CN107608347A - A kind of distributed AC servo system unmanned boat cluster surrounds tracking - Google Patents
A kind of distributed AC servo system unmanned boat cluster surrounds tracking Download PDFInfo
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Abstract
The present invention relates to unmanned boat formation control technical field, specifically discloses a kind of distributed AC servo system unmanned boat cluster and surrounds tracking, including:Perceive and detection surrounds object, distribute unmanned boat, virtual leader is set;Identification surrounds the mark and overall structure of ship, establishes the kinematics model for surrounding ship;Unmanned boat work compound, the cluster of unmanned boat is carried out, and to surrounding Object tracking;The virtual leader of Real time identification, until kinetic coordinate system overlaps, detour surrounding and seize with surrounding object motion coordinate system.The present invention provides a kind of distributed AC servo system unmanned boat cluster and surrounds tracking, using database to surrounding the matching of object motion model, the formation form of unmanned boat of being not limited to is surrounded to surround object, it can efficiently be followed the trail of in combination with Artificial Potential Field and expulsion surrounds object, there is safety, quick, efficiency high.
Description
Technical Field
The invention relates to the technical field of unmanned ship formation control, and particularly discloses a distributed control unmanned ship cluster enclosure tracking method.
Background
The unmanned surface vehicle is a water surface vehicle with full autonomous sensing and running capability. The device has the characteristics of small volume, high navigational speed, strong cruising ability, strong controllability, quick response and the like. The unmanned ship can realize tasks such as water quality monitoring, cruising and tracking in a wide river area and a wide sea area. Meanwhile, special tasks such as intelligence investigation, force striking and the like can be realized in future war. The unmanned ship technology is valued by various countries, and the development of unmanned ship collaborative operation research is of great significance.
The unmanned ship cluster of cooperative operation can improve detection range, promote the operating efficiency. Meanwhile, the unmanned boat cluster can execute multiple tasks in a high-complexity environment and has the advantages of being not negligible. Aiming at the conditions that an enemy ship breaks into the sea area of the enemy, illegally catches fish and the like, the unmanned ship can be used for distributed control to chase and expel.
However, the movement form of the enemy boat is not fixed when the enemy boat is found, and the enemy boat can change correspondingly with the situation of the capture, thereby causing great difficulty for the unmanned boat to capture the enemy boat.
Therefore, a more efficient method for pursuing a enemy vessel is needed.
Disclosure of Invention
To overcome the disadvantages and shortcomings of the prior art, it is an object of the present invention to provide a more efficient distributed control drones cluster chase tracking method for chase interception of enemy vessels.
In order to achieve the above purpose, the present invention adopts the following scheme.
A distributed control unmanned ship cluster enclosure tracking method comprises the following steps:
sensing and detecting the enclosure object, distributing the unmanned ship, and setting a virtual leader in the unmanned ship;
identifying the mark and the whole structure of the enclosure object, and establishing a kinematic model of the enclosure object;
the unmanned ships cooperatively work to cluster the unmanned ships and track the tracked objects;
and identifying the motion coordinate systems of the virtual leader and the enclosure object in real time until the virtual leader is coincided with the motion coordinate systems of the enclosure object, and performing enclosure capture on the enclosure object by cooperating with the unmanned ship.
As a preferred embodiment, sensing and detecting the enclosure object, allocating the unmanned ship, and setting the virtual leader in the unmanned ship specifically as follows:
acquiring information of a water area environment in real time by using an environment sensing technology, and carrying out scene analysis on the water area environment;
establishing a multi-source information fusion model by using a multi-source data processing and information fusion method, and identifying the enclosure object target;
distributing different numbers of unmanned boats according to the number and types of the objects to be tracked, and distributing at least three unmanned boats to each object to be tracked for tracking; firstly, detecting an unmanned boat enclosing an object, and enclosing the object by at least two adjacent unmanned boats;
and setting a virtual leader outside a certain range d from the direction of tracking the enclosure object to the unmanned boat which firstly detects the enclosure object.
As a preferred embodiment, the scene parsing specifically includes:
collecting a picture, dividing the picture into a plurality of small pictures, and merging regions with the same color and texture in the small pictures;
extracting colors and textures which are different from the environment in the picture area as characteristic values of the ship;
setting and training a classifier according to the characteristic value of the ship to identify and track the ship;
and checking whether the characteristic value division of the ship is correct or not by using a feedback mechanism.
As a preferred embodiment, establishing a kinematics model of the vessel for pursuing is specifically:
searching in the established ship type database according to the mark and the integral structure for identifying the vessel to be tracked;
if the matched ship type is found, establishing an effective and accurate kinematic model and model dynamic parameters according to the ship type;
and if the matched ship type is not found, constructing a surrounding object kinematic model in real time according to the detected draft, yaw angle, course, navigational speed and acceleration.
As a preferred embodiment, the unmanned boat detouring enclosure capturing specifically comprises:
the unmanned ship tracks the enclosure object and identifies a virtual leader and an enclosure object motion coordinate system in real time;
if the virtual leader is overlapped with the motion coordinate system of the enclosure object, setting the distance between the cooperative unmanned ship and the virtual leader to be equal to the distance between the cooperative unmanned ship and the enclosure object; if the virtual leader does not coincide with the motion coordinate system of the enclosure object, the unmanned ship continues to keep a distance d with the virtual leader to track the enclosure object;
setting artificial potential energy function control input, enabling the unmanned boat to detour the tracked object by the radius R with the overall potential energy reaching the minimum, and simultaneously keeping the distance between the unmanned boats;
warning the enclosure object and judging the state of the enclosure object, if the enclosure object stops, taking the enclosure object as the center and the distance R as the radius, and enabling the unmanned ship to run around anticlockwise; if the enclosure pursuit object keeps running at a constant speed, the unmanned boat carries out inverted V-shaped formation and tracking; and if the tracked object runs at an accelerated speed, clustering the unmanned boats again.
As a preferred embodiment, in the process of tracking the enclosure object by the unmanned ship, the virtual leader makes a change synchronized with the motion state of the enclosure object according to the motion state of the enclosure object, specifically:
establishing a horizontal plane non-inertial motion coordinate system, taking the gravity center of the virtual leader as the origin of coordinates, the advancing direction of the virtual leader as the positive direction of a y axis of a vertical coordinate, and the rightward direction perpendicular to the y axis as the positive direction of a horizontal x axis, which is perpendicular to the Y axisThe plane is horizontally downward and is in the positive direction of the z axis (namely, the plane points to the sea surface vertically and is in the positive direction of the z axis), and the stress condition of the enclosure object is analyzed according to the image display so as to judge the motion state of the enclosure object:
analyzing the stress condition of the enclosure object according to image display to judge the motion state of the enclosure object:
is the actual mass of the vessel when in motion,respectively representing the transverse speed, the longitudinal speed and the yaw rate of the ship body at the coordinate origin O;representing the coordinates of the tracked object relative to the origin of coordinates O,respectively representing the moment of inertia of the point O around the z axis and the moment of inertia of the point G around the z axis;respectively represents the total external moment of the point O around the z-axis and the rotating torque of the point G,respectively representing the components of the external force on the tracked object in the x axis and the y axis;
and according to the detected parameters of speed, position, quality and torque of the enclosure object, the virtual leader makes a change synchronous with the motion state of the enclosure object.
As a preferred embodiment, in the process of capturing and chasing an object by unmanned boats, each unmanned boat automatically controls its own speed to avoid collision, specifically:
establishing a two-dimensional space inertial coordinate system of a horizontal plane so that the collaborative unmanned ship and the virtual leader are located in a first quadrant of the coordinate system;
according to the dynamic principle, the unmanned boat is cooperatively controlled as follows: assuming that there are N cooperative unmanned boats,the motion condition analysis is as follows:
is the position vector of the unmanned boat;is the velocity vector of the unmanned boat;is a control input, which is decomposed into two components:,is a controlled quantity generated by artificial potential energy,is the control quantity of the self speed, and T represents the transposition of the vector in mathematics.
As a preferred embodiment, the method for synchronizing the motion state of the virtual leader by coordinating the unmanned ship to automatically adjust the heading, the speed and other targets comprises the following steps:
the established kinematic model of the object to be tracked sets the initial course and the navigation speed of the virtual leaderInitial positionDesigning a control algorithm, and analyzing the following steps:
is the input of the core control, and the core control,,is based onThe relative distance between the unmanned ship and the virtual leader is determined, and an artificial potential field function,is to adjustSpeed of the individual unmanned boat and the virtual leader.
The invention has the beneficial effects that: the distributed control unmanned ship cluster enclosure pursuit tracking method is characterized in that a database is used for matching an enemy ship kinematics model, enclosure pursuit of an enemy ship is not limited to a formation form of the unmanned ship, and meanwhile, the enemy ship can be efficiently tracked and expelled by combining an artificial potential field, so that the distributed control unmanned ship cluster enclosure pursuit tracking method has the advantages of safety, rapidness, high efficiency and the like.
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FIG. 1 is a flow chart of a method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a principle flow of object recognition and kinematic model establishment according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of the establishment of a kinematic coordinate system according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of tracking an enclosure object according to an embodiment of the present invention.
Detailed Description
For the understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention.
The embodiment provides a distributed control unmanned ship cluster enclosure tracking method, which comprises the following steps:
as shown in fig. 1, sensing and detecting the enclosure objects, distributing unmanned boats according to the number of the enclosure objects, and setting a virtual leader. The method comprises the steps of adopting a multi-source data processing and fusion technology, based on the environmental perception of image information, and utilizing a target detection selection searching method to carry out environmental analysis and target identification on a target area. And (3) carrying out scene analysis aiming at a complex environment, after photographing, analyzing a plurality of small pictures which are divided from the pictures, combining the regions with the same color and texture, and finally forming a plurality of large regions. The region comprises a main ship, background sky, ocean and the like, and the shape and the motion state of the ship are observed, wherein the color and the texture which are different from the environment are the expression of the characteristic value of the ship. And setting and training a classifier according to the characteristic values of the ship to identify and track the ship. When training the classifier, can input various pictures, the main part can have tank, aircraft, car, ship etc. in the picture. The scene also has sea surface conditions in a wide sea area, heavy fog weather, storm and other various weather. The purpose of training a classifier is to distinguish ships from environments in a complex environment and to efficiently identify and track the hulls of the ships. The feedback mechanism is used for checking whether the characteristic value division of the ship is correct or not, and if the characteristic value division is incorrect, the characteristic value needs to be modified.
And distributing the unmanned boats according to the number and the types of the objects to be tracked, interrupting the formation and the task which are being executed by the distributed unmanned boats, and carrying out cluster tracking and capturing on the objects to be tracked. In this embodiment, three unmanned boats are allocated to capture the object to be tracked. As shown in fig. 4, the first unmanned ship that finds the enclosure object is set as ship No. 1, and then sequentially numbered according to the distance from ship No. 1, and the ship adjacent to ship No. 1 and closer to it is ship No. 2, and the other adjacent unmanned ship is ship No. 3. And (3) the No. 2 ship and the No. 3 ship adjacent to the No. 1 ship are separated from the original formation and formation, and the preparation for tracking the enclosure objects is carried out. Meanwhile, a virtual leader in the unmanned ship is arranged on a connecting line between the No. 1 ship and the horizontal plane of the enclosure object and d meters away from the No. 1 ship of the unmanned ship.
Wherein the virtual leader range d is set to a value of,To find a safe distance for collision avoidance between an unmanned boat surrounding an object and an adjacent surrounding unmanned boat.
Searching an established ship type database according to the ship type or the ship structure to which the mark on the identified enclosure object belongs, and if a matched ship type is found, establishing an effective and accurate kinematic model and model power parameters according to the data of the enclosure object in the database; if not found, a surrounding object kinematic model is constructed in real time according to the detected draft, yaw angle, course, speed and acceleration.
And establishing mutual relation between the virtual leader and the enclosure object, and making changes synchronous with the enclosure object by the virtual leader at intervals according to the navigational speed and the course angle of the enclosure object. Referring to FIG. 3, a horizontal non-inertial motion coordinate system is established, with the gravity center of the virtual leader as the origin of coordinates, the forward direction of the virtual leader as the positive direction of the y-axis of the ordinate, and the direction perpendicular to the y-axis to the right as the positive direction of the horizontal x-axis, perpendicular to the y-axisThe plane is horizontally downward and is in the positive direction of the z axis (namely, the plane points to the sea surface vertically and is in the positive direction of the z axis), and the stress condition of the enclosure object is analyzed according to the image display so as to judge the motion state of the enclosure object:
wherein,。is the actual mass of the vessel when in motion,respectively representing the transverse speed, the longitudinal speed and the yaw rate of the ship body at the coordinate origin O;representing the coordinates of the vessel relative to the origin of coordinates O,respectively representing the moment of inertia of the point O around the z axis and the moment of inertia of the point G around the z axis;respectively represents the total external moment of the point O around the z-axis and the rotating torque of the point G,respectively representing the components of the external force on the tracked object in the x axis and the y axis;
and according to the detected speed, position, mass and torque of the enclosure object, the virtual leader makes a change synchronous with the motion state of the enclosure object.
No. 1, No. 2, No. 3 unmanned ship collaborative operation, trace and chase after the object to chasing after to enclosing, and to chasing after the object tracking control.
The speed of the unmanned boats No. 1, No. 2 and No. 3 is automatically controlled to avoid collision. Specifically, an inertial coordinate system is established by using a two-dimensional space of a horizontal plane, and the unmanned ships No. 1, No. 2 and No. 3 and the virtual leader are ensured to be in a first quadrant of the coordinate system.
According to the dynamic principle, the unmanned boat collaborative control model is as follows, and if 3 collaborative unmanned boats are provided,= 1,2,3, its schematic kinematic equation is:
wherein,is an unmanned boatA position vector of (a);is an unmanned boatIs determined by the velocity vector of (a),is an unmanned boatThe control input of (2) is decomposed into two components:,is an unmanned boatThe control quantity generated by artificial potential energy depends on the distance between two adjacent ships, and the functions of avoiding collision and polymerization are achieved.Depending on the average speed of the surrounding ships, reflecting unmanned shipsThe control amount of the self speed. No. 1, No. 2 and No. 3 unmanned boats automatically adjust targets such as course, navigational speed and the like to synchronizeThe motion state of the virtual leader is specifically as follows:
setting the initial course and the navigation speed of the virtual leader according to the established kinematic model of the enclosure objectInitial position. And designing a control algorithm to enable the unmanned ship to adjust the course and the speed to follow the virtual leader. The motion equation is
Is the input of the core control, and the core control,。is based onAnd the relative distance between the unmanned ship and the virtual leader determines an artificial potential field function.Is to adjustThe speed of the individual unmanned boat with the virtual leader to follow the virtual leader.
The navigation speed and the course of the virtual leader do not need to be changed within a certain time interval, and self-regulation is carried out according to the relative navigation speed and the course of the chasing object after the certain time interval.
The artificial potential field method has the core idea that the moving surrounding environment is abstracted into an artificial force field, the target point generates attraction force on the unmanned ship, and the obstacle generates repulsion force on the unmanned ship. As required by designThe potential energy function controls the quantity.
And when the virtual leader and the enclosure object coincide with the G point in the moving coordinate system, the strategy is changed. At this time, clustering between the unmanned ships and the virtual leader is realized, and an effective tracking strategy is carried out on the enclosure objects.
And in a safe and effective tracking range from the enclosure object, resetting the distance between the unmanned ship and the virtual leader, which is also equal to the distance between the unmanned ship and the enclosure object. And modifying artificial potential field control of previously constructed control inputsIn part, the enclosure of the object starts.
Setting an artificial potential energy function control input to an unmanned vehicle following a virtual leaderThe potential energy of all unmanned boats is enabled to reach the minimum overall potential energy on a circle with a distance radius R. In order to minimize the overall potential energy, the unmanned boats are clustered and change the speed, and the surrounding objects are detoured while the distance between the two boats is kept.
The object to be tracked is warned to slow down. After the enclosure object stops, the enclosure object is used as the center, the distance R is used as the radius, and the unmanned boat runs around anticlockwise to achieve the purpose of enclosing the enclosure object and achieve circular formation. If the enclosure objects keep running at a constant speed, the unmanned boat carries out inverted V-shaped formation. If the object to be tracked does not run at an accelerated speed, the unmanned ship clustering is carried out again.
The above description is only a preferred embodiment of the present invention, and for those skilled in the art, the present invention should not be limited by the description of the present invention, which should be interpreted as a limitation.
Claims (8)
1. A distributed control unmanned ship cluster enclosure tracking method is characterized by comprising the following steps:
sensing and detecting the enclosure object, distributing the unmanned ship, and setting a virtual leader in the unmanned ship;
identifying the mark and the whole structure of the enclosure object, and establishing a kinematic model of the enclosure object;
the unmanned ships cooperatively work to cluster the unmanned ships and track the tracked objects;
and identifying the motion coordinate systems of the virtual leader and the enclosure object in real time until the virtual leader is coincided with the motion coordinate systems of the enclosure object, and performing enclosure capture on the enclosure object by cooperating with the unmanned ship.
2. The distributed control unmanned ship cluster pursuit tracking method according to claim 1, characterized in that, the object of pursuit is sensed and detected, unmanned ships are allocated, and the virtual leader in the unmanned ships is specifically set as:
acquiring information of a water area environment in real time by using an environment sensing technology, and carrying out scene analysis on the water area environment;
establishing a multi-source information fusion model by using a multi-source data processing and information fusion method, and identifying the enclosure object;
distributing different numbers of unmanned boats according to the number and types of the objects to be tracked, wherein each object to be tracked is at least matched with three unmanned boats to be tracked; firstly, detecting an unmanned boat enclosing an object, and enclosing the object by at least two adjacent unmanned boats;
and setting a virtual leader outside a certain range d from the direction of tracking the enclosure object to the unmanned ship which firstly detects the enclosure object.
3. The distributed control unmanned ship cluster chasing tracking method according to claim 2, wherein the scene analysis specifically comprises:
collecting a picture of a scene, dividing the picture into a plurality of small pictures, and merging regions with the same color and texture in the small pictures;
extracting colors and textures which are different from the environment in the picture area as characteristic values of the ship;
setting and training a classifier according to the characteristic value of the ship to identify and track the ship;
and checking whether the characteristic value division of the ship is correct or not by using a feedback mechanism.
4. The distributed control unmanned ship cluster chasing tracking method according to claim 1, wherein the building of the kinematic model of the chasing object is specifically:
identifying the mark and the whole structure of the enclosure object, and searching the enclosure object data in the established ship type database;
if the matched ship type is found, establishing a kinematic model and a model power parameter according to the ship type;
and if the matched ship type is not found, constructing a surrounding object kinematic model in real time according to the detected draft, yaw angle, course, navigational speed and acceleration.
5. The distributed control unmanned ship cluster enclosure tracking method according to claim 2, wherein the enclosure around the enclosure object by the unmanned ship is specifically:
the unmanned ship tracks the enclosure object and identifies a virtual leader and an enclosure object motion coordinate system in real time;
if the virtual leader is overlapped with the motion coordinate system of the enclosure object, setting the distance between the cooperative unmanned ship and the virtual leader to be equal to the distance between the cooperative unmanned ship and the enclosure object; if the virtual leader does not coincide with the motion coordinate system of the enclosure object, the unmanned ship continues to keep a distance d with the virtual leader to track the enclosure object;
setting artificial potential energy function control input, enabling the unmanned boat to detour the tracked object by the radius R with the overall potential energy reaching the minimum, and simultaneously keeping the distance between the unmanned boats;
warning the enclosure object and judging the state of the enclosure object, if the enclosure object stops, taking the enclosure object as the center and the distance R as the radius, and enabling the unmanned ship to run around anticlockwise; if the enclosure pursuit object keeps running at a constant speed, the unmanned boat carries out inverted V-shaped formation and tracking; and if the tracked object runs at an accelerated speed, clustering the unmanned boats again.
6. The distributed control unmanned ship cluster pursuit tracking method according to claim 1, further comprising the step of the virtual leader making a change synchronized with the motion state of the pursuit object according to the motion state of the pursuit object during the process of tracking the pursuit object by the unmanned ship, specifically:
establishing a horizontal plane non-inertial motion coordinate system, taking the gravity center of the virtual leader as the origin of coordinates, the advancing direction of the virtual leader as the positive direction of a y axis of a vertical coordinate, and the rightward direction perpendicular to the y axis as the positive direction of a horizontal x axis, which is perpendicular to the Y axisThe horizontal downward direction of the plane is the positive direction of the z axis, and the stress condition of the enclosure object is analyzed according to the image display so as to judge the motion state of the enclosure object:
is the actual mass of the vessel when in motion,respectively representing the transverse speed, the longitudinal speed and the yaw rate of the ship body at the coordinate origin O;representing the coordinates of the hull relative to the origin of coordinates O,respectively representing the moment of inertia of the point O around the z axis and the moment of inertia of the point G around the z axis;respectively represents the total external moment of the point O around the z-axis and the rotating torque of the point G,respectively representing the components of the external force on the tracked object in the x axis and the y axis;
and according to the detected speed, position, mass and torque of the enclosure object, the virtual leader makes a change synchronous with the motion state of the enclosure object.
7. The distributed control unmanned ship cluster enclosure tracking method according to claim 1, further comprising that each unmanned ship automatically controls its own speed to avoid collision during the process of enclosing the enclosure object, specifically:
establishing a two-dimensional space inertial coordinate system of a horizontal plane so that the collaborative unmanned ship and the virtual leader are located in a first quadrant of the coordinate system;
the unmanned ship automatically analyzes and controls the speed of the unmanned ship: the number of the cooperative unmanned boats is N,the exercise condition is as follows:
is the position vector of the unmanned boat;is the velocity vector of the unmanned boat;is a control input, which is decomposed into two components:,is a controlled quantity generated by artificial potential energy,is the control quantity of the self speed, and T represents the transposition of the vector in mathematics.
8. The distributed control unmanned ship cluster chasing tracking method according to claim 1, further comprising adjusting a heading and a speed in coordination with the unmanned ships to synchronize the motion state of the virtual leader, specifically: establishing a kinematic model of the object to be tracked, and setting the initial course and the navigational speed of the virtual leaderInitial position,
Is the input of the core control, and the core control,,is based onAn artificial potential field function determined by the distance of the unmanned ship from the virtual leader,is to adjustSpeed of the individual unmanned boat and the virtual leader.
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Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
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Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105182973A (en) * | 2015-09-08 | 2015-12-23 | 郑州大学 | Self-adaptive hunting device using multiple robot pursuers to hunt single moving target and method |
US20160334230A1 (en) * | 2015-05-13 | 2016-11-17 | Uber Technologies, Inc. | Providing remote assistance to an autonomous vehicle |
CN106774331A (en) * | 2016-12-30 | 2017-05-31 | 广东华中科技大学工业技术研究院 | A kind of distributed AC servo system unmanned boat cluster sub-clustering formation method |
CN107085427A (en) * | 2017-05-11 | 2017-08-22 | 华南理工大学 | A kind of unmanned water surface ship formation control method for following structure based on leader |
-
2017
- 2017-09-04 CN CN201710785585.6A patent/CN107608347B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160334230A1 (en) * | 2015-05-13 | 2016-11-17 | Uber Technologies, Inc. | Providing remote assistance to an autonomous vehicle |
CN105182973A (en) * | 2015-09-08 | 2015-12-23 | 郑州大学 | Self-adaptive hunting device using multiple robot pursuers to hunt single moving target and method |
CN106774331A (en) * | 2016-12-30 | 2017-05-31 | 广东华中科技大学工业技术研究院 | A kind of distributed AC servo system unmanned boat cluster sub-clustering formation method |
CN107085427A (en) * | 2017-05-11 | 2017-08-22 | 华南理工大学 | A kind of unmanned water surface ship formation control method for following structure based on leader |
Non-Patent Citations (1)
Title |
---|
林子键等: "多机器人编队围捕算法研究", 《计算机仿真》 * |
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