CN113124876B - Path optimization method and system for unmanned ship in terrain complex sea area traversal monitoring - Google Patents
Path optimization method and system for unmanned ship in terrain complex sea area traversal monitoring Download PDFInfo
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Abstract
The invention discloses a path optimization method and a system for an unmanned ship in traversing monitoring of a complex terrain sea area, which comprises the steps of firstly determining the distribution of each point to be traversed on a grid line in a traversing area range; then when no barrier exists at each point to be traversed around the starting point, judging whether the point to be traversed still exists around the starting point; if the optimal working path exists, selecting a point to be traversed with the maximum probability, taking the path between the starting point and the point to be traversed with the maximum probability as the optimal working path, and taking the point to be traversed with the maximum probability as the next starting point; if not, selecting a point to be traversed which meets the traversal condition from the residual pool as a next starting point, and judging whether the residual pool is empty; if the number of the nodes is null, the traversal is ended; and if the residual pool is not empty, judging the obstacle again. The scheme disclosed by the invention realizes the traversal and patrol in offshore multi-island reefs, submerged reefs and multi-bay areas, avoids the omission of bays and dead angles, and greatly reduces repeated paths.
Description
Technical Field
The invention relates to the technical field of path optimization, in particular to a path optimization method and system for an unmanned ship in terrain complex sea area traversal monitoring.
Background
China has broad width of members, long coastlines and numerous islands and submerged reefs, carries out all-weather and normalized monitoring on marine environment near the bank and around the island, masters the change trend of the elements of the water surface and underwater environment in real time, and has very important significance on the aspects of environmental protection, safety, national defense and the like. However, "coastal landform" topographic conditions are complicated, generally belong to many islands reef, many submerged reefs, many gulfs regions, it is unusual difficult to utilize traditional driving manned ship to carry out the normalized monitoring of marine environment in coastal waters such as manual sampling to have the power fuel of manned ship easily cause secondary pollution to the waters, be not suitable for quality of water environmental monitoring.
Unmanned ship is equipped as emerging intelligent autonomous robot, and is small and exquisite, nimble, draft shallow, autonomy strong, can work in adverse circumstances such as high radiation, heavy pollution, has the unique advantage that traditional marine environment monitoring tool did not possess. The path optimization technology of the unmanned ship in the traversing monitoring of the terrain complex sea area is researched, so that the unmanned ship can autonomously adopt an optimal path to traverse in the terrain complex sea area, the repeated traversal, the omission of the traversal and the occurrence of dead corners are avoided, and the unmanned ship is applied to the periodic normalized monitoring of the marine environment around the offshore or island, on one hand, the manpower and material resources are saved, the working environment of personnel is improved, the labor efficiency is improved, on the other hand, the manual operation error is avoided to a great extent, and the real-time performance, the correctness and the effectiveness of monitoring data are enhanced.
The unmanned ship complete traversal path planning needs to meet two indexes: ergodicity and non-repeatability. The traversability means that the motion trail of the unmanned ship needs to be distributed over the reachable task space to the maximum extent, and reflects the problem of the working quality of the unmanned ship; the non-repeatability means that the walking route of the unmanned ship is prevented from being repeated as much as possible, and the problem of the working efficiency of the unmanned ship is reflected. Throughout the research on the unmanned ship path traversal aspect at home and abroad, the two indexes are served, and the targets are consistent: on the basis of ensuring the ergodicity, the repetition is reduced as much as possible, namely, the quality and the efficiency are ensured.
In addition, the operation characteristics of the unmanned ship are combined, the turning angle is reduced as much as possible in the running process of the unmanned ship, namely 'straight road is taken and no curved road is taken', and the turning in the running process can affect the stability of the ship body, so that the safety of the ship and the working state of shipborne equipment are affected.
At present, the unmanned ship complete traversal path planning adopts many algorithms including an artificial potential field method, a genetic algorithm, a neural network algorithm, a heuristic algorithm and the like. However, the artificial potential field method is obtained according to experience in the actual use process, and has the defects that once the terrain is too complex, the unmanned ship is likely to fall into a local optimal solution when the unmanned ship adopts the algorithm to completely traverse the path planning, so that a leakage area is generated; the genetic algorithm has low searching efficiency, and the ergodic requirement is difficult to meet in the face of complex and variable submarine environment; the neural network algorithm, the heuristic algorithm and the like need to acquire enough training sample data in advance to train an algorithm model, have the defects of random selection and repeated coverage, and are not suitable for the requirement of an online real-time terrain coverage scanning task of an unknown complex seabed area.
In summary, the conventional path traversal algorithm suitable for the unmanned ship is difficult to meet the traversal patrol requirements of the unmanned ship in offshore multi-island reefs, submerged reefs and multi-bay areas.
Disclosure of Invention
The invention aims to provide a path optimization method and a path optimization system for an unmanned ship in traversing and monitoring of complex-terrain sea areas, so as to realize traversing and patrolling of offshore multi-island reefs, submerged reefs and multi-bay areas.
In order to achieve the above object, the present invention provides a method for optimizing a path of an unmanned ship in traversing and monitoring a terrain complex sea area, the method comprising:
step S1: determining the spacing distance of grid lines in the range of a traversal area and the distribution of points to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship;
step S2: adding all points to be traversed into the residual pool, selecting any one point to be traversed from the residual pool as a starting point to start traversing, and adding the starting point into the traversed pool;
step S3: selecting points to be traversed around the starting point from the residual pool, and utilizing radar scanning on the unmanned ship to judge whether obstacles exist at the points to be traversed around the starting point; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; if no obstacle exists at each point to be traversed, executing step S4;
step S4: judging whether points to be traversed exist around the starting point; if the point to be traversed exists, executing step S5; if the points to be traversed do not exist, the unmanned ship enters dead corners, and step S7 is executed;
step S5: calculating the probability of each point to be traversed around the starting point;
step S6: selecting a point to be traversed with the maximum probability, taking a path between the starting point and the point to be traversed with the maximum probability as an optimal working path, taking the point to be traversed with the maximum probability as a next starting point, and adding the point to be traversed into a traversed pool;
step S7: selecting a point to be traversed which meets the traversal condition from the residual pool as a next starting point, and executing step S8;
step S8: judging whether the residual pool is empty or not; if the residual pool is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; if the remaining pool is not empty, return is made to "step S3".
Optionally, the specific formula for calculating the probability corresponding to each point to be traversed around the starting point is as follows:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
Optionally, before step S2, the method further includes: and the weights corresponding to the starting raster line and the ending raster line are increased progressively, and the weights corresponding to a plurality of points to be traversed on the same raster line are equal to the weights corresponding to the raster line.
Optionally, the traversal condition is that the weight is minimum and is closest to the starting point.
The invention also provides a path optimization system for the unmanned ship in the traversal monitoring of the terrain complex sea area, which comprises the following steps:
the distribution determining module of each point to be traversed is used for determining the spacing distance of grid lines in the range of a traversal area and the distribution of each point to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship;
the first selection module is used for adding all the points to be traversed into the residual pool, selecting any one point to be traversed from the residual pool as a starting point to start traversing, and adding the starting point into the traversed pool;
the first judgment module is used for selecting points to be traversed around the starting point from the residual pool and judging whether obstacles exist in the points to be traversed around the starting point or not by utilizing radar scanning on the unmanned ship; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; if no barrier exists in each point to be traversed, executing a second judgment module;
the second judgment module is used for judging whether points to be traversed exist around the starting point; if the point to be traversed exists, executing a probability calculation module; if the points to be traversed do not exist, the unmanned ship enters dead corners, and a second selection module is executed;
the probability calculation module is used for calculating the probability of each point to be traversed around the starting point;
the optimal working path determining module is used for selecting the point to be traversed with the maximum probability, taking the path between the starting point and the point to be traversed with the maximum probability as the optimal working path, taking the point to be traversed with the maximum probability as the next starting point, and adding the next starting point into the traversed pool;
a second selection module, configured to select a point to be traversed that meets the traversal condition from the remaining pool as a next starting point, and execute a "third determination module";
the third judging module is used for judging whether the residual pool is empty or not; if the residual pool is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; and if the residual pool is not empty, returning to the first judgment module.
Optionally, the specific formula for calculating the probability corresponding to each point to be traversed around the starting point is as follows:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
Optionally, the system further comprises: and the weight setting module is used for increasing the corresponding weights from the starting raster line to the ending raster line, and the weights corresponding to a plurality of points to be traversed on the same raster line are equal to the corresponding weights of the raster line.
Optionally, the traversal condition is that the weight is minimum and is closest to the starting point.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a path optimization method and a path optimization system for an unmanned ship in traversal monitoring of a complex-terrain sea area, which are used for realizing traversal patrol of offshore multi-island reefs, submerged reefs and multi-bay areas without performing terrain survey on the monitored sea area in advance, and the unmanned ship can automatically draw a barrier schematic diagram, an optimal working path diagram and a bay terrain diagram in the traversal driving process, so that the omission of bays and dead corners is avoided, repeated paths are greatly reduced, and the working efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a diagram of a path optimization system in traversal monitoring of an unmanned ship in a complex terrain sea area in embodiment 2 of the present invention;
fig. 2 is a schematic diagram of path optimization in sea area traversal monitoring of an unmanned ship in an embodiment 3 of the present invention under normal conditions;
fig. 3 is a schematic diagram of path optimization of an unmanned ship in sea area traversal monitoring including an independent circular obstacle according to embodiment 4 of the present invention;
fig. 4 is a schematic diagram of path optimization of an unmanned ship in sea area traversal monitoring including an independent diamond-shaped obstacle according to embodiment 5 of the present invention;
fig. 5 is a schematic diagram of path optimization of the unmanned ship in sea area traversal monitoring including independent irregular obstacles according to the embodiment 6 of the present invention;
fig. 6 is a schematic diagram of path optimization of the unmanned ship in sea area traversal monitoring including independent irregular obstacles according to embodiment 6 of the present invention;
fig. 7 is a schematic diagram of path optimization of an unmanned ship in a sea area including a bay according to embodiment 7 of the present invention;
fig. 8 is a schematic diagram of path optimization in an actual application scene simulation of the unmanned ship in embodiment 8 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a path optimization method and a path optimization system for an unmanned ship in traversing and monitoring of complex-terrain sea areas, so as to realize traversing and patrolling of offshore multi-island reefs, submerged reefs and multi-bay areas.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example 1
Presetting conditions:
before traversing, grid lines are divided according to the range of the traversing sea area and the range of the unmanned shipborne radar, a traversing path is appointed according to the sequence of the grid lines, and the unmanned shipborne radar travels according to a preset route under the condition of no obstacles. When an obstacle is encountered, the next traversal point is selected according to equation 1.
The formula:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
Description of the formula:
(1) p is the probability of each point, and the larger P is, the higher the probability of the point being selected as the next traversal point is;
(2) a is the weight of the point, the grid lines from the starting point to the end point of the unmanned ship are sequentially increased, and the weight of the grid lines at the starting point is 0;
(3) theta is a steering angle, namely an angle which needs to be steered when the unmanned ship reaches the next position from the current position, and when theta is 0 (without steering), the P value is maximum;
(4) when A is the same, the smaller theta is, the higher P value is;
(5) the smaller A, the higher P value when θ is the same.
Strategy description:
p is the selection probability of the point to be reached, and the larger P is, the higher the selection probability is.
A is the weight of the point, and the closer to the starting point, the larger A is, and the same weight of the point of the same longitudinal grid line is.
When a is the same, the smaller θ is, the higher the selection probability is, and the infinite selection probability is given to a point (θ is 0) in the same traveling direction.
All points on the grid line of the traversal region are divided into a traversed pool, an unretraversed pool and an obstacle pool, and the point collection of the 3 pools is the total point number.
After entering a dead corner, if the residual pool is not empty, the selection strategy of the next traversal point is as follows: and selecting the point which has the smallest weight and is closest to the current point from the residual pool as the next traversal point.
At the beginning of traversal, the "not traversed pool" is the total number of points, and the "traversed pool" and the "obstacle pool" are empty.
As the traversal progresses, the obstacle points scanned by the radar are all added into an obstacle pool, and if the points in the pool (including the traversal area boundary line) form a closed loop, all the points in the loop are considered as the obstacle points; the "not traversed pool" is empty and the traversal ends.
Based on the strategy description and the preset conditions, the invention summarizes a path optimization method for the unmanned ship in the traversal monitoring of the terrain complex sea area, and the method comprises the following steps:
step S1: determining the spacing distance of grid lines in the range of a traversal area and the distribution of points to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship; and the weights corresponding to the starting raster line and the ending raster line are increased progressively, and the weights corresponding to a plurality of points to be traversed on the same raster line are equal to the weights corresponding to the raster line.
Step S2: adding all points to be traversed into the residual pool, and selecting any one point to be traversed from the residual pool as a starting point to start traversing; and adding the starting point to the traversed pool.
Step S3: selecting points to be traversed around the starting point from the residual pool, and utilizing radar scanning on the unmanned ship to judge whether obstacles exist at the points to be traversed around the starting point; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; if there is no obstacle for each point to be traversed, "step S4 is executed.
Step S4: judging whether points to be traversed exist around the starting point; if the point to be traversed exists, executing step S5; if no point to be traversed exists, the unmanned ship is indicated to enter a dead angle, and step S7 is executed.
Step S5: according to
Calculating the probability of each point to be traversed around the starting point; wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
Step S6: and selecting the point to be traversed with the maximum probability, taking the path between the starting point and the point to be traversed with the maximum probability as an optimal working path, taking the point to be traversed with the maximum probability as the next starting point, and adding the next starting point into the traversed pool.
Step S7: a point to be traversed satisfying the traversal condition is selected from the remaining pool as a next starting point, and "step S8" is performed. The traversal condition is that the weight is minimum and the distance from the starting point is nearest.
Step S8: judging whether the residual pool is empty or not; if the 'residual pool' is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; if the "remaining pool" is not empty, the flow returns to step S3.
The technical problems to be solved by the unmanned ship in the near-shallow sea complete path traversal technology are as follows: avoiding the occurrence of missing bay and repeated bay, reducing the turning amplitude of the ship and reducing the repeated path as much as possible. In view of the fact that the traditional path traversal technology cannot meet the traversal requirements of the unmanned ship on complex terrains such as offshore areas, shallow sea areas and multiple submerged reefs and bays, the technical characteristics and the traversal requirements of the unmanned ship are fully considered, and the novel path optimization method suitable for the unmanned ship in the traversal monitoring of the complex terrains and seas is provided. The path optimization method realizes traversal and inspection in offshore multi-island reefs, submerged reefs and multi-bay areas without performing terrain reconnaissance on a monitored sea area in advance, and the unmanned ship can automatically draw a barrier schematic diagram, an optimal working path diagram and a bay terrain diagram in the traversal and driving process, so that bay and dead corners are avoided being omitted, repeated paths are greatly reduced, and further the working efficiency is improved.
Example 2
As shown in fig. 1, the present invention further provides a path optimization system for unmanned ship in terrain complex sea area traversal monitoring, where the system includes:
and the distribution determining module 101 for each point to be traversed is used for determining the spacing distance of the grid lines in the range of the traversal area and the distribution of each point to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship.
The weight setting module 102 is configured to increment weights corresponding to a starting raster line and an ending raster line, where the weights corresponding to multiple points to be traversed on the same raster line are equal to the weights corresponding to the raster line.
The first selecting module 103 is configured to add all the points to be traversed to the remaining pool, select any one point to be traversed from the remaining pool as a starting point to start traversal, and add the starting point to the traversed pool.
The first judging module 104 is configured to select each point to be traversed around the starting point from the remaining pool, and judge whether an obstacle exists in each point to be traversed around the starting point by using radar scanning on the unmanned ship; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; and if no barrier exists in each point to be traversed, executing a second judgment module.
A second judging module 105, configured to judge whether there is a point to be traversed around the starting point; if the point to be traversed exists, executing a probability calculation module; and if the points to be traversed do not exist, the unmanned ship enters dead corners, and a second selection module is executed.
And a probability calculating module 106, configured to calculate probabilities corresponding to the points to be traversed around the starting point.
And an optimal working path determining module 107, configured to select a point to be traversed with the highest probability, use a path between the starting point and the point to be traversed with the highest probability as an optimal working path, use the point to be traversed with the highest probability as a next starting point, and add the next starting point to the traversed pool.
And a second selecting module 108, configured to select a point to be traversed that meets the traversal condition from the remaining pool as a next starting point, and execute a "third determining module". The traversal condition is that the weight is minimum and the distance from the starting point is nearest.
A third judging module 109, configured to judge whether the remaining pool is empty; if the residual pool is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; and if the residual pool is not empty, returning to the first judgment module.
Specifically, the specific formula for calculating the probability corresponding to each point to be traversed around the starting point is as follows:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
Example 3
As shown in fig. 2, (a) is an optimal working path diagram, (b) is a schematic diagram of points to be traversed stored in a traversed pool, (c) is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) is a schematic diagram of points to be traversed stored in a residual pool. Under normal conditions, obstacles are not found in the sea area, and the unmanned ship gradually traverses according to the divided grids. For example, when the unmanned ship drives to the point to be traversed 20, the traversable points that it can scan are the point to be traversed 13, the point to be traversed 19, the point to be traversed 29, and the point to be traversed 21, wherein the point to be traversed 13 and the point to be traversed 19 are in the traversed pool and are not considered. When the point to be traversed 29 and the point to be traversed 21 are selected, according to the formula 1, the weight of the point to be traversed 21 is 2, the weight of the point to be traversed 29 is 3, in addition, in the process that the unmanned ship turns to the point to be traversed 20 towards the point to be traversed 21, the turning theta is 0, the P value is infinite, in the process that the point to be traversed 20 towards the point to be traversed 29, the turning theta is 90, therefore, the P values of the point to be traversed 29 and the point to be traversed 21 are comprehensively calculated, and the next traversal point is the point to be traversed 21 instead of the point to be traversed 29.
Example 4
As shown in fig. 3, (a) is an optimal working path diagram, (b) is a schematic diagram of points to be traversed stored in a traversed pool, (c) is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) is a schematic diagram of points to be traversed stored in a residual pool. When a regularly shaped obstacle is encountered (e.g., a separate circular obstacle), the traversal strategy is as follows: when the unmanned ship runs to the point to be traversed 20, the points to be traversed which can be scanned by the unmanned ship are 13, 19, 29 and 21. 13. 19 in the traversed pool, are not considered any more. 29 and 21, when selecting, 21 can be identified as an obstacle area and added to the 'obstacle pool', so 29 is the next point to be traversed, and then, the point-by-point traversal is performed according to the formula 1 until the point 33 to be traversed, and 27 and 28 are added to the 'obstacle pool'. 33 are scannable points to be traversed 25 and 41. Wherein, the weight of 25 is 3, the weight of 41 is 5, and the steering is 90. According to formula 1, the next point to be traversed is selected 25 and traversed point by point to 26, and in the traversal process 22 is added to the "barrier pool", and a complete circular barrier contour is determined, and all points belonging to the contour are added to the "barrier pool".
The point to be traversed, which may be scanned at 26, is empty, but the "rest pool" is not empty, indicating that 26 is a "dead corner". And selecting 41 as the next point to be traversed based on the principle of minimum weight and nearest distance. It should be noted that in the process of 26 to 41, the unmanned ship can arrive in the most convenient straight-line running mode without the need of the grid line course. And after reaching the point 41 to be traversed, continuing traversing according to the formula 1 until the 'residual pool' is empty, and ending the traversing.
Example 5
As shown in fig. 4, (a) is an optimal working path diagram, (b) is a schematic diagram of points to be traversed stored in a traversed pool, (c) is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) is a schematic diagram of points to be traversed stored in a residual pool. When the unmanned ship reaches the point to be traversed 20, the point to be traversed 21 and the point to be traversed 29 are added into an obstacle pool, and the point to be traversed 30 serves as the next point to be traversed, and the unmanned ship gradually traverses until the point to be traversed 37. Comparing 44 and 45, the weight is 5 when the weight is the same, but the turning direction 44 is less than 45, and the next point to be traversed is 44 according to the formula 1. In the process that one path traverses to the point 22 to be traversed, a complete obstacle outline is drawn, and all the points to be traversed in the outline are added into an obstacle pool. And selecting 45 as the next point to be traversed, continuing to traverse according to the formula 1 until the 'residual pool' is empty, and ending the traverse.
Example 6
As shown in fig. 5, (a) is an optimal working path diagram, (b) is a schematic diagram of points to be traversed stored in a traversed pool, (c) is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) is a schematic diagram of points to be traversed stored in a residual pool. For this case, when the traversal reaches the point to be traversed 38, the next point to be traversed is selected as 46 according to equation 1. And traversing and drawing the barrier contour point by point according to the formula 1 and the traversal strategy until the traversal is finished.
If the radar can detect the point 45 to be traversed in the oblique front, based on that the values of a of the point 45 to be traversed and a point 46 to be traversed are the same, but for the point 45 to be traversed, θ is smaller, the next point to be traversed can be selected to be 45, and finally sea area traversal can be well completed, and formula 1 has strong general applicability, as shown in fig. 6, (a) the graph is an optimal working path graph, (b) the graph is a schematic diagram of points to be traversed stored in a traversed pool, (c) the graph is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) the graph is a schematic diagram of points to be traversed stored in a residual pool.
Example 7
As shown in fig. 7, (a) is an optimal working path diagram, (b) is a schematic diagram of points to be traversed stored in a traversed pool, (c) is a schematic diagram of points to be traversed stored in an obstacle pool, and (d) is a schematic diagram of points to be traversed stored in a residual pool. Also traversing the bay according to equation 1 and strategy, as can be seen from the route depicted in fig. 7, the algorithm can avoid the situations of "missing bay" and "repeating bay" and well solve the occurrence of "dead corners".
The above embodiments 3-7 basically include the common offshore terrain, and it can be seen from the above that the unmanned ship can well complete the traversal task by using the formula 1. However, in reality, the above situations are generally combined randomly, and the applicability of the following formula 1 in the actual use process is analyzed.
Example 8
As shown in fig. 8, the conditions of several obstacles and bays are integrated to simulate the situation of a sea area with relatively complex terrain, and as shown in fig. 8, the conditions of various obstacles and bays are integrated, and the path traversal simulated by using the formula 1 is performed, it can be seen from fig. 8 that the traversal path of the unmanned ship to the terrain complex sea area is clear, no bay and "dead angle" are missed, and the terrain map of the sea area is clearly drawn. Thus, the method is proved to be correct and effective.
The method disclosed by the invention has the following advantages:
(1) before traversing, the terrain survey of the monitored sea area is not required in advance, and the grid lines and the preset traversing path are calculated only by determining the traversing area range and the range of the shipborne radar according to the actual condition.
(2) The occurrence of missing bay and dead corners is effectively avoided, the turning amplitude of the unmanned ship in the driving process is reduced to a great extent, and the traversing requirement of the unmanned ship in the terrain complex sea area is met.
(3) In the traversing process, a topographic map of the monitored sea area is drawn at the same time, and the barrier area and the bay area are clearly marked, so that a good foundation is provided for subsequent application.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (6)
1. A method for optimizing a path of an unmanned ship in traversal monitoring of a terrain complex sea area is characterized by comprising the following steps:
step S1: determining the spacing distance of grid lines in the range of a traversal area and the distribution of points to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship;
step S2: adding all points to be traversed into the residual pool, selecting any one point to be traversed from the residual pool as a starting point to start traversing, and adding the starting point into the traversed pool;
step S3: selecting points to be traversed around the starting point from the residual pool, and utilizing radar scanning on the unmanned ship to judge whether obstacles exist at the points to be traversed around the starting point; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; if no obstacle exists at each point to be traversed, executing step S4;
step S4: judging whether points to be traversed exist around the starting point; if the point to be traversed exists, executing step S5; if the points to be traversed do not exist, the unmanned ship enters dead corners, and step S7 is executed;
step S5: calculating the probability of each point to be traversed around the starting point;
step S6: selecting a point to be traversed with the maximum probability, taking a path between the starting point and the point to be traversed with the maximum probability as an optimal working path, taking the point to be traversed with the maximum probability as a next starting point, and adding the point to be traversed into a traversed pool;
step S7: selecting a point to be traversed which meets the traversal condition from the residual pool as a next starting point, and executing step S8;
step S8: judging whether the residual pool is empty or not; if the residual pool is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; if the remaining pool is not empty, return to "step S3";
the specific formula for calculating the probability corresponding to each point to be traversed around the starting point is as follows:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
2. The method for optimizing the path of the unmanned ship in the traversal monitoring of the terrain complex sea area according to claim 1, further comprising, before step S2: and the weights corresponding to the starting raster line and the ending raster line are increased progressively, and the weights corresponding to a plurality of points to be traversed on the same raster line are equal to the weights corresponding to the raster line.
3. The method for optimizing the path of the unmanned ship in the traversal monitoring of the terrain complex sea area according to claim 1, wherein the traversal condition is that the weight is minimum and the distance from the starting point is nearest.
4. A system for optimizing a path of an unmanned ship in terrain complex sea area traversal monitoring, is characterized by comprising:
the distribution determining module of each point to be traversed is used for determining the spacing distance of grid lines in the range of a traversal area and the distribution of each point to be traversed on the grid lines according to the search range and the search area of the radar on the unmanned ship;
the first selection module is used for adding all the points to be traversed into the residual pool, selecting any one point to be traversed from the residual pool as a starting point to start traversing, and adding the starting point into the traversed pool;
the first judgment module is used for selecting points to be traversed around the starting point from the residual pool and judging whether obstacles exist in the points to be traversed around the starting point or not by utilizing radar scanning on the unmanned ship; if each point to be traversed has an obstacle, adding each point to be traversed into an obstacle pool; if no barrier exists at each point to be traversed, executing a second judgment module;
the second judgment module is used for judging whether points to be traversed exist around the starting point; if the point to be traversed exists, executing a probability calculation module; if the points to be traversed do not exist, the unmanned ship enters dead corners, and a second selection module is executed;
the probability calculation module is used for calculating the probability of each point to be traversed around the starting point;
the optimal working path determining module is used for selecting the point to be traversed with the maximum probability, taking the path between the starting point and the point to be traversed with the maximum probability as the optimal working path, taking the point to be traversed with the maximum probability as the next starting point, and adding the next starting point into the traversed pool;
a second selection module, configured to select a point to be traversed that meets the traversal condition from the remaining pool as a next starting point, and execute a "third determination module";
the third judging module is used for judging whether the residual pool is empty or not; if the residual pool is empty, the traversal is finished, the barrier diagram is determined based on each point to be traversed in the barrier pool, and the optimal working path diagram is determined based on each point to be traversed in the traversed pool; if the residual pool is not empty, returning to the first judgment module;
the specific formula for calculating the probability corresponding to each point to be traversed around the starting point is as follows:
wherein, P is the probability corresponding to each point to be traversed, A is the weight of each point to be traversed, and theta is the steering angle.
5. The system for optimizing the path of the unmanned ship in the traversal monitoring of the terrain complex sea area according to claim 4, further comprising: and the weight setting module is used for increasing the corresponding weights from the starting raster line to the ending raster line, and the weights corresponding to a plurality of points to be traversed on the same raster line are equal to the corresponding weights of the raster line.
6. The system for optimizing the path of the unmanned ship in the traversal monitoring of the terrain complex sea area according to claim 4, wherein the traversal condition is that the weight is minimum and the distance from the starting point is nearest.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102004839A (en) * | 2010-12-17 | 2011-04-06 | 北京优纳科技有限公司 | Method for optimizing full-node traversal path |
| KR20140003249A (en) * | 2012-06-29 | 2014-01-09 | 인텔렉추얼디스커버리 주식회사 | Moving robot and method for online complete coverage path planning |
| CN107505939A (en) * | 2017-05-13 | 2017-12-22 | 大连理工大学 | A kind of complete coverage path planning method of mobile robot |
| CN110941261A (en) * | 2019-10-19 | 2020-03-31 | 中国海洋大学 | Autonomous underwater vehicle multi-zone traversal path planning method |
| CN111012251A (en) * | 2019-12-17 | 2020-04-17 | 哈工大机器人（合肥）国际创新研究院 | Planning method and device for full-coverage path of cleaning robot |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102004839A (en) * | 2010-12-17 | 2011-04-06 | 北京优纳科技有限公司 | Method for optimizing full-node traversal path |
| KR20140003249A (en) * | 2012-06-29 | 2014-01-09 | 인텔렉추얼디스커버리 주식회사 | Moving robot and method for online complete coverage path planning |
| CN107505939A (en) * | 2017-05-13 | 2017-12-22 | 大连理工大学 | A kind of complete coverage path planning method of mobile robot |
| CN110941261A (en) * | 2019-10-19 | 2020-03-31 | 中国海洋大学 | Autonomous underwater vehicle multi-zone traversal path planning method |
| CN111012251A (en) * | 2019-12-17 | 2020-04-17 | 哈工大机器人（合肥）国际创新研究院 | Planning method and device for full-coverage path of cleaning robot |
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