Robot cluster navigator selection method based on view field opening degree evaluation

Abstract

The invention belongs to the field of robot cluster autonomous navigation, and particularly relates to a robot cluster navigator selection method based on visual field opening degree evaluation, and the method comprises the steps: selecting candidate navigators through a convex hull, and obtaining the visual field opening degree of each candidate navigator through Gaussian distribution; meanwhile, calculating unit vectors between position center points and target points of all candidate navigators, obtaining the arrival cost of each candidate navigator according to the projection of each candidate navigator and the position center point vectors on the unit vectors, and carrying out weighted summation on the openness and the arrival cost to obtain a comprehensive evaluation function value of each candidate navigator; and the optimal navigator is selected. According to the cluster navigator switching method provided by the invention, the problems that a traditional method excessively depends on an initial navigator and cannot deal with a complex dynamic scene and the like are solved, and a robot with a wide view field and high target accessibility in a cluster can be selected as a new navigator in less time; and the requirement of fast transfer navigation of a robot cluster can be met.

Description

Technical Field

[0001] The present invention belongs to the field of robot cluster autonomous navigation, and in particular relates to a robot cluster leader selection method based on field of view width evaluation. Background Art

[0002] With the continuous development of robotics technology, the application scenarios of robots are becoming increasingly diversified, and the collaborative operation of robot swarms has become an important research direction in the field of robotics. However, in the process of robot swarm navigation, the problem of different degrees of limited vision of each robot is often encountered, including the obstruction of vision by other robots and surrounding obstacles. Therefore, how to select a reliable navigator in a complex dynamic vision-limited environment and realize the rapid and safe transfer of robot swarms has become a key issue.

[0003] Some studies have proposed a feedback control strategy under the condition of field of vision and visibility constraints, in which the leader is responsible for ensuring that the robot cluster avoids obstacles when navigating towards the target point, and the follower is responsible for ensuring visibility maintenance with the leader and avoiding collisions between vehicles. However, this strategy only considers the problem of limited follower field of vision in static structured environments. When faced with complex scenarios, such as dynamic obstacles or dead-end environments such as the end of corridors, when most of the leader's field of vision is blocked and the navigation task cannot be completed, the cluster will not be able to achieve safe transfer. In this regard, some studies have proposed a solution to replace the leader, but it only considers the change of the leader according to the deviation of the formation in an open environment, which makes this solution very limited in complex environments.

[0004] Therefore, there is an urgent need for a robot cluster leader selection method that can cope with complex dynamic scenes, which can not only ensure that the leader has a broad field of vision but also lead the entire robot cluster to the destination safely and quickly at a lower arrival cost. Summary of the invention

[0005] In order to overcome the defects of the prior art, the present invention proposes a robot cluster leader selection method based on field of view openness evaluation. This method uses the convex hull to surround all current robots, selects candidate leaders according to the convex hull points, and uses Gaussian distribution to obtain the perceived field of view of each candidate leader, and calculates the openness of the perceived field of view of each candidate leader; at the same time, the unit vector between the position center point and the target point of all candidate leaders is calculated, and the arrival cost of the destination relative to each candidate leader is obtained according to the projection of the vector of each candidate leader and the position center point on the unit vector. The comprehensive evaluation function value of each candidate leader is obtained by weighted summation of the openness and arrival cost, and then the best leader is selected.

[0006] The technical solution of the present invention is as follows: A method for selecting a leader of a robot cluster based on field of view evaluation, wherein the robot cluster includes more than two robots, comprises the following steps: Step 1, organize the robot cluster into a point set according to the position coordinates of each robot, and sort the point set; process each point in the point set one by one in the sorted order, construct the upper hull and the lower hull of the convex hull respectively, and remove the duplicate points in the upper hull and the lower hull; the obtained convex hull is a convex polygon surrounding the robot cluster, and the robots at the vertex positions of the convex polygon are used as candidate leader robots.

[0007] Step 2, segmenting the sensor data of the candidate navigator robots, eliminating the interference of similar robots, and obtaining the field of view angle range of each candidate navigator robot; calculating the field of view radius threshold of each candidate navigator robot at different field of view angles through Gaussian distribution.

[0008] Step 3: Use polar coordinates to evenly divide the field of view angle range of each candidate navigator robot into multiple unit sectors. The field of view angles of all candidate navigators are the same. Match the sensor data of each candidate navigator robot to each sector. According to the occupancy of each sector, the field of view width of each candidate navigator robot is obtained while ensuring that the sector is not only visible but also passable. ; When the field of view of a candidate leader robot is less than the set field of view threshold, the robot will no longer be a candidate leader robot.

[0009] Step 4: After step 3, calculate the position center point C of all remaining candidate leader robots, the target point is point G, and find the The projection of the vector from each candidate navigator robot to the position center point C on the unit vector is recorded as the target point arrival cost of the candidate navigator robot .

[0010] Step 5: Calculate the comprehensive evaluation function value of each candidate leader robot ,in , They are the current candidate pilot robots The candidate navigator robot with the largest comprehensive evaluation function value is selected as the final navigator based on the weights of the field of view and the cost of reaching the target point.

[0011] Furthermore, in step 1, the point set is sorted specifically by sorting the point set according to the value of the horizontal coordinate or vertical coordinate. When multiple points have the same current sorting coordinate value, they are sorted by another coordinate. Thus, an ordered coordinate point set is obtained, which is convenient for determining a reasonable starting point and the order of subsequent traversal points, and for gradually constructing the convex hull from the "outermost" point.

[0012] Furthermore, in step 1, each point in the point set is processed one by one in the arranged order to construct the upper hull of the convex hull (the lower right part that bends to the upper left). Specifically, assuming that the current point is being processed points, marked as , the point sequence in the constructed upper package is ,in Represented by coordinates (x, y), Indicates the total number of packages; when , calculate the last two points in the package , And the current point to be added The vector cross product of (1) When the point set is sorted from small to large according to the coordinate value, if the calculated result is greater than 0, it means that the point Relative to vector In the counterclockwise direction, it means joining To maintain the convexity of the convex hull, put the point Adding the upper package will make the upper package become ; If the calculation result is less than or equal to 0, it means that the point Relative to vector In the clockwise direction or collinear with the two points, and because the interior angle of a convex polygon must be less than or equal to , add in clockwise direction Points will make the interior angle greater than , will destroy the convexity of the upper bag. Then put the last point in the upper bag Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the upper package; When the point set is sorted from large to small according to the coordinate value, contrary to the above situation, if the calculated result is less than 0, the point Adding the upper package will make the upper package become ; If the calculated result is greater than or equal to 0, then the last point in the upper package Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is less than 0, then put the point Add to bag.

[0013] By iteratively processing each sorted point, the construction of the upper part of the convex hull is finally completed.

[0014] Furthermore, in step 1, the points in the point set are processed in the opposite order to the order of constructing the upper convex hull to construct the lower convex hull (the upper left part that bends to the lower right). Specifically, assuming that the point is currently being processed points, marked as , the point sequence in the constructed lower package is ,in It is represented by the coordinates (x, y), and m represents the total number of package drops; when , calculate the last two points in the packet , And the current point to be added The vector cross product of (2) When the point set is sorted from large to small according to the coordinate value, if the calculated result is greater than 0, it means that the point Relative to vector In the counterclockwise direction, it means joining To maintain the convexity of the convex hull, put the point Add the next package, that is, make the next package become ; If the calculation result is less than or equal to 0, it means that the point Relative to vector In the clockwise direction or collinear with the two points, and because the interior angle of a convex polygon must be less than or equal to , add in clockwise direction Points will make the interior angle greater than , will destroy the convexity of the lower bag. Then put the last point in the lower bag Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the package; When the point set is sorted from small to large in coordinate value, contrary to the above situation, if the calculated result is less than 0, the point Add the next package, that is, make the next package become ; If the calculated result is greater than or equal to 0, the last point in the next package Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is less than 0, then put the point Add the next package.

[0015] By iteratively processing each sorted point, the construction of the lower part of the convex hull is finally completed.

[0016] Furthermore, the method for constructing the convex hull adopts one of the Graham scanning method, the Jarvis stepping method, and the fast hull method.

[0017] Furthermore, in step 2, the sensor of the candidate navigator robot is a laser sensor with a 360° field of view. However, part of the field of view is blocked by the same type, and this part of the blockage is also time-varying, so this part of the field of view is not helpful for the navigator to observe the surrounding environment. Therefore, it is necessary to exclude this part of the field of view and only evaluate the openness of the field of view of the part without the same type of blockage, which is called the perception field of view.

[0018] The convex hull constructed in step 1 will be used for the perception field extraction in this step. As mentioned in step 1, each vertex of the convex polygon is considered to be a candidate leader robot. At this time, we only need to determine the outer angle of each convex polygon. This operation can perfectly eliminate similar interference and focus on the evaluation of the external environment.

[0019] Furthermore, in step 2, the specific process of calculating the field of view radius threshold of each candidate pilot robot at different field of view angles is as follows: suppose that the vertices of the convex polygon obtained in step 1 are arranged in order to obtain a set of candidate pilot robot positions, First, calculate a candidate leader robot A Current field of view The difference from the middle angle reflects the degree to which the current angle deviates from the overall center angle. (3) in, , , and the candidate pilot robot A The previous adjacent candidate leader robot B and the next candidate pilot robot C ; Considering that the vision at different angles has different importance, the present invention adopts the difference in the vision radius threshold value caused by the angle difference according to the Gaussian distribution. The corresponding weight values ​​are: (4) in, is a natural constant, is the standard deviation parameter of the Gaussian distribution, which determines the "width" of the Gaussian distribution curve, that is, the sensitivity of the angle difference to the weight; The field of view radius threshold for the current field of view angle is: (5) Here and Respectively represent the lower and upper limit settings of the field of view radius threshold.

[0020] After the above processing, the closer the part is to the middle, the larger the corresponding threshold is, and vice versa, presenting a bell-shaped curve feature with high in the middle and low on both sides. This helps to focus more on the key vision and avoid misjudgment of the overall vision due to interference from the edge vision.

[0021] Furthermore, the sensor data of the candidate leader robot is segmented, and the ground point cloud and noise are removed.

[0022] Furthermore, in step 3, the visual field width of each candidate navigator robot is obtained. The specific process is: Match the sensor data of each candidate navigator robot after step 2 with its corresponding multiple unit sectors, and determine the number of obstacle information in each unit sector. When it exceeds the set value, the unit sector is an occupied unit sector, otherwise the unit sector is a free unit sector; when the number of consecutive free unit sectors on the left and right sides of the free unit sector exceeds the target value, the free unit sector is a passable unit sector; count the total number of unit sectors within the field of view of each candidate navigator robot and the number of accessible unit sectors , then the field of vision of each candidate leader robot is .

[0023] Furthermore, the specific process of step 4 is as follows: After step 3, calculate the position center points of the remaining n candidate leader robots ,Right now (6) in Indicates The two-dimensional coordinates of the candidate leader robots; According to the target point With the center point Find the unit vector , the specific calculation is as follows (7) The vector from each candidate leader robot to the position center point C is the unit vector The projection on the target point is recorded as the target point arrival cost of the candidate leader robot. , (8) in , Indicates The coordinates of the candidate leader robots.

[0024] The beneficial effect of the present invention is that the cluster leader selection method proposed in the present invention overcomes the problems of traditional methods that are too dependent on the initial navigator and cannot cope with complex dynamic scenes. It can select a robot with a wide field of view and a lower target point arrival cost in the cluster as a navigator, which can meet the needs of fast and safe transfer navigation of robot clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a specific flow chart of the present invention.

[0026] Figure 2 This is the effect diagram of generating a convex polygon based on the current position of the robot.

[0027] Figure 3 This is a rendering of the perception field of view of the candidate leader robot generated based on convex polygons.

[0028] Figure 4 It is a diagram for evaluating the openness within the perceived field of view.

[0029] Figure 5 It is an effect diagram that evaluates the target point relative to the arrival cost of each candidate leader robot.

[0030] Figure 6 This is a schematic diagram of the effect of navigator selection in scene one.

[0031] Figure 7 This is a schematic diagram of the navigator selection effect in scene two. DETAILED DESCRIPTION

[0032] The specific implementation of the present invention is described in detail below in conjunction with the technical scheme and the accompanying drawings.

[0033] A method for selecting a leader of a robot cluster based on field of view evaluation, wherein the robot cluster includes more than two robots, comprises the following steps: Step 1: In the preparation stage, each robot obtains its absolute position based on the world coordinate system through real-time positioning and map construction, and publishes it to the robot operating system local area network through the wireless network. Each robot receives the same position and its own current position, and organizes the robot cluster into a point set according to the position coordinates of each robot. The point set is sorted according to the value of the horizontal or vertical coordinate. When multiple points have the same current sorting coordinate value, they are sorted by another coordinate. Each point in the point set is processed one by one in the sorted order, and the upper and lower hulls of the convex hull are constructed respectively, and the duplicate points in the upper and lower hulls are removed; The upper hull of the convex hull is constructed as follows: Assuming that the current points, marked as , the point sequence in the constructed upper package is ,in Represented by coordinates (x, y), Indicates the total number of packages; when , calculate the last two points in the package , And the current point to be added The vector cross product of When the point set is sorted from small to large according to the coordinate value, if the calculated result is greater than 0, it means that the point Relative to vector In the counterclockwise direction, it means joining To maintain the convexity of the convex hull, put the point Adding the upper package will make the upper package become ; If the calculation result is less than or equal to 0, it means that the point Relative to vector In the clockwise direction or collinear with the two points, and because the interior angle of a convex polygon must be less than or equal to , add in clockwise direction Points will make the interior angle greater than , will destroy the convexity of the upper bag. Then put the last point in the upper bag Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the upper package; When the point set is sorted from large to small according to the coordinate value, contrary to the above situation, if the calculated result is less than 0, the point Adding the upper package will make the upper package become ; If the calculated result is greater than or equal to 0, then the last point in the upper package Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is less than 0, then put the point Add to bag.

[0034] By iteratively processing each sorted point, the construction of the upper part of the convex hull is finally completed.

[0035] Among them, the points in the point set are processed in the opposite order to the order of constructing the upper convex hull to construct the lower convex hull. Specifically, suppose that the current point is being processed. points, marked as , the point sequence in the constructed lower package is ,in It is represented by the coordinates (x, y), and m represents the total number of package drops; when , calculate the last two points in the packet , And the current point to be added The vector cross product of When the point set is sorted from large to small according to the coordinate value, if the calculated result is greater than 0, it means that the point Relative to vector In the counterclockwise direction, it means joining To maintain the convexity of the convex hull, put the point Add the next package, that is, make the next package become ; If the calculation result is less than or equal to 0, it means that the point Relative to vector In the clockwise direction or collinear with the two points, and because the interior angle of a convex polygon must be less than or equal to , add in clockwise direction Points will make the interior angle greater than , will destroy the convexity of the lower bag. Then put the last point in the lower bag Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the package; When the point set is sorted from small to large in coordinate value, contrary to the above situation, if the calculated result is less than 0, the point Add the next package, that is, make the next package become ; If the calculated result is greater than or equal to 0, the last point in the next package Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is less than 0, then put the point Add the next package.

[0036] By iteratively processing each sorted point, the construction of the lower part of the convex hull is finally completed.

[0037] The method for constructing the convex hull may be one of the Graham scanning method, the Jarvis stepping method, and the fast hull method.

[0038] The obtained convex hull is a convex polygon surrounding the robot cluster, and the robots at the vertex positions of the convex polygon are used as candidate leader robots.

[0039] Step 2: The sensor of the candidate navigator robot is a laser sensor with a 360° field of view. The sensor data of the candidate navigator robot is segmented and the ground point cloud and noise are removed. Assume that the vertices of the convex polygon obtained in step 1 are arranged in order to obtain the candidate navigator robot position set. First, calculate a candidate leader robot A Current field of view The difference from the middle angle reflects the degree to which the current angle deviates from the overall center angle. in, , , and the candidate pilot robot A The previous adjacent candidate leader robot B and the next candidate pilot robot C ; Considering that the fields of view at different angles have different importance, this embodiment adopts the field of view radius threshold difference caused by the angle difference given by Gaussian distribution. The corresponding weight values ​​are: in, is a natural constant, is the standard deviation parameter of the Gaussian distribution, which determines the "width" of the Gaussian distribution curve, that is, the sensitivity of the angle difference to the weight; The field of view radius threshold for the current field of view angle is: Here and Respectively represent the lower and upper limit settings of the field of view radius threshold.

[0040] Step 3, using polar coordinates to evenly divide the field of view angle range of each candidate navigator robot into multiple unit sectors, and the field of view angle of the unit sectors of all candidate navigator robots is the same; match the sensor data of each candidate navigator robot processed in step 2 with its corresponding multiple unit sectors, and determine the number of obstacle information in each unit sector. When it exceeds the set value, the unit sector is an occupied unit sector, otherwise the unit sector is a free unit sector; when the number of continuous free unit sectors on the left and right sides of the free unit sector exceeds the target value, the free unit sector is a passable unit sector; this adds continuous unit sector detection when calculating the openness, and only when the surrounding free sectors appear continuously, the sector is considered to be open, thereby avoiding the problem of "false openness". Count the total number of unit sectors within the field of view angle range of each candidate navigator robot and the number of accessible unit sectors , then the field of vision of each candidate leader robot is ; When the field of view of a candidate leader robot is less than the set field of view threshold, the robot will no longer be a candidate leader robot.

[0041] Step 4: After step 3, calculate the position center points of the remaining n candidate leader robots. ,Right now in Indicates The two-dimensional coordinates of the candidate leader robots; According to the target point With the center point Find the unit vector , the specific calculation is as follows The vector from each candidate leader robot to the position center point C is the unit vector The projection on the target point is recorded as the target point arrival cost of the candidate leader robot. , in , Indicates The coordinates of the candidate leader robots.

[0042] Step 5: Calculate the comprehensive evaluation function value of each candidate leader robot ,in , They are the current candidate pilot robots The weight of the visual field width and the target point arrival cost is used to select the candidate navigator robot with the largest comprehensive evaluation function value as the final navigator. The effects are as follows: Figure 6 and Figure 7 As shown in the figure, after comprehensive evaluation based on the field of view width evaluation and the target point arrival cost, Figure 6 The navigator in the game is robot No. 2. Figure 7 The navigator in the figure is robot No. 1 (the diamond in the figure is the navigator, the circle is the follower, and the five-pointed star is the target point).

[0043] At this point, a navigator selection task is completed. The test is performed in a cycle at a frequency of 1HZ to ensure the optimality and timeliness of the navigator selection.

[0044] The above is a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A robot cluster leader selection method based on field of vision evaluation, characterized in that: The robot cluster includes more than two robots, and includes the following steps: Step 1: The robot cluster is formed into a point set according to the position coordinates of each robot, and the point set is sorted; each point in the point set is processed one by one in the sorted order, and the upper and lower hulls of the convex hull are constructed respectively, and duplicate points in the upper and lower hulls are removed; the obtained convex hull is a convex polygon surrounding the robot cluster, and the robots at the vertex positions of the convex polygon are taken as candidate leader robots; Step 2, segmenting the sensor data of the candidate navigator robots, eliminating the interference of similar robots, and obtaining the field of view angle range of each candidate navigator robot; calculating the field of view radius threshold of each candidate navigator robot at different field of view angles through Gaussian distribution; Step 3: Use polar coordinates to evenly divide the field of view angle range of each candidate navigator robot into multiple unit sectors. The field of view angles of all candidate navigators are the same. Match the sensor data of each candidate navigator robot to each sector. According to the occupancy of each sector, the field of view width of each candidate navigator robot is obtained while ensuring that the sector is not only visible but also passable. ; When the visual field width of a candidate leader robot is less than the set visual field width threshold, the robot will no longer be a candidate leader robot; Step 4: After step 3, calculate the position center point C of all remaining candidate leader robots, the target point is point G, and find the The projection of the vector from each candidate navigator robot to the position center point C on the unit vector is recorded as the target point arrival cost of the candidate navigator robot ; Step 5: Calculate the comprehensive evaluation function value of each candidate leader robot ,in , They are the current candidate pilot robots The candidate navigator robot with the largest comprehensive evaluation function value is selected as the final navigator based on the weights of the field of view and the cost of reaching the target point.

2. The method for selecting a robot cluster leader based on field of vision evaluation according to claim 1, characterized in that: In step 1, the point set is sorted specifically by sorting the point set according to the magnitude of the horizontal coordinate or vertical coordinate value of the point set. When multiple points have the same current sorting coordinate value, another coordinate is used for sorting.

3. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: In step 1, each point in the point set is processed one by one in the arranged order to construct the upper hull of the convex hull. Specifically, suppose that the point points, marked as , the point sequence in the constructed upper package is ,in Represented by coordinates (x, y), Indicates the total number of packages; when , calculate the last two points in the package , And the current point to be added The vector cross product of （1） When the point set is sorted from small to large according to the coordinate value, if the calculated result is greater than 0, the point Adding the upper package will make the upper package become ; If the calculated result is less than or equal to 0, then the last point in the upper package Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the upper package; When the point set is sorted from large to small according to the coordinate value, if the calculated result is less than 0, the point Adding the upper package will make the upper package become ; If the calculated result is greater than or equal to 0, then the last point in the upper package Remove, and the package becomes Then check the last two points of the new upper package again. Repeat this operation until the calculated result is less than 0, then put the point Add to bag.

4. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: In step 1, the points in the point set are processed in the opposite order to the order of constructing the upper convex hull to construct the lower convex hull. Specifically, assuming that the current point is being processed points, marked as , the point sequence in the constructed lower package is ,in Represented by coordinates (x, y), m represents the total number of package drops; when , calculate the last two points in the packet , And the point to be added The vector cross product of （2） When the point set is sorted from large to small according to the coordinate value, if the calculated result is greater than 0, the point Add the next package, that is, make the next package become ; If the calculated result is less than or equal to 0, the last point in the next package Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is greater than 0, then put the point Add to the package; When the point set is sorted from small to large according to the coordinate value, if the calculated result is less than 0, the point Add the next package, that is, make the next package become ; If the calculated result is greater than or equal to 0, the last point in the next package Remove, the download package becomes Then check the last two points of the new packet again. Repeat this operation until the calculated result is less than 0, then put the point Add the next package.

5. The method for selecting a robot cluster leader based on field of vision evaluation according to claim 1, characterized in that: In step 2, the sensor of the candidate navigator robot is a laser sensor with a 360° field of view.

6. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: In step 2, the specific process of calculating the field of view radius threshold of each candidate pilot robot at different field of view angles is as follows: suppose that the vertices of the convex polygon obtained in step 1 are arranged in order to obtain a set of candidate pilot robot positions, First, calculate a candidate leader robot A Current field of view The difference from the middle angle, （3） in, , , and the candidate pilot robot A The previous adjacent candidate leader robot B and the next candidate pilot robot C ; Current field of view The corresponding weight values ​​are: （4） in, is a natural constant, is the standard deviation parameter of the Gaussian distribution; The field of view radius threshold for the current field of view angle is: （5） Here and Respectively represent the lower and upper limit settings of the field of view radius threshold.

7. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: Step 3: Obtain the field of view of each candidate leader robot The specific process is: Match the sensor data of each candidate navigator robot after step 2 with its corresponding multiple unit sectors, and determine the number of obstacle information in each unit sector. When it exceeds the set value, the unit sector is an occupied unit sector, otherwise the unit sector is a free unit sector; when the number of consecutive free unit sectors on the left and right sides of the free unit sector exceeds the target value, the free unit sector is a passable unit sector; count the total number of unit sectors within the field of view of each candidate navigator robot and the number of accessible unit sectors , then the field of vision of each candidate leader robot is .

8. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: The specific process of step 4 is as follows: After step 3, calculate the position center points of the remaining n candidate leader robots ,Right now （6） in Indicates The two-dimensional coordinates of the candidate leader robots; According to the target point With the center point Find the unit vector , the specific calculation is as follows （7） The vector from each candidate leader robot to the position center point C is the unit vector The projection on the target point is recorded as the target point arrival cost of the candidate leader robot. , （8） in , Indicates The coordinates of the candidate leader robots.

9. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: Step 2: segment the sensor data of the candidate leader robot and remove the ground point cloud and noise.

10. The method for selecting a robot swarm leader based on field of vision evaluation according to claim 1, characterized in that: Step 1: construct the convex hull by using one of the Graham scanning method, Jarvis stepping method and quick hull method.

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