CN109489672B - Energy-saving A star path planning method considering influence of ocean current and unmanned ship dynamics - Google Patents
Energy-saving A star path planning method considering influence of ocean current and unmanned ship dynamics Download PDFInfo
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Abstract
The invention provides an energy-saving A star path planning method considering the influence of ocean current and unmanned ship dynamics, which comprises the following steps: (1) acquiring global chart information and gridding; (2) acquiring the position information of a starting point and an end point of the unmanned ship; (3) setting the current position as a starting position, and creating an OPEN and a CLOSD table; (4) calculating the navigational speed pile of the unmanned ship under the influence of ocean currents; (5) storing the current position into an OPEN table; (6) whether the unmanned ship at the current position can run in eight directions around is sequentially judged. On the basis of a traditional A star path planning algorithm, an energy consumption heuristic function E _ heurstic considering ocean current influence is designed by combining an unmanned ship dynamics model under the influence of ocean current, dynamic adjustment of algorithm energy-saving efficiency is achieved by adjusting the weight of the function, and technical support is provided for long-time work of the unmanned ship on the sea.
Description
Technical Field
The invention relates to the field of global path planning of unmanned surface vehicles, in particular to an energy-saving A star path planning method considering the influence of ocean currents and the dynamics of unmanned surface vehicles.
Background
In the 21 st century, people pay more and more attention to the exploration of oceans, and unmanned boats serve as an intelligent unmanned system on the sea and are widely applied to civil use and military use. With the rapid development of scientific technology, unmanned ship technology is also continuously developing and advancing, however, more enhanced functions correspond to higher energy expenditure, and how to improve the endurance and working time of unmanned ships on the sea under the condition of limited energy becomes one of the focus problems of people.
In the literature, "research on fast path planning of underwater robots in marine environment", people in Wang Lei and the like take energy conservation as a main target of global path planning, analyze the motion characteristics of the underwater robots when influenced by ocean currents, provide a planning scheme comprehensively considering two factors of path length and ocean currents, respectively perform global path planning with shortest distance and global path planning with least energy consumption aiming at a tangent diagram environment model of the intelligent underwater robot, and verify in a simulation system. However, in order to realize rapid planning, the method does not combine a dynamic model of a planning object under the influence of ocean currents, and the accuracy of the obtained path for saving energy is difficult to ensure; and the path planning based on the tangent diagram can not ensure that the result is the optimal energy-saving path, and the unmanned ship works on the water surface, the sea current is much stronger than that of the deep sea, and the energy-saving path needs to be searched more comprehensively to ensure the optimal energy-saving effect, so the method can not be directly applied to the energy-saving path planning of the unmanned ship.
The patent application entitled "a method for planning unmanned surface vehicle path based on neighborhood intelligent water drop algorithm" in 2016, 3, 9, publication number CN103744428B improves the problems of stagnation of the method and slow convergence rate caused by the fact that the basic intelligent water drop method easily falls into the local optimal solution, so as to obtain the neighborhood intelligent water drop method, thereby avoiding premature aging caused by the fact that the method falls into the local optimal solution, and improving the convergence rate of the optimization of the method. However, the method is not improved on the aspect of energy conservation, and the planned path cannot save energy for the unmanned ship, so that the target of energy-saving path planning is not met.
The patent application entitled "an energy-saving real-time dynamic path planning method suitable for intelligent networked automobiles" on publication No. CN107389076A in 24/11/2017 can search a travel path with the shortest theoretical travel time in the whole course in a three-dimensional space-time network, can obviously reduce the energy consumption of vehicle driving, and achieves the goal of energy-saving travel. However, the motion characteristics and the working environment of the automobile and the unmanned ship are greatly different, and the method does not consider the influence of the environment on a planning object, so that the method can not be applied to energy-saving path planning of the unmanned ship.
The unmanned ship energy-saving path planning method takes the purposes of saving self energy of the unmanned ship as much as possible and realizing the maximum endurance as the final goal, considers the influence of ocean current on the motion trail of the unmanned ship on the basis of the classic A star algorithm, combines an unmanned ship dynamics model under the action of the ocean current, designs an unmanned ship energy consumption heuristic function, realizes dynamic adjustment on the energy-saving efficiency of a planned path by adjusting the weight of the unmanned ship energy consumption heuristic function, completes the energy-saving path planning task of the unmanned ship under the influence of the ocean current and obtains good effect through a simulation test.
Disclosure of Invention
The invention aims to provide an energy-saving A star path planning method considering the influence of ocean current and unmanned ship dynamics. Based on the A star algorithm and based on an unmanned ship dynamics model under the action of ocean current, an unmanned ship energy consumption heuristic function E _ heurstic considering ocean current is designed, the energy-saving efficiency of the energy-saving planning algorithm can be dynamically adjusted, the energy of the unmanned ship is effectively saved, and the cruising ability of the unmanned ship is greatly improved.
The invention specifically comprises the following steps:
(1) acquiring global chart information and global ocean current information, setting a gridding resolution n, and gridding the chart and the ocean current graph to form n x n grid charts and grid ocean current graphs;
(2) the barrier value in the grid chart is Inf, the others are 1, and the flow velocity U of the ocean current in each unit grid is included in the grid chartcurrent(x, y) and flow direction Dcurrent(x,y)；
(3) Obtaining the starting position (x) of the unmanned shipstart,ystart) And end position (x)goal,ygoal) Information, and order the current position (x) of the unmanned shipusv，yusv) Is equal to (x)start,ystart) Creating an OPEN table and a CLOSED table;
(4) u _ stack _ usv represents the unmanned ship speed required to be provided by the engine when each unit grid unmanned ship on the N x N map runs towards the eight directions of E, W, S, N, SE, SW, NW and NE under the action of ocean current in sequence from the lowest layer to the uppermost layer; calculating a speed stack U _ stack _ usv of the unmanned ship under the action of ocean current;
(5) will (x)usv，yusv) Storing the data into an OPEN table;
(6) judging the current position (x) of the unmanned shipusv,yusv) Around the ith survey position (x)i,yi) If the Inf is not Inf, turning to the step (7) if the Inf is Inf, and otherwise, turning to the step (8);
(7) judging whether i is equal to 8, if so, turning to the step (18), otherwise, enabling i to be i +1 and returning to the step (6);
(8) according to (x)usv，yusv) And (x)i,yi) Calculating the running direction f _ c and the distance d _ c of the unmanned ship according to the relative positions;
(9) according to f _ c and (x)usv，yusv) Selecting the corresponding unmanned ship speed U _ c in U _ stack _ usv;
(10) according to U _ c, UgroundAnd d _ c, calculating the unmanned ship from (x) by using the unmanned ship dynamic model under the action of ocean currentusv，yusv) To (x)i,yi) Consumed energy e _ cost (i);
(11) let sofar _ cost be e _ cost (i) + sofar _ cost, so that sofar _ cost is used as the starting point for storage (x)start,ystart) To (x)i,yi) The required energy, initial value is 0;
(12) calling the heuristic function E _ predicate, evaluating the Slave (x)i,yi) To (x)goal,ygoal) The energy e _ regenerative (i) to be consumed;
(13) judgment (x)i,yi) If it does not belong to either the CLOSED table or the OPEN table, then (x)i,yi) Adding OPEN table, that is, enabling OPEN (x)i,yi) (1) equal to sofar _ cost, OPEN (x)i,yi) (2) equals e _ hesistic (i) and go to step (17), otherwise go to step (14);
(14) judgment (x)i,yi) If the list belongs to the OPEN list, turning to the step (15) if yes, and turning to the step (16) if not;
(15) judging whether the sofar _ cost is less than OPEN (x)i,yi) (1) is (x)i,yi) Update OPEN (x)i,yi) Turning to the step (17) according to the corresponding value;
(16) judging whether the sofar _ cost is less than CLOSED (x)i,yi) If yes, command CLOSED (x)i,yi) Equal to sofar _ cost, go to step (17);
(17) calculating e _ function (i) ═ α · costchart (x)i,yi) + β. e _ heuristic (i), where α, β represent the weight parameters of the cost value and heuristic value, respectively, α>>Beta, the higher the energy saving but the lower the programming speed; otherwise, turning to the step (7) if the planning speed is higher and the energy saving is lower;
(18) the current position (x) of the unmanned shipusv，yusv) Deleting from the OPEN table, and adding a CLOSED table;
(19) (x) corresponding to the minimum value in { e _ function }i,yi) Order (x)usv，yusv) Is equal to (x)i,yi)；
(20) Judgment (x)usv，yusv) Whether or not to be equal to (x)goal,ygoal) If yes, finishing the end point planning, otherwise, returning to the step (5);
the step (4) specifically comprises the following steps:
(4-1) dividing the current velocity U in the n x n gridcurrent(x, y) and flow direction Dcurrent(x, y) decomposing to obtain a list U of n x n ocean current velocities in the x directioncurrentXAnd y-direction ocean current velocity list UcurrentY；
(4-2) pointing to the four directions (east, south, west, north and east) respectivelyNorth, northwest, southeast, southwest) unmanned boat speed to ground Uground(the user self-defines the size according to the actual situation) to obtain an 8 x 1 x-direction ground speed list UgroundXAnd y-direction ground speed list UgroundY；
(4-3) according to UcurrentX、UcurrentY、UgroundXAnd UgroundYRespectively calculating x-direction three-dimensional unmanned ship speed stacks U of n x n 8usvXAnd Y-direction three-dimensional unmanned ship speed stack UusvY；
(4-4) according to UusvXAnd UusvYAnd calculating a three-dimensional unmanned ship speed stack U _ stack _ usv of n x 8 under the influence of the ocean current by pythagorean theorem.
The step (12) specifically comprises:
(12-1) calculating a current survey position (x)i,yi) To the end point (x)goal，ygoal) Manhattan diagonal distance heuristic _ d and straight distance heuristic _ s;
(12-2) calculating (x)i,yi) And (x)goal，ygoal) Relative position angle f _ h therebetween;
(12-3) according to (x)i,yi) F _ h, heuristic _ d, and heuristic _ s select all unmanned boat speeds { U _ h } on the corresponding heuristic path heuristic in U _ stack _ usv;
(12-4) determining if heuristic _ d is equal to 0, if so, using { U _ h }, UgroundAnd heuristic _ s calculation
Obtaining an energy estimate e _ hetic, otherwise proceeding to step (12-5), wherein
Representing all drone speeds on the heuristic path heuristic;
(12-5) according to (x)i,yi)、(xgoal，ygoal)、{U_h}、UgroundHeuristic _ s and heuristic _ d, calculating
Wherein
Representing unmanned boat speed on all diagonal paths,
representing the speeds of the unmanned ship on all straight paths, and the epsilon is the same as the step (10);
the unmanned ship dynamics model under the action of the ocean current in the step (10) specifically comprises the following steps:
the unmanned boat is driven by the following components (x)usv，yusv) To (x)i,yi) The consumed energy e _ cost (i) is calculated by the following formula:
e_cost＝ε·|U_c3/Uground|·d_c；
where epsilon is the towing force coefficient of the unmanned boat.
Compared with the prior art, the invention has the beneficial effects that:
1. aiming at the problem of planning the energy-saving path of the unmanned ship under the influence of ocean currents, the invention provides a speed stack U _ stack _ usv of the unmanned ship under the influence of ocean currents, so that the state of the unmanned ship in each unit grid under the action of ocean currents can be estimated, and an independent variable solution space is provided for calculating the actual energy consumption e _ cost and the heuristic energy consumption e _ heading of the unmanned ship in the energy-saving planning process;
2. based on the A star algorithm, an energy consumption heuristic function E _ heurstic considering ocean current is designed according to an unmanned ship dynamic model in an ocean current state, dynamic adjustment of energy-saving efficiency of an energy-saving planning algorithm is achieved through adjustment of a weight of the function, unmanned ship energy-saving path planning is effectively completed through simulation verification, and cruising ability of the unmanned ship on the sea is improved.
Drawings
FIG. 1 is a main flow chart of an energy-saving A star path planning method considering the coupling influence of ocean currents and unmanned ship dynamics;
FIG. 2 is a diagram of U _ stack _ usv structure;
FIG. 3 is a flow chart of the calculation of unmanned boat velocity stack U _ stack _ usv under the influence of ocean currents;
FIG. 4 is a flow chart of a calculation of an unmanned ship energy consumption heuristic function E _ heading that considers ocean currents.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings:
with reference to fig. 1, the method comprises the following steps:
based on the A star algorithm and based on an unmanned ship dynamics model under the action of ocean current, an unmanned ship energy consumption heuristic function E _ heurstic considering ocean current is designed, the energy-saving efficiency of the energy-saving planning algorithm can be dynamically adjusted, the energy of the unmanned ship is effectively saved, and the cruising ability of the unmanned ship is greatly improved.
The invention mainly comprises the following steps:
(1) acquiring global chart information and global ocean current information, setting a gridding resolution n, and gridding the chart and the ocean current graph to form n x n grid charts and grid ocean current graphs;
(2) setting the barrier value in the grid chart to Inf, namely infinite, and setting the other to 1, indicates that the movement of the still water surface from one grid to the adjacent grid needs to consume 1 unit of energy, and the grid chart contains the flow rate U of the ocean current in each unit gridcurrent(x, y) and flow direction Dcurrent(x,y)；
(3) Obtaining the starting position (x) of the unmanned shipstart,ystart) And end position (x)goal,ygoal) Information, and order the current position (x) of the unmanned shipusv，yusv) Is equal to (x)start,ystart) Creating an OPEN table and a CLOSED table;
(4) calculating a speed stack U _ stack _ usv of the unmanned ship under the action of ocean current;
(4-1) dividing the current velocity U in the n x n gridcurrent(x, y) and flow direction Dcurrent(x, y) decomposing to obtain a list U of n x n ocean current velocities in the x directioncurrentXAnd y-direction ocean current velocity list UcurrentY；
(4-2) pointing to the four directions (east, south, west, north, northeast, northwest and east respectivelySouth, southwest) unmanned boat ground speed Uground(the user self-defines the size according to the actual situation) to obtain an 8 x 1 x-direction ground speed list UgroundXAnd y-direction ground speed list UgroundY；
(4-3) according to UcurrentX、UcurrentY、UgroundXAnd UgroundYRespectively calculating x-direction three-dimensional unmanned ship speed stacks U of n x n 8usvXAnd Y-direction three-dimensional unmanned ship speed stack UusvY；
(4-4) according to UusvXAnd UusvYCalculating a three-dimensional unmanned ship speed stack U _ stack _ usv of n x 8 under the influence of ocean current by pythagorean theorem;
(5) will (x)usv，yusv) Storing the data into an OPEN table;
(6) judging the current position (x) of the unmanned shipusv,yusv) Around the ith survey position (x)i,yi) If the Inf is not Inf, turning to the step (7) if the Inf is Inf, and otherwise, turning to the step (8);
(7) judging whether i is equal to 8, if so, turning to the step (18), otherwise, enabling i to be i +1 and returning to the step (6);
(8) according to (x)usv，yusv) And (x)i,yi) Calculating the running direction f _ c and the distance d _ c of the unmanned ship according to the relative positions;
(9) according to f _ c and (x)usv，yusv) Selecting the corresponding unmanned ship speed U _ c in U _ stack _ usv;
(10) according to U _ c, UgroundD _ c, using the unmanned ship dynamic model e _ cost ∈ · | U _ c under the action of ocean current3/Uground|·d cCalculating unmanned ship from (x)usv，yusv) To (x)i,yi) The consumed energy e _ cost (i), wherein epsilon is the drag coefficient of the unmanned boat and is related to the shape and the draught of the boat body;
(11) let sofar _ cost be e _ cost (i) + sofar _ cost, so that sofar _ cost is used as the starting point for storage (x)start,ystart) To (x)i,yi) The required energy, initial value is 0;
(12) calling heuristic functionsE _ hesic, estimated from (x)i,yi) To (x)goal,ygoal) The energy e _ regenerative (i) to be consumed;
(12-1) calculating a current survey position (x)i,yi) To the end point (x)goal，ygoal) Manhattan diagonal distance heuristic _ d and straight distance heuristic _ s;
(12-2) calculating (x)i,yi) And (x)goal，ygoal) Relative position angle f _ h therebetween;
(12-3) according to (x)i,yi) F _ h, heiristic _ d, and heiristic _ s select all unmanned boat speeds { U _ h } on the corresponding heuristic path heiristic in U _ stack _ usv, e.g., when f _ h is 60 °, considered to be heading northeast, U _ stack _ usv should be selected in turn all speeds of the (x, x + 1.., x + heiristic) row (y, y + 1.., y + heiristic) column NE layer, wherein heiristic _ d + heiristic _ s;
(12-4) determining if heuristic _ d is equal to 0, if so, using { U _ h }, UgroundAnd heuristic _ s calculation
Obtaining an energy estimate e _ hetic, otherwise proceeding to step (12-5), wherein
Representing all drone speeds on the heuristic path heuristic;
(12-5) according to (x)i,yi)、(xgoal，ygoal)、{U_h}、UgroundHeuristic _ s and heuristic _ d, calculating
Wherein
Representing unmanned boat speed on all diagonal paths,
representing the speeds of the unmanned ship on all straight paths, and the epsilon is the same as the step (10);
(13) judgment (x)i,yi) If it does not belong to either the CLOSED table or the OPEN table, then (x)i,yi) Adding OPEN table, that is, enabling OPEN (x)i,yi) (1) equal to sofar _ cost, OPEN (x)i,yi) (2) equals e _ hesistic (i) and go to step (17), otherwise go to step (14);
(14) judgment (x)i,yi) If the list belongs to the OPEN list, turning to the step (15) if yes, and turning to the step (16) if not;
(15) judging whether the sofar _ cost is less than OPEN (x)i,yi) (1) is (x)i,yi) Update OPEN (x)i,yi) Turning to the step (17) according to the corresponding value;
(16) judging whether the sofar _ cost is less than CLOSED (x)i,yi) If yes, command CLOSED (x)i,yi) Equal to sofar _ cost, go to step (17);
(17) calculating e _ function (i) ═ α · costchart (x)i,yi) + β. e _ heuristic (i), where α, β represent the weight parameters of the cost value and heuristic value, respectively, α>>Beta, the higher the energy saving but the lower the programming speed; otherwise, turning to the step (7) if the planning speed is higher and the energy saving is lower;
(18) the current position (x) of the unmanned shipusv，yusv) Deleting from the OPEN table, and adding a CLOSED table;
(19) (x) corresponding to the minimum value in { e _ function }i,yi) Order (x)usv，yusv) Is equal to (x)i,yi)；
(20) Judgment (x)usv，yusv) Whether or not to be equal to (x)goal,ygoal) If yes, finishing the end point planning, otherwise, returning to the step (5);
the unmanned boat speed stack U _ stack _ usv is a core of the invention, and the following is a detailed description of U _ stack _ usv:
the structure of U _ stack _ usv is as shown in fig. 2, and represents in sequence from the lowest layer to the uppermost layer that unmanned boats in each unit grid on N × N map need the unmanned boat speed provided by the engine when traveling in eight directions, E (east), W (west), S (south), N (north), SE (south), SW (south), NW (north) and NE (north-east), under the action of ocean currents, so as to realize the estimation of unmanned boat speed under different conditions in the global map. With reference to fig. 3, the calculation steps of the unmanned ship speed stack U _ stack _ usv under the action of ocean currents are as follows:
(1) respectively calculating x-direction ocean current velocity list UcurrentXAnd y-direction ocean current velocity list UcurrentY；
(2) Respectively calculating x-direction ground speed list UgroundXAnd y-direction ground speed list UgroundY；
(3) Let i equal 1; (4) let j equal 1; (5) let k equal 1;
(6) respectively calculating speed of unmanned boat in x directionusvX(i，j，k)＝UgroundX(k)-UcurrentX(i, j), y-direction unmanned boat speed stack UusvY(i，j，k)＝UgroundY(k)-UcurrentY(i，j)；
(7) Judging whether k is equal to 8, if so, turning to the step (8), otherwise, turning to the step (6) if k is equal to k + 1;
(8) judging whether j is equal to n, if so, turning to the step (9), otherwise, turning to the step (5) if j is equal to j + 1;
(9) judging whether i is equal to n, if so, turning to the step (10), otherwise, turning to the step (4) if i is equal to i + 1;
(10) calculating unmanned boat speed stack U _ stack _ usv ═ U _ stack ═ (U)usvX 2+UusvY 2)0.5；
The unmanned ship energy consumption heuristic function E _ heurstic under the action of ocean current is the second core of the invention, and the following is a specific description about E _ heurstic:
with reference to FIG. 3, the steps of the E _ heading function are as follows:
(1) calculating from the current survey position (x)i,yi) To the end point (x)goal，ygoal) Manhattan diagonal distance heuristic _ d and straight distance heuristic _ s, where
heuristic_d＝min(abs(xi-xgoal),abs(yi-ygoal))
heuristic_s＝abs(xi-xgoal)+abs(yi-ygoal)-2×heuristic_d
(2) Calculating (x)i,yi) Relative position angle f _ h with the end point;
(3) selecting all unmanned ship speeds { U _ h } on a corresponding heuristic path heuristic in U _ stack _ usv, wherein heuristic is heuristic _ d + heuristic _ s;
(4) judging whether the heuristic _ d is equal to 0, if so, calculating
Otherwise, turning to the step (5);
(5) computing
The unmanned ship energy consumption heuristic function E _ heurstic considering ocean current is designed based on the A star algorithm and based on the unmanned ship dynamic model under the ocean current effect, the energy saving efficiency of the energy saving planning algorithm can be dynamically adjusted, the energy of the unmanned ship is effectively saved, and the cruising ability of the unmanned ship is greatly improved. Compared with the prior art, the beneficial effects are that:
1. aiming at the problem of planning the energy-saving path of the unmanned ship under the influence of ocean currents, the invention provides a speed stack U _ stack _ usv of the unmanned ship under the influence of ocean currents, so that the state of the unmanned ship in each unit grid under the action of ocean currents can be estimated, and an independent variable solution space is provided for calculating the actual energy consumption e _ cost and the heuristic energy consumption e _ heading of the unmanned ship in the energy-saving planning process;
2. based on the A star algorithm, an energy consumption heuristic function E _ heurstic considering ocean current is designed according to an unmanned ship dynamic model in an ocean current state, dynamic adjustment of energy-saving efficiency of an energy-saving planning algorithm is achieved through adjustment of a weight of the function, unmanned ship energy-saving path planning is effectively completed through simulation verification, and cruising ability of the unmanned ship on the sea is improved.
Claims (4)
1. An energy-saving A star path planning method considering the influence of ocean current and unmanned ship dynamics specifically comprises the following steps:
(1) acquiring global chart information and global ocean current information, setting a gridding resolution n, and gridding the chart and the ocean current graph to form n x n grid charts and grid ocean current graphs;
(2) the barrier value in the grid chart is Inf, the others are 1, and the flow velocity U of the ocean current in each unit grid is included in the grid chartcurrent(x, y) and flow direction Dcurrent(x，y)；
(3) Obtaining the starting position (x) of the unmanned shipstart，ystart) And end position (x)goal，ygoal) Information, and order the current position (x) of the unmanned shipusv，yusv) Is equal to (x)start，ystart) Creating an OPEN table and a CLOSED table;
(4) u _ stack _ usv represents the unmanned ship speed required to be provided by the engine when each unit grid unmanned ship on the N x N map runs towards the eight directions of E, W, S, N, SE, SW, NW and NE under the action of ocean current in sequence from the lowest layer to the uppermost layer; calculating a speed stack U _ stack _ usv of the unmanned ship under the action of ocean current;
(5) will (x)usv，yusv) Storing the data into an OPEN table;
(6) judging the current position (x) of the unmanned shipusv，yusv) Around the ith survey position (x)i，yi) If the Inf is not Inf, turning to the step (7) if the Inf is Inf, and otherwise, turning to the step (8);
(7) judging whether i is equal to 8, if so, turning to the step (18), otherwise, enabling i to be i +1 and returning to the step (6);
(8) according to (x)usv，yusv) And (x)i，yi) Calculating the running direction f _ c and the distance d _ c of the unmanned ship according to the relative positions;
(9) according to f _ c and (x)usv，yusv) Selecting the corresponding unmanned ship speed U _ c in U _ stack _ usv;
(10) according to U _ c, UgroundAnd d _ c, calculating the unmanned ship from (x) by using the unmanned ship dynamic model under the action of ocean currentusv，yusv) To (x)i，yi) Consumed energy e _ cost (i); u shapegroundThe ground speed of the unmanned boat is measured;
(11) let sofar _ cost be e _ cost (i) + sofar _ cost, so that sofar _ cost is used as the starting point for storage (x)start，ystart) To (x)i，yi) The required energy, initial value is 0;
(12) calling the heuristic function E _ predicate, evaluating the Slave (x)i，yi) To (x)goal，ygoal) The energy e _ regenerative (i) to be consumed;
(13) judgment (x)i，yi) If it does not belong to either the CLOSED table or the OPEN table, then (x)i，yi) Adding OPEN table, that is, enabling OPEN (x)i，yi) (1) equal to sofar _ cost, OPEN (x)i，yi) (2) equals e _ hesistic (i) and go to step (17), otherwise go to step (14);
(14) judgment (x)i，yi) If the list belongs to the OPEN list, turning to the step (15) if yes, and turning to the step (16) if not;
(15) judging whether the sofar _ cost is less than OPEN (x)i，yi) (1) is (x)i，yi) Update OPEN (x)i，yi) Turning to the step (17) according to the corresponding value;
(16) judging whether the sofar _ cost is less than CLOSED (x)i，yi) If yes, command CLOSED (x)i，yi) Equal to sofar _ cost, go to step (17);
(17) calculating e _ function (i) ═ α · costchart (x)i，yi) + β. e _ heuristic (i), where α, β represent the weight parameters of the cost value and heuristic value, respectively, and α > β is the higher the energy saving but the lower the programming speed; otherwise, turning to the step (7) if the planning speed is higher and the energy saving is lower;
(18) the current position (x) of the unmanned shipusv，yusv) Deleting from the OPEN table, and adding a CLOSED table;
(19) (x) corresponding to the minimum value in { e _ function }i，yi) Order (x)usv，yusv) Is equal to (x)i，yi)；
(20) Judgment (x)usv，yusv) Whether or not to be equal to (x)goal，ygoal) If yes, the end of the terminal planning is reached, otherwise, the step (5) is returned.
2. The method for planning an energy-saving A-star path considering the influence of ocean currents and unmanned ship dynamics as claimed in claim 1, wherein the step (4) specifically comprises:
(4-1) dividing the current velocity U in the n x n gridcurrent(x, y) and flow direction Dcurrent(x, y) decomposing to obtain a list U of n x n ocean current velocities in the x directioncurrentXAnd y-direction ocean current velocity list UcurrentY；
(4-2) respectively pointing to the four directions: speed U of unmanned boat to groundgroundDecomposing, and customizing U by the user according to the actual situationgroundThe size of the ground speed is obtained, and an x-direction ground speed list U of 8 x 1 is obtainedgroundXAnd y-direction ground speed list UgroundY；
(4-3) according to UcurrentX、UcurrentY、UgroundXAnd UgroundYRespectively calculating x-direction three-dimensional unmanned ship speed stacks U of n x n 8usvXAnd Y-direction three-dimensional unmanned ship speed stack UusvY；
(4-4) according to UusvXAnd UusvYAnd calculating a three-dimensional unmanned ship speed stack U _ stack _ usv of n x 8 under the influence of the ocean current by pythagorean theorem.
3. The method for planning an energy-saving a-star path considering the influence of ocean currents and unmanned ship dynamics as claimed in claim 1, wherein the step (12) specifically comprises:
(12-1) calculating a current survey position (x)i，yi) To the end point (x)goal，ygoal) Manhattan diagonal distance heuristic _ d and straight distance heuristic_s；
(12-2) calculating (x)i，yi) And (x)goal，ygoal) Relative position angle f _ h therebetween;
(12-3) according to (x)i，yi) F _ h, heuristic _ d, and heuristic _ s select all unmanned boat speeds { U _ h } on the corresponding heuristic path heuristic in U _ stack _ usv;
(12-4) determining if heuristic _ d is equal to 0, if so, using { U _ h }, UgroundAnd heuristic _ s calculation
Obtaining an energy estimate e _ hetic, otherwise proceeding to step (12-5), wherein
Representing all drone speeds on the heuristic path heuristic;
(12-5) according to (x)i，yi)、(xgoal，ygoal)、{U_h}、UgroundHeuristic _ s and heuristic _ d, calculating
Wherein
Representing unmanned boat speed on all diagonal paths,
representing the unmanned boat velocity on all straight paths, and epsilon is the towing force coefficient of the unmanned boat.
4. The method for planning an energy-saving a-star path considering the influence of ocean currents and unmanned ship dynamics as claimed in claim 1, wherein the unmanned ship dynamics model under the action of ocean currents in the step (10) specifically comprises:
the unmanned boat is driven by the following components (x)usv，yusv) To (x)i，yi) The consumed energy e _ cost (i) is calculated by the following formula:
e_cost＝ε·|U_c3/Uground|·d_c；
where epsilon is the towing force coefficient of the unmanned boat.
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| CN108983789A (en) * | 2018-08-20 | 2018-12-11 | 广东华中科技大学工业技术研究院 | A kind of path planning of unmanned boat and lay dispatching method |
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| CN111256694A (en) * | 2019-12-16 | 2020-06-09 | 中国船舶工业系统工程研究院 | Method for determining path of unmanned surface vehicle |
| CN111984009B (en) * | 2020-08-04 | 2021-06-25 | 智慧航海（青岛）科技有限公司 | Ship collision avoidance environment modeling method |
| CN112214023B (en) * | 2020-10-14 | 2021-05-14 | 哈尔滨工程大学 | Real-time optimization method and navigation method of course of wave-propelled natural energy driven unmanned ship |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102175245A (en) * | 2011-01-28 | 2011-09-07 | 哈尔滨工程大学 | Underwater vehicle path planning method based on ocean current historical statistic information |
| CN103744428A (en) * | 2014-01-17 | 2014-04-23 | 哈尔滨工程大学 | Unmanned surface vehicle path planning method based on neighborhood intelligent water drop algorithm |
| CN104536442A (en) * | 2014-12-11 | 2015-04-22 | 西北工业大学 | Underwater vehicle path planning method based on dynamic planning |
| WO2017004419A1 (en) * | 2015-06-30 | 2017-01-05 | Unmanned Innovations, Inc. | Systems and methods for multi-mode unmanned vehicle mission planning and control |
| CN107168335A (en) * | 2017-06-28 | 2017-09-15 | 大连海事大学 | A kind of unmanned surface vehicle path trace method of guidance for considering mixing multiple target avoidance |
| CN107389076A (en) * | 2017-07-01 | 2017-11-24 | 兰州交通大学 | A kind of real-time dynamic path planning method of energy-conservation suitable for intelligent network connection automobile |
-
2019
- 2019-01-16 CN CN201910041363.2A patent/CN109489672B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102175245A (en) * | 2011-01-28 | 2011-09-07 | 哈尔滨工程大学 | Underwater vehicle path planning method based on ocean current historical statistic information |
| CN103744428A (en) * | 2014-01-17 | 2014-04-23 | 哈尔滨工程大学 | Unmanned surface vehicle path planning method based on neighborhood intelligent water drop algorithm |
| CN104536442A (en) * | 2014-12-11 | 2015-04-22 | 西北工业大学 | Underwater vehicle path planning method based on dynamic planning |
| WO2017004419A1 (en) * | 2015-06-30 | 2017-01-05 | Unmanned Innovations, Inc. | Systems and methods for multi-mode unmanned vehicle mission planning and control |
| CN107168335A (en) * | 2017-06-28 | 2017-09-15 | 大连海事大学 | A kind of unmanned surface vehicle path trace method of guidance for considering mixing multiple target avoidance |
| CN107389076A (en) * | 2017-07-01 | 2017-11-24 | 兰州交通大学 | A kind of real-time dynamic path planning method of energy-conservation suitable for intelligent network connection automobile |
Non-Patent Citations (1)
| Title |
|---|
| Efficient Path Planning Algorithms for Unmanned Surface Vehicle;Hanlin Niu等;《IFAC PAPERSONLINE》;20161101;第49卷(第23期);第121-126页 * |
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