collision detection in the traditional traversal algorithm in combination with the actual working mode of the workboat, solves the problem that the traversal algorithm cannot search in narrow channels, and improves the efficiency of the traversal algorithm. As Figure 2 As shown in (a), P is the workboat and S is the covered work area. In the embodiment, the length and width of the workboat are 2×2 m, and the resolution d1×d1 of the basic grid map is taken as 2×2 m. If the working width of the workboat is 14 m, 14 / 2 = 7, and rounding down to an odd number does not require adjusting d1; if the working width of the boat is 16 m, 16 / 2 = 8, and the result rounded down to an even number 8, then the basic grid resolution needs to be adjusted to 16 / (8 - 1) and rounded to two decimal places as 2.29×2.29 m.

[0057] After that, the full-coverage return traversal method for optimizing the traversal range is used to plan the full-coverage operation trajectory, and the method includes the following steps:

[0058] Step S31: Starting from the starting point as shown in Figure 2 (b), determine the traversal direction, start traversing in the direction parallel to the long side of the grid map, and start traversing at a distance of c unit grid distances from the boundary, where c = (b - 1) / 2 = 3;

[0059] Step S32: Count the covered area. The covered area is perpendicular to the traversal direction. Add the three grids on the left and right sides of the workboat and the grid where it is located to the traversed list HLIST;

[0060] Step S33: Detect the obstacle or boundary situation in front of the current working direction of the workboat. If one of the three grids in front along the current traversal direction is an obstacle, boundary, or traversed grid, the turning strategy is executed according to the algorithm rules. The turning priority rule of the traversal algorithm is up, left, right, down. The specific method for searching the next grid is to query the grids above, below, left, and right of the current point in turn and remove the obstacles, boundaries, and traversed points, and take the first qualified grid as the next waypoint of the workboat;

[0061] Step S34: If no point meets the turning condition in Step S33, it means that the traversal algorithm has fallen into a dead zone. At this time, the improved A* algorithm needs to be used to search for the nearest uncovered feasible point, obtain the trajectory from the dead zone point to the nearest feasible point, and then the workboat reaches the target feasible point along the trajectory. The workboat does not perform operations during this process.

[0062] The specific steps for the improved A* algorithm to search for the nearest uncovered feasible point include:

[0063] Step S41: First, store the points searched by the traditional A* algorithm into the LIST list;

[0064] Step S42: Take the first node as the starting point and connect it to the next node. If the connection line does not pass through an obstacle, this node is used as an alternative node, and continue to determine whether the next node meets the requirements of an alternative node until a node that does not meet the requirements is encountered;

[0065] Step S43: Set the nearest alternative node as the next node of the starting point, delete the intermediate nodes, and update the LIST list;

[0066] Step S44: Move the starting point backward by one node, and repeat steps S42, S43, and S44 until all nodes complete this optimization calculation.

[0067] As Figure 3 shown in (a), among the three nodes obtained by the search, compared with the other two points, the connection line distance between (4, 2) and the starting point is the longest, and it meets the condition of not crossing obstacles. Therefore, the workboat directly sails to the (4, 2) node. As Figure 3 shown in (b), update the nodes in TEMP, and repeat the above steps again with the last updated node as the starting point until all nodes are updated.

[0068] The improvement of the present invention on the A* algorithm reduces the number of turns of the path planned by the A* algorithm, increases the turning angle of the corner, which is more conducive to the path tracking of the workboat, and also reduces the path length and the number of nodes.

[0069] After the full-coverage path is generated through the above steps, the workboat starts to execute the corresponding operation tasks according to the planned path. Before the operation is completed, it real-time detects the remaining amount of bait (liquid medicine) and battery power of the aquaculture feeding and medicine application boat. When the stock of bait (liquid medicine) on the workboat drops to 0% or the power of the workboat drops to the safe power required for returning, record the current position G1 of the workboat as the return point, and send a return prompt to the mobile terminal through the 4G module to notify the user that the workboat starts to return and the reason for returning. Use the improved A* algorithm to search for the return path from the return point G1 to the dock S. After the search is completed, the workboat returns to the dock along the return path and waits for the user to replenish.

[0070] The specific steps to determine the return point are as follows:

[0071] Through the planned operation trajectory, according to the weight of the bait (liquid medicine) actually loaded this time and the consumption of bait (liquid medicine) for each unit grid operation, calculate the remaining weight of the bait (liquid medicine) after each step of operation. The calculation method is:

[0072]

[0073] where G is the total weight of the bait (liquid medicine) loaded this time, l i is the consumption of bait (liquid medicine) for each unit grid operation, G r(k) is the remaining weight of bait (liquid medicine) at the k-th step of the operation. Let G r (k)=0, and calculate the total number of operation steps n when the bait (liquid medicine) on the operation ship is exhausted;

[0074] During the operation of the bait and medicine application ship, the improved A* algorithm is used to calculate the return route with the current point as the return point at each step, and calculate the power safety value E required to return from the current point (the k-th step of the operation) s , E s The calculation method is:

[0075]

[0076] Among them is the single-step energy consumption of straight-line driving at the j-th step during return, L cj is the single-step energy consumption coefficient of straight-line driving at the j-th step during return, v is the speed of the ship at this moment, G0 is the weight of the hull, is the remaining weight of bait (liquid medicine) at the k-th step of the operation; is the single-step energy consumption of turning driving at the j-th step during return, T cj is the single-step energy consumption coefficient of turning driving at the j-th step during return, v t is the speed of the ship when entering the bend, θ is the turning angle of the ship, p is the safety power margin coefficient, and m is the maximum number of steps during return. If the operation ship is to return smoothly, the remaining energy should be greater than the power safety value E s . The power margin coefficient is taken as 1.2, and judge whether the remaining weight of bait (liquid medicine) is zero at this time or whether the current remaining power is less than or equal to the power safety value E s , if it is satisfied, select this point as the return point, record the return point G1, and return to the dock for resupply; if it is not satisfied, continue the operation;

[0077] After the resupply is completed, the user sends a battery life command through the mobile software, and the operation ship starts to plan the battery life path according to the battery life strategy.

[0078] The specific steps of the battery life strategy are:

[0079] As Figure 4 shown, through the planned operation trajectory, according to the weight of the bait (liquid medicine) actually loaded this time and the bait (liquid medicine) consumption of each unit grid operation, calculate the total number of operation steps n when the bait (liquid medicine) on the operation ship is exhausted, predict the return point G2 of this operation according to the full-coverage traversal trajectory, and respectively use G1 and G2 as the battery life points of this operation according to the recorded return point G1 of the previous operation, and calculate the energy consumption E cG1 , E cG2 required to continue the battery life to the battery life point of this operation. The calculation method is:

[0080]

[0081] Among them, L ci is the single-step energy consumption coefficient of straight-line driving at the i-th step during endurance, v is the current speed of the ship, G0 is the weight of the hull, G is the weight of the loaded bait (liquid medicine), and T ci is the single-step energy consumption coefficient of turning driving at the i-th step during endurance, v t is the speed of the ship when entering the bend, θ is the turning angle of the ship, and q is the maximum number of steps during endurance;

[0082] Next, taking G1 and G2 as the endurance points of this operation respectively, calculate the energy consumption E mG1 、E mG2 when the bait and medicine spraying ship returns after completing this operation. The calculation method is as follows:

[0083]

[0084] Among them, L cj is the single-step energy consumption coefficient of straight-line driving at the j-th step when returning after the end of this operation, v is the current speed of the ship, G0 is the weight of the hull, and T cj is the single-step energy consumption coefficient of turning driving at the j-th step when returning, v t is the speed of the ship when entering the bend, θ is the turning angle of the ship, and r is the maximum number of steps when returning;

[0085] Calculate the sum of the return endurance energy consumptions E cG1 +E mG1 、E cG2 +E mG2 respectively with G1 and G2 as the endurance points of this operation. Select the point with the smaller energy consumption as the endurance point. In this embodiment, E cG1 +E mG1 >E cG2 +E mG2 Therefore, select G2 as the endurance point of this operation, and use G1 as the preset end point of this operation to generate the trajectory of this operation.

[0086] Repeat the above method until all the operation trajectories are traversed.

[0087] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0088] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for trajectory planning and efficient autonomous return and endurance of an aquaculture feeding and drug application ship for full-coverage operation in a pond, characterized in that, The method includes the following steps: A. Collect the longitude and latitude coordinates of the pond vertices and obstacles, and convert the longitude and latitude coordinates into plane coordinates. B. Separate the traversal coverage range and collision detection. Determine the basic grid size based on the hull size, safety distance, and operation width, determine the operation grid size based on the operation width, establish a pond grid map, and use the full-coverage return traversal method with an optimized traversal range to generate a variable operation trajectory for the full coverage of the feeding and drug application ship according to the required feeding and drug application density in each area. C. During the operation of the feeding and drug application ship according to the set trajectory, continuously detect the remaining amount of bait or liquid medicine and battery power of the aquaculture feeding and drug application ship. First, judge whether all operation tasks have been completed. If so, it is necessary to automatically plan the optimal return route and return to the pond dock autonomously, and the operation ends. If all tasks have not been completed, then judge whether the remaining bait or liquid medicine and battery power are insufficient and need to return to the pond dock for replenishment. If sufficient, continue normal operation. If insufficient, it is necessary to record the return point, automatically plan the optimal return route, return to the dock autonomously, and perform corresponding replenishment. D. After the operation ship completes the replenishment, automatically plan the optimal endurance route and operation trajectory, continue the feeding and drug application operation, and jump to step C. In step B, the basic grid size is determined based on the hull size, safety distance, and operation width, and the operation grid size is determined based on the operation width. The method includes the following steps: Step S21: First, use the larger value d1 of the ship length and ship width as the side length of the basic grid. Step S22: Calculate the ratio of the operation width w to d1, and take the value after rounding down as a. Judge that if a is odd, the ratio b of the operation grid to the basic grid side length is a; if a is even, the ratio b of the operation grid to the basic grid side length is a - 1. Then, adjust the basic grid side length to d = w / b in combination with the safety distance. In step B, the full-coverage return traversal method with an optimized traversal range is used. The method includes the following steps: Step S31: Start from the starting point, determine the traversal direction, start traversing in the direction parallel to the long side of the grid map, and start traversing at a distance of c unit grids from the boundary, where c = (b - 1) / 2. Step S32: Count the covered area. The covered area is perpendicular to the traversal direction. Add c grids on the left and right sides of the operation ship and the grid where it is located to the traversed list HLIST. Step S33: Detect the obstacles and boundary conditions in front of the operation direction of the current operation ship. If there is an obstacle, boundary, or traversed grid in one of the c grids in front along the current traversal direction, execute the turning strategy according to the algorithm rules. The turning priority rule of the traversal algorithm is up, left, right, down. The specific method for searching the next grid is to query the grids above, below, left, and right of the current point in turn and remove the obstacles, boundaries, and traversed points, and take the first qualified grid as the next waypoint of the operation ship. Step S34: If no point meets the turning condition in step S33, it means that the traversal algorithm has fallen into a dead zone.

2. The pond full-coverage operation trajectory planning and efficient autonomous return and endurance method for the aquaculture feeding and drug application ship according to claim 1, characterized in that, In step S34, if no point meeting the turning condition is found in step S33, it means that the traversal algorithm has fallen into a dead zone. At this time, it is necessary to use the improved A* algorithm to search for the nearest unvisited feasible point, obtain the trajectory from the dead zone point to the nearest feasible point, and then the workboat reaches the target feasible point along the trajectory. During this process, the workboat does not perform operations. The use of the improved A* algorithm includes the following steps: Step S41: First, store the points searched by the traditional A* algorithm into the LIST list; Step S42: Take the first node as the starting point and connect the starting point with the next node. If the connection does not pass through an obstacle, this node is used as an alternative node, and continue to judge whether the next one meets the alternative node until an unqualified node is encountered; Step S43: Set the nearest alternative node as the next node of the starting point, delete the intermediate nodes, and update the LIST list; Step S44: Move the starting point backward by one node, and repeat steps S42, S43, and S44 until all nodes complete this optimization calculation.

3. A method for pond full-coverage operation trajectory planning and efficient autonomous return and endurance of an aquaculture feeding and drug application ship according to claim 2, characterized in that, In step C, it is judged whether the remaining bait or liquid medicine and battery power are insufficient and it is necessary to return to the pond dock for resupply, including the following steps: Step S51: Through the planned operation trajectory, calculate the remaining weight of the bait or liquid medicine after each step of operation according to the weight of the bait or liquid medicine actually loaded this time and the consumption of the bait or liquid medicine for each unit grid operation. The calculation method is: Among them, G is the total weight of the bait or liquid medicine loaded this time, and l i is the consumption of bait or liquid medicine for each unit grid operation, G r (k) is the remaining weight of bait or liquid medicine at the k-th step of the operation. Let G r (k) = 0, and calculate the total number of operation steps n when the bait or liquid medicine on the operation ship is exhausted; Step S52: During the operation of the bait and medicine application ship, use the improved A* algorithm to calculate the return route with the current point as the return point at each step, and calculate the power safety value E required to return from the current point (the k-th step of operation). s , E s The calculation method is as follows: Among which L cj v(G0 + G r(k-1) ) is the single-step energy consumption for straight-line driving at the j-th step during the return journey, L cj is the single-step energy consumption coefficient for straight-line driving at the j-th step during the return journey, v is the speed of the ship at this moment, G0 is the weight of the hull, G r(k-1) is the weight of the remaining bait or liquid medicine at the k-th step of the operation; T cj v t θ(G0 + G r(k-1) ) is the single-step energy consumption for turning driving at the j-th step during the return journey, T cj is the single-step energy consumption coefficient for turning driving at the j-th step during the return journey, v t is the speed of the ship when entering the turn, θ is the turning angle of the ship, p is the safety power margin coefficient, and m is the maximum number of steps during the return journey; Step S53: Determine whether the remaining weight of the bait or liquid medicine is zero at this time or whether the current remaining power is less than or equal to the power safety value E s , if satisfied, mark this point as the return point G1 and return to the dock for resupply; if not satisfied, continue the operation.

4. A method for pond full-coverage operation trajectory planning and efficient autonomous return and endurance of an aquaculture feeding and drug application ship according to claim 1, characterized in that In step D, after the workboat completes resupply, it automatically plans the optimal endurance route and operation trajectory, including the following steps: Step S61: Calculate the total number of steps of this operation by the method described in step S51. Predict the return point G2 of this operation according to the full-coverage traversal trajectory. Take G1 and G2, which are the return points of the previous operation recorded in step S53, as the endurance points of this operation respectively, and calculate the energy consumption E for loading bait or liquid medicine to reach the endurance points of this operation cG1 , E cG2 , and the calculation method is as follows: Among them, L ci is the single-step energy consumption coefficient for straight-line driving in the i-th step during endurance, v is the current speed of the ship, G0 is the weight of the hull, G is the weight of the loaded bait or liquid medicine, T ci is the single-step energy consumption coefficient for turning driving in the i-th step during endurance, v t is the speed when the ship enters the bend, θ is the turning angle of the ship, and q is the maximum number of steps during endurance; Next, taking G1 and G2 as the endurance points of this operation respectively, calculate the energy consumption E when the bait and medicine application boat returns after completing this operation mG1 and E mG2 . The calculation method is as follows: Among them, L cj is the single-step energy consumption coefficient for straight-line driving at the jth step during the return journey. v is the current speed of the ship, G0 is the weight of the hull, T cj is the single-step energy consumption coefficient for turning driving at the jth step during the return journey. v t is the speed when the ship enters the turn, θ is the turning angle of the ship, and r is the maximum number of steps during the return journey; Step S62: Calculate the sum of the return flight endurance energy consumptions E cG1 +E mG1 、E cG2 +E mG2 respectively, with G1 and G2 as the endurance points for this operation, and select the point with the smaller energy consumption as the endurance point; Step S63: If G1 is selected as the endurance point for this operation, then set G2 as the preset end point for this operation and generate the operation trajectory for this operation; if G2 is selected as the endurance point for this operation, then set G1 as the preset end point for this operation and generate the operation trajectory for this operation.

Images