CN115903853B - Safe feasible domain generation method and system based on effective barrier - Google Patents

Safe feasible domain generation method and system based on effective barrier Download PDF

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CN115903853B
CN115903853B CN202310016889.1A CN202310016889A CN115903853B CN 115903853 B CN115903853 B CN 115903853B CN 202310016889 A CN202310016889 A CN 202310016889A CN 115903853 B CN115903853 B CN 115903853B
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obstacle
stack
representing
unmanned vehicle
polygon
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CN115903853A (en
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龚建伟
张曦
宋佳睿
臧政
陈信燃
王博洋
吕超
吴绍斌
齐建永
王泽麟
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Beilihuidong Beijing Education Technology Co ltd
Beijing Institute of Technology BIT
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Beijing Institute of Technology BIT
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Abstract

The invention discloses a safe and feasible region generation method and system based on effective barriers, and relates to the technical field of unmanned aerial vehicles. The method comprises the following steps: acquiring attitude information of an unmanned vehicle; collecting space pose information of an obstacle; building a stack, wherein the stack is currently empty; based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle, storing the related information of the 1 st obstacle into a stack; based on the pose information of the unmanned vehicle and the space pose information of the obstacle, judging the effectiveness of the rest obstacle, and storing the related information of the effective obstacle into a stack; a safe feasible region is generated based on all valid obstacles in the stack. According to the invention, the interaction relation between the barriers and the target unmanned vehicles is considered, the invalid barriers are screened out, the safe feasible region dimension is reduced, so that the safe feasible region dimension is smaller than or equal to the number of the barriers, the effect is particularly obvious under the condition that the barriers are dense, and the safe feasible region dimension is greatly reduced.

Description

Safe feasible domain generation method and system based on effective barrier
Technical Field
The invention relates to the technical field of unmanned aerial vehicle, in particular to a safe feasible region generation method and system based on effective barriers.
Background
Unmanned vehicles (simply unmanned vehicles) have become a research hotspot in recent years. The local path planning of the unmanned vehicle is taken as one of the key technologies, and the performance of the unmanned vehicle directly determines whether the unmanned vehicle runs successfully or not.
The unmanned vehicle running track needs to meet three requirements of smoothness, optimality and real-time performance. Therefore, in recent years, many students describe the unmanned vehicle trajectory planning problem as an optimization problem, but the non-convex obstacle avoidance constraint can change the original problem into a non-convex optimization problem which is difficult to solve. Description of collision-free solution space for unmanned vehicles using safe-viable domains is a common approach in recent years. Most typically, the non-convex optimization problem can be effectively converted into a convex optimization problem by describing the collision-free solution space with a safety corridor. The security corridor is generated in a security feasible region and is a reduced security feasible region with more abundant functionality.
In the conventional safe feasible region generation method, the dimension of the safe feasible region is equal to the number of the barriers, and the more the barriers are, the higher the dimension of the safe feasible region is. However, the higher the dimension of the safe feasible region, the lower the efficiency of many methods such as the safe corridor.
Disclosure of Invention
The invention aims to provide a safe feasible region generation method and system based on effective barriers, which are used for reducing the dimension of the safe feasible region and improving the efficiency.
In order to achieve the above object, the present invention provides the following solutions:
a safe feasible region generation method based on effective barriers, comprising:
acquiring attitude information of an unmanned vehicle, and describing the unmanned vehicle by utilizing a polygon;
collecting space pose information of an obstacle, and describing the obstacle by utilizing a convex polygon;
building a stack, wherein the stack is currently empty;
based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle, storing the related information of the 1 st obstacle into the stack; the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle, the 1 st obstacle being nearest to the unmanned aerial vehicle, and the polygon vertexes of the unmanned aerial vehicle, the unmanned aerial vehicle being nearest to the 1 st obstacle;
based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle, judging the effectiveness of the rest obstacle, and storing the related information of the effective obstacle into the stack;
a safe feasible region is generated based on all valid obstacles in the stack.
Optionally, the expression of the attitude information of the unmanned vehicle is as follows:
Figure 759304DEST_PATH_IMAGE001
p=(x ego ,y ego )'
Figure 256538DEST_PATH_IMAGE002
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;
Figure 770696DEST_PATH_IMAGE003
an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;
Figure 226559DEST_PATH_IMAGE004
Representing the kth vertex relative coordinates of the unmanned vehicle polygon;
Figure 759040DEST_PATH_IMAGE005
Representing a collection of unmanned polygonal vertices.
Optionally, the expression of the spatial pose information of the obstacle is as follows:
Figure 909399DEST_PATH_IMAGE006
Figure 38416DEST_PATH_IMAGE007
Figure 361950DEST_PATH_IMAGE008
wherein i represents the number of the obstacle; q i Representing coordinates of the ith obstacle in the driving environment; w (W) i Appearance information indicating an i-th obstacle;
Figure 686621DEST_PATH_IMAGE009
representing the number of obstacles;
Figure 463341DEST_PATH_IMAGE010
An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;
Figure 342304DEST_PATH_IMAGE011
Representing the j-th vertex relative coordinates of the i-th obstacle polygon;
Figure 211472DEST_PATH_IMAGE012
Representing an ith set of obstacle polygon vertices; j (j) i Representing the number of vertices of the ith barrier polygon.
Optionally, based on the pose information of the unmanned vehicle and the spatial pose information of the obstacle, the method for judging the validity of the remaining obstacle specifically includes:
determining obstacle related information for each remaining obstacle based on the pose information of the unmanned vehicle and the space pose information of the obstacle; the obstacle related information comprises an obstacle polygon vertex with the nearest obstacle distance from the unmanned vehicle, an unmanned vehicle polygon vertex with the nearest unmanned vehicle distance from the obstacle and a corresponding obstacle number;
and judging the effectiveness of the rest obstacles based on the obstacle related information and the stack top element information of the stack.
Optionally, the generation formula of the safe feasible region is as follows:
Figure 203699DEST_PATH_IMAGE013
Figure 413969DEST_PATH_IMAGE014
Figure 780229DEST_PATH_IMAGE015
Figure 993035DEST_PATH_IMAGE016
wherein ,
Figure 498491DEST_PATH_IMAGE017
representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;
Figure 551766DEST_PATH_IMAGE018
Representing a set of safe feasible domains->
Figure 874163DEST_PATH_IMAGE017
Points within;
Figure 156240DEST_PATH_IMAGE019
Representing the surrounding security feasible region set +.>
Figure 513272DEST_PATH_IMAGE017
Is a convex polygon of (a); b represents the surrounding security feasible region set +.>
Figure 271537DEST_PATH_IMAGE017
The offset of each edge in the convex polygon of (a);
Figure 81230DEST_PATH_IMAGE020
Represent the first
Figure 166997DEST_PATH_IMAGE021
Coordinates of the individual obstacles in the driving environment;
Figure 644115DEST_PATH_IMAGE021
Representing stack->
Figure 180139DEST_PATH_IMAGE022
I in the m-th element;
Figure 73533DEST_PATH_IMAGE023
Indicate->
Figure 618784DEST_PATH_IMAGE021
The +.>
Figure 950408DEST_PATH_IMAGE024
The relative coordinates of the vertices;
Figure 267120DEST_PATH_IMAGE024
Representing stack->
Figure 644880DEST_PATH_IMAGE022
J in the m-th element;
Figure 555391DEST_PATH_IMAGE025
Polygonal representation of unmanned vehicle
Figure 475943DEST_PATH_IMAGE026
The relative coordinates of the vertices;
Figure 619348DEST_PATH_IMAGE026
Representing stack->
Figure 500717DEST_PATH_IMAGE022
K in the m-th element;
Figure 653349DEST_PATH_IMAGE027
representing stack->
Figure 696916DEST_PATH_IMAGE022
Is a length of (c).
The invention also provides a safe feasible region generation system based on the effective barrier, which comprises the following steps:
the unmanned aerial vehicle attitude information acquisition module is used for acquiring attitude information of the unmanned aerial vehicle and describing the unmanned aerial vehicle by utilizing polygons;
the obstacle space pose information acquisition module is used for acquiring space pose information of an obstacle and describing the obstacle by utilizing a convex polygon;
the stack establishing module is used for establishing a stack, and the stack is currently empty;
the storage module is used for storing the related information of the 1 st obstacle into the stack based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle; the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle, the 1 st obstacle being nearest to the unmanned aerial vehicle, and the polygon vertexes of the unmanned aerial vehicle, the unmanned aerial vehicle being nearest to the 1 st obstacle;
the judging module is used for judging the effectiveness of the rest barriers based on the attitude information of the unmanned vehicle and the space attitude information of the barriers, and storing the related information of the effective barriers into the stack;
and the safe feasible domain generation module is used for generating a safe feasible domain based on all effective barriers in the stack.
Optionally, the expression of the attitude information of the unmanned vehicle is as follows:
Figure 604698DEST_PATH_IMAGE001
p=(x ego ,y ego )'
Figure 832417DEST_PATH_IMAGE028
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;
Figure 132948DEST_PATH_IMAGE003
an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;
Figure 293671DEST_PATH_IMAGE004
Representing the kth vertex relative coordinates of the unmanned vehicle polygon;
Figure 250651DEST_PATH_IMAGE005
Representing a collection of unmanned polygonal vertices.
Optionally the expression of the spatial pose information of the obstacle is as follows:
Figure 90299DEST_PATH_IMAGE006
Figure 928942DEST_PATH_IMAGE007
Figure 678593DEST_PATH_IMAGE008
wherein i represents the number of the obstacle; q i Representing coordinates of the ith obstacle in the driving environment; w (W) i Appearance information indicating an i-th obstacle;
Figure 600281DEST_PATH_IMAGE029
representing the number of obstacles;
Figure 602260DEST_PATH_IMAGE030
An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;
Figure 962703DEST_PATH_IMAGE031
Representing the j-th vertex relative coordinates of the i-th obstacle polygon;
Figure 301280DEST_PATH_IMAGE032
Representing an ith set of obstacle polygon vertices; j (j) i Representing the number of vertices of the ith barrier polygon.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
unlike conventional safe feasible region generation methods, the method does not use all barriers in the map to generate the safe feasible region, but considers the interaction relation between the barriers and the target unmanned vehicles, screens out invalid barriers to reduce the safe feasible region dimension, so that the safe feasible region dimension is smaller than or equal to the number of the barriers, the effect is particularly obvious under the condition that the barriers are dense, the safe feasible region dimension is greatly reduced, and the reduction of the safe feasible region dimension can improve the efficiency of a plurality of methods such as a safe corridor and the like when the safe feasible region is used.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a safe feasible region generation method based on effective barriers;
FIG. 2 is a schematic diagram of a stacked;
FIG. 3 is a schematic diagram of a return stack top element;
FIG. 4 is a schematic view of the minimum distance between the unmanned vehicle and the 1 st obstacle;
fig. 5 is a schematic view of an effective barrier.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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 invention aims to provide a safe feasible region generation method and system based on effective barriers, which are used for reducing the dimension of the safe feasible region and improving the efficiency.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, the safe feasible region generation method based on the effective barrier provided by the invention comprises the following steps:
step 101: and acquiring attitude information of the unmanned aerial vehicle, and describing the unmanned aerial vehicle by utilizing the polygon.
The method mainly aims at solving the safe feasible region under certain appointed unmanned aerial vehicle attitude information
Figure 393870DEST_PATH_IMAGE033
The unmanned vehicle posture information is thus given in advance.
The method comprises the steps of collecting target attitude information of the unmanned vehicle, wherein the target attitude information is defined as follows:
Figure 427685DEST_PATH_IMAGE034
(1)
in the formula (1), k represents the number of polygon vertexes of the unmanned vehicle; p is the coordinates of the unmanned vehicle in the driving environment, which are in an absolute coordinate system established with a fixed origin, and the subsequent steps solve the safe and feasible region based on p
Figure 114188DEST_PATH_IMAGE033
；
Figure 651480DEST_PATH_IMAGE035
An abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;
Figure 570763DEST_PATH_IMAGE036
Representing the kth vertex relative coordinates of the unmanned vehicle polygon;
Figure 623033DEST_PATH_IMAGE037
Representing an ith set of obstacle polygon vertices; the method uses quadrilateral as an example to describe unmanned vehicle, < ->
Figure 262962DEST_PATH_IMAGE038
Representing the absolute coordinates of the kth vertex of the unmanned polygon. Safe feasible area->
Figure 844640DEST_PATH_IMAGE033
Is an area containing the unmanned vehicle and not containing the obstacle, i.e. when p in the unmanned vehicle posture information is +.>
Figure 279033DEST_PATH_IMAGE033
Inside, the unmanned vehicle will not collide with the obstacle.
Step 102: and acquiring the space pose information of the obstacle, and describing the obstacle by utilizing the convex polygon.
The method comprises the steps of obtaining space pose information of a dynamic and static obstacle (simply referred to as an obstacle) in the environment from an environment sensing module, describing the shape of the obstacle by utilizing a convex polygon, and representing the space pose information of the obstacle as follows:
Figure 802287DEST_PATH_IMAGE039
(2)
wherein i is an obstacle number; j represents the polygon vertex number of the obstacle; q i Representing coordinates of the ith obstacle in the driving environment; w (W) i Appearance information indicating an i-th obstacle;
Figure 714748DEST_PATH_IMAGE040
an abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;
Figure 757791DEST_PATH_IMAGE041
The j-th polygon vertex coordinates of the i-th obstacle are represented, and the coordinates are values in a relative coordinate system of the vehicle body;
Figure 834855DEST_PATH_IMAGE042
Representing an ith set of obstacle polygon vertices;
Figure 110985DEST_PATH_IMAGE043
For the number of obstacles, j i The number of vertices of the ith barrier polygon. Due to the +.>
Figure 905766DEST_PATH_IMAGE033
Since the safety feasible region including p and not including the obstacle is established for the environmental transient information at a certain time, the space pose information of the obstacle can be represented by the formula (2). When the i-th obstacle is a dynamic obstacle, (q) i ,W i ) The geometric center coordinates and the shape information of the dynamic obstacle at a certain determined time are represented.
Step 103: a stack is established, which is currently empty.
The stack is a data structure in the computer field, and the method uses the stack to describe the storage and use of effective obstacle information.
Build a stack L valid Current stack L valid Is empty, stack L valid The elements to be stored in the system are (i, j, k) which respectively represent the barrier serial numbers, the barrier polygon vertex serial numbers and the unmanned vehicle polygon vertex serial numbers. Give a pair L valid Is a single-phase clock, four operations of:
(1)L valid push: stacking, adding new element (i, j, k) to the stack. As shown in FIG. 2, elements (1, 2, 1) and (2,4,3) are pushed onto the stack L valid Obtaining a new L valid The element sequence in the stack is that the first element is at the stack bottom and then the second element is at the stack top.
(2)L valid getTop: returns the top of stack element (i, j, k), but does not pop, where L valid getTop (1) represents i, L in the return stack top element valid getTop (2) represents j, L in the return top element valid getTop (3) represents k in the return stack top element. As shown in FIG. 3, L valid Get Top returns to top of stack element (1, 2, 3), L valid Get Top (1) returns the value 2, L valid Get Top (2) returns the value 4, L valid getTop (3) returns the value 3.
(3)L valid (m): return to stack bottom and mth element (i, j, k), L valid (m), (1) represents i, L in the m-th element valid (m), (2) represents j, L in the m-th element valid (m), (3) represents k in the m-th element. Stack L with FIG. 3 valid For example, when m=1, l valid (m) represents a return element (1, 2, 1), when m=2, l valid (m) represents a return element (2,4,3).
(4)L valid Length of the return stack. Taking fig. 2 as an example, before pushing the stack, the empty stack length is 0, and after pushing two elements, the stack length is 2.
This step results in a stack L valid The effective barrier will be pushed onto the stack in a subsequent step.
Step 104: based on the pose information of the unmanned vehicle and the spatial pose information of the obstacle, storing the related information of the 1 st obstacle to the stack L valid In (a) and (b); the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle nearest to the 1 st obstacle and the most distant from the 1 st obstacleA near unmanned polygonal vertex.
1 st obstacle-related information (i, j) i,opt ，k i,opt ) Push stack L valid Wherein i represents an obstacle number, j i,opt 、k i,opt The nearest vertex number indicating the vehicle and obstacle i. Taking fig. 4 as an example, the 4 th vertex of the unmanned vehicle is closest to the 2 nd vertex of obstacle i, so j i,opt =2，k i,opt =4. The discrimination formulas for the two nearest vertices of the drone and the obstacle are shown as formulas (3 a), (3 b) and (3 c).
i=1 (3a)
Figure 724686DEST_PATH_IMAGE044
(3b)
Figure 704143DEST_PATH_IMAGE045
(3c)
A c =(q i -p)'
In the formula (3 a), A c A two-dimensional vector representing an obstacle i as an end point with the center of the unmanned vehicle as a start point, i=1 since this step is discussed with respect to the 1 st obstacle; in the formula (3 b)
Figure 142602DEST_PATH_IMAGE046
The 1 st barrier +.>
Figure 990341DEST_PATH_IMAGE046
The vertex is nearest to the unmanned vehicle; substituting the result of formula (3 b) into formula (3 c), wherein +_in formula (3 c)>
Figure 132610DEST_PATH_IMAGE047
Indicating the unmanned vehicle is far from the 1 st obstacle +.>
Figure 955072DEST_PATH_IMAGE046
The vertex is nearest.
Figure 815581DEST_PATH_IMAGE046
,
Figure 888184DEST_PATH_IMAGE047
The specific value depends on the relative position of the drone with respect to the 1 st obstacle, and is not given here. Finally will (i, < >)>
Figure 275172DEST_PATH_IMAGE046
,
Figure 658749DEST_PATH_IMAGE047
) Push stack L valid Is a kind of medium.
Step 105: based on the pose information of the unmanned vehicle and the space pose information of the obstacle, judging the validity of the rest obstacle, and storing the related information of the valid obstacle into a stack L valid Is a kind of medium.
Update-based stack L valid Screening for obstacle i. The process is illustrated by the description of steps 1051-1053:
step 1051: processing the ith (i.gtoreq.2) obstacle by using step 104 to obtain (i, j) i,opt ，k i,opt ) The formula is as follows:
Figure 537712DEST_PATH_IMAGE048
(4a)/>
Figure 136708DEST_PATH_IMAGE049
(4b)
step 1052: and effectively judging the ith barrier by utilizing stack top element information, wherein a judgment formula is as follows:
Figure DEST_PATH_IMAGE050
(5)
in formula (5): l (L) valid getTop is seen in operation (2) defined in step 103.
If inequality (5) holds, the ith obstacle is the effective obstacle, and (i, j) i,opt ，k i,opt ) Push stack L valid 。
If inequality (5) is not satisfied, the ith obstacle is an invalid obstacle, for stack L valid No operation is performed.
In the validity judgment effect of inequality (5), when obstacle m is judged as an invalid obstacle, obstacle m is "behind" the 1 st obstacle with respect to the unmanned vehicle; when obstacle n is determined to be a valid obstacle, obstacle n is "in front of" the 1 st obstacle with respect to the unmanned vehicle. In short, in the process of driving, the unmanned vehicle only needs to pay attention to the surrounding obstacles closest to the unmanned vehicle, but the obstacles behind the obstacles are not considered, and in fig. 5, the obstacle m is the obstacle behind the obstacle 1 and is an ineffective obstacle; the opposite is true of obstacle n.
Step 1053: repeating steps 1051-1052 until the validity judgment is completed for all the remaining obstacles, and placing the related information of the valid obstacles in a stack in sequence
Figure 643782DEST_PATH_IMAGE051
Is a kind of medium.
Step 106: based on stacks
Figure 463839DEST_PATH_IMAGE051
Is used to generate a safe feasible region.
The number of effective barriers can be used
Figure 301869DEST_PATH_IMAGE052
The length of the return stack is obtained and satisfies:
Figure 232785DEST_PATH_IMAGE053
(6)
will L valid Sequentially taking out, constructing a safe and feasible domain set based on all effective barriers, and describing the following formula:
Figure 407415DEST_PATH_IMAGE054
(7)
wherein ：
Figure 726269DEST_PATH_IMAGE014
Figure 51596DEST_PATH_IMAGE055
(8)
Figure 599252DEST_PATH_IMAGE056
in the formula (8), the amino acid sequence of the compound,
Figure 612076DEST_PATH_IMAGE057
representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;
Figure 586985DEST_PATH_IMAGE058
Representing a set of safe feasible domains->
Figure 193416DEST_PATH_IMAGE057
Points within;
Figure 660608DEST_PATH_IMAGE059
Representing the surrounding security feasible region set +.>
Figure 731201DEST_PATH_IMAGE057
Is a convex polygon of (a); b represents the surrounding security feasible region set +.>
Figure 1645DEST_PATH_IMAGE057
The offset of each edge in the convex polygon of (a);
Figure 174001DEST_PATH_IMAGE060
Represent the first
Figure 453672DEST_PATH_IMAGE061
Coordinates of the individual obstacles in the driving environment;
Figure 522647DEST_PATH_IMAGE061
Representing stack->
Figure 88626DEST_PATH_IMAGE062
I in the m-th element;
Figure 607332DEST_PATH_IMAGE063
Indicate->
Figure 221853DEST_PATH_IMAGE061
The +.>
Figure 614176DEST_PATH_IMAGE064
The relative coordinates of the vertices;
Figure 757581DEST_PATH_IMAGE064
Representing stack->
Figure 153796DEST_PATH_IMAGE062
J in the m-th element;
Figure 775271DEST_PATH_IMAGE065
Polygonal representation of unmanned vehicle
Figure 818838DEST_PATH_IMAGE066
The relative coordinates of the vertices;
Figure 477352DEST_PATH_IMAGE066
Representing stack->
Figure 564126DEST_PATH_IMAGE062
K in the m-th element;
Figure 254870DEST_PATH_IMAGE067
representing stack->
Figure 228642DEST_PATH_IMAGE062
Is a length of (c).
Thus, the safe feasible domain is obtained
Figure 307325DEST_PATH_IMAGE033
As shown in formula (7). As is clear from the equation (6), the safety-feasible-area dimension obtained by the equation (7) is equal to or less than the number of obstacles, and the effect is more remarkable when the obstacles are dense. The reduced dimension of the safe feasible region can improve the efficiency of a plurality of methods such as a safe corridor and the like when the safe feasible region is used.
In the method, the appearance of the unmanned aerial vehicle and the appearance of the obstacle are considered in the process of generating the safe feasible region, and the dimension of the safe feasible region is reduced by screening out invalid obstacles. From steps 104-105, it can be seen that, starting from the 1 st obstacle, the method compares the spatial positions of the following obstacle, the preceding obstacle and the unmanned vehicle, where the comparison formula is formula (5), that is, if the preceding obstacle is located between the following obstacle and the unmanned vehicle, the formula (5) is not satisfied, and the following obstacle is an ineffective obstacle, and otherwise is an effective obstacle. In short, the unmanned vehicle only needs to pay attention to the obstacle nearest to the unmanned vehicle in the surrounding during the running process, and the obstacle behind the obstacle is not needed to be considered.
Example two
In order to perform a corresponding method of the above embodiment to achieve the corresponding functions and technical effects, a safe and feasible region generation system based on effective obstacles is provided below, which includes:
the unmanned aerial vehicle attitude information acquisition module is used for acquiring attitude information of the unmanned aerial vehicle and describing the unmanned aerial vehicle by utilizing polygons;
the obstacle space pose information acquisition module is used for acquiring space pose information of the obstacle and describing the obstacle by utilizing the convex polygon;
the stack building module is used for building a stack, and the stack is currently empty;
the storage module is used for storing the related information of the 1 st obstacle into a stack based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle; the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle, the 1 st obstacle being nearest to the unmanned aerial vehicle, and the polygon vertexes of the unmanned aerial vehicle, the unmanned aerial vehicle being nearest to the 1 st obstacle;
the judging module is used for judging the effectiveness of the rest obstacles based on the pose information of the unmanned vehicle and the space pose information of the obstacles, and storing the related information of the effective obstacles into a stack;
and the safe feasible domain generation module is used for generating the safe feasible domain based on all effective barriers in the stack.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.

Claims (6)

1. A safe feasible region generation method based on effective barriers, which is characterized by comprising the following steps:
acquiring attitude information of an unmanned vehicle, and describing the unmanned vehicle by utilizing a polygon;
collecting space pose information of an obstacle, and describing the obstacle by utilizing a convex polygon;
building a stack, wherein the stack is currently empty;
based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle, storing the related information of the 1 st obstacle into the stack; the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle, the 1 st obstacle being nearest to the unmanned aerial vehicle, and the polygon vertexes of the unmanned aerial vehicle, the unmanned aerial vehicle being nearest to the 1 st obstacle;
based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle, judging the effectiveness of the rest obstacle, and storing the related information of the effective obstacle into the stack;
generating a safe feasible region based on all effective obstacles in the stack;
the method for judging the validity of the remaining obstacle based on the attitude information of the unmanned vehicle and the space attitude information of the obstacle specifically comprises the following steps:
determining obstacle related information for each remaining obstacle based on the pose information of the unmanned vehicle and the space pose information of the obstacle; the obstacle related information comprises an obstacle polygon vertex with the nearest obstacle distance from the unmanned vehicle, an unmanned vehicle polygon vertex with the nearest unmanned vehicle distance from the obstacle and a corresponding obstacle number;
judging the effectiveness of the residual obstacle based on the obstacle related information and the stack top element information of the stack;
the generation formula of the safe feasible domain is as follows:
Figure QLYQS_1
Figure QLYQS_2
Figure QLYQS_3
Figure QLYQS_4
wherein ,
Figure QLYQS_9
representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;
Figure QLYQS_5
Representing a set of safe feasible domains->
Figure QLYQS_7
Points within;
Figure QLYQS_17
Representing the surrounding security feasible region set +.>
Figure QLYQS_20
Is a convex polygon of (a); b represents the surrounding security feasible region set +.>
Figure QLYQS_11
The offset of each edge in the convex polygon of (a);
Figure QLYQS_14
Indicate->
Figure QLYQS_22
Coordinates of the individual obstacles in the driving environment; p represents the coordinates of the unmanned vehicle in the running environment;
Figure QLYQS_24
Representation stack
Figure QLYQS_18
I in the m-th element; i represents the number of the obstacle;
Figure QLYQS_25
Indicate->
Figure QLYQS_16
The +.>
Figure QLYQS_23
The relative coordinates of the vertices;
Figure QLYQS_19
Representing stack->
Figure QLYQS_21
J in the m-th element;
Figure QLYQS_10
The +.o representing the polygon of an unmanned vehicle>
Figure QLYQS_12
The relative coordinates of the vertices;
Figure QLYQS_13
Representing stack->
Figure QLYQS_15
K in the m-th element;
Figure QLYQS_6
Representing stack->
Figure QLYQS_8
Is a length of (c).
2. The effective obstacle-based safe feasible region generation method according to claim 1, wherein the expression of the pose information of the unmanned vehicle is as follows:
Figure QLYQS_26
p=(x ego ,y ego )'
Figure QLYQS_27
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;
Figure QLYQS_28
an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;
Figure QLYQS_29
Representing the kth vertex relative coordinates of the unmanned vehicle polygon;
Figure QLYQS_30
Representing a collection of unmanned polygonal vertices.
3. The safe feasible region generation method based on effective obstacle according to claim 2, wherein the expression of the spatial pose information of the obstacle is as follows:
Figure QLYQS_31
Figure QLYQS_32
Figure QLYQS_33
wherein i represents the number of the obstacle; q i Representing coordinates of the ith obstacle in the driving environment; w (W) i Appearance information indicating an i-th obstacle;
Figure QLYQS_34
representing the number of obstacles;
Figure QLYQS_35
An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;
Figure QLYQS_36
Representing the j-th vertex relative coordinates of the i-th obstacle polygon;
Figure QLYQS_37
Representing an ith set of obstacle polygon vertices; j (j) i Representing the number of vertices of the ith barrier polygon.
4. A safe-feasible-area generation system based on effective obstacles, comprising:
the unmanned aerial vehicle attitude information acquisition module is used for acquiring attitude information of the unmanned aerial vehicle and describing the unmanned aerial vehicle by utilizing polygons;
the obstacle space pose information acquisition module is used for acquiring space pose information of an obstacle and describing the obstacle by utilizing a convex polygon;
the stack establishing module is used for establishing a stack, and the stack is currently empty;
the storage module is used for storing the related information of the 1 st obstacle into the stack based on the attitude information of the unmanned vehicle and the spatial attitude information of the obstacle; the related information of the 1 st obstacle comprises the number of the 1 st obstacle, the polygon vertexes of the obstacle, the 1 st obstacle being nearest to the unmanned aerial vehicle, and the polygon vertexes of the unmanned aerial vehicle, the unmanned aerial vehicle being nearest to the 1 st obstacle;
the judging module is used for judging the effectiveness of the rest barriers based on the attitude information of the unmanned vehicle and the space attitude information of the barriers, and storing the related information of the effective barriers into the stack;
the safe feasible region generation module is used for generating a safe feasible region based on all effective barriers in the stack;
the method for judging the validity of the remaining obstacle based on the attitude information of the unmanned vehicle and the space attitude information of the obstacle specifically comprises the following steps:
determining obstacle related information for each remaining obstacle based on the pose information of the unmanned vehicle and the space pose information of the obstacle; the obstacle related information comprises an obstacle polygon vertex with the nearest obstacle distance from the unmanned vehicle, an unmanned vehicle polygon vertex with the nearest unmanned vehicle distance from the obstacle and a corresponding obstacle number;
judging the effectiveness of the residual obstacle based on the obstacle related information and the stack top element information of the stack;
the generation formula of the safe feasible domain is as follows:
Figure QLYQS_38
Figure QLYQS_39
Figure QLYQS_40
Figure QLYQS_41
wherein ,
Figure QLYQS_52
representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;
Figure QLYQS_48
Representing a set of safe feasible domains->
Figure QLYQS_50
Points within;
Figure QLYQS_55
Representing the surrounding security feasible region set +.>
Figure QLYQS_62
Is a convex polygon of (a); b represents the surrounding security feasible region set +.>
Figure QLYQS_59
The offset of each edge in the convex polygon of (a);
Figure QLYQS_61
Indicate->
Figure QLYQS_56
Coordinates of the individual obstacles in the driving environment; p represents the coordinates of the unmanned vehicle in the running environment;
Figure QLYQS_58
Representation stack
Figure QLYQS_43
I in the m-th element; i represents the number of the obstacle;
Figure QLYQS_60
Indicate->
Figure QLYQS_46
The +.>
Figure QLYQS_47
The relative coordinates of the vertices;
Figure QLYQS_53
Representing stack->
Figure QLYQS_57
J in the m-th element;
Figure QLYQS_44
The +.o representing the polygon of an unmanned vehicle>
Figure QLYQS_49
The relative coordinates of the vertices;
Figure QLYQS_51
Representing stack->
Figure QLYQS_54
K in the m-th element;
Figure QLYQS_42
Representing stack->
Figure QLYQS_45
Is a length of (c).
5. The effective obstacle-based safe feasible region generation system according to claim 4, wherein the expression of the pose information of the unmanned vehicle is as follows:
Figure QLYQS_63
p=(x ego ,y ego )'
Figure QLYQS_64
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;
Figure QLYQS_65
an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;
Figure QLYQS_66
Representing the kth vertex relative coordinates of the unmanned vehicle polygon;
Figure QLYQS_67
Representing a collection of unmanned polygonal vertices. />
6. The effective obstacle-based safe feasible region generation system of claim 4, wherein the spatial pose information of the obstacle is expressed as follows:
Figure QLYQS_68
Figure QLYQS_69
Figure QLYQS_70
wherein i represents the number of the obstacle; q i Representing coordinates of the ith obstacle in the driving environment; w (W) i Appearance information indicating an i-th obstacle;
Figure QLYQS_71
representing the number of obstacles;
Figure QLYQS_72
An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;
Figure QLYQS_73
Representing the j-th vertex relative coordinates of the i-th obstacle polygon;
Figure QLYQS_74
Representing an ith set of obstacle polygon vertices; j (j) i Indicating the ith obstacleThe number of vertices of the polygon. />
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