CN114035574A - Autonomous obstacle avoidance method for unmanned surface vehicle - Google Patents
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Abstract
The invention relates to the technical field of unmanned ship intelligent control, in particular to an autonomous obstacle avoidance method for an unmanned ship on water surface, which comprises the following steps: establishing an obstacle avoidance area model: taking the unmanned ship as a circle center, and sequentially dividing the whole navigation area into a forbidden area, an emergency obstacle avoidance area, a conventional obstacle avoidance area and a safe area from inside to outside; conventionally, obstacle avoidance: when an obstacle intrudes into the conventional obstacle avoidance area, avoiding by adopting a linear speed control method; emergency obstacle avoidance: when the conventional obstacle avoidance fails, the method is started, and when an obstacle intrudes into an emergency obstacle avoidance area, the expected course is calculated by adopting an artificial potential field method to avoid. The invention can realize the collision avoidance of the obstacle ships under multiple rules by the combined application of the conventional obstacle avoidance and the emergency obstacle avoidance.
Description
Technical Field
The invention relates to the technical field of unmanned surface vehicle intelligent control, in particular to an autonomous obstacle avoidance method for an unmanned surface vehicle.
Background
The unmanned surface vessel is an unmanned surface vessel, is mainly used for executing dangerous tasks which are not suitable for being executed by the unmanned surface vessel, is used as a small-sized autonomous surface task platform, has the advantages of intelligence, flexibility, concealment, extreme condition resistance, high cost performance and the like, has wide effects in both the civil field and the military field, and is a technical power for promoting the rapid and healthy development of marine economy under the background that the marine economy is continuously valued and developed.
As the centralized embodiment of the intelligent degree of the USV (intelligent unmanned vehicle on water, namely unmanned boat and the like), the autonomous obstacle avoidance path planning is always an important content of the research of the unmanned surface vehicle, the autonomous path planning capability is an important part for realizing the USV obstacle avoidance function, and the obstacle avoidance path planning is to find an optimal traveling path from a starting point to a target according to the traveling requirement and the acquired state information of the obstacle and finally safely reach the target. The obstacle avoidance path planning of the unmanned surface vehicle can be divided into a global path planning algorithm based on complete information and a local path planning algorithm based on sensor information, and the smooth completion of a set mission task can be ensured only by the close combination of the global path planning and the real-time avoidance of local danger.
Because electronic sea charts and the like cannot give complete environmental information, the unmanned surface vessel can encounter some unknown static and dynamic obstacles during navigation. Unlike static global path planning, where the environmental information is known, dynamic path planning needs to find a balance between path optimization and computation, and plan paths that are as excellent as possible while consuming as little resources as possible. Because the range detected by the sensor is used as the environment of the local path planning, which is usually unknown and dynamically changing, a fast and efficient environment modeling is required during the local path planning, and the obstacle avoidance and dynamic performance requirements during the path search are higher.
Local path planning can be divided into two categories; firstly, when the barrier is static, the barrier is called as a static obstacle avoidance; secondly, when the obstacle is dynamic, the obstacle is called dynamic obstacle avoidance, and the dynamic obstacle avoidance algorithm can also be used for static obstacle avoidance. The dynamic obstacle avoidance algorithm is difficult, because the motion information of the dynamic obstacle is difficult to accurately obtain by moving a sensor carried by the unmanned ship, and the motion trend of the obstacle cannot be accurately predicted. The local path planning has small calculation amount and good real-time performance, but the environment information is not completely known, so that the local path planning is easy to fall into a tiny value point. Therefore, the research on the unmanned ship local path planning is meaningful.
Disclosure of Invention
The invention aims to provide an autonomous obstacle avoidance method for an unmanned surface vehicle.
In order to achieve the purpose, the invention provides the following technical scheme:
an autonomous obstacle avoidance method for an unmanned surface vehicle is characterized by comprising the following steps:
establishing an obstacle avoidance area model: taking the unmanned ship as a circle center, and sequentially dividing the whole navigation area into a forbidden area, an emergency obstacle avoidance area, a conventional obstacle avoidance area and a safe area from inside to outside;
conventionally, obstacle avoidance: when an obstacle intrudes into the conventional obstacle avoidance area, avoiding by adopting a linear speed control method;
emergency obstacle avoidance: when the conventional obstacle avoidance fails, the method is started, and when an obstacle intrudes into an emergency obstacle avoidance area, the expected course is calculated by adopting an artificial potential field method to avoid.
Further, the radius R of the forbidden zone is the safe meeting distance DCPAs of the unmanned ship, the radius R1 of the emergency obstacle avoidance zone is n1 × Vusv × DCPAs, and the radius R2 of the conventional obstacle avoidance zone is n2 × Vusv × DCPAs; wherein Vusv is the speed of the unmanned ship, the unit is m/s, and n1 and n2 are preset coefficients.
Further, the safe encounter distance DCPAs is 4 times the coxswain of the unmanned boat, and the coefficients n1 and n2 are set to 0.25 and 0.4, respectively.
Further, environment modeling is also included: converting the coordinates of the obstacles into rectangular grid data, calculating corresponding grid rectangular coordinates according to the grid row and column numbers when the grids have the obstacles, converting the grid rectangular coordinates into a heading coordinate system which takes the unmanned boat as the center of a circle and takes the true north as 0 degree, and acquiring the azimuth angle of the obstacles; the azimuth of the obstacle is converted into a fan-shaped grid number, and the fan-shaped grid at the number is considered to be occupied by the obstacle.
Further, in the conventional obstacle avoidance, when the straight line speed control method cannot successfully avoid, the feasible course is designed by adopting a vector field histogram algorithm to avoid.
Further, the vector field histogram algorithm designs feasible headings including:
1. and (3) interval division: filling fan-shaped grids by using rectangular grids, wherein the number of the fan-shaped grids is calculated according to the set unit fan angle, and the calculation formula of the number K of the fan-shaped grids is as follows: k is 360/angle;
2. and (4) judging the safety direction: when an obstacle exists at the grid, calculating a corresponding grid rectangular coordinate according to the grid row and column number, converting the grid rectangular coordinate into a course coordinate system with the unmanned ship as the center of a circle and the true north as 0 degree, and acquiring an obstacle azimuth angle; converting the azimuth of the obstacle into a fan-shaped grid number, wherein the fan-shaped grid at the number is regarded as being occupied by the obstacle;
3. judging the feasibility direction: when the fan-shaped grid corresponding to the expected course of the unmanned ship is not occupied by the obstacle, the unmanned ship continues to sail along the expected course; otherwise, searching fan-shaped grid numbers which can be passed when the unmanned ship turns left and turns right, calculating the angular bisector direction of the unmanned ship as a candidate direction, comparing the cost of turning left and right, and selecting the direction with low cost as a feasible azimuth angle.
Further, when an artificial potential field method is adopted for emergency obstacle avoidance, when the distance between the unmanned boat and the target is larger than the set distance, the attraction force is set to be a constant.
Further, in the manual potential field method, the direction of the repulsive force component force is rotated by a certain angle theta, so that the included angle between the resultant force and the attractive force is less than or equal to 90 degrees.
Further, introducing the distance rho (X, X) between the unmanned ship and the target into a repulsion function of an artificial potential field methodg) Forbidden zone radius r, the repulsion function is modified as:
in the formula, λ2Is the repulsive force gain coefficient, X, X0、XgRespectively representing the spatial positions of the unmanned boat, the obstacle and the target, rho (X, X)0) And ρ(X，Xg) Representing the distance, p, of the unmanned boat to the obstacle and target, respectively0Is the influence radius of the barrier on the unmanned ship, and r is the forbidden zone radius.
Further, in the process that the unmanned ship drives away from the obstacle, the expected target obtained through calculation by the LOS guidance method replaces an actual target in the artificial potential field method to calculate the expected heading.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention can realize the collision avoidance of the obstacle ships under multiple rules by the combined application of the conventional obstacle avoidance and the emergency obstacle avoidance.
2. The invention solves the problems that the barrier is driven into a forbidden zone, falls into local minimum, cannot reach a destination due to a barrier potential field high wall and the like by improving the application of an artificial potential field method in the unmanned ship.
Drawings
Fig. 1 is a flow chart of autonomous obstacle avoidance of the unmanned surface vehicle in the embodiment.
Fig. 2 is a schematic diagram of an obstacle avoidance area model in the embodiment.
Fig. 3 is a schematic view of repulsive force deflection in the embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 2-3, an autonomous obstacle avoidance method for an unmanned surface vehicle, also a method for planning a local path of an unmanned surface vehicle (USV for short), includes:
firstly, establishing an obstacle avoidance area model
The method of circular safe collision avoidance range is adopted, and the whole navigation area is divided into 4 areas of safe area, conventional obstacle avoidance area, emergency obstacle avoidance area and forbidden area according to different radiuses, as shown in figure 2.
For the convenience of calculation, the safe meeting distance DCPAs is set to be 4 times of the boat length, the safe meeting distance DCPAs is the radius r of the forbidden zone, the approximate rounding is carried out, the maneuverability of the unmanned boat is considered to be good, and through multiple simulation attempts and comparison, the function of the area radius, the safe meeting distance DCPAs and the navigation speed is as follows:
R1＝0.25×VUSV×DCPAs
R2＝0.4×VUSV×DCPAs
wherein the unit of the unmanned boat navigational speed Vusv is m/s.
As shown in fig. 2, the area outside the radius R2 is a safe area, the annular areas with the radii R1 and R2 are conventional obstacle avoidance areas, and the annular areas with the radii R1 and R are emergency obstacle avoidance areas.
Second, environment modeling
And (4) converting the coordinates of the obstacle into rectangular grid data, and checking whether the obstacle is in the obstacle avoidance area. When an obstacle exists at the grid, calculating a corresponding grid rectangular coordinate according to the grid row and column number, converting the grid rectangular coordinate into a course coordinate system with the unmanned ship as the center of a circle and the true north as 0 degree, and acquiring an obstacle azimuth angle; the azimuth of the obstacle is converted into a fan-shaped grid number, and the fan-shaped grid at the number is considered to be occupied by the obstacle. And the calculated sector raster data is used for calculating the passable course interval.
Calculating the grid number of an X axis and a Y axis according to the radius R2 and the granularity N of grid division, wherein the calculation formula of the row number M and the column number N of the rectangular grid is as follows: m is N is R2×2/n。
If an obstacle intrudes into the annular region with the radius R1-R2, the sector-shaped grids are filled with rectangular grids, and the number of the sector-shaped grids is calculated according to the set unit sector angle, wherein the calculation formula of the number K of the sector-shaped grids is as follows: k is 360/angle.
Secondly, conventionally avoiding obstacles:
when an obstacle intrudes into the conventional obstacle avoidance area, a linear speed control method is preferably adopted for avoiding; when the linear speed control method cannot successfully avoid, the feasible course is planned and calculated in real time by adopting the course designed by a Vector Field Histogram (VFH for short).
For the USV executing the accurate tracking task and the large USV with difficult steering or larger steering cost, when an unknown obstacle is detected, an obstacle avoidance strategy, namely a linear speed control method, which only changes the speed of the USV and does not change the course can be adopted.
The principle of the linear speed control method is that for other dynamic barriers which are not in a meeting type and are not in an overriding type, the unmanned boat can select to accelerate a flight path passing through the barriers to avoid the barriers, or select to decelerate so that the barriers firstly pass through the flight path of the unmanned boat and then recover the original speed to avoid the barriers. In the design of the scheme, the unmanned boat is selected to pass through the tail part of the obstacle by default.
The judgment basis of the collision risk of the linear speed control method is as follows:
wherein r is the forbidden zone radius, dminIndicating the minimum Distance (DCPA) from the obstacle that the drone would appear if it were maintaining the current heading.
A navigation speed value for enabling the minimum Distance (DCPA) between the unmanned ship and the obstacle to be not less than the radius r of the forbidden zone of the unmanned ship is calculated by adopting a linear speed control method. Firstly, judging whether the speed value meets the speed limiting condition of the unmanned ship, and if the speed is in a reasonable range, considering that the barrier can be avoided by adopting a mode of adjusting the speed.
The linear speed control method enables the unmanned ship to keep linear navigation, the shortest obstacle avoidance path is achieved, the course of the unmanned ship does not need to be changed, the parameters of the algorithm do not need to be adjusted according to the model of the unmanned ship, and the method has universality for the unmanned ships of different models. But it may happen that the calculated speed is greater than the highest speed of the unmanned boat or too small to be a good choice. At this time, a Vector Field Histogram (VFH) designed course may be adopted, and the specific steps include:
s1, interval division: filling fan-shaped grids by using rectangular grids, wherein the number of the fan-shaped grids is calculated according to the set unit fan angle, and the calculation formula of the number K of the fan-shaped grids is as follows: k is 360/angle.
S2, safety direction judgment: when an obstacle exists at the grid, calculating a corresponding grid rectangular coordinate according to the grid row and column number, converting the grid rectangular coordinate into a course coordinate system with the unmanned ship as the center of a circle and the true north as 0 degree, and acquiring an obstacle azimuth angle; the azimuth of the obstacle is converted into a fan-shaped grid number, and the fan-shaped grid at the number is considered to be occupied by the obstacle.
S3, judging feasibility direction: when the fan-shaped grid corresponding to the expected course of the unmanned ship is not occupied by the obstacle, the unmanned ship continues to sail along the expected course; otherwise, searching fan-shaped grid numbers which can be passed when the unmanned ship turns left and turns right, calculating the angular bisector direction of the unmanned ship as a candidate direction, comparing the cost of turning left and right, and selecting the direction with low cost as a feasible azimuth angle.
Fourthly, emergency obstacle avoidance
When the conventional obstacle avoidance fails and an obstacle intrudes into the emergency obstacle avoidance area, the expected course is calculated by adopting an optimized artificial Potential Field method (artificial Potential Field). The potential force field expression of the artificial potential field method is as follows:
Fatt(X)＝λ1ρ(X，Xg)
wherein λ is1And λ2Gain factors of attraction and repulsion, respectively, X, X0、XgRespectively representing the spatial positions of the unmanned boat, the obstacle and the target, rho (X, X)0) And ρ (X, X)g) Representing the distance, p, of the unmanned boat to the obstacle and target, respectively0Is the radius of influence of the obstacle on the unmanned surface vehicle.
When distance between USV and target ρ (X, X)g) And when the distance value is larger than the preset distance value, the gravitation value is regarded as a constant, so that the problem that the gravitation becomes very large when the distance between the USV and the target is too large is avoided.
When the attraction force potential field at a certain point is equal to the repulsion force potential field, the resultant force applied to the unmanned ship at the point is 0, and the points are called local minimum value points. When the unmanned ship moves in the potential field, the unmanned ship may be trapped in the local minimum point, and the unmanned ship trapped in the local minimum point stops moving or cannot be separated by vibrating back and forth near the local minimum point. This condition is referred to as a local minimum being stuck, meaning that the local path planning fails.
In order to solve the problem of local minimum points of an artificial potential field method, the following improvements can be made on the traditional repulsion potential field function: the direction of the repulsive force is modified and the repulsive force coefficient is adjusted in an adaptive mode, so that the balance of the attractive force and the repulsive force of the potential field at the local minimum point is broken.
As shown in FIG. 3, θ is the repulsive force component Frep1The angle of rotation of (a); beta is an included angle between a connecting line of the obstacle (obstacle) and the unmanned boat (Robot) and a connecting line of the unmanned boat and the target (Goal); alpha is an included angle between a connecting line of the barrier and the target and a connecting line of the unmanned boat and the target; l is the distance from the unmanned boat to the obstacle; frep1Rotated to obtain F'rep1The resultant force is converted from F to F'.
Repulsive force component Frep1And gravitational force FattAn included angle is formed between the two unmanned boats, and when the included angle is an obtuse angle, the unmanned boats have the possibility of falling into local minimum points. Further analysis, when the resultant force F and the gravitational force FattWhen the included angle between the unmanned ship and the unmanned ship is an obtuse angle, the unmanned ship is more likely to sink into a local minimum point. By mixing Frep1Is rotated by an angle theta so that the resultant force F and the attractive force FattThe included angle is less than or equal to 90 degrees, and the unmanned boat can avoid local minimum points.
The magnitude of the rotation angle θ is related to two factors, namely the angle β and the distance l. Because the angle beta is not visual enough, an intermediate variable d is introduced to describe the angle theta, and the expression is as follows:
d＝l·sinβ
θ＝θ0-μ·d·l
in the formula, theta0At 90 °, μ is the rotation angle adjustment factor,
when d is notWhen the distance is reduced, the rotation angle is increased; when the distance is constant and d is reduced, the rotation angle becomes large.
In order to solve the problem that an obstacle drives into an unmanned ship forbidden zone and a target cannot be reached, the distance between the unmanned ship and the target and a forbidden zone radius factor r are introduced into a traditional repulsion function, and the repulsion function is modified as follows:
wherein r is the forbidden zone radius.
When the unmanned ship is close to the obstacle, the repulsive force field is increased, the repulsive force is increased, and when the distance between the unmanned ship and the obstacle is equal to the radius of the forbidden region, the potential energy of the repulsive force field tends to be infinite, so that the obstacle is prevented from entering the forbidden region of the unmanned ship in principle.
The size of the repulsive force field of the traditional artificial force field is only related to the distance from the unmanned boat to the obstacle and is not related to the distance from the unmanned boat to the target. When the target is within the influence range of the obstacle, the attractive force potential field of the unmanned boat is gradually reduced in the process of reaching the target, and the repulsive force potential field is continuously increased at the moment, so that the unmanned boat cannot reach the target. Therefore, the repulsive force potential field function needs to be modified, the distance between the unmanned boat and the target is introduced into the repulsive force potential field function as a parameter, when the unmanned boat approaches the target point, the repulsive force potential field is also reduced, and the repulsive force potential field and the attractive force potential field are both changed into 0 when the unmanned boat reaches the target.
The unmanned ship can not fast return to the initial route after obstacle avoidance is finished. According to the scheme, in the process that the unmanned ship drives away from the obstacle, the expected target obtained by calculation through the LOS guidance method replaces the actual target XgA desired heading is calculated.
In the LOS guiding method, a sight distance vector is designed by combining a target and the current position of an unmanned ship, an expected target position is obtained through calculation, a real-time expected heading angle of the unmanned ship is determined according to the expected target position, and then an automatic heading controller of the unmanned ship continuously maintains the expected heading angle, so that the steering law of sight line navigation is completed. When the distance from the unmanned ship to the target is long, the expected target is adopted to replace the actual target to calculate the expected heading, and the heading angle of the unmanned ship rapidly returning to the initial route can be obtained.
The process of autonomous obstacle avoidance of the unmanned surface vehicle in the scheme is shown in figure 1.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. An autonomous obstacle avoidance method for an unmanned surface vehicle is characterized by comprising the following steps:
establishing an obstacle avoidance area model: taking the unmanned ship as a circle center, and sequentially dividing the whole navigation area into a forbidden area, an emergency obstacle avoidance area, a conventional obstacle avoidance area and a safe area from inside to outside;
conventionally, obstacle avoidance: when an obstacle intrudes into the conventional obstacle avoidance area, avoiding by adopting a linear speed control method;
emergency obstacle avoidance: when the conventional obstacle avoidance fails, the method is started, and when an obstacle intrudes into an emergency obstacle avoidance area, the expected course is calculated by adopting an artificial potential field method to avoid.
2. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 1, characterized in that: the radius R of the forbidden zone is the safe meeting distance DCPAs of the unmanned ship, the radius R1 of the emergency obstacle avoidance zone is n1 multiplied by Vusv multiplied by DCPAs, and the radius R2 of the conventional obstacle avoidance zone is n2 multiplied by Vusv multiplied by DCPAs; wherein Vusv is the speed of the unmanned ship, the unit is m/s, and n1 and n2 are preset coefficients.
3. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 2, characterized in that: the safe encounter distance DCPAs is 4 times that of the captain of the unmanned boat, and the coefficients n1 and n2 are set to 0.25 and 0.4, respectively.
4. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 1, characterized in that: further comprising environment modeling: converting the coordinates of the obstacles into rectangular grid data, calculating corresponding grid rectangular coordinates according to the grid row and column numbers when the grids have the obstacles, converting the grid rectangular coordinates into a heading coordinate system which takes the unmanned boat as the center of a circle and takes the true north as 0 degree, and acquiring the azimuth angle of the obstacles; the azimuth of the obstacle is converted into a fan-shaped grid number, and the fan-shaped grid at the number is considered to be occupied by the obstacle.
5. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 1, characterized in that: in the conventional obstacle avoidance, when the linear speed control method cannot successfully avoid, a feasible course is designed by adopting a vector field histogram algorithm to avoid.
6. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 5, wherein: the vector field histogram algorithm design feasible course comprises the following steps:
s1, interval division: filling fan-shaped grids by using rectangular grids, wherein the number of the fan-shaped grids is calculated according to the set unit fan angle, and the calculation formula of the number K of the fan-shaped grids is as follows: k is 360/angle;
s2, safety direction judgment: when an obstacle exists at the grid, calculating a corresponding grid rectangular coordinate according to the grid row and column number, converting the grid rectangular coordinate into a course coordinate system with the unmanned ship as the center of a circle and the true north as 0 degree, and acquiring an obstacle azimuth angle; converting the azimuth of the obstacle into a fan-shaped grid number, wherein the fan-shaped grid at the number is regarded as being occupied by the obstacle;
s3, judging feasibility direction: when the fan-shaped grid corresponding to the expected course of the unmanned ship is not occupied by the obstacle, the unmanned ship continues to sail along the expected course; otherwise, searching fan-shaped grid numbers which can be passed when the unmanned ship turns left and turns right, calculating the angular bisector direction of the unmanned ship as a candidate direction, comparing the cost of turning left and right, and selecting the direction with low cost as a feasible azimuth angle.
7. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 1, characterized in that: when an artificial potential field method is adopted for emergency obstacle avoidance, when the distance between the unmanned boat and the target is larger than the set distance, the attraction force is set to be a constant.
8. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 7, wherein: in the manual potential field method, the direction of the repulsive force component force is rotated by a certain angle theta, so that the included angle between the resultant force and the attractive force is less than or equal to 90 degrees.
9. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 8, wherein: introducing the distance rho (X, X) between the unmanned boat and the target into the repulsion function of the artificial potential field methodg) Forbidden zone radius r, the repulsion function is modified as:
in the formula, λ2Is the repulsive force gain coefficient, X, X0、XgRespectively representing the spatial positions of the unmanned boat, the obstacle and the target, rho (X, X)0) And ρ (X, X)g) Representing the distance, p, of the unmanned boat to the obstacle and target, respectively0Is the influence radius of the barrier on the unmanned ship, and r is the forbidden zone radius.
10. The autonomous obstacle avoidance method of the unmanned surface vehicle of claim 9, characterized in that: in the process that the unmanned ship drives away from the obstacle, the expected target obtained through calculation by the LOS guidance method replaces an actual target in an artificial potential field method to calculate the expected heading.
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| CN115344039B (en) * | 2022-07-06 | 2023-08-18 | 中国船舶科学研究中心 | Unmanned ship cluster obstacle avoidance method based on self-adaptive separation combination strategy |
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