Motion control method of unmanned aerial vehicle and unmanned vehicle cooperative system

Abstract

The invention provides a motion control method of an unmanned aerial vehicle and unmanned vehicle cooperative system. The motion control method comprises the following steps: step 1, obtaining a first point cloud map based on a laser radar carried by an unmanned vehicle; obtaining boundary data of each building higher than the unmanned vehicle path according to the first point cloud map, wherein the boundary data comprises a two-dimensional coordinate of each point in the boundary of the building; 2, constructing a database, wherein the database comprises a plurality of sets; each set is composed of two-dimensional coordinates of each point in the boundary of each building; 3, obtaining a second point cloud map based on a laser radar carried by the unmanned aerial vehicle, and fusing the second point cloud map with the first point cloud map to generate a three-dimensional map; 4, matching the two-dimensional coordinate of the boundary of each building with the point cloud information of the three-dimensional map to obtain the three-dimensional coordinate of the boundary of each building; the flight path of the unmanned aerial vehicle is planned according to the three-dimensional coordinates of the boundary of each building; and 5, dynamically scheduling the working sequence of the unmanned aerial vehicles and the unmanned aerial vehicles according to the flight paths of the unmanned aerial vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-unmanned system cooperative control, and in particular to a motion control method for a cooperative system of a drone and an unmanned vehicle. Background Art

[0002] Drones and unmanned vehicles are widely used in the field of security patrols, especially in environments such as factories and campuses that require efficient and safe patrols. However, when drones and unmanned vehicles are used alone for security patrols, there are many defects.

[0003] Disadvantages of drone patrol system: 1) Limited battery life: The battery life of drones is short, which requires frequent battery replacement or charging during large-scale patrol missions, affecting the continuity and efficiency of patrols.

[0004] 2) Limited environmental perception capabilities: A single drone sensor may not be able to accurately perceive all potential threats in a complex environment, and is prone to false alarms and missed alarms.

[0005] 3) Limited coverage: Although drones can cover an aerial perspective, their field of view and coverage are still limited in areas with many obstacles such as buildings and trees, making it impossible to achieve all-round monitoring.

[0006] Disadvantages of unmanned vehicle patrol system: 1) Ground obstacle problem: When patrolling on the ground, unmanned vehicles are easily hindered by ground obstacles, such as steps, ramps, obstacles, etc., which limit their patrol paths and efficiency.

[0007] 2) Slow response speed: Compared with drones, unmanned vehicles move more slowly and are not as fast as drones in responding to emergencies.

[0008] 3) Environmental perception limitations: Similar to drones, the single sensor of unmanned vehicles has limited perception capabilities in complex environments, making it difficult to fully cover the patrol area.

[0009] Most existing drone and unmanned vehicle systems operate independently and lack effective coordination mechanisms, making it impossible to achieve full patrol coverage. The inability to dynamically schedule the working order of drones and unmanned vehicles leads to many drawbacks, such as limited coverage, ground obstacles, and limited battery life. Summary of the invention

[0010] The purpose of the present invention is to provide a motion control method for a cooperative system of unmanned aerial vehicles and unmanned vehicles, which can solve the problem that the working order of unmanned aerial vehicles and unmanned vehicles cannot be dynamically scheduled when unmanned aerial vehicles or unmanned vehicles are used in security patrols in the prior art.

[0011] The objective of the present invention is achieved through the following technical solutions: A motion control method for a cooperative system of a drone and an unmanned vehicle comprises the following steps: Step 1: Obtain a first point cloud map based on the laser radar carried by the unmanned vehicle; obtain the boundary data of each building above the path of the unmanned vehicle based on the first point cloud map, including the two-dimensional coordinates (X Ni , Y Ni ); Step 2: Build a database M. The database M contains multiple sets Ni. Each set Ni consists of the two-dimensional coordinates (X Ni , Y Ni )composition; Step 3: Obtain a second point cloud map based on the laser radar carried by the drone, and fuse it with the first point cloud map to generate a three-dimensional map; Step 4: Use the two-dimensional coordinates (X Ni , Y Ni ) is matched with the point cloud information of the 3D map to obtain the 3D coordinates of each building boundary (X Ni , Y Ni , Z Ni ); According to the three-dimensional coordinates of each building boundary (X Ni , Y Ni , Z Ni ) Plan the flight path of the drone; Step 5: Dynamically schedule the working order of the drone and the unmanned vehicle according to the flight path of the drone; In the flight path of the drone in step 4, the height difference and horizontal straight-line distance between the drone and each building boundary are calculated, and the trajectory function is: G f (X f , Y f , Z f );X f =X Ni + ; Y f =Y Ni + ; Z f =Z Ni +h;L1= ; Among them, X f , Y f , Z f are the three-dimensional coordinates of the drone during flight; L1 is the straight-line distance between the drone and the building boundary, and All are manually adjustable values; h is the vertical height between the drone and the building boundary, which is also a manually adjustable value; Preferably, the step five specifically includes: distinguishing and calibrating each building according to the two-dimensional coordinate information of each point in the set Ni: N1, N2, N3...; the unmanned vehicle travels on a pre-set route based on the three-dimensional map, automatically identifying all distinguished and calibrated buildings during the driving process and detecting and calculating the straight-line distance L2 between the buildings; and taking off the drone at a fixed point according to the straight-line distance L2 and waiting for the drone to land.

[0012] Preferably, the real-time three-dimensional coordinates (X ti , Y ti , Z ti ), when the unmanned vehicle detects the minimum straight-line distance to the distinguished and calibrated building as L3, the straight-line distance L2 to the distinguished and calibrated building is calculated: L2= ; =(X ti -X Ni ) 2 ; =(Y ti -Y Ni ) 2 ; When the unmanned vehicle detects for the first time that the minimum straight-line distance to the distinguished and calibrated building is less than L2, the drone is started, and the drone performs the patrol mission according to the trajectory function in step 4, and the unmanned vehicle continues to drive according to the navigation; when the unmanned vehicle detects that the minimum straight-line distance to the same distinguished and calibrated building is greater than L2, the unmanned vehicle stops driving and waits for the drone to land; when the drone lands on the unmanned vehicle, the unmanned vehicle starts and continues driving and detects other distinguished and calibrated buildings.

[0013] The present invention realizes the dynamic scheduling of the working order of the drone and the unmanned vehicle through two aspects: first, the unmanned vehicle detects the straight-line distance L2 between the distinguished and calibrated buildings to start and recover the drone; second, the flight path of the drone is planned by constructing a three-dimensional map. The drone and unmanned vehicle collaborative motion control method avoids the situation where the drone works uninterruptedly for a long time and solves the problem of limited coverage of the unmanned vehicle, improves patrol efficiency and reduces the work intensity of the drone and the unmanned vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a schematic structural diagram of the straight-line distance measurement process between a drone and a building in Example 1 of the present invention.

[0015] Figure 2 This is a schematic structural diagram of the straight-line distance measurement process between an unmanned vehicle and a building in Example 1 of the present invention. DETAILED DESCRIPTION

[0016] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0017] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand the advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0018] Embodiment 1 A motion control method for a cooperative system of a drone and an unmanned vehicle comprises the following steps: Step 1: Obtain a first point cloud map based on the laser radar carried by the unmanned vehicle; obtain the boundary data of each building above the path of the unmanned vehicle based on the first point cloud map, including the two-dimensional coordinates (X Ni , Y Ni ); LiDAR includes a laser ranging system, an optical mechanical scanning unit, a control and recording unit, a global positioning system, an inertial measurement system, and an imaging device.

[0019] Step 2: Build a database M. The database M contains multiple sets Ni. Each set Ni consists of the two-dimensional coordinates (X Ni , Y Ni ). Specifically, the signal detected by the laser radar is transmitted to the external terminal by the unmanned vehicle, and a point cloud map is formed at the external terminal. The point cloud map contains the three-dimensional coordinate information of each point, which is also the three elements of X, Y, and Z that we often say, and sometimes also contains color information, reflection intensity information, echo number information, etc.

[0020] Step 3: Obtain a second point cloud map based on the laser radar carried by the drone, and fuse it with the first point cloud map to generate a three-dimensional map; Step 4: Use the two-dimensional coordinates (X Ni , Y Ni ) is matched with the point cloud information of the 3D map to obtain the 3D coordinates of each building boundary (X Ni , Y Ni , Z Ni ); According to the three-dimensional coordinates of each building boundary (X Ni , Y Ni , Z Ni) Plan the flight path of the drone; Step 5: Dynamically schedule the working order of the drone and the unmanned vehicle according to the flight path of the drone; like Figure 1 As shown, the height difference and horizontal straight-line distance between the drone and each building boundary are calculated in the flight path of the drone in step 4, and the trajectory function is: G f (X f , Y f , Z f );X f =X Ni + ; Y f =Y Ni + ; Z f =Z Ni +h;L1= ; Among them, X f , Y f , Z f are the three-dimensional coordinates of the drone during flight; L1 is the straight-line distance between the drone and the building boundary, and are manually adjustable values; h is the vertical height between the drone and the building boundary, which is also a manually adjustable value; h, and The data adjustment can change the width and height of the drone patrol, that is, the field of view of the drone, thereby changing the clarity of the point cloud map, and corresponding changes can be made according to actual needs.

[0021] Furthermore, the step five specifically includes: distinguishing and calibrating each building according to the two-dimensional coordinate information of each point in the set Ni: N1, N2, N3...; the unmanned vehicle travels on a pre-set route based on the three-dimensional map, automatically identifying all distinguished and calibrated buildings during the driving process and detecting and calculating the straight-line distance L2 between the buildings; and taking off the drone at a fixed point according to the straight-line distance L2 and waiting for the drone to land.

[0022] like Figure 2 As shown, further, the real-time three-dimensional coordinates (X ti , Y ti , Z ti ), when the unmanned vehicle detects the minimum straight-line distance to the distinguished and calibrated building as L3, the straight-line distance L2 to the distinguished and calibrated building is calculated: L2= ; =(X ti -X Ni ) 2 ; =(Y ti -Y Ni ) 2 ; When the unmanned vehicle detects for the first time that the minimum straight-line distance to the distinguished and calibrated building is less than L2, the drone is started, and the drone performs the patrol mission according to the trajectory function in step 4, and the unmanned vehicle continues to drive according to the navigation; when the unmanned vehicle detects that the minimum straight-line distance to the same distinguished and calibrated building is greater than L2, the unmanned vehicle stops driving and waits for the drone to land; when the drone lands on the unmanned vehicle, the unmanned vehicle starts and continues driving and detects other distinguished and calibrated buildings.

[0023] The minimum straight-line distance of L3 is artificially set to prevent the drone from colliding with buildings during takeoff. At the same time, the distance is limited to avoid an increase in detection error after setting a too large distance.

[0024] The present invention realizes the dynamic scheduling of the working order of the drone and the unmanned vehicle through two aspects: first, the unmanned vehicle detects the straight-line distance L2 between the distinguished and calibrated buildings to start and recover the drone; second, the flight path of the drone is planned by constructing a three-dimensional map. The drone and unmanned vehicle collaborative motion control method avoids the situation where the drone works uninterruptedly for a long time and solves the problem of limited coverage of the unmanned vehicle, improves patrol efficiency and reduces the work intensity of the drone and the unmanned vehicle.

[0025] The above is only for explaining the implementation mode of the present invention and is not intended to limit the present invention. For those skilled in the art, any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention without creative work should be included in the protection scope of the present invention.

Claims

1. A motion control method for a cooperative system of a drone and an unmanned vehicle, characterized in that: The following steps are involved: Step 1: Obtain a first point cloud map based on the laser radar carried by the unmanned vehicle; obtain the boundary data of each building above the path of the unmanned vehicle based on the first point cloud map, including the two-dimensional coordinates (X Ni , Y Ni ); Step 2: Build a database M. The database M contains multiple sets Ni. Each set Ni consists of the two-dimensional coordinates (X Ni , Y Ni )composition; Step 3: Obtain a second point cloud map based on the laser radar carried by the drone, and fuse it with the first point cloud map to generate a three-dimensional map; Step 4: Use the two-dimensional coordinates (X Ni , Y Ni ) is matched with the point cloud information of the 3D map to obtain the 3D coordinates of each building boundary (X Ni , Y Ni , Z Ni ); According to the three-dimensional coordinates of each building boundary (X Ni , Y Ni , Z Ni ) Plan the flight path of the drone; Step 5: Dynamically schedule the working order of the drone and the unmanned vehicle according to the flight path of the drone; In the flight path of the drone in step 4, the height difference and horizontal straight-line distance between the drone and each building boundary are calculated, and the trajectory function is: G f (X) f ,AND f ,Z f );X f =X Ni + ;AND f =And Ni + ;Z f =Z Ni +h;L1= ; Among them, X f , Y f , Z f are the three-dimensional coordinates of the drone during flight; L1 is the straight-line distance between the drone and the building boundary, and All are manually adjustable values; h is the vertical height between the drone and the building boundary, which is also a manually adjustable value.

2. The motion control method of a UAV and unmanned vehicle cooperative system according to claim 1, characterized in that: The step five specifically includes: According to the two-dimensional coordinate information of each point in the set Ni, each building is marked differently: N1, N2, N3...; The unmanned vehicle travels along a pre-set route based on a three-dimensional map. During the driving process, it automatically identifies all marked buildings and detects and calculates the straight-line distance L2 between the buildings. It takes off the drone at a fixed point based on the straight-line distance L2 and waits for the drone to land.

3. The motion control method of a UAV and unmanned vehicle cooperative system according to claim 2, characterized in that: Get the real-time 3D coordinates of the unmanned vehicle from the 3D map (X ti , Y ti , Z ti ), set that when the unmanned vehicle detects that the minimum straight-line distance to the distinguished and calibrated building is L3, the drone takes off or recovers and lands, and calculates the straight-line distance L2 to the distinguished and calibrated building: L2= ; =(X ti -X Ni ) 2 ; =(And ti -AND Ni ) 2 ; When the unmanned vehicle detects for the first time that the minimum straight-line distance L3 to the distinguished and calibrated building is less than L2, the drone is started, and the drone performs the patrol mission according to the trajectory function in step 4, and the unmanned vehicle continues to drive according to the navigation; when the unmanned vehicle detects that the minimum straight-line distance L3 to the same distinguished and calibrated building is greater than L2, the unmanned vehicle stops driving and waits for the drone to land; when the drone lands on the unmanned vehicle, the unmanned vehicle starts and continues driving and detects other distinguished and calibrated buildings.

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