CN115903853B - Safe feasible domain generation method and system based on effective barrier - Google Patents
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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
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:
p=(x ego ,y ego )'
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;Representing the kth vertex relative coordinates of the unmanned vehicle polygon;Representing a collection of unmanned polygonal vertices.
Optionally, the expression of the spatial pose information of the obstacle is as follows:
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;representing the number of obstacles;An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;Representing the j-th vertex relative coordinates of the i-th obstacle polygon;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:
wherein ,representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;Representing a set of safe feasible domains->Points within;Representing the surrounding security feasible region set +.>Is a convex polygon of (a); b represents the surrounding security feasible region set +.>The offset of each edge in the convex polygon of (a);Represent the firstCoordinates of the individual obstacles in the driving environment;Representing stack->I in the m-th element;Indicate->The +.>The relative coordinates of the vertices;Representing stack->J in the m-th element;Polygonal representation of unmanned vehicleThe relative coordinates of the vertices;Representing stack->K in the m-th element;representing stack->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:
p=(x ego ,y ego )'
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;Representing the kth vertex relative coordinates of the unmanned vehicle polygon;Representing a collection of unmanned polygonal vertices.
Optionally the expression of the spatial pose information of the obstacle is as follows:
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;representing the number of obstacles;An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;Representing the j-th vertex relative coordinates of the i-th obstacle polygon;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 informationThe 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:
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;An abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;Representing the kth vertex relative coordinates of the unmanned vehicle polygon;Representing an ith set of obstacle polygon vertices; the method uses quadrilateral as an example to describe unmanned vehicle, < ->Representing the absolute coordinates of the kth vertex of the unmanned polygon. Safe feasible area->Is an area containing the unmanned vehicle and not containing the obstacle, i.e. when p in the unmanned vehicle posture information is +.>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:
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;an abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;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;Representing an ith set of obstacle polygon vertices;For the number of obstacles, j i The number of vertices of the ith barrier polygon. Due to the +.>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)
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)The 1 st barrier +.>The vertex is nearest to the unmanned vehicle; substituting the result of formula (3 b) into formula (3 c), wherein +_in formula (3 c)>Indicating the unmanned vehicle is far from the 1 st obstacle +.>The vertex is nearest.,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, < >)>,) 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:
step 1052: and effectively judging the ith barrier by utilizing stack top element information, wherein a judgment formula is as follows:
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 sequenceIs a kind of medium.
The number of effective barriers can be usedThe length of the return stack is obtained and satisfies:
will L valid Sequentially taking out, constructing a safe and feasible domain set based on all effective barriers, and describing the following formula:
wherein :
in the formula (8), the amino acid sequence of the compound,representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;Representing a set of safe feasible domains->Points within;Representing the surrounding security feasible region set +.>Is a convex polygon of (a); b represents the surrounding security feasible region set +.>The offset of each edge in the convex polygon of (a);Represent the firstCoordinates of the individual obstacles in the driving environment;Representing stack->I in the m-th element;Indicate->The +.>The relative coordinates of the vertices;Representing stack->J in the m-th element;Polygonal representation of unmanned vehicleThe relative coordinates of the vertices;Representing stack->K in the m-th element;representing stack->Is a length of (c).
Thus, the safe feasible domain is obtainedAs 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:
wherein ,representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;Representing a set of safe feasible domains->Points within;Representing the surrounding security feasible region set +.>Is a convex polygon of (a); b represents the surrounding security feasible region set +.>The offset of each edge in the convex polygon of (a);Indicate->Coordinates of the individual obstacles in the driving environment; p represents the coordinates of the unmanned vehicle in the running environment;Representation stackI in the m-th element; i represents the number of the obstacle;Indicate->The +.>The relative coordinates of the vertices;Representing stack->J in the m-th element;The +.o representing the polygon of an unmanned vehicle>The relative coordinates of the vertices;Representing stack->K in the m-th element;Representing stack->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:
p=(x ego ,y ego )'
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;Representing the kth vertex relative coordinates of the unmanned vehicle polygon;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:
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;representing the number of obstacles;An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;Representing the j-th vertex relative coordinates of the i-th obstacle polygon;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:
wherein ,representing a set of safe feasible domains; a represents a vector of the unmanned vehicle pointing to an effective obstacle;Representing a set of safe feasible domains->Points within;Representing the surrounding security feasible region set +.>Is a convex polygon of (a); b represents the surrounding security feasible region set +.>The offset of each edge in the convex polygon of (a);Indicate->Coordinates of the individual obstacles in the driving environment; p represents the coordinates of the unmanned vehicle in the running environment;Representation stackI in the m-th element; i represents the number of the obstacle;Indicate->The +.>The relative coordinates of the vertices;Representing stack->J in the m-th element;The +.o representing the polygon of an unmanned vehicle>The relative coordinates of the vertices;Representing stack->K in the m-th element;Representing stack->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:
p=(x ego ,y ego )'
wherein k represents the number of polygon vertexes of the unmanned vehicle; p represents the coordinates of the unmanned vehicle in the running environment;an abscissa value and an ordinate value representing coordinates of the unmanned vehicle in a running environment;Representing the kth vertex relative coordinates of the unmanned vehicle polygon;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:
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;representing the number of obstacles;An abscissa value and an ordinate value representing coordinates of the ith obstacle in the driving environment;Representing the j-th vertex relative coordinates of the i-th obstacle polygon;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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