Improved grid shape search method based on barrier direction priority
By improving the grid-based search method based on obstacle direction priority, the problems of high repetition rate and dead zone trapping in the traditional grid-based search method in UAV area coverage are solved, and more efficient area coverage and path optimization are achieved.
Patent Information
- Application Number
- CN202511214825.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-28
- Publication Date
- 2025-12-02
AI Technical Summary
Traditional grid-based search methods suffer from high repetition rates, poor map applicability, inability to cover concave areas, and a tendency to get stuck in dead zones when performing UAV area coverage searches.
An improved grid-based search method based on obstacle orientation is adopted. By introducing a priority list to adjust the UAV's heading, the location of obstacles is given priority, the search path is optimized, and duplicate areas and dead zones are avoided.
It improves the efficiency of UAV area coverage search, reduces search time and path duplication, and enhances search coverage in complex environments.
Smart Images
Figure CN121048624A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to an improved grid-based search method based on obstacle direction priority, belonging to the field of route planning and optimization search technology. Background Technology
[0002] The development of unmanned aerial vehicle (UAV) technology in the military field is extensive and profound, playing a vital role in reconnaissance, strike, communication, and logistics transportation. With continuous improvements in flight control systems, autonomous navigation technology, and sensor technology, the flight performance and combat capabilities of UAVs have been significantly enhanced. This enables UAVs to perform more complex and precise tasks, such as reconnaissance and early warning, target tracking and positioning, precision strikes, and battlefield search and rescue. Simultaneously, the use of UAVs in actual combat is becoming increasingly frequent.
[0003] When using drones for area coverage searches, the traditional grid search method, also known as the scanline-based grid search method, can be employed. This involves movement from left to right and from bottom to top, as shown in the attached diagram. Figure 1 As shown, when a drone encounters an obstacle, it will choose to go around to one side of the obstacle, thus causing it to miss the area on the other side of the obstacle.
[0004] Reference (1) (He Chengyu. Research on Path Planning and Obstacle Avoidance Algorithm for Cleaning Robots [D]. Harbin University of Science and Technology, 2021: 25-27.) uses a grid method based on initial point direction priority, that is, when the drone's starting point is located in the lower left corner, the direction priority is downward and leftward. This method has two drawbacks: Firstly, for concave regions with downward openings, the search method based on the initial point direction priority cannot search the interior of the concave region, as shown in the attached diagram. Figure 2 As shown by the red line in the image. Secondly, for concave areas with a relatively long length, it is easy for the drone to get stuck in a dead zone.
[0005] When UAVs perform area coverage searches, traditional grid-based search algorithms have poor map applicability and relatively low search coverage. This invention proposes a grid-based search algorithm based on obstacle direction priority, which can change the direction priority during the search process, greatly improve search efficiency, and reduce the number of times the UAV gets stuck in dead zones.
[0006] Therefore, there is an urgent need to design an improved grid search method based on obstacle orientation priority that can solve the above-mentioned technical problems. Summary of the Invention
[0007] The purpose of this invention is to address the shortcomings of the existing technology and provide an improved grid-based search method based on obstacle direction priority. This method can flexibly adjust the priority changes when the search is obstructed by obstacles, and can achieve full-area coverage search as much as possible. It avoids the process of the UAV circling and covering unsearched areas after completing the search along the original route, thereby reducing search time and search path and improving search efficiency.
[0008] To achieve the above objectives, the present invention adopts the following technical solution: An improved grid-based search method based on obstacle direction priority, as described in this invention, is characterized by the following steps: Step 1: The drone flies along a grid-like search route; Step 2: During the journey, if there are no obstacles, the direction of the starting point takes priority; Step 3: During the flight, if an obstacle is encountered, the obstacle's position relative to the drone is used as the priority for changing the drone's heading. A priority list is introduced to indicate the drone's next movement direction. The list elements... , respectively This indicates that obstacle avoidance is being performed. Step 4: After avoiding obstacles, continue the grid search according to the new location point.
[0009] Preferably, the specific steps of step 2 are as follows: (1) The search mode priority is divided into two groups: horizontal and vertical. When the search area is rectangular, the longer side is used as the highest priority. The horizontal length of the search area is... Vertical width is , At that time, consider making the horizontal or As the highest position in the priority list; (2) Both ends in the vertical or horizontal direction should be spaced apart in the priority list, such as... correct, Not advisable; (3) The initial position determines the order of the initial priority list, as shown in the appendix. Figure 3 The priority list of starting points is as follows: That is, the direction opposite to the initial direction of the drone has the highest priority; (4) When the drone changes from vertical to horizontal movement, the priority list remains unchanged; (5) When the drone changes from a horizontal to a vertical orientation, if the vertical orientation is the same as the original vertical orientation, the orientation priority remains unchanged. If it is the opposite, then... Priority switching. For example... Transform into ; (6) When the drone moves along the S direction, if there is an obstacle on the right or the area has already been searched, the priority is... .
[0010] The improved grid-based search method based on obstacle direction priority of the present invention has the following advantages: Traditional grid-based search methods suffer from high repetition rates and poor map applicability when performing area coverage searches. This invention proposes an improved grid-based search method based on obstacle direction priority. This method reduces the number of times UAVs get stuck in dead zones and the path repetition rate when performing area coverage searches, shortens flight time, and optimizes grid-based search paths. It has certain reference value for improving the search efficiency of UAVs in complex environments. Attached Figure Description
[0011] Figure 1 This is a schematic diagram of a grid-based search method based on scan line patterns. Figure 2 This is a schematic diagram of a grid-based search method based on the orientation priority of the initial point; Figure 3 This is a schematic diagram of a grid-based search method based on obstacle orientation priority; Figure 4 The diagrams show traditional and improved search methods. In the diagram, (a) is a traditional grid search diagram, (b) is a traditional grid search diagram, (c) is a search diagram of the method proposed in reference (1), (d) is a search diagram of the method proposed in reference (1), (e) is a search diagram of the improved grid search proposed in this invention, and (f) is a search diagram of the improved grid search proposed in this invention. Figure 5 The diagrams show different search algorithms in complex regions. In the diagram, (a) is a global search diagram of the traditional grid method, (b) is a global search diagram of the algorithm in reference (1), and (c) is a global search diagram of the improved grid method. Detailed Implementation
[0012] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.
[0013] Reference Figure 3-5 An improved grid-shaped search method based on obstacle direction priority in this embodiment includes the following steps: Step 1: The drone flies along a grid-like search route; Step 2: During the journey, if there are no obstacles, the direction of the starting point takes priority; Step 3: During the flight, if an obstacle is encountered, the obstacle's position relative to the drone is used as the priority for changing the drone's heading. A priority list is introduced to indicate the drone's next movement direction. The list elements... , respectively This indicates that obstacle avoidance is being performed. Step 4: After avoiding obstacles, continue the grid search according to the new location point.
[0014] The specific steps of step 2 are as follows: (1) The search mode priority is divided into two groups: horizontal and vertical. When the search area is rectangular, the longer side is taken as the highest priority. The horizontal length of the search area is... Vertical width is , At that time, consider making the horizontal or As the highest position in the priority list; (2) Both ends in the vertical or horizontal direction should be spaced apart in the priority list, such as... correct, Not advisable; (3) The initial position determines the order of the initial priority list. The priority list for the starting point is as follows: That is, the direction opposite to the initial direction of the drone has the highest priority; (4) When the drone changes from vertical to horizontal movement, the priority list remains unchanged; (5) When the drone changes from a horizontal to a vertical orientation, if the vertical orientation is the same as the original vertical orientation, the orientation priority remains unchanged. If it is the opposite, then... Priority switching, such as Transform into ; (6) When the drone moves along the S direction, if there is an obstacle on the right or the area has already been searched, the priority is... .
[0015] In this embodiment of the invention, an improved grid pattern based on obstacle direction priority is introduced: when there is no obstacle, the starting point direction is prioritized; when an obstacle is reached, the position of the obstacle relative to the UAV is used as the basis for changing the UAV's heading priority.
[0016] A priority list is introduced to indicate the next direction of movement for the drone. List elements... , respectively express.
[0017] As attached Figure 3 As shown, the drone's initial position is located in the lower left corner of the area. The specific principles are as follows: (1) Search mode priority is divided into two groups: horizontal and vertical. When the search area is rectangular, the longer side is used as the highest priority. For example, if the horizontal length of the search area is... Vertical width is , At that time, one could consider adjusting the level. or It is the highest position in the priority list.
[0018] (2) Both ends of items in the vertical or horizontal direction should be spaced apart in the priority list. For example... correct, Not advisable.
[0019] (3) The initial position determines the order of the initial priority list, as shown in the appendix. Figure 3 The priority list of the starting points is as follows: That is, the direction opposite to the initial direction of the drone has the highest priority.
[0020] (4) When the drone changes from vertical to horizontal movement, the priority list remains unchanged.
[0021] (5) When the drone changes from a horizontal to a vertical orientation, if the vertical orientation is the same as the original vertical orientation, the orientation priority remains unchanged. If it is the opposite, then... Priority switching. For example... Transform into .
[0022] (6) When the drone moves along the S direction, if there is an obstacle on the right or the area has already been searched, the priority is... .
[0023] The above principles briefly explain the setting of the highest priority level, the location setting of priority, and the method of priority transformation. When the drone is near obstacles, the priority setting should prioritize the impact of obstacles, and then the area search can be completed according to the above principles.
[0024] Combined with appendix Figure 3 To further illustrate the effects of the present invention, the search area is rasterized.
[0025] (1) Comparative analysis of simple search regions The search area is a rectangular area of 10km × 10km. The UAV's starting point is located at (2,2), with an initial heading of 90°. The search process is shown in the attached figure. Figure 4 As shown.
[0026] Simulation Result Analysis: Traditional Grid-Based Search: When the UAV encounters an obstacle, it avoids it, resulting in omissions in the search of the other side of the obstacle. Furthermore, for obstacles with special shapes, the traditional grid-based method cannot satisfy the requirement of searching inside the obstacle.
[0027] The improved method mentioned in reference (1) (He Chengyu. Research on Path Planning and Obstacle Avoidance Algorithm for Cleaning Robots [D]. Harbin University of Science and Technology, 2021: 25-27.) is a grid-based search method based on starting point direction priority. Appendix Figure 4 The drone initially positions itself in the lower left corner of the area, with left and lower directions prioritized. When the drone encounters an obstacle, it avoids it and then prioritizes traversing the unsearched areas on either side. However, for obstacles with unusual shapes, the algorithm cannot complete the traversal search within the affected area.
[0028] The grid method proposed in this embodiment effectively solves the problems encountered in the simulation of the two algorithms mentioned above. Currently common search methods often fail to achieve full area coverage due to obstacles and oversights of areas within obstacles. The method proposed in this embodiment can complete the entire search of the designated area.
[0029] (2) Comparative analysis of complex search regions The search area was set at 25km × 25km, with the starting point at (2,2) and an initial heading of 90°. The search area contained both rectangular and concave obstacles. The search process is shown in the attached figure. Figure 5 As shown.
[0030] Simulation results analysis: Traditional grid-based methods may miss areas on the other side of obstacles. The search area comprises 499 nodes. Traditional grid-based methods traversed all 499 nodes, while a grid-based method prioritizing the starting point direction traversed 293 nodes. After achieving 58.71% coverage, the search entered a dead zone.
[0031] When performing region search using the improved grid method mentioned in reference (1) (He Chengyu. Research on Path Planning and Obstacle Avoidance Algorithm for Cleaning Robots [D]. Harbin University of Science and Technology, 2021: 25-27.), this method can effectively address the shortcomings of the traditional grid search method by prioritizing the traversal of the region on the other side of the obstacle. The search area comprises 499 nodes, and 181 nodes are traversed using a grid method based on the starting point direction priority. After achieving a region search coverage of 36.27%, the search enters a dead zone.
[0032] During the simulation, it was found that the search algorithm mentioned in reference (1) (He Chengyu. Research on path planning and obstacle avoidance algorithm of cleaning robot [D]. Harbin University of Science and Technology, 2021: 25-27.) has two shortcomings when searching for special obstacles: (1) When the opening of the concave area is downward, the current search method will cause the search area to be missed. (2) When the concave area is high and narrow, the method is more likely to enter the dead zone.
[0033] The improved grid method based on obstacle direction priority proposed in this embodiment will not leave gaps in the searched obstacle area, and can complete the search traversal inside the concave area. It is suitable for more complex search areas and has a high coverage. The search area has a total of 499 nodes. The grid method based on starting point direction priority is used to traverse 489 of them. After completing the area search coverage of 98%, it gets stuck in the dead zone.
[0034] This embodiment proposes an improved grid-based UAV search method based on obstacle direction priority. This method can achieve full-area coverage search as much as possible, avoiding the process of UAVs circling and covering unsearched areas after completing the search along the original route, thereby reducing search time and search path and improving search efficiency.
[0035] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. An improved grid-shaped search method based on obstacle direction priority, characterized in that... Includes the following steps: Step 1: The drone flies along a grid-like search route; Step 2: During the journey, if there are no obstacles, the direction of the starting point takes priority; Step 3: During the flight, if an obstacle is encountered, the obstacle's position relative to the drone is used as the priority for changing the drone's heading. A priority list is introduced to indicate the drone's next movement direction. The list elements... , respectively This indicates that obstacle avoidance is being performed. Step 4: After avoiding obstacles, continue the grid search according to the new location point.
2. The improved grid search method based on obstacle direction priority according to claim 1, characterized in that... The specific steps of step 2 are as follows: (1) The search mode priority is divided into two groups: horizontal and vertical. When the search area is rectangular, the longer side is taken as the highest priority. The horizontal length of the search area is... Vertical width is , At that time, consider making the horizontal or As the highest position in the priority list; (2) Both ends in the vertical or horizontal direction should be spaced apart in the priority list, such as... correct, Not advisable; (3) The initial position determines the order of the initial priority list. The priority list for the starting point is as follows: That is, the direction opposite to the initial direction of the drone has the highest priority; (4) When the drone changes from vertical to horizontal movement, the priority list remains unchanged; (5) When the drone changes from a horizontal to a vertical orientation, if the vertical orientation is the same as the original vertical orientation, the orientation priority remains unchanged; if it is opposite, then... Priority switching, such as Transform into ; (6) When the drone moves along the S direction, if there is an obstacle on the right or the area has already been searched, the priority is... .