CN113359762A - Dynamic planning method for unmanned surface vehicle - Google Patents

Dynamic planning method for unmanned surface vehicle Download PDF

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CN113359762A
CN113359762A CN202110751457.6A CN202110751457A CN113359762A CN 113359762 A CN113359762 A CN 113359762A CN 202110751457 A CN202110751457 A CN 202110751457A CN 113359762 A CN113359762 A CN 113359762A
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ship
dynamic
unmanned surface
surface vehicle
force
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CN113359762B (en
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孙明晓
原张杰
栾添添
胡占永
谢春旺
王万鹏
王涵旭
王浩
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Harbin University of Science and Technology
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    • 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

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Abstract

The invention relates to a dynamic planning method for an unmanned surface vehicle, which comprises the following steps: considering that most of dynamic obstacles encountered by unmanned surface vehicles on the sea are ships, an elliptical model is established according to the shape characteristics of the ships; on the basis of building an ellipse model, analyzing the ellipse model, determining the influence range of the dynamic barrier of the ship, and building an ellipse repulsion force field in the influence range to provide repulsion force, so as to guide the unmanned surface vehicle to avoid the dynamic barrier; further considering the instability and unpredictability of the motion of the dynamic barriers of the ship, the unmanned surface vehicle needs to avoid the dynamic barriers in a short time, so that a method of changing the coefficient of repulsion is adopted, repulsion is increased, and the direction of resultant force is changed, so that the effect of quickly guiding the unmanned surface vehicle to avoid the dynamic barriers is achieved.

Description

Dynamic planning method for unmanned surface vehicle
Technical Field
The invention relates to a dynamic planning method for an unmanned surface vehicle, and belongs to the field of motion control and dynamic planning of marine unmanned vehicles.
Background
As demands such as ocean defense and the like are continuously expanded, all countries are building ocean unmanned comprehensive platforms, and water surface unmanned boats are comprehensively developed as novel unmanned equipment. Dynamic planning of surface unmanned vehicle motion maneuvers is not yet mature.
Commonly used dynamic programming methods include velocity repulsion field algorithms, dynamic window algorithms, visual algorithms, artificial potential field methods, and the like. Compared with other algorithms, the artificial potential field method has the advantages of short operation time, strong real-time performance, good adaptability and the like. However, the application of the traditional artificial potential field method in the fields of unmanned surface vehicle motion control and dynamic planning has the following problems:
(1) the problem of difficult modeling of dynamic barriers is solved, because most of the unmanned surface craft meet the dynamic barriers, the dynamic barriers are considered as particles by the traditional artificial potential field method, the influence range of repulsive force is circular, the influence range of the dynamic barriers of the ships is difficult to determine, and the planned path cannot be safely guaranteed;
(2) the method is characterized in that the problem of rapid obstacle avoidance is solved, a repulsion coefficient and a attraction coefficient of a traditional manual potential field method are fixed, the generated repulsion is increased along with the reduction of the distance between a water surface unmanned ship and a ship dynamic obstacle, the attraction is reduced along with the reduction of the distance between the water surface unmanned ship and a target point, the position of the water surface unmanned ship is changed constantly, meanwhile, the instability and unpredictability of the motion of the ship dynamic obstacle need to be considered, and the coefficient is fixed, so that rapid, reliable and real-time dynamic planning is difficult to realize.
The improved method provided by the patent of unmanned ship ocean dynamic obstacle avoidance control algorithm based on ellipse clustering-collision cone deduction has the following problems:
(1) the method carries out elliptical clustering on the dynamic ship, clusters the dynamic ship into dynamic elliptical barriers according to the size and the shape of the dynamic ship, but the shape of the elliptical barriers is not determined, and the planned path cannot be safely guaranteed;
(2) the invention needs to acquire the motion state of the dynamic barrier, and has the advantages of large amount of information, high calculation difficulty and poor real-time performance.
In summary, how to solve the application of the artificial potential field method in the dynamic environment of the unmanned surface vehicle becomes a difficult point to be solved urgently.
Disclosure of Invention
The invention aims to provide a dynamic planning method for an unmanned surface vehicle, which solves the problems of difficult dynamic obstacle modeling, rapid obstacle avoidance and the like when the traditional artificial potential field method is applied to the dynamic planning process of the unmanned surface vehicle.
The invention adopts the following technical scheme for solving the problems: designing a dynamic planning method of the unmanned surface vehicle, establishing an ellipse equivalent model for dynamic barriers of a ship, and setting an influence range meeting constraint conditions; and the repulsion coefficient is changed according to the relationship between the attraction force and the repulsion force, so that the repulsion force is increased, the resultant force is changed, the barrier is quickly avoided, and the efficient, reliable and real-time dynamic planning is realized in the next movement. The method specifically comprises the following steps:
step 1:
setting a gravitational coefficient mu and a repulsive coefficient eta in an artificial potential field method, and setting a semi-major axis a of the unmanned surface vehicleqSemi-minor axis bqInitial position qsAnd target point position qgSemi-major axis a of ship dynamic barrier modelpSemi-minor axis bpSemi-focal length cpLeft focal position cp1And right focal position cp2Semi-major axis A of influence range of dynamic barrier of shippAnd semi-minor axis BpThe following constraints need to be satisfied:
Figure BDA0003144532760000021
then entering step 2;
step 2:
judging whether the current position q of the unmanned surface vehicle reaches qgIf yes, ending, otherwise, entering step 3;
and step 3:
constructing a gravity function:
Fa(q)＝μ·d(q,qg) (2)
in the formula: fa(q) is gravitational force, d (q, q)g) Is a vector with modulo lengths q and qgIn the direction q points to qgGravitational force Fa(q) generating attraction force on the unmanned surface vehicle, and guiding the unmanned surface vehicle to go to a target point under the action of the attraction force;
r＝d(q,cp1)+d(q,cp2) (3)
in the formula: r is a vector and r is a vector obtained by dividing d (q, c) by the parallelogram rulep1) And d (q, c)p2) Are added to obtain d (q, c)p1) Is a vector with modulo lengths q and cp1In the direction of cp1Pointing to q, same, d (q, c)p2) Is also a vector with modulo lengths q and cp2In the direction of cp2Pointing to q;
constructing a repulsion function:
Figure BDA0003144532760000031
in the formula: fe(q) is a repulsive force, repulsive force Fe(q) and r are in the same direction, and | r | is the module length of the vector r, and when the unmanned surface vessel is in the influence range of the dynamic barrier of the vessel, the repulsive force Fe(q) generating a repulsive force to the ship, keeping the ship away from the ship, and then entering the step 4;
and 4, step 4:
judgment of repulsive force Fe(q) if the value is 0, entering a step 6 if the value is 0, and otherwise, entering a step 5;
and 5:
at the moment, the water surface unmanned ship changes the repulsion coefficient eta in order to avoid the dynamic barrier of the ship as soon as possible within the influence range of the dynamic barrier of the ship, so that the repulsion is increased in the next step of movement, and the change formula of the repulsion coefficient eta is as follows:
Figure BDA0003144532760000032
then entering step 6;
step 6:
constructing a resultant force formula:
Ft(q)＝Fa(q)+Fe(q) (6)
in the formula: ft(q) is resultant force, wherein the resultant force direction is the next movement direction of the unmanned surface vehicle, and then the step 7 is carried out;
and 7:
and calculating the next motion, and then returning to the step 2 to circulate.
The invention has the following beneficial effects:
1. the method establishes an elliptic equivalent model of the dynamic barrier of the ship, determines the influence range of the dynamic barrier of the ship, constructs a repulsive force potential field in the influence range, generates repulsive force on the unmanned ship, ensures that the unmanned ship can smoothly avoid the dynamic barrier and meets the requirement of safe navigation;
2. the method adopts a variable repulsion coefficient method to change repulsion force and further change resultant force, thereby achieving the effect that the unmanned surface vehicle can quickly avoid dynamic obstacles of the ship and realizing efficient, reliable and real-time dynamic planning;
3. the method of the invention defines the shape of the dynamic elliptical barrier, so that the established model is accurate and the planned path is safe;
4. the method mainly utilizes the position information, has low acquisition difficulty, small calculated amount and good real-time performance, and can achieve the purpose of rapidly avoiding obstacles.
Drawings
FIG. 1 is a flow chart of a dynamic planning method for an unmanned surface vehicle;
FIG. 2 is an elliptical model of a vessel dynamic barrier;
FIG. 3 is a stress analysis diagram of the unmanned surface vehicle;
FIG. 4 is a dynamic planning diagram of the unmanned surface vehicle when t is 1 s;
FIG. 5 is a dynamic planning diagram of the unmanned surface vehicle when t is 14 s;
FIG. 6 is a dynamic planning diagram of the unmanned surface vehicle when t is 28 s;
FIG. 7 is a dynamic planning diagram of the unmanned surface vehicle when t is 47 s;
FIG. 8 is a dynamic planning diagram of the unmanned surface vehicle when t is 62 s;
FIG. 9 is a dynamic planning diagram of the unmanned surface vehicle when t is 68 s;
FIG. 10 is a dynamic planning diagram of the unmanned surface vehicle when t is 69 s;
FIG. 11 is a dynamic planning diagram of the unmanned surface vehicle when t is 81 s;
FIG. 12 is a dynamic planning diagram of the unmanned surface vehicle when t is 97 s;
fig. 13 is a dynamic planning diagram of the unmanned surface vehicle when t is 122 s.
Detailed Description
Fig. 1 is a flow chart of a dynamic planning method for the unmanned surface vehicle, which comprises the following steps:
step 1:
setting a gravitational coefficient mu and a repulsive coefficient eta in an artificial potential field method, and setting a semi-major axis a of the unmanned surface vehicleqSemi-minor axis bqInitial position qsAnd target point position qgSemi-major axis a of ship dynamic barrier modelpSemi-minor axis bpSemi-focal length cpLeft focal position cp1And right focal position cp2Semi-major axis A of influence range of dynamic barrier of shippAnd semi-minor axis BpThe following constraints need to be satisfied:
Figure BDA0003144532760000051
the ship dynamic barrier model and the influence range thereof are shown in FIG. 2, and then step 2 is carried out;
step 2:
judging whether the current position q of the unmanned surface vehicle reaches qgIf yes, ending, otherwise, entering step 3;
and step 3:
constructing a gravity function:
Fa(q)＝μ·d(q,qg) (2)
in the formula: fa(q) is gravitational force, d (q, q)g) Is a vector with modulo lengths q and qgIn the direction q points to qgGravitational force Fa(q) Generating attraction force on the unmanned surface vehicle, and guiding the unmanned surface vehicle to go to a target point under the action of the attraction force;
r＝d(q,cp1)+d(q,cp2) (3)
in the formula: r is a vector and r is a vector obtained by dividing d (q, c) by the parallelogram rulep1) And d (q, c)p2) Are added to obtain d (q, c)p1) Is a vector with modulo lengths q and cp1In the direction of cp1Pointing to q, same, d (q, c)p2) Is also a vector with modulo lengths q and cp2In the direction of cp2Pointing to q.
Constructing a repulsion function:
Figure BDA0003144532760000061
in the formula: fe(q) is a repulsive force, repulsive force Fe(q) and r are in the same direction, and | r | is the module length of the vector r, and when the unmanned surface vessel is in the influence range of the dynamic barrier of the vessel, the repulsive force Fe(q) generating a repulsive force to the ship, keeping the ship away from the ship, and then entering the step 4;
and 4, step 4:
judgment of repulsive force Fe(q) if the value is 0, entering a step 6 if the value is 0, and otherwise, entering a step 5;
and 5:
at the moment, the water surface unmanned ship changes the repulsion coefficient eta in order to avoid the dynamic barrier of the ship as soon as possible within the influence range of the dynamic barrier of the ship, so that the repulsion is increased in the next step of movement, and the change formula of the repulsion coefficient eta is as follows:
Figure BDA0003144532760000062
then entering step 6;
step 6:
constructing a resultant force formula:
Ft(q)＝Fa(q)+Fe(q) (6)
in the formula: ft(q) is the resultant force, the direction of the resultant force is the next movement direction of the unmanned surface vehicle, as shown in fig. 3, q is the current position of the unmanned surface vehicle, and q is the current position of the unmanned surface vehiclegIs a target point, cp1And cp2Left and right foci of the elliptical model of the ship, Fa(q) is gravitational force, Fe(q) as a repulsive force, synthesizing a resultant force F using the parallelogram rulet(q) then proceeding to step 7;
and 7:
and calculating the next motion, and then returning to the step 2 to circulate.
The simulation results are shown in fig. 4-13, where the solid line is the unmanned boat path, the dotted line is the ship path, and the arrows indicate the respective directions of motion. When t is 1s, as shown in fig. 4, the unmanned boat starts towards the target point; when t is 14s, as shown in fig. 5, the unmanned ship enters the influence range of the ship ellipse model; fig. 6, 7, 8 and 9 show that the unmanned boat moves under the action of resultant force in the influence range of the dynamic barrier of the ship and rapidly leaves the influence range of the dynamic barrier of the ship; FIG. 10 shows that the unmanned surface vehicle continues to advance toward the target point after leaving the dynamic barrier influence range of the vessel; FIG. 11 shows that the unmanned surface vehicle enters the dynamic obstacle influence range of the ship again under the action of gravity and rapidly leaves the dynamic obstacle influence range of the ship again; fig. 12 is the drone heading toward the target point; fig. 13 shows the final arrival of the unmanned boat at the target point.

Claims (1)

1. The invention designs a dynamic planning method for an unmanned surface vehicle, which solves the problems of difficult modeling of dynamic barriers of ships, rapid obstacle avoidance and the like, and is characterized in that:
step 1:
setting a gravitational coefficient mu and a repulsive coefficient eta in an artificial potential field method, and setting a semi-major axis a of the unmanned surface vehicleqSemi-minor axis bqInitial position qsAnd target point position qgSemi-major axis a of ship dynamic barrier modelpSemi-minor axis bpSemi-focal length cpLeft focal position cp1And right focal position cp2Semi-major axis A of influence range of dynamic barrier of shippAnd semi-minor axis BpIt is required to satisfy the followingBundling conditions:
Figure FDA0003144532750000011
then entering step 2;
step 2:
judging whether the current position q of the unmanned surface vehicle reaches qgIf yes, ending, otherwise, entering step 3;
and step 3:
constructing a gravity function:
Fa(q)＝μ·d(q,qg) (2)
in the formula: fa(q) is gravitational force, d (q, q)g) Is a vector with modulo lengths q and qgIn the direction q points to qgGravitational force Fa(q) generating attraction force on the unmanned surface vehicle, and guiding the unmanned surface vehicle to go to a target point under the action of the attraction force;
r＝d(q,cp1)+d(q,cp2) (3)
in the formula: r is a vector and r is a vector obtained by dividing d (q, c) by the parallelogram rulep1) And d (q, c)p2) Are added to obtain d (q, c)p1) Is a vector with modulo lengths q and cp1In the direction of cp1Pointing to q, same, d (q, c)p2) Is also a vector with modulo lengths q and cp2In the direction of cp2Pointing to q;
constructing a repulsion function:
Figure FDA0003144532750000021
in the formula: fe(q) is a repulsive force, repulsive force Fe(q) and r are in the same direction, and | r | is the module length of the vector r, and when the unmanned surface vessel is in the influence range of the dynamic barrier of the vessel, the repulsive force Fe(q) generating a repulsive force to the ship, keeping the ship away from the ship, and then entering the step 4;
and 4, step 4:
judgment of repulsive force Fe(q) if the value is 0, entering a step 6 if the value is 0, and otherwise, entering a step 5;
and 5:
at the moment, the water surface unmanned ship changes the repulsion coefficient eta in order to avoid the dynamic barrier of the ship as soon as possible within the influence range of the dynamic barrier of the ship, so that the repulsion is increased in the next step of movement, and the change formula of the repulsion coefficient eta is as follows:
Figure FDA0003144532750000022
then entering step 6;
step 6:
constructing a resultant force formula:
Ft(q)＝Fa(q)+Fe(q) (6)
in the formula: ft(q) is resultant force, wherein the resultant force direction is the next movement direction of the unmanned surface vehicle, and then the step 7 is carried out;
and 7:
and calculating the next motion, and then returning to the step 2 to circulate.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114077255A (en) * 2021-11-22 2022-02-22 江苏理工学院 Intelligent vehicle path finding method based on elliptical model artificial potential field method
CN115562291A (en) * 2022-10-19 2023-01-03 哈尔滨理工大学 Path planning method for improving potential field dynamic coefficient based on artificial potential field method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105717923A (en) * 2016-01-16 2016-06-29 上海大学 Unmanned surface vessel ocean dynamic obstacle avoiding control algorithm based on ellipse clustering-collision awl deduction
CN107608346A (en) * 2017-08-30 2018-01-19 武汉理工大学 Ship intelligent barrier avoiding method and system based on Artificial Potential Field
KR20180094286A (en) * 2017-02-15 2018-08-23 국방과학연구소 Path Planning System of Unmanned Surface Vehicle for Autonomous Tracking of Underwater Acoustic Target
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
CN110850873A (en) * 2019-10-31 2020-02-28 五邑大学 Unmanned ship path planning method, device, equipment and storage medium
CN112379672A (en) * 2020-11-24 2021-02-19 浙大宁波理工学院 Intelligent unmanned ship path planning method based on improved artificial potential field

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105717923A (en) * 2016-01-16 2016-06-29 上海大学 Unmanned surface vessel ocean dynamic obstacle avoiding control algorithm based on ellipse clustering-collision awl deduction
KR20180094286A (en) * 2017-02-15 2018-08-23 국방과학연구소 Path Planning System of Unmanned Surface Vehicle for Autonomous Tracking of Underwater Acoustic Target
CN107608346A (en) * 2017-08-30 2018-01-19 武汉理工大学 Ship intelligent barrier avoiding method and system based on Artificial Potential Field
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
CN110850873A (en) * 2019-10-31 2020-02-28 五邑大学 Unmanned ship path planning method, device, equipment and storage medium
CN112379672A (en) * 2020-11-24 2021-02-19 浙大宁波理工学院 Intelligent unmanned ship path planning method based on improved artificial potential field

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
JIANFA WU 等: "Obstacle Avoidance Based on Virtual Repulsive Potential Fields under Limited Perceptions", 《2019 IEEE 15TH INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA)》 *
刘琨 等: "基于改进人工势场法的无人船路径规划算法", 《海南大学学报自然科学版》 *
蒲华燕 等: "基于椭圆碰撞锥的无人艇动态避障方法", 《仪器仪表学报》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114077255A (en) * 2021-11-22 2022-02-22 江苏理工学院 Intelligent vehicle path finding method based on elliptical model artificial potential field method
CN114077255B (en) * 2021-11-22 2023-07-18 江苏理工学院 Intelligent vehicle road-finding method based on elliptical model artificial potential field method
CN115562291A (en) * 2022-10-19 2023-01-03 哈尔滨理工大学 Path planning method for improving potential field dynamic coefficient based on artificial potential field method
CN115562291B (en) * 2022-10-19 2023-12-12 哈尔滨理工大学 Path planning method for improving potential field dynamic coefficient based on artificial potential field method

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