CN107168335B - Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance - Google Patents
Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance Download PDFInfo
- Publication number
- CN107168335B CN107168335B CN201710504472.4A CN201710504472A CN107168335B CN 107168335 B CN107168335 B CN 107168335B CN 201710504472 A CN201710504472 A CN 201710504472A CN 107168335 B CN107168335 B CN 107168335B
- Authority
- CN
- China
- Prior art keywords
- obstacle
- obstacle avoidance
- dynamic
- boat
- guidance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 10
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 67
- 230000008569 process Effects 0.000 claims abstract description 18
- 230000007704 transition Effects 0.000 claims abstract description 18
- 238000011217 control strategy Methods 0.000 claims abstract description 8
- 238000012163 sequencing technique Methods 0.000 claims abstract description 7
- 230000003068 static effect Effects 0.000 claims description 40
- 238000001514 detection method Methods 0.000 claims description 29
- 230000004888 barrier function Effects 0.000 claims description 11
- 230000033001 locomotion Effects 0.000 claims description 11
- 238000005070 sampling Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 6
- 238000013178 mathematical model Methods 0.000 claims description 6
- 102100029469 WD repeat and HMG-box DNA-binding protein 1 Human genes 0.000 claims description 4
- 101710097421 WD repeat and HMG-box DNA-binding protein 1 Proteins 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000014509 gene expression Effects 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 10
- 238000009395 breeding Methods 0.000 description 4
- 230000001488 breeding effect Effects 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 241000233948 Typha Species 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000013016 damping Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 230000007480 spreading Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 208000034699 Vitreous floaters Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/0206—Control of position or course in two dimensions specially adapted to water vehicles
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/12—Target-seeking control
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a hybrid multi-target obstacle avoidance-considered water surface unmanned ship path tracking guidance method, which divides a guidance process into two modes of path tracking and obstacle avoidance operation guidance, takes an improved DVS guidance algorithm as a basic framework, dynamically plans a smooth reference path consisting of straight lines and curves by a GVS, and respectively corresponds to different guide variables of the DVS in a path tracking mode and an obstacle avoidance operation mode. For obstacle avoidance guidance of a plurality of or mixed obstacles, firstly, a current obstacle avoidance target is judged and determined according to priority sequencing and obstacle avoidance operation conditions, an obstacle avoidance operation mode is started, and a transition function ensures smoothness of a DVS guide variable among different mode switching. The method has applicability to various control strategies, is convenient to combine with the existing advanced control algorithm, and the control algorithm plays a role in ensuring the convergence of a real ship on the DVS and ensuring the effectiveness of a guidance strategy.
Description
Technical Field
The invention relates to the field of ship control engineering and automatic navigation of ships, in particular to a hybrid multi-target obstacle avoidance-considering unmanned surface vehicle path tracking guidance method.
Background
The key technology for controlling the motion of the ship is to realize track keeping and collision/obstacle avoidance of the ship through a guidance strategy. The guidance algorithm for ship path tracking is mainly a visual distance (LOS) guidance algorithm and a dynamic virtual small ship (DVS) guidance algorithm which are widely applied at present. The obstacle avoidance algorithm can use the control of a mobile robot and a land trolley for reference, and adopts an obstacle avoidance algorithm based on a nonlinear control theory stable limit cycle (stable limit cycles) concept, namely a limit cycle obstacle avoidance algorithm. A guidance strategy combining the guidance algorithm for ship path tracking and an obstacle avoidance algorithm becomes a hotspot studied in recent years. The guidance strategy of the existing path tracking ship guidance algorithm and the limit-ring obstacle avoidance algorithm in combination is briefly introduced below.
Document [1]]The guidance strategy of the LOS guidance algorithm combined with the obstacle avoidance algorithm is given, the basic principle of the LOS guidance algorithm is shown in figure 1, under the premise that the forward distance ▽ is fixed, the LOS guidance algorithm is based on the position of a real ship and a point A on a straight line reference pathFThe geometric relation between the two points obtains the path tracking expected yaw angle psi of each sampling time pointlosForward speed upKeeping the position unchanged, and further guiding the ship to realize the tracking of the straight reference path. The guidance strategy enables the real ship index to converge on the reference straight line path.
In FIG. 1, Pi-1PiFor the straight path currently tracked by the real ship, d is the distance from the real ship to the perpendicular of the path, and (x, y) is the current position coordinate of the real ship, then:
considering the under-actuated characteristic of a real ship, introducing the compensation of drift angle into the expected heading angle, and obtaining the path tracking expected heading angle:
when the ship enters the waypoint PiWhen the ship turns to the boundary ring (circle of arrival), the tracking path of the ship is switched to PiPi+1。
From the above derivation it can be seen that: the LOS guidance algorithm does not have a path planning function at the turning point, and failure of the guidance algorithm occurs if an obstacle is encountered at the turning point. Meanwhile, the algorithm does not meet the assumption that all reference paths can be generated by a virtual boat, and is difficult to combine with related research results of path tracking control.
When a single ship meets, the position of the ship relative to a real ship is sensed through a detection ring virtually defined on the meeting ship. In the path tracking mode, if the obstacle avoidance control condition is met, the real ship is switched from the path tracking mode to the obstacle avoidance control mode, and the forward motion is changed from upAccelerating to the obstacle avoidance speed uoaAnd according to the expected heading angle psioaThe navigation is guided. The expected obstacle avoidance heading angle can guide the real ship to converge on a stable safety limit ring with the meeting ship radius smaller than the detection radius, so that the safety distance between the real ship and the meeting ship is ensured. The parameter description of the obstacle avoidance strategy is shown in fig. 2, wherein G denotes a reference path.
As shown in FIG. 2, the detection ring has a radius RmSafe limit ring radius of RoAnd when the real ship enters the detection ring, if the ship arrival distance sigma of the real ship meets the following obstacle avoidance control condition, starting an obstacle avoidance control mode.
As can be seen from the obstacle avoidance strategy geometry shown in fig. 2:
obstacle avoidance expectation heading angle psi under obstacle avoidance control modeoaThe following are selected:
in the formula (5), the error e ═ σ -Ro(ii) a Δ is a forward distance (lookup distance) manually set in the obstacle avoidance operation mode; lambda is selected to be +/-1 according to the requirements of COLREGs, wherein +1 represents that the safety limit ring is encircled in a clockwise direction, and-1 represents that the safety limit ring is encircled in a counterclockwise direction; k is used for compensating the meeting ship motion to the heading angle psioaThe resulting effect, defined as:
wherein the content of the first and second substances,
the obstacle avoidance strategy ensures that the obstacle avoidance speed meets uoa≥uc≥V0。
Under the precondition that the control algorithm can ensure the effective convergence of the actual heading angle and the actual advancing speed of the actual ship to the expected heading angle and the advancing speed, the guidance strategy switches back and forth between a path tracking mode and an obstacle avoidance control mode according to the position of the current obstacle and the obstacle avoidance control condition. When two ships meet, a collision avoidance task is executed firstly, the selection strategy of the obstacle avoidance expected yaw angle can ensure that the real ship converges on the safety limit ring of the coming ship, and when the obstacle avoidance operation condition is not met, the real ship returns to the path tracking task of the straight line reference path from the beginning. Correspondingly, the expected forward speed of the real ship is also switched according to different mission modes. The execution of the guidance strategy is shown in the flow chart of fig. 3.
The method has the advantage of being very important to have the curve segment path planning capability. For the path tracking control part, not only a straight reference path needs to be planned, but also a curve segment path needs to be planned near a turning point; for the obstacle avoidance control part, the position of the obstacle is uncertain, so that the curve segment path planning is particularly important for the effectiveness of obstacle avoidance.
In addition, the ship obstacle avoidance/collision avoidance behavior mainly occurs in complex marine environments such as narrow busy water channels or fishing boat operation areas, and the like, and the obstacle avoidance strategy should cope with various obstacle avoidance/collision avoidance conditions as much as possible and have multi-adaptability so as to reflect the requirement of highly intelligent navigation of the ship.
Meanwhile, the effectiveness of ship path tracking and obstacle avoidance guidance is ensured only by a control strategy, and a guidance algorithm is convenient to combine with a control algorithm.
Therefore, the LOS guidance algorithm described in the document [1] combines the drawbacks of the guidance strategy of obstacle avoidance control, and is summarized as follows:
(1) the guidance algorithm is established based on the LOS path tracking guidance algorithm, so that the defects of the LOS guidance algorithm are overcome. The algorithm does not have a path planning function at a turning point, and if an obstacle is encountered at the turning point, the guidance algorithm fails; the algorithm does not meet the assumption that all reference paths can be generated by a virtual boat, and is difficult to combine with the research results related to the path tracking control of the under-actuated ship.
(2) The guidance algorithm does not have the function of avoiding obstacles on multiple obstacles, is only suitable for the situation of meeting and avoiding collision of a single ship, and is not suitable for obstacle avoidance control under the complex marine environment and on a high-speed ship. In addition, the switching process of the path tracking mode and the obstacle avoidance control mode of the guidance algorithm has steps, and the switching process is not smooth.
Reference to the literature
[1]S.Moe,K.Y.Pettersen.Set-Based Line-of-Sight(LOS)Path Followingwith Collision Avoidance for Underactuated Unmanned Surface Vessel[C].24thMediterrean Conference on Control and Automation,2016:402-409.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a DVS guidance algorithm which is convenient to combine with a control algorithm and has the capacity of planning a curve segment path, and the guidance algorithm not only overcomes the defects of an LOS guidance algorithm, but also meets the time requirement of path tracking to a certain extent. In addition, the invention sets collision avoidance priority and corresponding heading angle and speed planning strategies, and realizes effective obstacle avoidance of the ship on multiple static obstacles, multiple dynamic obstacles and mixed obstacles.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance comprises the following steps:
s1: setting waypoint information W1,W2,…,WnRespectively establishing a motion mathematical model of a guide virtual boat and a dynamic virtual boat;
s2: the method comprises the steps that a guide virtual boat plans a reference path according to a guidance algorithm, always runs along the reference path, starts a path tracking guidance mode, leads the heading angle of the dynamic virtual boat to be equal to the true azimuth angle of the guide virtual boat relative to the dynamic virtual boat at the moment, sends a guidance command to a real boat to guide the real boat to track the path, and continuously obtains a guidance variable of the dynamic virtual boat by the real boat;
s3: sampling is carried out at a sampling time point, whether the dynamic virtual boat enters an obstacle detection ring or not is judged, if the dynamic virtual boat enters the obstacle detection ring, an obstacle sequencing process is carried out, and S4 is executed; if the obstacle detection loop is not entered, keeping the path tracking guidance mode, and executing S6;
s4: entering an obstacle ordering process: sorting the priorities of the obstacle avoidance objects to obtain a priority sequence of the obstacles, selecting the obstacle with the highest priority as a current obstacle avoidance target, judging whether the current obstacle avoidance target meets obstacle avoidance operation conditions, and if the current obstacle avoidance target meets the obstacle avoidance operation conditions, entering an obstacle avoidance guidance mode for the current obstacle, namely executing S5; if the current obstacle avoidance target does not meet the obstacle avoidance control condition, selecting the obstacle with the secondary priority as the current obstacle avoidance target; if all the obstacles do not meet the obstacle avoidance control condition, entering a path tracking mode and executing S6;
s5: entering an obstacle avoidance guidance mode: judging whether the obstacle avoidance control condition of the current obstacle is met or not at each sampling time point, if so, starting an obstacle avoidance guidance mode for the current obstacle, acquiring a guidance variable of the dynamic virtual boat, and guiding the real boat; if the obstacle avoidance control condition is not met, removing the current obstacle from the obstacle priority sequence, and executing S4;
s6: adjusting the input of an actuator of the real ship in real time according to the guide variable and the control strategy of the dynamic virtual small ship, and controlling the real ship to track the dynamic virtual small ship;
s7: and measuring the position of the real ship, judging whether the real ship reaches the terminal, if so, ending the navigation of the ship, and if not, executing S2.
Further, in S1, the expressions of the mathematical models of the motions of the guided virtual boat and the dynamic virtual boat are:
wherein d represents a dynamic virtual boat, g represents a guiding virtual boat, and (x, y) are position coordinates,
respectively the first derivative of the distance, psi the heading angle, u the forward speed and r the heading angular speed.
Further, in S4, the method for generating the obstacle priority sequence includes:
s41: dividing the obstacles into static obstacles and dynamic obstacles, wherein the priority of the static obstacles is higher than that of the dynamic obstacles;
s42: the priority of the static obstacles is inversely proportional to the distance e from the dynamic virtual boat to the safety limit ring of the static obstacles, and the obstacle with the minimum e has the highest priority;
s43: the priority of the dynamic obstacle is determined by the following formula
Wherein F is an evaluation function, RmRadius of the obstacle-detecting ring, RoIs the radius of the safety limit cycle, e is the distance from the dynamic virtual boat to the safety limit cycle of the dynamic barrier,
the derivative of the distance of the dynamic virtual boat from the obstacle in the path tracking mode, udoThe obstacle avoidance speed of the dynamic virtual boat is represented as a constant, the value of the constant is larger than the speed of all dynamic obstacles,
is a weight parameter.
Further, in S4, the obstacle avoidance operation conditions are divided into obstacle avoidance operation conditions for a static obstacle and obstacle avoidance operation conditions for a dynamic obstacle, where the obstacle avoidance operation conditions for the static obstacle are: the heading of the dynamic virtual boat is between two tangent lines of a safety limit ring from the dynamic virtual boat to the static barrier; the obstacle avoidance control condition for the dynamic obstacle is the following formula:
wherein, sigma is the distance between the dynamic virtual boat and the dynamic obstacle, RoRadius of the ultimate safety ring for dynamic obstacles, RmThe radius of the detection ring for a dynamic obstacle,
is the derivative of the dynamic virtual boat to dynamic obstacle distance in path tracking mode.
Further, when the path tracking guidance mode and the obstacle avoidance guidance mode are switched and when the obstacle avoidance guidance modes of different obstacles are switched, the following time transition functions are adopted:
wherein α (t) is a time transition function, tcTo initiate a switching time point, tsIs a manually set transition time.
Further, in the obstacle avoidance guidance mode described in S5, the speed u of the dynamic virtual boatdAdjusting the heading angle to be the obstacle avoidance speed, and selecting the heading angle according to the following method:
s51: if the current obstacle avoidance target is a static obstacle, then
Wherein psidoThe heading angle of the dynamic virtual boat in the obstacle avoidance guidance mode is shown, phi is the true azimuth angle of the static obstacle relative to the dynamic virtual boat, and delta is the set forward distanceλ ═ 1 determines the direction around the static obstacle when the dynamic virtual boat avoids the obstacle, +1 is the safety limit ring around the static obstacle in the clockwise direction, -1 is the safety limit ring around the static obstacle in the counterclockwise direction;
s52: if the current obstacle avoidance target is a dynamic obstacle, then
Wherein, phi is the true azimuth angle of the dynamic obstacle relative to the dynamic virtual boat, delta is the set forward distance, k is the compensation parameter, lambda is + -1, +1 is the safety limit ring surrounding the dynamic obstacle clockwise, and-1 is the safety limit ring surrounding the dynamic obstacle counterclockwise.
Further, in S2, the guiding variables of the dynamic virtual boat include a heading angle ψdAnd a forward speed udThe heading angle psidThe calculation formula of (2) is as follows:
wherein g represents GVS, d represents DVS, and (x, y) are position coordinates;
forward speed udThe calculation formula of (2) is as follows:
wherein k isdFor setting parameters for adjusting the convergence rate, ldgFor dynamic virtual boat to guided virtual boat distance, ugFor guiding the forward speed of the virtual boat,. psigFor guiding the heading angle, psi, of the virtual boatdFor dynamic virtual boat heading angle,/dbsetFor the upper limit setting of the distance from the real ship to the dynamic virtual boat,/dbThe distance from the real ship to the dynamic virtual boat.
Further, in S3, the radius R of the obstacle detection ringmDetermining the obstacle according to the size of the obstacleThe larger the product, the larger the value.
According to the technical scheme, the guidance process is divided into two modes of path tracking and obstacle avoidance operation guidance, the improved DVS guidance algorithm is used as a basic framework, the smooth reference path composed of straight lines and curves is dynamically planned by the GVS, and the path tracking mode and the obstacle avoidance operation mode respectively correspond to different guide variables of the DVS. For obstacle avoidance guidance of a plurality of or mixed obstacles, firstly, a current obstacle avoidance target is judged and determined according to priority sequencing and obstacle avoidance operation conditions, an obstacle avoidance operation mode is started, and a transition function ensures smoothness of a DVS guide variable among different mode switching. The method has applicability to various control strategies, is convenient to combine with the existing advanced control algorithm, and the control algorithm plays a role in ensuring the convergence of a real ship on the DVS and ensuring the effectiveness of a guidance strategy.
Drawings
FIG. 1 is a basic schematic diagram of a LOS guidance algorithm in the prior art;
FIG. 2 is a schematic diagram of a prior art obstacle avoidance strategy for a single ship encounter;
FIG. 3 is a flow chart of a prior art guidance algorithm for LOS path tracking and obstacle avoidance;
FIG. 4 is a basic schematic diagram of the improved DVS guidance algorithm of the present invention;
FIG. 5 is a schematic diagram of a multi-static-target obstacle avoidance situation;
FIG. 6 is a schematic diagram of a multi-dynamic target obstacle avoidance situation;
FIG. 7 is a schematic diagram of a hybrid multi-target obstacle avoidance scenario;
FIG. 8 is a parameter diagram of a hybrid multi-target obstacle avoidance scenario of the present invention;
FIG. 9 is a flow chart of the water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance of the present invention;
FIG. 10 is a schematic view of a "spread" ship of the university of maritime teaching practice ship;
FIG. 11 is a schematic view of a three-dimensional wave surface for the Pufu wind, class 6 sea state;
fig. 12 to 15 are actual ship trajectory diagrams when t is 240s,290s,345s, and 600s, respectively;
FIG. 16 is a plot of the time variation of the DVS pilot variable in one embodiment;
FIG. 17 is a plot of control input versus pitch P and rudder angle δ over time for one embodiment.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In the following detailed description of the embodiments of the present invention, in order to clearly illustrate the structure of the present invention and to facilitate explanation, the structure shown in the drawings is not drawn to a general scale and is partially enlarged, deformed and simplified, so that the present invention should not be construed as limited thereto.
In the following embodiment of the present invention, please refer to fig. 9, fig. 9 is a flowchart of a hybrid multi-target obstacle avoidance-considered water surface unmanned ship path tracking guidance method of the present invention, and the present invention is further understood with reference to fig. 4 to 8. As shown in fig. 9, the method for tracking and guiding the path of the unmanned surface vehicle considering the hybrid multi-target obstacle avoidance of the invention comprises the following steps:
s1: setting waypoint information W1,W2,…,WnAnd respectively establishing motion mathematical models of the guide virtual boat and the dynamic virtual boat.
S2: and the guiding virtual boat plans a reference path according to a guidance algorithm, always runs along the reference path, starts a path tracking guidance mode, constantly sets the heading angle of the dynamic virtual boat equal to the true azimuth angle of the guiding virtual boat relative to the dynamic virtual boat, sends a guidance command to the real boat to guide the real boat to track the path, and continuously obtains the guidance variable of the dynamic virtual boat by the real boat.
In the above steps, please refer to fig. 4, fig. 4 is a schematic diagram of a guidance algorithm of an improved dynamic virtual boat (DVS). In the guidance algorithm, a guidance virtual boat (GVS) and a DVS are ideal boats without considering inertia force and damping force, only plane motion is considered, and the guidance virtual boat (GVS) and the DVS respectively adopt independent motion mathematical equations as follows:
wherein d represents a dynamic virtual boat, g represents a guiding virtual boat, and (x, y) are position coordinates,
respectively the first derivative of the distance, psi the heading angle, u the forward speed and r the heading angular speed.
GVS based on set waypoint Wi-1,Wi,Wi+1According to the traditional DVS guidance algorithm, a reference path, namely a position and attitude time sequence of the GVS is drawn. The reference path is divided into a straight line reference path part and a curve reference path part at the waypoint, the curve segment reference path is generated by an interpolation method of circular arcs, and the problem that the waypoint accessory cannot guide in the prior art is solved by the curve segment reference path. Setting longitudinal velocity u of GVSrAnd the angular speed r of the bowrAnd the requirement on the performance of the real ship actuator is met, and the real ship sails along the reference path of the straight line and the curve segment according to the kinematic relationship of the formula (7).
In the traditional DVS guidance algorithm, a DVS is generated between a real ship and a GVS and used as a direct tracking target of the real ship, the position of the DVS is fixed on a connecting line of the real ship and the GVS, and the position of the DVS is restrained and is not suitable for multi-target obstacle avoidance/collision avoidance guidance. In order to further meet the requirements of obstacle avoidance/collision avoidance guidance, the DVS guidance algorithm is improved, namely the generation of the DVS is not limited by the GVS and the position of a real ship any more and is regarded as a target for independent navigation according to the kinematic relationship shown in the formula (7). In Path tracking mode, DVS heading angle time psidChosen as the true azimuth ψ of the GVS relative to the DVSdpI.e. formula (8):
wherein g represents GVS, d represents DVS, and (x, y) are position coordinates.
In order to ensure the exponential convergence of the DVS to the GVS position in the path tracking mode, the path tracking DVS velocity is defined as equation (9) and u is expressed asd＝udp
Wherein k isdFor setting parameters for adjusting the convergence rate, the larger the value is, the larger u isdpThe larger the DVS is, the faster the DVS converges on the GVS, which may result in a larger real vessel actuator input, and therefore should be chosen according to the actuator capability trade-off. ldbsetSetting the upper limit of the distance from the real ship to the DVS, wherein the selection value is also determined by the actuator capacity of the ship, |dgFor dynamic virtual boat to guided virtual boat distance, ugFor guiding the forward speed of the virtual boat,. psigFor guiding the heading angle, psi, of the virtual boatdFor dynamic virtual boat heading angle,/dbThe distance from the real ship to the dynamic virtual boat. As can be seen from equation (9), the DVS path tracking speed and the distance l from the real ship to the DVSdbAnd has a linear relationship. When l isdb＝ldbsetTime, velocity udpThis means that in the path tracking mode, the DVS does not exceed l centered on the real shipdbsetWithin a circle of radius. This setting ensures that in the path tracking mode, excessive actuator input due to the actual vessel being too far from the DVS position does not occur, and the design takes into account the saturation characteristics of the actuator.
As can be seen from the above discussion, the DVS in the improved DVS guidance algorithm is independent, and the DVS attitude command can be adjusted in real time according to the position of the DVS attitude command relative to the obstacle target to implement collision avoidance/obstacle avoidance guidance.
S3: sampling is carried out at a sampling time point, whether the dynamic virtual boat enters an obstacle detection ring or not is judged, if the dynamic virtual boat enters the obstacle detection ring, an obstacle sequencing process is carried out, and S4 is executed; if the obstacle detection loop is not entered, the path tracking guidance mode is maintained, and S6 is executed.
S4: entering an obstacle ordering process: sorting the priorities of the obstacle avoidance objects to obtain a priority sequence of the obstacles, selecting the obstacle with the highest priority as a current obstacle avoidance target, judging whether the current obstacle avoidance target meets obstacle avoidance operation conditions, and if the current obstacle avoidance target meets the obstacle avoidance operation conditions, entering an obstacle avoidance guidance mode for the current obstacle, namely executing S5; if the current obstacle avoidance target does not meet the obstacle avoidance control condition, selecting the obstacle with the secondary priority as the current obstacle avoidance target; if all the obstacles do not satisfy the obstacle avoidance operation condition, the method enters a path tracking mode, and S6 is executed.
S5: entering an obstacle avoidance guidance mode: judging whether the obstacle avoidance control condition of the current obstacle is met or not at each sampling time point, if so, starting an obstacle avoidance guidance mode for the current obstacle, acquiring a guidance variable of the dynamic virtual boat, and guiding the real boat; if the obstacle avoidance manipulation condition is not satisfied, the current obstacle is removed from the obstacle priority sequence, and S4 is executed.
S6: and adjusting the input of an actuator of the real ship in real time according to the guide variable and the control strategy of the dynamic virtual small ship, and controlling the real ship to track the dynamic virtual small ship.
In the above process, a determination is first made as to whether the DVS enters the obstacle detection loop. And if the obstacle avoidance task enters the obstacle avoidance system, changing the path tracking guidance mode into an obstacle avoidance guidance mode, and sequencing obstacle avoidance priorities of the obstacles according to the types and the numbers of the obstacles in the obstacle avoidance guidance mode to sequentially complete the obstacle avoidance task.
In order to facilitate the sorting of the obstacle avoidance priorities, the obstacle avoidance task is divided into three obstacle avoidance situations (H in fig. 5 represents a static obstacle, and I in fig. 6 represents a dynamic obstacle) as shown in fig. 5 to 7: the method comprises the steps of respectively obtaining a multi-static target obstacle avoidance situation, a multi-dynamic target obstacle avoidance situation and a mixed multi-target obstacle avoidance situation. The multi-target obstacle avoidance situation refers to that the DVS is located in a detection ring of a plurality of obstacles. Since the control algorithm will ensure that a real ship converges quickly to the DVS, it is reasonable to assume that the DVS has the capability to detect obstacles. The invention avoids the obstacles one by distributing the priorities of the obstacles, and does not consider other obstacles when avoiding the obstacles with the highest priority. Because the guidance strategy can ensure the safety of DVS fast converging to the obstacleLimit ring (with radius R as shown in FIG. 8)oSolid circles) and there is also a safety distance between obstacles (such as between multiple ships and between a ship and an island), i.e., there is no intersection between safety limit rings of the obstacles, so that when the DVS avoids an obstacle, it is not interfered by other obstacles. Radius R of the obstacle detecting ring shown in fig. 8mAnd radius R of the safety limit ringoThe larger the obstacle, the larger its value, determined by the size of the obstacle. In fact, the obstacle detection loop and the safety limit loop are one embodiment of the detection capability of a real ship. The invention provides that multiple static obstacle avoidance determine the priority of static obstacles according to the distance e from the DVS to the safety limit ring shown in FIG. 8, the obstacle with the minimum e has the highest priority, and so on; for multi-dynamic obstacle avoidance, the priority is determined according to the maximization principle of the evaluation function, and the formula of the evaluation function is as follows:
wherein F is an evaluation function, RmRadius of the obstacle-detecting ring, RoIs the radius of the safety limit cycle, e is the distance from the dynamic virtual boat to the safety limit cycle of the dynamic barrier,
the derivative of the distance of the dynamic virtual boat from the obstacle in the path tracking mode, udoThe obstacle avoidance speed of the dynamic virtual small ship is represented as a constant, and the value of the constant is greater than the speed of all dynamic obstacles, so that the obstacle avoidance effectiveness is ensured, and meanwhile, the requirement on the performance of an actuator of a real ship is met;
the larger the value of the weight parameter, the more important the distance between the DVS and the obstacle in the evaluation function is, the less important the DVS is to the relative speed of the obstacle, and vice versa. For the case of simultaneous static and dynamic obstacles, the guidance strategy dictates that static obstacles have a higher than dynamicAnd the priority ranking is performed on all static obstacles, and then the priority ranking is performed on the dynamic obstacles.
And after the priority order of the obstacles is determined, whether an obstacle avoidance operation mode is started or not is determined according to whether the obstacle avoidance operation conditions are met or not. As shown in fig. 8, for a static obstacle, the obstacle avoidance operation condition is that the heading of the DVS is at a tangent line l1And l2To (c) to (d); for a dynamic obstacle, the obstacle avoidance operation condition is shown as follows:
wherein, sigma is the distance between the dynamic virtual boat and the dynamic obstacle, RoRadius of the ultimate safety ring for dynamic obstacles, RmThe radius of the detection ring for a dynamic obstacle,
is the derivative of the dynamic virtual boat to dynamic obstacle distance in path tracking mode. Namely, when the dynamic virtual boat enters the safety limit ring of the dynamic obstacle, the obstacle needs to be avoided immediately, otherwise, collision can occur; when the dynamic virtual boat enters the detection ring and the derivative of the distance from the dynamic virtual boat to the dynamic obstacle in the path tracking mode is less than 0, the danger of collision is indicated, and measures are required to be taken to avoid the collision.
If the obstacle with higher priority does not meet the obstacle avoidance control condition, the algorithm turns to search the obstacle avoidance control condition with the next priority; if all the obstacles do not meet the obstacle avoidance control condition, the algorithm keeps the path tracking mode unchanged; and if the current priority barrier meets the obstacle avoidance operation condition, starting an obstacle avoidance operation mode. And at each sampling time point after the obstacle avoidance operation mode is started, the guidance algorithm does not sort the priorities of the obstacles any more, only judges whether the obstacle avoidance operation condition of the current obstacle is still met, exits the obstacle avoidance operation mode if the obstacle avoidance operation condition of the current obstacle is not met, judges the relative position of the DVS and the obstacle, restarts priority sorting if the DVS is in the obstacle detection ring, and otherwise starts the path tracking mode.
In the obstacle avoidance maneuver mode, firstly, the DVS speed udCan be adjusted to the target obstacle avoidance speed udo. Selecting an obstacle avoidance DVS heading angle of the static obstacle target as follows:
wherein psidoThe heading angle of the dynamic virtual boat in the obstacle avoidance guidance mode, phi is the true azimuth angle of the static obstacle relative to the dynamic virtual boat, and delta is the set forward distance, the smaller the value is, the faster the convergence speed of the DVS to the limit ring is, so that the steering amplitude of the real boat is possibly larger, and the dynamic virtual boat can be flexibly selected according to the steering capacity of the real boat. λ ═ 1 determines the direction of the surrounding static obstacle, +1 is the safety limit cycle clockwise around the static obstacle, -1 is the safety limit cycle counter-clockwise around the static obstacle.
Selecting an obstacle avoidance DVS heading angle of the dynamic obstacle target as follows:
wherein phi is the true azimuth angle of the dynamic obstacle relative to the dynamic virtual boat, delta is the set forward distance, k is the compensation parameter, which is defined by the same formula (6), V0＝uccos(π-φ+θ)，ucAs is the speed of the current dynamic obstacle,
λ ═ 1, +1 is the safety limit cycle that surrounds the dynamic obstacle clockwise, -1 is the safety limit cycle that surrounds the dynamic obstacle counterclockwise. When the dynamic barrier is a single ship, the lambda is selected to meet the requirements of international maritime collision avoidance rules (COLREGs), and when the dynamic barrier is other, such as floaters and the like, the lambda is selected according to the following principle:
wherein psidpTo guide the true azimuth of the virtual boat relative to the dynamic virtual boat,
is the true azimuth of the dynamic obstacle relative to the dynamic virtual boat. When the true azimuth angle of the guiding virtual boat relative to the dynamic virtual boat is less than or equal to the true azimuth angle of the dynamic obstacle relative to the dynamic virtual boat, the lambda is equal to +1, and the dynamic obstacle is surrounded clockwise; and when the true azimuth angle of the guiding virtual boat relative to the dynamic virtual boat is less than or equal to the true azimuth angle of the dynamic obstacle relative to the dynamic virtual boat, the lambda is equal to-1, and the dynamic obstacle is surrounded anticlockwise. The selection principle of the surrounding direction of the obstacle in the formula (14) ensures the minimum surrounding length of the obstacle, and reduces the flight waste.
To guarantee DVS guidance variable (u)d,ψd) The smoothness when two modes of obstacle avoidance control and path tracking are switched and different obstacles are avoided is introduced into a time transition function shown as a formula (15):
wherein α (t) is a time transition function, tcTo initiate a switching time point, tsThe transition time is set manually, and the value of the transition time is selected to ensure that the transition is smooth as far as possible on the premise of not influencing the obstacle avoidance safety performance. By psidFor example, the handover process is shown in equation (16):
ψd(t)＝(1-α)ψd_start+αψd_end(16)
wherein psidWill be at tsStarting heading angle psi from switch-over completed in timed_startHeading angle psi to target moded_endThe transition process is smooth. For udIn other words, the target obstacle avoidance speed udoIs set manually and is not changed for the used obstacles, so udHas a transition of only udp→udo,udo→udpTwo cases.
S7: and measuring the position of the real ship, judging whether the real ship reaches the terminal, if so, ending the navigation of the ship, and if not, executing S2.
In summary, the guidance process is divided into two modes of path tracking and obstacle avoidance control guidance, the improved DVS guidance algorithm is used as a basic framework, a smooth reference path composed of straight lines and curves is dynamically planned by the GVS, and the path tracking mode and the obstacle avoidance control mode respectively correspond to different guide variables of the DVS. For obstacle avoidance guidance of a plurality of or mixed obstacles, firstly, a current obstacle avoidance target is judged and determined according to priority sequencing and obstacle avoidance operation conditions, an obstacle avoidance operation mode is started, and a transition function ensures smoothness of a DVS guide variable among different mode switching. The invention can also have applicability to various control strategies, is convenient to be combined with the existing advanced control algorithm, and the control algorithm plays a role in ensuring the convergence of a real ship on the DVS and ensuring the effectiveness of a guidance strategy.
In order to verify the effectiveness of the guidance algorithm provided by the invention, the part takes a teaching practice ship of university of maritime affairs "breeding and spreading" (as shown in figure 10) as a controlled object, and a computer simulation experiment is carried out by utilizing matlab. Table 1 gives the main scale parameters of the "breeding" wheel. A three-degree-of-freedom underactuated mathematical model (17) is adopted, and a related hydrodynamic coefficient of the model is obtained by utilizing an advanced system identification algorithm based on a series of real ship maneuverability tests developed by a 9-month 'spread-breeding' wheel in 2013.
TABLE 1 Main parameters of the "Breeding and spreading" wheel
Wherein the high-order fluid dynamic term expression is
Wherein, P is the pitch, and delta is the rudder angle, which is used as the input of the control system.
In this example, the planned route consists of 4 waypoints W1(200,0)，W2(200,1000)，W3(1200,1500)，W4(1200,2500) determining. A plurality of static barriers, a plurality of dynamic barriers and a dynamic-static mixed barrier are arranged near a planned route, and the condition that a ship passes through a multi-island reef water area and a busy shipping water area is simulated. The initial state of the ship is [ x, y, psi, u, v, r]t＝0＝[0m,0m,90deg,0m/s,0m/s,0deg/s]And the parameters of the guidance algorithm are set as follows: u. ofg＝10Kn，udo＝12Kn，ldbset＝200m，kd＝0.05，Δ＝20m，
tsIn order to be closer to the real environment, the simulation considers the interference of the marine environment of wind, wave and current. The control algorithm is robust to the neural damping control law, and the application embodies the good combination of the invention and the advanced control algorithm.
The environmental interference used in the simulation experiment is as follows: wind speed (Typha wind 6 grade) Vwind15.25m/s, wind direction ψwind50 deg; the sea wave interference is generated by coupling of a wind interference model, namely, sea waves generated by full growth under the condition of the Typha wind level 7, and a three-dimensional view of the test sea wave interference is shown in FIG. 11; ocean current Vcurrent0.5m/s, flow direction βcurrent280 deg. Fig. 12 to 15 show the real ship trajectory diagrams obtained by the guidance strategy of the present invention at 4 time points under the above experimental conditions. It can be seen that the guidance and control strategy ensures that the real ship effectively converges on the safety limit ring of the obstacle when avoiding the obstacle, and quickly returns to the path tracking mode after the obstacle avoidance is finished, and the single-ship obstacle avoidance requirement is metAnd according to the requirements of COLREGs, the multi-ship obstacle avoidance executes the obstacle avoidance task according to the priority order. Fig. 16 shows the change of the guiding variable obtained by the guidance strategy with time in the whole experimental process, and it can be seen that the introduction of the transition function in the guidance strategy ensures smooth transition of the guiding variable between mode switching. Fig. 17 shows control inputs-a pitch P and a rudder angle δ in an experimental process, the control inputs meet the bounded requirement of an actuator, buffeting is small, and the buffeting can be directly used as the input of the actuator and is close to engineering practice.
Through the simulation experiment and comparison with the existing research, the beneficial effects brought by the invention are summarized as the following 3 points:
1) the invention provides an improved DVS guidance technology suitable for complex navigation situations with multiple static targets, multiple dynamic targets and mixed multi-target obstacles, and the application range is wider. The guidance algorithm creatively combines ship path tracking guidance with hybrid obstacle avoidance guidance. The hybrid obstacle avoidance guidance mechanism under the strategy has the capabilities of multi-static obstacle avoidance, multi-dynamic obstacle avoidance and hybrid multi-target obstacle avoidance, and after the obstacle avoidance task is finished, the ship can quickly return to the path tracking task, so that the application range is wider.
2) The obstacle avoidance strategy based on the limit ring can ensure that the ship can be quickly converged on the safety limit ring of the obstacle, and the safety performance is high. In the algorithm, the safety margin of the obstacle avoidance target and the detection ring (determined by the measurement capability of shipborne equipment, such as a radar, a camera and the like) are reasonably designed, so that the safety margin of the ship obstacle avoidance operation and the convergence speed of the recovery route after the obstacle avoidance operation can be flexibly adjusted. In actual engineering, the safety limit ring and the detection ring of the obstacle avoidance target are one embodiment of real ship detection capability, and the process that a real ship enters the obstacle detection ring is equivalent to the process that an obstacle enters the real ship detection range, so that the guidance algorithm is convenient for engineering realization.
3) The guidance strategy provided by the invention inherits the advantages of the DVS guidance strategy, and can provide a reasonable and effective guidance mechanism under a straight line segment, a curve segment and various ship navigation situations to guide a ship to complete an intelligent navigation task; the strategy has the universality of a control theory, and a bridge is built for the combination of an advanced control algorithm and engineering practice; the strategy considers the limitation of a ship execution device and accords with the theme of 'green and energy saving'.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (5)
1. A water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance is characterized by comprising the following steps:
s1: setting waypoint information W1,W2,…,WnRespectively establishing a motion mathematical model of a guide virtual boat and a dynamic virtual boat; the expressions of the motion mathematical models of the guide virtual boat and the dynamic virtual boat are as follows:
wherein d represents a dynamic virtual boat, g represents a guiding virtual boat, and (x, y) are position coordinates,
respectively, a first derivative of the distance, psi is a heading angle, u is an advancing speed, and r is a heading angular speed;
s2: the method comprises the steps that a guide virtual boat plans a reference path according to a guidance algorithm, always runs along the reference path, starts a path tracking guidance mode, leads the heading angle of the dynamic virtual boat to be equal to the true azimuth angle of the guide virtual boat relative to the dynamic virtual boat at the moment, sends a guidance command to a real boat to guide the real boat to track the path, and continuously obtains a guidance variable of the dynamic virtual boat by the real boat; wherein the guiding variables of the dynamic virtual boat comprise a heading angle psidAnd a forward speed udBow of the vesselDirection angle psidThe calculation formula of (2) is as follows:
wherein d represents a dynamic virtual boat, g represents a guiding virtual boat, and (x, y) are position coordinates;
forward speed udThe calculation formula of (2) is as follows:
wherein k isdFor setting parameters for adjusting the convergence rate, ldgFor dynamic virtual boat to guided virtual boat distance, ugFor guiding the forward speed of the virtual boat,. psigFor guiding the heading angle, psi, of the virtual boatdFor dynamic virtual boat heading angle,/dbsetFor the upper limit setting of the distance from the real ship to the dynamic virtual boat,/dbThe distance from the real ship to the dynamic virtual boat;
s3: sampling is carried out at a sampling time point, whether the dynamic virtual boat enters an obstacle detection ring or not is judged, if the dynamic virtual boat enters the obstacle detection ring, an obstacle sequencing process is carried out, and S4 is executed; if the obstacle detection loop is not entered, keeping the path tracking guidance mode, and executing S6;
s4: entering an obstacle ordering process: sorting the priorities of the obstacle avoidance objects to obtain a priority sequence of the obstacles, selecting the obstacle with the highest priority as a current obstacle avoidance target, judging whether the current obstacle avoidance target meets obstacle avoidance operation conditions, and if the current obstacle avoidance target meets the obstacle avoidance operation conditions, entering an obstacle avoidance guidance mode for the current obstacle, namely executing S5; if the current obstacle avoidance target does not meet the obstacle avoidance control condition, selecting the obstacle with the secondary priority as the current obstacle avoidance target; if all the obstacles do not meet the obstacle avoidance control condition, entering a path tracking mode and executing S6;
s5: entering an obstacle avoidance guidance mode: at each sampling time point, judging whether the obstacle avoidance control condition of the current obstacle is fullIf the obstacle avoidance control conditions are met, starting an obstacle avoidance guidance mode for the current obstacle, acquiring a guidance variable of the dynamic virtual boat, and guiding the real boat; if the obstacle avoidance control condition is not met, removing the current obstacle from the obstacle priority sequence, and executing S4; wherein, in the obstacle avoidance guidance mode of S5, the speed u of the dynamic virtual boatdAdjusting the heading angle to be the obstacle avoidance speed, and selecting the heading angle according to the following method:
s51: if the current obstacle avoidance target is a static obstacle, then
Wherein psidoThe heading angle of the dynamic virtual boat in an obstacle avoidance guidance mode is shown, phi is the true azimuth angle of the static obstacle relative to the dynamic virtual boat, e is the distance from the dynamic virtual boat to a safety limit ring of the static obstacle, delta is a set forward distance, lambda is +/-1 to determine the direction of the dynamic virtual boat surrounding the static obstacle when the dynamic virtual boat avoids the obstacle, +1 is the safety limit ring surrounding the static obstacle in the clockwise direction, and-1 is the safety limit ring surrounding the static obstacle in the anticlockwise direction;
s52: if the current obstacle avoidance target is a dynamic obstacle, then
Phi is a true azimuth angle of the dynamic obstacle relative to the dynamic virtual boat, delta is a set forward distance, e is a distance from the dynamic virtual boat to a safety limit ring of the dynamic obstacle, lambda is +/-1, +1 is the safety limit ring which surrounds the dynamic obstacle clockwise, and-1 is the safety limit ring which surrounds the dynamic obstacle anticlockwise; the compensation parameter k is used for compensating the influence of the ship motion on the heading angle, and is defined as follows:
wherein the content of the first and second substances,
b＝-2eV0 2，c＝-(Δ2+e2)V0 2and u isdo≥uc≥V0；
；
ucIs the speed of the current dynamic obstacle; u. ofdoRepresenting the obstacle avoidance speed of the dynamic virtual boat;
s6: adjusting the input of an actuator of the real ship in real time according to the guide variable and the control strategy of the dynamic virtual small ship, and controlling the real ship to track the dynamic virtual small ship;
s7: and measuring the position of the real ship, judging whether the real ship reaches the terminal, if so, ending the navigation of the ship, and if not, executing S2.
2. The method for tracking and guiding the path of the unmanned surface vehicle considering the hybrid multi-target obstacle avoidance according to claim 1, wherein in S4, the method for generating the priority sequence of the obstacles comprises:
s41: dividing the obstacles into static obstacles and dynamic obstacles, wherein the priority of the static obstacles is higher than that of the dynamic obstacles;
s42: the priority of the static obstacles is inversely proportional to the distance e from the dynamic virtual boat to the safety limit ring of the static obstacles, and the obstacle with the minimum e has the highest priority;
s43: the priority of the dynamic obstacle is determined by the following formula
Wherein F is an evaluation function, RmRadius of the obstacle-detecting ring, RoIs the radius of the safety limit cycle, e is the distance from the dynamic virtual boat to the safety limit cycle of the dynamic barrier,
the derivative of the distance of the dynamic virtual boat from the obstacle in the path tracking mode, udoThe obstacle avoidance speed of the dynamic virtual boat is represented as a constant, the value of the constant is larger than the speed of all dynamic obstacles,
is a weight parameter.
3. The method for tracking and guiding the path of the unmanned surface vehicle considering the hybrid multiple-target obstacle avoidance according to claim 1, wherein in S4, the obstacle avoidance operation conditions are divided into obstacle avoidance operation conditions for static obstacles and obstacle avoidance operation conditions for dynamic obstacles, and the obstacle avoidance operation conditions for the static obstacles are as follows: the heading of the dynamic virtual boat is between two tangent lines of a safety limit ring from the dynamic virtual boat to the static barrier; the obstacle avoidance control condition for the dynamic obstacle is the following formula:
wherein, sigma is the distance between the dynamic virtual boat and the dynamic obstacle, RoRadius of the ultimate safety ring for dynamic obstacles, RmThe radius of the detection ring for a dynamic obstacle,
is the derivative of the dynamic virtual boat to dynamic obstacle distance in path tracking mode.
4. The water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance as claimed in claim 1, wherein the following time transition functions are adopted when the path tracking guidance mode and the obstacle avoidance guidance mode are switched and when the obstacle avoidance guidance modes of different obstacles are switched:
wherein α (t) is a time transition function, tcTo initiate a switching time point, tsIs a manually set transition time.
5. The method for tracking and guiding the path of the unmanned surface vehicle with the hybrid multi-target obstacle avoidance in consideration of claim 1, wherein in S3, the radius R of the obstacle detection ringmThe larger the obstacle, the larger its value, determined by the size of the obstacle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710504472.4A CN107168335B (en) | 2017-06-28 | 2017-06-28 | Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710504472.4A CN107168335B (en) | 2017-06-28 | 2017-06-28 | Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107168335A CN107168335A (en) | 2017-09-15 |
| CN107168335B true CN107168335B (en) | 2020-06-23 |
Family
ID=59827740
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710504472.4A Active CN107168335B (en) | 2017-06-28 | 2017-06-28 | Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107168335B (en) |
Families Citing this family (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107544500B (en) * | 2017-09-18 | 2020-12-29 | 哈尔滨工程大学 | Unmanned ship berthing behavior trajectory planning method considering constraint |
| CN107966152B (en) * | 2017-11-22 | 2021-05-07 | 大连海事大学 | Collision avoidance and path tracking guidance method with collision risk prediction mechanism |
| CN108459602B (en) * | 2018-02-28 | 2021-03-30 | 哈尔滨工程大学 | Autonomous berthing method of under-actuated unmanned ship in multi-obstacle complex environment |
| CN109489672B (en) * | 2018-03-25 | 2022-03-18 | 哈尔滨工程大学 | Energy-saving A star path planning method considering influence of ocean current and unmanned ship dynamics |
| US11126199B2 (en) * | 2018-04-16 | 2021-09-21 | Baidu Usa Llc | Learning based speed planner for autonomous driving vehicles |
| CN108762074B (en) * | 2018-05-23 | 2020-12-29 | 大连海事大学 | Ship control method for improving safety guarantee capability of ship under severe sea conditions |
| CN108563113B (en) * | 2018-06-12 | 2020-11-20 | 哈尔滨工程大学 | Multi-loop model-free adaptive heading control method for ship |
| CN109752957B (en) * | 2019-01-11 | 2021-07-30 | 大连海事大学 | Guidance instruction regulator structure of unmanned ship and design method |
| CN109916419A (en) * | 2019-03-12 | 2019-06-21 | 哈尔滨工程大学 | A kind of hybrid genetic algorithm unmanned boat real-time route planing method of object-oriented |
| CN109857124B (en) * | 2019-03-22 | 2021-09-24 | 大连海事大学 | Unmanned ship accurate path tracking control method based on speed and course dual guidance |
| CN109960262B (en) * | 2019-03-25 | 2020-05-19 | 华中科技大学 | Unmanned ship dynamic obstacle avoidance method and system based on geometric method |
| CN110018687B (en) * | 2019-04-09 | 2022-03-04 | 大连海事大学 | Optimal trajectory tracking control method for unmanned surface vessel based on reinforcement learning method |
| CN110083159B (en) * | 2019-05-14 | 2022-03-08 | 江苏科技大学 | Unmanned ship autonomous dynamic collision avoidance method based on SBG and dynamic window constraint |
| CN110134130A (en) * | 2019-06-14 | 2019-08-16 | 西交利物浦大学 | A kind of unmanned boat automatic obstacle avoiding method based on improvement angle potential field method |
| CN110758669B (en) * | 2019-10-30 | 2021-01-26 | 青岛科技大学 | Double-layer relative field acquisition method for open busy water area |
| CN111487966B (en) * | 2020-04-13 | 2022-09-09 | 哈尔滨工程大学 | Self-adaptive path tracking control method for unmanned surface vehicle based on waypoints |
| CN111798701B (en) * | 2020-07-07 | 2022-07-26 | 中国船舶工业系统工程研究院 | Unmanned ship path tracking control method, system, storage medium and terminal |
| CN111951609B (en) * | 2020-07-24 | 2022-08-09 | 深圳市云洲创新科技有限公司 | Bridge active anti-collision early warning method, device, equipment and storage medium |
| CN112422184B (en) * | 2020-09-28 | 2022-05-27 | 东方红卫星移动通信有限公司 | Rotation control method and device of coarse pointing device for space optical communication |
| CN113031598B (en) * | 2021-03-02 | 2024-02-06 | 中国人民解放军火箭军工程大学 | Path tracking obstacle avoidance guidance method and system |
| CN113093742B (en) * | 2021-03-30 | 2023-05-26 | 大连海事大学 | Unmanned ship path tracking system capable of automatically avoiding multiple obstacles |
| CN112947494B (en) * | 2021-04-22 | 2022-10-04 | 中国船舶重工集团公司第七0七研究所九江分部 | Fuzzy PID (proportion integration differentiation) -based automatic ship berthing control method |
| CN113189992B (en) * | 2021-04-26 | 2023-05-12 | 四川大学 | Group intelligent obstacle avoidance method based on local orientation |
| CN113176788B (en) * | 2021-04-27 | 2022-08-16 | 北京理工大学 | Aircraft path tracking method based on variable forward distance LOS guidance law |
| CN113296401B (en) * | 2021-05-17 | 2022-04-19 | 哈尔滨工业大学 | Direct obstacle avoidance tracking control method based on switching strategy and storage medium |
| CN114185351B (en) * | 2021-12-06 | 2023-12-01 | 北京云迹科技股份有限公司 | Operation method and device of disinfection robot |
| CN114527744B (en) * | 2022-01-11 | 2024-04-02 | 燕山大学 | Unmanned sailing boat path tracking guidance method based on longhorn beetle whisker search optimization |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104020771B (en) * | 2014-06-13 | 2017-03-01 | 大连海事大学 | A kind of underactuated surface vessel path trace planing method based on dynamic virtual canoe guidance algorithm |
| CN106324619A (en) * | 2016-10-28 | 2017-01-11 | 武汉大学 | Automatic obstacle avoiding method of substation inspection robot |
-
2017
- 2017-06-28 CN CN201710504472.4A patent/CN107168335B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN107168335A (en) | 2017-09-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107168335B (en) | Water surface unmanned ship path tracking guidance method considering hybrid multi-target obstacle avoidance | |
| Wang et al. | A COLREGs-based obstacle avoidance approach for unmanned surface vehicles | |
| Tan et al. | Fast marching square method based intelligent navigation of the unmanned surface vehicle swarm in restricted waters | |
| CN106959698B (en) | A kind of path trace avoidance method of guidance | |
| CN109828570B (en) | Control and guide method for self-adaptive boundary layer water surface unmanned ship | |
| Bertaska et al. | Experimental evaluation of automatically-generated behaviors for USV operations | |
| Liao et al. | Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis | |
| Lazarowska | A discrete artificial potential field for ship trajectory planning | |
| CN109283842A (en) | A kind of unmanned boat Track In Track intelligence learning control method | |
| Amundsen et al. | Autonomous ROV inspections of aquaculture net pens using DVL | |
| JP2004042884A (en) | Method and system maneuvering movable object | |
| CN107966152B (en) | Collision avoidance and path tracking guidance method with collision risk prediction mechanism | |
| WO2021230356A1 (en) | Method for autonomously guiding vessel, program for autonomously guiding vessel, system for autonomously guiding vessel, and vessel | |
| CN113759939B (en) | Intelligent navigation method and device for limited water area | |
| Liu et al. | Drift angle compensation-based adaptive line-of-sight path following for autonomous underwater vehicle | |
| Du et al. | Cooperative multi-agent control for autonomous ship towing under environmental disturbances | |
| Wang et al. | Path following control of the wave glider in waves and currents | |
| Song et al. | Method of emergency collision avoidance for unmanned surface vehicle (USV) based on motion ability database | |
| Nie et al. | Planar path-following tracking control for an autonomous underwater vehicle in the horizontal plane | |
| Guan et al. | Autonomous collision avoidance of unmanned surface vehicles based on improved A-star and dynamic window approach algorithms | |
| CN113093804B (en) | Unmanned ship formation control method and control system based on inversion sliding mode control | |
| Sans-Muntadas et al. | Spiral path planning for docking of underactuated vehicles with limited FOV | |
| Raimondi et al. | Hierarchical fuzzy/lyapunov control for horizontal plane trajectory tracking of underactuated AUV | |
| CN113359737A (en) | Ship formation self-adaptive event trigger control method considering formation expansion | |
| CN114035574A (en) | Autonomous obstacle avoidance method for unmanned surface vehicle |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |