CN117490713A - Path planning method, device, computer equipment and readable storage medium - Google Patents
Path planning method, device, computer equipment and readable storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
Abstract
The invention relates to the technical field of intelligent driving, and discloses a path planning method, a device, computer equipment and a readable storage medium, wherein the method comprises the following steps: constructing an artificial potential field according to pose information of the automobile at a starting point and a target point and position information of an obstacle; determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle to obtain a dispersed direction angle; determining the speed range of the automobile based on the speed constraint condition of the automobile and dispersing the speed to obtain a discrete speed; determining a plurality of adjacent points according to the discrete direction angle and the discrete speed; calculating the total potential energy of each adjacent point by using the artificial potential field, and selecting an optimal connection point from a plurality of adjacent points according to the total potential energy of each adjacent point; and connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path. The invention can improve the accuracy and reliability of path planning, so that the planned path accords with the kinematic model of the automobile and meets the actual driving state of the automobile.
Description
Technical Field
The invention relates to the technical field of intelligent driving, in particular to a path planning method, a path planning device, computer equipment and a readable storage medium.
Background
With the continuous improvement of the artificial intelligence level, the development hot spot of the automobile field gradually changes from the research and development of the traditional engine, the gearbox and the clutch into the research and development of the automatic driving technology. The research of the automatic driving technology mainly focuses on five aspects of sensing, positioning, decision making, planning and control, wherein the planning technology is environment sensing, and the vehicle control is started downwards, so that the method is a key ring of starting upwards and downwards in the automatic driving technology.
In the prior art, the automatic driving planning technology is mainly divided into two parts of transverse planning and longitudinal planning. The lateral planning mainly refers to path planning, and a collision-free path from a starting point to a target point needs to be planned for the automobile. The longitudinal planning mainly refers to speed planning, speed information is added to the path on the basis of transverse planning, and a complete track is finally formed. For transverse path planning, the artificial potential field method is one of the current common methods for solving paths, the method assumes that a target point generates attractive force to a vehicle and an obstacle generates repulsive force to the vehicle, and the resultant force of the two artificial forces controls the vehicle to move from a high potential field to a low potential field in a potential field formed by the target point and the obstacle.
The search of the artificial potential field method is carried out in a discrete space, and the search points are adjacent nodes around the search center point by taking the current automobile coordinate point as the center point. On a two-dimensional map, the manual potential field method only carries out local search in the x dimension and the y dimension, the solved original path can be regarded as being formed by connecting straight-line segments with different lengths, and further the situation that the sharp turning direction and the like do not accord with the kinematic constraint of an automobile possibly occurs, so that the original path cannot be directly used as a final path, namely, the path planning result cannot meet the actual driving condition.
Disclosure of Invention
In view of the above, the present invention provides a path planning method, apparatus, computer device and readable storage medium, so as to solve the problem that the path planning result cannot meet the actual driving situation.
In a first aspect, the present invention provides a path planning method, including:
constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle;
determining a direction angle range of the automobile based on a direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a dispersed direction angle;
Determining a speed range of the automobile based on the speed constraint condition of the automobile, and dispersing the speed in the speed range to obtain a discrete speed;
determining a plurality of adjacent points according to the discrete direction angle and the discrete speed;
calculating the total potential energy of each adjacent point by using the artificial potential field, and selecting an optimal connection point from a plurality of adjacent points according to the total potential energy of each adjacent point;
and connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path.
According to the path planning method provided by the embodiment of the invention, an artificial potential field is constructed according to the starting point pose information, the target point pose information and the obstacle position information, the direction angle range and the speed range of the automobile are obtained based on the direction angle constraint condition and the speed constraint condition of the automobile, the discrete direction angle and the discrete speed are obtained in the direction angle range and the speed range, a plurality of adjacent points are determined, an optimal connection point is selected according to the total potential energy of each adjacent point in the artificial potential field, and the optimal connection point is connected with a target point according to a preset connection mode, so that a planned path is obtained. According to the invention, the running adjacent points of the automobile are searched in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the path planning is performed based on the adjacent points, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, and the actual driving state of the automobile is satisfied.
In an alternative embodiment, connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path, including: and on the basis of meeting the turning radius constraint condition of the automobile, performing curve connection on the optimal connection point and the target point according to a preset connection mode to obtain a planned path.
After the optimal connection point is searched, the optimal connection point is still connected with the target point based on the direction angle constraint condition of the automobile, so that the planned path can be further ensured to conform to the running model of the automobile, and the actual driving state of the automobile is met.
In an alternative embodiment, after the optimal connection point is connected with the target point in a curve according to a preset connection mode, the method further includes: and obtaining an obstacle grid map, and detecting the obstacle of the planned path according to the obstacle grid map.
According to the invention, by detecting the obstacle collision of the planned path, the automobile can be ensured not to collide with the existing obstacle on the path when traveling according to the planned path, the obstacle avoidance planning is performed for the user in advance, and the driving safety of the user is ensured.
In an alternative embodiment, constructing the artificial potential field based on the first pose information of the vehicle at the start point, the second pose information of the target point, and the position information of the obstacle comprises: acquiring first pose information of a starting point and second pose information of a target point; constructing an attractive potential field of the target point according to the first pose information and the second pose information; constructing a corresponding barrier grid diagram based on the barriers in a preset range, acquiring position information of the barrier grid, and constructing a barrier repulsive force potential field according to the position information and the first pose information; and superposing the target point attractive potential field and the obstacle repulsive potential field to obtain an artificial potential field.
According to the invention, the artificial potential field comprising the target point attractive potential field and the obstacle repulsive potential field is constructed, so that the primary planning of the automobile driving path can be performed according to the target point and the obstacle. In addition, the meshing process is carried out on the obstacle, so that the problem that the shape of the obstacle is irregular and difficult to directly express can be solved, and the accuracy of the obstacle repulsive potential field can be improved by considering the repulsive force generated by each obstacle grid when the obstacle repulsive potential field is constructed.
In an alternative embodiment, performing obstacle detection on the planned path according to the obstacle grid map includes: dispersing the planned path according to preset distance intervals to obtain a plurality of collision detection points; selecting a current collision detection point from a plurality of collision detection points; judging whether an obstacle grid exists at the current collision detection point; when the current collision detection point does not have an obstacle grid, selecting the next collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the selected next collision detection point as the current collision detection point, and returning to the step of judging whether the current collision detection point has the obstacle grid; and when the current collision detection point has an obstacle grid, determining that an obstacle exists in the planned path.
According to the invention, the originally obtained planned path is subjected to discrete and collision detection, so that whether the optimal connection point and the target point can be successfully connected on the premise that the collision between the automobile and the existing obstacle is ensured, the detection time can be shortened by performing the collision detection according to the originally obtained planned path, and meanwhile, the smoothness of the path and the real-time performance of the detection are both considered.
In an alternative embodiment, after determining that an obstacle exists in the planned path, the method further includes: and selecting the last collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the last collision monitoring point as an optimal connection point, connecting the optimal connection point with the target point according to a preset connection mode, obtaining an adjusted planned path, returning to obtain an obstacle grid diagram, and detecting the obstacle of the planned path according to the obstacle grid diagram.
According to the method, after the fact that the automobile collides with the obstacle according to the primarily planned path is detected, path planning adjustment is carried out according to the collision detection point before collision, and cyclic adjustment of the planned path can be achieved, so that collision with the obstacle is prevented absolutely on the whole finally obtained planned path, the situation that a user needs to adjust the driving state in an emergency mode to avoid the obstacle in actual driving is avoided, and driving safety is improved. And the obstacle avoidance analysis and the path planning adjustment are combined, so that the path can be smoothly processed while the obstacle avoidance is ensured, the calculation mode is simple, and the real-time performance is strong.
In a second aspect, the present invention provides a path planning apparatus, the apparatus comprising:
the potential field construction module is used for constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle;
the direction angle discrete module is used for determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a discrete direction angle;
the speed dispersing module is used for determining the speed range of the automobile based on the speed constraint condition of the automobile, dispersing the speed in the speed range and obtaining a dispersing speed;
the adjacent point acquisition module is used for determining a plurality of adjacent points according to the discrete direction angle and the discrete speed;
the connection point searching module is used for respectively calculating the total potential energy of each adjacent point by using the artificial potential field and selecting the optimal connection point from a plurality of adjacent points according to the total potential energy of each adjacent point;
and the path planning module is used for connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path.
According to the path planning device provided by the embodiment of the invention, an artificial potential field is constructed according to the starting point pose information, the target point pose information and the obstacle position information, the direction angle range and the speed range of the automobile are obtained based on the direction angle constraint condition and the speed constraint condition of the automobile, the discrete direction angle and the discrete speed are obtained in the direction angle range and the speed range, a plurality of adjacent points are determined, an optimal connection point is selected according to the total potential energy of each adjacent point in the artificial potential field, and the optimal connection point is connected with a target point according to a preset connection mode, so that a planned path is obtained. According to the invention, the running adjacent points of the automobile are searched in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the path planning is performed based on the adjacent points, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, and the actual driving state of the automobile is satisfied.
In a third aspect, the present invention provides a computer device comprising: the system comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, so that the path planning method of the first aspect or any implementation mode corresponding to the first aspect is executed.
In a fourth aspect, the present invention provides a vehicle comprising the computer apparatus of the third aspect.
In a fifth aspect, the present invention provides a computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the path planning method of the first aspect or any one of its corresponding embodiments.
The invention has the beneficial effects that:
(1) According to the invention, the running state of the automobile is discretized based on the kinematic constraint condition of the automobile in the path planning process, the running track of the automobile is simulated, so that discrete adjacent points are obtained, and the optimal connection point is selected according to the potential energy of the adjacent points in the artificial potential field, so that the optimal connection point is connected with the target point, the path is initially planned, the planned path can be ensured to conform to the running model of the automobile, and the actual driving state of the automobile is met.
(2) According to the invention, the preliminary planning path is subjected to discrete and obstacle collision detection, so that the cyclic adjustment of the planning path is realized, and the situation that the automobile runs according to the final planning path and cannot collide with an obstacle can be ensured, thereby ensuring the driving safety of a user.
(3) According to the invention, the path planning in the real driving state is performed by combining the adjacent point search, the path planning and the obstacle avoidance analysis, so that the planned path can be smoothly processed while obstacle avoidance is ensured, and the overall calculation mode is simple and the real-time performance is strong.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a path planning method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a discrete trajectory of a path planning method according to an embodiment of the present invention;
FIG. 3 is a flow chart of another path planning method according to an embodiment of the present invention;
FIG. 4 is an obstacle meshing intent of another path planning method in accordance with an embodiment of the invention;
FIG. 5 is a flow chart of yet another path planning method according to an embodiment of the present invention;
FIG. 6 is a flow chart of yet another path planning method according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of planned path collision detection for another path planning method according to an embodiment of the present invention;
FIG. 8 is a block diagram of a path planning apparatus according to an embodiment of the present invention;
fig. 9 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention is suitable for a scene of planning the driving path of the automobile according to the preset destination. The embodiment of the invention provides a path planning method, which performs potential energy adjacent point search by introducing a direction angle constraint condition of an automobile and a speed constraint condition of the automobile in the path planning process so as to achieve the effect that the planned path meets the actual driving condition. It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
In this embodiment, a path planning method is provided, which may be used in the above-mentioned computer, and fig. 1 is a flowchart of the path planning method according to an embodiment of the present invention, as shown in fig. 1, where the flowchart includes the following steps:
step S101, constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle.
Specifically, in the embodiment of the invention, the current position of the automobile is taken as a starting point, the information of the surrounding environment is acquired by utilizing various sensors carried on the automobile body, and a world coordinate system is established by selecting a proper position. The embodiment of the invention performs path planning on a two-dimensional plane, constructs a world coordinate system by taking a rear axle central point of an automobile initial state as an origin, then determines coordinates of a starting point and coordinates (x, y) of a destination target point, simultaneously acquires a course angle of the automobile at the starting point or the target point, and respectively represents first pose information of the starting point and second pose information of the target point as (x) start ，y start ，θ start ) And (x) goal ，y goal ，θ goal ). At the same time, the embodiment of the invention determines the obstacle in a certain range and acquires the position information (x) of the obstacle under the constructed time coordinate system obs ，y obs )。
In an alternative implementation, the embodiment of the present invention uses an artificial potential field method to perform path planning, where the artificial potential field method simulates the concept of potential fields in physics, but is not a single field, but is formed by overlapping and combining two fields: a gravitational field of the target location and a repulsive field of the obstacle. The gravitational field attracts the vehicle toward the target point, while the repulsive field keeps the vehicle as far away from the obstacle as possible. The embodiment of the invention is based on the first pose information (x) start ，y start ，θ start ) And second pose information (x) goal ，y goal ，θ goal ) Constructing a target point attractive potential field based on the position information (x obs ，y obs ) And pose information of the origin (x start ，y start ，θ start ) And constructing an obstacle repulsive force potential field, and superposing the target point attractive force potential field and the obstacle repulsive force potential field to obtain an artificial potential field.
Step S102, determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a dispersion direction angle.
And step S103, determining the speed range of the automobile based on the speed constraint condition of the automobile, and dispersing the speed in the speed range to obtain a discrete speed.
Specifically, in the embodiment of the present invention, the biggest defect of the artificial potential field method is a problem that a local minimum trap may be trapped. When the gravitational field and the repulsive field cancel each other, there will be other points with a gradient of 0 except the target point, and the trajectory found is incorrect. Therefore, in the embodiment of the invention, the kinematic constraint conditions of the automobile, such as the maximum turning radius and the minimum turning radius of the automobile, the highest speed per hour of the automobile and the like, are considered to be generated due to the automobile performance factors in the actual driving process of the automobile, the kinematic constraint conditions of the automobile are classified into the direction angle constraint conditions and the speed constraint conditions, then the artificial potential field is searched for the adjacent points, and the path planning is carried out according to the adjacent points. Wherein the direction angle constraint condition is set according to the minimum turning radius of the automobile, namely the direction angle of the automobileTo meet the minimum turning radius R min Is formulated as follows:
meanwhile, the speed constraint condition is set according to the highest speed of the automobile, namely, the automobile speed is smaller than the highest speed.
In an alternative implementation, the embodiment of the invention determines the range of the steering angle of the automobile with the maximum steering angle under the constraint of the steering angleAnd discretizing the direction angle within the direction angle range to obtain a plurality of discrete direction angles. At the same time, the speed range [ V ] of the vehicle is determined at the highest speed per hour under the speed constraint max ，-V max ]And discretizing the speed within the speed range to obtain a plurality of discrete speeds. The discrete number is determined according to the path algorithm and the demand and the calculation force of the calculation chip, and when the automatic driving level of the automobile is high, the calculation force of the vehicle-mounted calculation chip is enough, and the discrete number of the speed and the direction angle can be set to be a large value. The embodiment of the invention sets the discrete number of the direction angle and the speed to 3, namely the discrete direction angle comprises: />0 and->The discrete speeds include: v (V) max 0 and-V max By way of example only, and not limitation.
Step S104, determining a plurality of adjacent points according to the discrete direction angle and the discrete speed.
Specifically, in the embodiment of the invention, any one of a plurality of discrete direction angles and discrete speeds is selected, the vehicle is simulated to run at a constant speed in unit time according to a certain discrete direction angle and a certain discrete speed, namely, the vehicle is simulated to do constant motion in unit time at a constant speed and a constant course angle under the assumption that the vehicle speed and the direction angle are constant in unit time, and the track of the vehicle in the unit time can be solved by utilizing a dynamics model of the vehicle. Different tracks can be obtained under the combination of different discrete direction angles and different discrete speeds, so that the tracks are called discrete tracks, and the end points of the discrete tracks are used as the adjacent points obtained by searching. According to the embodiment of the invention, the current position of the automobile is taken as a center point, and the automobile is driven at a constant speed according to 3 discrete direction angles and 3 discrete speeds to obtain 6 discrete tracks (the discrete speeds are still at the center point when 0), as shown in fig. 2, 6 adjacent points can be obtained, but the invention is not limited thereto. In the path planning process, the more the discrete number of direction angles and speeds, the more the number of adjacent points can be searched, and the greater the probability of finding a proper path.
Step S105, calculating the total potential energy of each adjacent point by using the artificial potential field, and selecting the optimal connection point from a plurality of adjacent points according to the total potential energy of each adjacent point.
Specifically, in the embodiment of the invention, all the searched adjacent points are in the constructed artificial potential field, so the embodiment of the invention calculates the total potential energy of each adjacent point according to the artificial potential field, selects the adjacent point with the lowest potential energy as the optimal connection point, i.e. performs path planning according to the optimal connection point to obtain the most suitable path, but not limited to the optimal connection point. At this time, the pose information of the best connection point in the world coordinate system is (x) cur ，y cur ，θ cur )。
And S106, connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path.
Specifically, in the embodiment of the present invention, the search space is discretized when the adjacent point is searched, but the space is continuous when the vehicle is in the state space, which results in that the target point of the vehicle may never be searched when the discrete space is searched, that is, the target point cannot be found in the search space shown in fig. 2, so that the adjacent point and the target point need to be connected by a continuous curve. At this time, the optimal connection point is connected to the target point so as to confirm that the corresponding discrete trajectory of the optimal connection point is the optimal running direction of the vehicle. The connection is not a straight line or curve connection in a simple sense, but a curve connection for path planning according to an automobile kinematic model. The embodiment of the invention adopts the RS curve or Dubin curve commonly used in the field for connection, and the specific connection mode is not repeated here. The RS curve or the Dubin curve can be used for planning a connectable target point (x goal ,y goal ,θ goal ) And the best connection point (x) cur ,y cur ,θ cur ) And takes this curve as the planned path.
According to the path planning method provided by the embodiment of the invention, an artificial potential field is constructed according to the starting point pose information, the target point pose information and the obstacle position information, the direction angle range and the speed range of the automobile are obtained based on the direction angle constraint condition and the speed constraint condition of the automobile, the discrete direction angle and the discrete speed are obtained in the direction angle range and the speed range, a plurality of adjacent points are determined, an optimal connection point is selected according to the total potential energy of each adjacent point in the artificial potential field, and the optimal connection point is connected with a target point according to a preset connection mode, so that a planned path is obtained. According to the invention, the running adjacent points of the automobile are searched in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the path planning is performed based on the adjacent points, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, and the actual driving state of the automobile is satisfied.
In this embodiment, a path planning method is provided, which may be used in the above-mentioned computer, and fig. 3 is a flowchart of the path planning method according to an embodiment of the present invention, as shown in fig. 3, where the flowchart includes the following steps:
Step S301, constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle.
Specifically, the step S301 includes:
step S3011, acquiring first pose information of a start point and second pose information of a target point. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S3012, constructing a target point attractive potential field according to the first pose information and the second pose information.
Specifically, in the embodiment of the present invention, first pose information (x) of a start point under a constructed world coordinate system is acquired start ,y start ,x start ) And second pose information (x) goal ,y goal ,x goal ) Then, the gravitational potential field for the target pointThe method has the characteristics of strong attractive force when the method is far away from the obstacle and weak attractive force when the method is close to the obstacle, a target point attractive potential field in a preset range is constructed, and the expression of the established target point attractive potential is as follows:
||X-X goal || 2 ＝(x-x goal ) 2 +(y-y goal ) 2
wherein U is at (X) is attractive potential energy, and X is coordinate information (X) of a starting point start ,y start )，X goal Is coordinate information (x goal ,y goal )，K at To attract potential field coefficient, ||X-X goal || 2 The square of the Euclidean distance from the starting point to the target point;
step S3013, constructing a corresponding barrier grid diagram based on the barriers in the preset range, acquiring the position information of the barrier grid, and constructing a barrier repulsive force potential field according to the position information and the first pose information.
Specifically, in the embodiment of the present invention, since the shape of the obstacle is mostly irregular and difficult to directly express, it is necessary to disperse the obstacle in the form of a mesh into the world coordinate system, treat the obstacle as a mesh of the obstacle whose coordinate position is known in a regular manner, and thereby acquire information of the shape, size, position, and the like of the obstacle. As shown in fig. 4, the embodiment of the present invention approximates the shape of the obstacle by a plurality of closely arranged rectangular grids, and uses the coordinates of the center point of each grid to represent the coordinates of a single grid in the world coordinate system, which can be represented as (x obsi ,y obsi ) Finally, the obstacle can be represented as a plurality of obstacle meshes arranged and combined on a plane. The smaller the grid size is, the more accurate the shape of the fitted obstacle is, and the size of the search space can be increased, but the calculation amount brought by the size is also increased, and the specific grid size can be adjusted according to the actual algorithm requirement.
In an optional implementation manner, each obstacle grid is regarded as an obstacle, and the repulsive potential field of all obstacles in the whole obstacle grid map has the characteristics of strong repulsive force when approaching the obstacle and weak repulsive force when separating from the obstacle, and all obstacle grids in the obstacle grid map have repulsive force on the position where the starting point of the automobile is located, so that the repulsive potential field of the starting point is the superposition of the obstacle potential fields generated by all obstacle grids. The expression of the established obstacle repulsive force potential field is as follows:
Wherein U is re (X) is the repulsive force potential energy,k is the position information of the barrier grid re For repulsive potential field coefficient, < >>Is the square of the euclidean distance from the start point to the obstacle mesh i.
Step S3014, the target point attractive potential field and the obstacle repulsive potential field are superimposed to obtain an artificial potential field.
Specifically, in the embodiment of the present invention, the expression of the artificial potential field is as follows:
U(X)＝U at (X)+U re (X)
step S302, determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a dispersion direction angle. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S303, determining the speed range of the automobile based on the speed constraint condition of the automobile, and dispersing the speed in the speed range to obtain a discrete speed. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S304, determining a plurality of adjacent points according to the discrete direction angle and the discrete speed. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
In step S305, the total potential energy of each adjacent point is calculated by using the artificial potential field, and the optimal connection point is selected from the plurality of adjacent points according to the total potential energy of each adjacent point. Please refer to step S105 in the embodiment shown in fig. 1 in detail, which is not described herein.
And step S306, connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path. Please refer to step S106 in the embodiment shown in fig. 1 in detail, which is not described herein.
According to the path planning method provided by the embodiment of the invention, the running adjacent points of the automobile are searched in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the path planning is performed based on the adjacent points, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, and the actual driving state of the automobile is satisfied.
In this embodiment, a path planning method is provided, which may be used in the above-mentioned computer, and fig. 5 is a flowchart of the path planning method according to an embodiment of the present invention, as shown in fig. 5, where the flowchart includes the following steps:
step S501, an artificial potential field is constructed according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle. Please refer to step S301 in the embodiment shown in fig. 3 in detail, which is not described herein.
Step S502, determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a dispersion direction angle. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
In step S503, the speed range of the automobile is determined based on the speed constraint condition of the automobile, and the speed is discretized in the speed range to obtain a discrete speed. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S504, determining a plurality of adjacent points according to the discrete direction angle and the discrete speed. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
In step S505, the total potential energy of each adjacent point is calculated by using the artificial potential field, and the optimal connection point is selected from the plurality of adjacent points according to the total potential energy of each adjacent point. Please refer to step S105 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S506, connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path. Please refer to step S106 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S507, an obstacle grid chart is obtained, and obstacle detection is carried out on the planned path according to the obstacle grid chart.
Specifically, in the embodiment of the invention, the path planning by adopting the RS curve or the Dubin curve can meet the kinematic constraint of the automobile, and is one of the path planning algorithms commonly used in the open space of the automobile, but the RS curve or the Dubin curve does not avoid the obstacle, so that the embodiment of the invention detects the collision of the obstacle on the obtained planned path, and judges whether the curve connection is successful or not. Therefore, the embodiment of the invention carries out meshing processing on the obstacle, so that the obstacle detection is carried out only according to the obstacle mesh when the obstacle detection is carried out, namely whether the obtained planning path has the obstacle mesh or not is judged, and if the planning path has the obstacle mesh, the planning path is adjusted, so that the obstacle avoidance is realized in advance.
According to the path planning method provided by the embodiment of the invention, the path planning is carried out on the basis of the approach points by searching the approach points of the automobile running in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the obstacle collision detection is carried out on the planned route, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, the actual driving state of the automobile is met, and the comfort and the safety of the automobile running of a user are improved.
In this embodiment, a path planning method is provided, which may be used in the above-mentioned computer, and fig. 6 is a flowchart of the path planning method according to an embodiment of the present invention, as shown in fig. 6, where the flowchart includes the following steps:
step S601, constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle. Please refer to step S301 in the embodiment shown in fig. 3 in detail, which is not described herein.
Step S602, determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a dispersion direction angle. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S603, determining a speed range of the automobile based on the speed constraint condition of the automobile, and dispersing the speed in the speed range to obtain a discrete speed. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S604, determining a plurality of adjacent points according to the discrete direction angle and the discrete speed. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S605, the total potential energy of each adjacent point is calculated by using the artificial potential field, and the optimal connection point is selected from the plurality of adjacent points according to the total potential energy of each adjacent point. Please refer to step S105 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S606, connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path. Please refer to step S106 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S607, an obstacle mesh map is acquired, and obstacle detection is performed on the planned path according to the obstacle mesh map.
Specifically, the step S607 includes:
step S6071, discretizing the planned path according to the preset distance interval to obtain a plurality of collision detection points.
Specifically, in the embodiment of the present invention, as shown in fig. 7, the planned path of the RS curve is discretized according to the preset distance interval, so as to obtain a plurality of collision detection points. The preset distance interval is determined according to the size of the vehicle body or the size of each obstacle grid, for example, may be set to 1/2 of the vehicle length, which is only used as an example and not limited thereto.
Step S6072, selecting a current collision detection point from the plurality of collision detection points.
Specifically, in the embodiment of the present invention, the discrete path includes a plurality of collision detection points, the optimal connection point is taken as a starting point, the target point is taken as an end point, and the collision detection points are sequentially selected from the starting point on the planned path as the current collision detection points.
Step S6073, judging whether the current collision detection point has an obstacle mesh.
Specifically, in the embodiment of the present invention, it is determined whether or not an obstacle mesh exists at the collision detection point. If the obstacle grid does not exist at the position, the vehicle can not collide with the obstacle when running to the position according to the planned path, and all collision detection points can be sequentially detected to avoid collision, the planned path is taken as a final planned path, and a user can drive the vehicle to safely run according to the path, so that the situations of the obstacle, the sharp turn and the like can not occur.
Step S6074, when the current collision detection point does not have the obstacle grid, selecting the next collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the selected next collision detection point as the current collision detection point, and returning to the step of judging whether the current collision detection point has the obstacle grid.
Specifically, in the embodiment of the present invention, collision detection points are sequentially selected from the optimal connection point as a starting point to perform obstacle detection, so that steps S6073-S6074 are repeated to implement point-by-point detection on the collision detection points on the planned path, thereby gradually ensuring the running safety of the planned path.
Step S6075, when the current collision detection point has an obstacle grid, it is determined that an obstacle exists in the planned path.
Specifically, in the embodiment of the present invention, if an obstacle grid exists at a certain collision detection point, it represents that the vehicle collides with the obstacle when traveling to the point according to the planned path, and the detection is stopped at this time, and the planned path is adjusted.
Step S6076, selecting the last collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the last collision detection point as the optimal connection point, connecting the optimal connection point with the target point according to a preset connection mode, obtaining an adjusted planned path, returning to obtain an obstacle grid diagram, and detecting the obstacle of the planned path according to the obstacle grid diagram.
Specifically, in the embodiment of the present invention, when an obstacle is detected in the current collision detection point, the collision detection point that has been detected before the current collision detection point is represented as safe, so that starting from the previous collision detection point, the previous collision detection point is connected with the target point again according to the preset connection mode in step 606, so as to adjust the planned path in time, and obtain the adjusted planned path. The connection process is detailed in step S106 in the embodiment shown in fig. 1, and will not be described herein.
In an alternative implementation manner, the embodiment of the present invention performs obstacle detection on the adjusted planned path again, that is, repeats steps S6071-S6076, which is equivalent to performing cyclic adjustment on the planned path, and continuously combines the adjusted path with the path that has been previously detected as not having a collision until all detection points on the planned path have not collided when reaching the target point, so that a smooth path without collision can be obtained, which is used as the final result of path planning. In the embodiment of the invention, under the condition that the target point is reachable, as long as the optimal connecting point obtained by continuous searching is close enough to the target point, the adjacent point and the target point can be successfully connected through an RS curve or a Dubins curve.
According to the path planning method provided by the embodiment of the invention, the path planning is carried out on the basis of the approach points by searching the approach points of the automobile running in the artificial potential field based on the direction angle constraint condition of the automobile and the speed constraint condition of the automobile, and the point-by-point obstacle collision detection is carried out on the planned route, so that the accuracy and the reliability of the path planning can be improved, the planned path accords with the kinematic model of the automobile, the actual driving state of the automobile is met, and the comfort and the safety of the automobile running of a user are improved.
The present embodiment also provides a path planning device, which is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides a path apparatus, as shown in fig. 8, including:
a potential field construction module 801, configured to construct an artificial potential field according to first pose information of an automobile at a starting point, second pose information of a target point, and position information of an obstacle;
the direction angle discretizing module 802 is configured to determine a direction angle range of the automobile based on a direction angle constraint condition of the automobile, and discretize a direction angle in the direction angle range to obtain a discrete direction angle;
a speed dispersing module 803, configured to determine a speed range of the automobile based on a speed constraint condition of the automobile, and disperse the speed within the speed range to obtain a discrete speed;
a neighboring point acquisition module 804, configured to determine a plurality of neighboring points according to the discrete direction angle and the discrete speed;
The connection point searching module 805 is configured to calculate total potential energy of each neighboring point by using the artificial potential field, and select an optimal connection point from a plurality of neighboring points according to the total potential energy of each neighboring point;
the path planning module 806 is configured to connect the optimal connection point with the target point according to a preset connection mode, so as to obtain a planned path.
In some alternative embodiments, potential field construction module 801 includes:
and the pose information acquisition unit is used for acquiring the first pose information of the starting point and the second pose information of the target point.
And the target point attractive potential field construction unit is used for constructing a target point attractive potential field according to the first pose information and the second pose information.
An obstacle repulsive force potential field construction unit is used for constructing a corresponding obstacle grid diagram based on the obstacles in a preset range, acquiring position information of the obstacle grid, and constructing an obstacle repulsive force potential field according to the position information and the first pose information.
And the artificial potential field construction unit is used for superposing the target point attractive potential field and the obstacle repulsive potential field to obtain an artificial potential field.
In some alternative embodiments, the path planning module 804 includes:
and the preliminary path planning unit is used for carrying out curve connection on the optimal connection point and the target point according to a preset connection mode on the basis of meeting the turning radius constraint condition of the automobile to obtain a planned path.
And the path obstacle detection unit is used for acquiring the obstacle grid diagram and detecting the obstacle of the planned path according to the obstacle grid diagram.
In some alternative embodiments, the path obstacle detection unit includes:
the path obstacle discrete detection subunit is used for dispersing a planned path according to a preset distance interval to obtain a plurality of collision detection points; selecting a current collision detection point from a plurality of collision detection points; judging whether an obstacle grid exists at the current collision detection point; when the current collision detection point does not have an obstacle grid, selecting the next collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the selected next collision detection point as the current collision detection point, and returning to the step of judging whether the current collision detection point has the obstacle grid; and when the current collision detection point has an obstacle grid, determining that an obstacle exists in the planned path.
And the path adjustment subunit is used for selecting the last collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the last collision detection point as the optimal connection point, connecting the optimal connection point with the target point according to a preset connection mode, obtaining an adjusted planned path, returning to obtain an obstacle grid graph, and detecting the obstacle of the planned path according to the obstacle grid graph.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The path planning means in this embodiment are presented in the form of functional units, here referred to as ASIC (Application Specific Integrated Circuit ) circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above described functionality.
The embodiment of the invention also provides a computer device which is provided with the path planning device shown in the figure 8.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 9, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 9.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.
The embodiment of the invention also provides a vehicle provided with the computer equipment shown in the figure 9.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method of path planning, the method comprising:
constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle;
determining a direction angle range of an automobile based on a direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a discrete direction angle;
determining a speed range of the automobile based on the speed constraint condition of the automobile, and dispersing the speed in the speed range to obtain a discrete speed;
determining a plurality of adjacent points according to the discrete direction angle and the discrete speed;
calculating the total potential energy of each adjacent point by using the artificial potential field, and selecting an optimal connection point from the plurality of adjacent points according to the total potential energy of each adjacent point;
and connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path.
2. The method according to claim 1, wherein connecting the optimal connection point with the target point according to a preset connection manner to obtain a planned path includes:
and on the basis of meeting the turning radius constraint condition of the automobile, performing curve connection on the optimal connection point and the target point according to a preset connection mode to obtain a planned path.
3. The method according to claim 2, further comprising, after performing curve connection on the optimal connection point and the target point according to a preset connection manner, obtaining a planned path:
and obtaining an obstacle grid map, and detecting the obstacle of the planned path according to the obstacle grid map.
4. The method of claim 1, wherein constructing the artificial potential field based on the first pose information of the vehicle at the start point, the second pose information of the target point, and the position information of the obstacle comprises:
acquiring first pose information of the starting point and second pose information of the target point;
constructing a target point attractive potential field according to the first pose information and the second pose information;
constructing a corresponding barrier grid diagram based on barriers in a preset range, acquiring position information of the barrier grid, and constructing a barrier repulsive force potential field according to the position information and the first pose information;
And superposing the target point attractive potential field and the obstacle repulsive potential field to obtain an artificial potential field.
5. A method according to claim 3, wherein said obstacle detecting of said planned path according to said obstacle grid map comprises:
dispersing the planned path according to preset distance intervals to obtain a plurality of collision detection points;
selecting a current collision detection point from a plurality of collision detection points;
judging whether the obstacle grid exists in the current collision detection point or not;
when the obstacle grid does not exist in the current collision detection point, selecting the next collision detection point of the current collision detection point in the planned path according to a preset selection rule, taking the selected next collision detection point as the current collision detection point, and returning to the step of judging whether the obstacle grid exists in the current collision detection point;
and when the current collision detection point exists the obstacle grid, judging that an obstacle exists in the planned path.
6. The method of claim 5, further comprising, after determining that an obstacle is present in the planned path:
And selecting the last collision detection point of the current collision detection point from the planned path according to a preset selection rule, taking the last collision detection point as an optimal connection point, connecting the optimal connection point with the target point according to a preset connection mode, obtaining an adjusted planned path, returning to obtain an obstacle grid diagram, and detecting the obstacle of the planned path according to the obstacle grid diagram.
7. A path planning apparatus, the apparatus comprising:
the potential field construction module is used for constructing an artificial potential field according to the first pose information of the automobile at the starting point, the second pose information of the target point and the position information of the obstacle;
the direction angle discrete module is used for determining the direction angle range of the automobile based on the direction angle constraint condition of the automobile, and dispersing the direction angle in the direction angle range to obtain a discrete direction angle;
the speed dispersing module is used for determining the speed range of the automobile based on the speed constraint condition of the automobile, dispersing the speed in the speed range and obtaining a dispersing speed;
the adjacent point acquisition module is used for determining a plurality of adjacent points according to the discrete direction angle and the discrete speed;
The connection point searching module is used for respectively calculating the total potential energy of each adjacent point by utilizing the artificial potential field and selecting the optimal connection point from the plurality of adjacent points according to the total potential energy of each adjacent point;
and the path planning module is used for connecting the optimal connection point with the target point according to a preset connection mode to obtain a planned path.
8. A computer device, comprising:
a memory and a processor in communication with each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the path planning method of any of claims 1 to 6.
9. A vehicle comprising the computer device of claim 8.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the path planning method of any one of claims 1 to 6.
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