Sea-air integrated cross-domain heterogeneous collaborative planning method

Abstract

The invention provides a sea-air integrated cross-domain heterogeneous collaborative planning method, and belongs to the technical field of unmanned system command and control. According to the method, a cross-domain heterogeneous collaborative planning framework comprising an unmanned aerial vehicle, an unmanned surface vessel and an autonomous underwater vehicle is provided. By comprehensively considering the characteristics and task requirements of the unmanned system and the influence of a propagation channel and an information flow, a complete collaborative planning model is established, and various constraint conditions such as feasible space constraint and terminal distance constraint are introduced, so that efficient completion of a collaborative task is ensured. And under the guidance of the optimization target, path planning of the AUV, the USV and the UAV is performed in sequence by adopting an asynchronous planning strategy, so that the search efficiency and the task success rate of the underwater target are improved. The method has a more complete collaborative planning framework and performance advantages, is suitable for a complex underwater environment, and can effectively overcome the problems of weak search capability, low communication efficiency and the like in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned system command and control, and in particular to a cross-domain heterogeneous collaborative planning method for sea and air integration. Background Art

[0002] Compared with a single unmanned system, the collaboration between multiple unmanned systems can effectively improve the success rate of the mission, so the collaboration between unmanned systems has received widespread attention. Common unmanned systems include unmanned aerial vehicles (UAVs), unmanned vehicles (UGVs), unmanned surface vehicles (USVs), and autonomous underwater vehicles (AUVs), which can be used to perform air, ground, surface, and underwater missions.

[0003] There have been a lot of research on collaboration between unmanned systems of the same type, such as drones working together to save communication energy and detect terrain changes; unmanned vehicles working together to perform road inspections to improve inspection efficiency and safety; unmanned surface vehicles working together to achieve maritime search and rescue missions; and autonomous underwater vehicles working together to collect data and maintain underwater wells.

[0004] However, there are relatively few studies on the collaboration between heterogeneous unmanned systems. Common ones include UAV / UGA collaboration to build three-dimensional maps and UAV / USV collaboration to solve ocean-related problems. Due to the limitations of communication mechanisms, there are few studies on UAV / AUV collaboration. The AUV / USV collaborative system can establish a surface and underwater communication network through acoustic communication and positioning to improve the search efficiency for underwater targets.

[0005] Currently, researchers have proposed some methods for heterogeneous collaborative planning, such as UAV / AUV collaboration, AUV / USV collaboration, etc. However, these collaborative mechanisms still have some problems.

[0006] Cross-domain heterogeneous collaboration between UAV and AUV: Compared with a single AUV system, it can improve the positioning accuracy of underwater targets. However, the information exchange process is limited, and the electromagnetic signals used for communication between AUV and UAV will be severely attenuated in water, resulting in low communication efficiency between the two.

[0007] Heterogeneous collaboration between AUV and USV: A surface-underwater target search network can be established based on acoustic propagation to improve the underwater navigation performance of AUV. However, without the high maneuverability and wide field of view of UAV as an aid, the coverage of target surveillance under the collaboration of the two is relatively limited.

[0008] In summary, many current technical means consider the collaboration between homogeneous unmanned systems, but there are relatively few studies on cross-domain heterogeneous unmanned system collaborative planning, and the existing heterogeneous collaborative methods still have some shortcomings. Therefore, the present invention proposes a cross-domain heterogeneous collaborative planning method for sea and air integration, designs a UAV-USV-AUV cross-domain heterogeneous system, realizes collaborative planning tasks, and solves the shortcomings of the above-mentioned prior art. Summary of the invention

[0009] The purpose of the present invention is to provide a cross-domain heterogeneous collaborative planning method that integrates sea and air, has a more complete collaborative planning framework and performance advantages, is suitable for complex underwater environments, and can effectively overcome the problems of weak search capability and low communication efficiency in the prior art.

[0010] To achieve the above object, the present invention provides a cross-domain heterogeneous collaborative planning method for sea and air integration, comprising the following steps: Step S1, modeling unmanned systems and underwater targets, including modeling unmanned aerial vehicles (UAVs), unmanned surface vessels (USVs), autonomous underwater vehicles (AUVs), and underwater targets; Step S2: Based on the modeling results in step S1, the feasible space constraints, terminal distance constraints, cross-domain heterogeneous information connection constraints, and energy consumption constraints are comprehensively considered to set boundary conditions and restrictions for cross-domain heterogeneous collaborative planning; Step S3: Under the constraints of step S2, according to the characteristics of the unmanned system and the task requirements, establish the optimization goal of the search and tracking phase; Step S4: Under the guidance of the optimization goal of step S3, an asynchronous planning strategy is adopted to sequentially plan the paths of the autonomous underwater vehicle AUV, the unmanned surface vessel USV and the unmanned aerial vehicle UAV.

[0011] Preferably, in step S1, the UAV model is as follows: At each time step, the UAV adjusts its range radius by adjusting the path loss To complete the search mission, since the UAV can always see the USV, the communication connection between the UAV and the USV is modeled as a line-of-sight LOS path, and the height of the UAV and range radius The relationship between them is expressed as: ; in, Represents the communication loss index under the LOS path, which is determined by the loss of the LOS path.

[0012] Preferably, in step S1, the unmanned surface vehicle USV is modeled as follows: As a relay for wireless communication, the USV operates randomly at sea to ensure the transmission of information between the USV and the UAV. The success rate of communication between the unmanned surface vessel USV and the unmanned aerial vehicle UAV is as follows: ; in, represents the signal to interference plus noise ratio, express The threshold value of express probability.

[0013] Preferably, in step S1, the autonomous underwater vehicle AUV is modeled as follows: Each AUV is modeled as a target tracker, whose information communication and energy constraints must be met, acoustic path loss and carrier frequency , Propagation distance The relationship is as follows: ; in, represents the expansion factor in the geometric propagation process; It represents the acoustic path loss during the communication process of the autonomous underwater vehicle AUV; represents the propagation loss coefficient; Total energy consumption of autonomous underwater vehicle AUV It is expressed as: ; in, Indicates the energy consumption of exercise. Indicates the communication energy consumption.

[0014] Preferably, in step S1, the underwater target is modeled as follows: When the underwater target enters the search area, the search mission begins. It is assumed that the underwater target can sense the approach of the autonomous underwater vehicle AUV and escape at a speed of represents the random initial velocity of the underwater target, represents the direction vector from the AUV cluster center to the underwater target, The underwater target safety area with radius Defined as: ; in, Indicates O- xyz The approximate position of the underwater target received by the unmanned surface vehicle USV from the autonomous underwater vehicle AUV in the coordinate system; Respectivelyx, y, z Approximate position of underwater targets in three coordinate axes; Indicates the actual position of the underwater target.

[0015] Preferably, in step S2, the feasible space constraints are as follows: ; in, Indicates the distance between the underwater target position and the center of the search range; Indicates the position coordinates of the underwater target in the sea space; Represents the center of the cross-domain collaborative search scope; The terminal distance constraints are as follows: ; in, They represent the terminal moment, the spatial state information of the underwater target and the autonomous underwater vehicle AUV respectively; It represents the distance threshold that the autonomous underwater vehicle AUV should meet with the underwater target at the terminal time; Cross-domain heterogeneous information connection constraints include UAV-USV information connection constraints and USV-AUV information connection constraints; The UAV-USV information connection constraints are as follows: ; The USV-AUV information connection constraints are as follows: ； in, represents the number of autonomous underwater vehicles AUV; Indicates unmanned system Communication connection index; constant Indicates the requirements of unmanned systems for information connectivity; The energy consumption constraint formula of the autonomous underwater vehicle AUV system is as follows: ; ; in, represents the energy consumption of the autonomous underwater vehicle AUV system; represents underwater information connectivity; Respectively represent the position information of UAV, USV, AUV and underwater targets; Respectively represent the speed information of UAV, USV, AUV and underwater target; For the The energy value inside the autonomous underwater vehicle AUV, constant It represents the requirements of the cross-domain collaborative system on the internal energy balance of the autonomous underwater vehicle (AUV).

[0016] Preferably, in step S3, the optimization target is as follows: ; in, They represent the search space ranges of three unmanned systems: UAV, USV, and AUV. Indicates the underwater space range, , They represent the optimization objective functions of the target search phase and the tracking phase respectively.

[0017] Preferably, in step S4, under the guidance of the optimization goal of step S3, an asynchronous planning strategy is adopted to sequentially perform path planning for the autonomous underwater vehicle AUV, the unmanned surface vehicle USV and the unmanned aerial vehicle UAV as follows: At each sampling moment, the autonomous underwater vehicle AUV that detects the underwater target first determines the optimal path based on the target's predicted position and optimization objectives; The USV conducts path planning based on the actions of the AUV, where the USV needs to consider the limitations of communication with the AUV; The optimization indicators of the unmanned surface vehicle USV are as follows: ; in, Indicates that the unmanned surface vehicle USV and the underwater target are in the The distance of time; represents the motion optimization function of the unmanned surface vehicle USV; The UAV performs path planning, and the distance constraint between the UAV and the unmanned surface vessel USV needs to be considered during the process; The optimization indicators for UAV decision-making are as follows: ; in, Indicates that UAV and underwater targets are The distance of time; Represents the motion optimization function of the UAV.

[0018] Therefore, the present invention adopts the above-mentioned sea-air integrated cross-domain heterogeneous collaborative planning method, and the beneficial technical effects are as follows: (1) A more complete cross-domain heterogeneous collaborative planning framework: A cross-domain heterogeneous collaborative planning framework including UAVs, USVs, and AUVs is established, taking into account the collaborative cooperation of the three unmanned systems. This overcomes the relatively weak search capabilities of existing homogeneous unmanned systems, AUV-UAV collaboration, and AUV-USV collaboration.

[0019] (2) Performance advantages: The present invention takes into account the influence of propagation channels and information flows, and introduces information connection constraints between UAV-USV and USV-AUV, making the cross-domain heterogeneous collaborative planning method more in line with the actual situation of complex underwater environments and helping to better complete collaborative planning tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention is a flow chart of a cross-domain heterogeneous collaborative planning method for sea and air integration. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0022] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0023] Embodiment 1 For underwater target search and tracking tasks, there are some shortcomings in using a single AUV, multiple AUVs for collaborative tracking, UAV and AUV collaborative systems, or USV and AUV collaboration. For example, the search capabilities of USV and AUV are relatively weak, and the communication efficiency between UAV and AUV is low. In addition, the limited bandwidth and fading characteristics of the underwater acoustic channel will affect the decision-making of AUVs.

[0024] To this end, the idea of ​​the present invention is to establish a cross-domain heterogeneous collaborative planning framework for UAV, USV and AUV under the influence of propagation channels and information flows, thereby improving the efficiency of completing the search task for underwater targets.

[0025] like Figure 1 As shown, the specific steps of the present invention include the following: 1. Unmanned systems and underwater target modeling.

[0026] 101. UAV modeling: At each time step, the UAV adjusts Furthermore, since the USV is always visible to the UAV, the communication link between the UAV and the USV can be modeled as a line-of-sight (LOS) path. and range radius The relationship between can be expressed as ; in, Represents the communication loss index under the LOS path, which is determined by the loss of the LOS path.

[0027] 102. USV modeling: As a relay for wireless communication, the USV operates randomly at sea to ensure the transmission of information between the UAV and the USV. Indicates the success rate of communication between UAV and USV, as shown below: ; in, represents the signal to interference plus noise ratio, express The threshold value of express probability.

[0028] 103. AUV modeling: In this embodiment, each AUV is modeled as a target tracker, so its information communication and energy constraints must be met. It shows the relationship between the acoustic path loss and the carrier frequency. , Propagation distance Among them, represents the expansion factor in the geometric propagation process, represents the propagation loss coefficient. The total energy consumption of AUV can be expressed as .in, Indicates the energy consumption of exercise. Indicates the communication energy consumption.

[0029] 104. Underwater target modeling: When the underwater target enters the search area, the search mission begins. It is assumed that the underwater target can sense the approach of the AUV and escape at a speed of represents the random initial velocity of the underwater target, represents the direction vector from the AUV cluster center to the underwater target, The underwater target safety area with radius Defined as: ; in, Indicates O- xyz The approximate position of the underwater target received by the unmanned surface vehicle USV from the autonomous underwater vehicle AUV in the coordinate system; Respectively x, y, z Approximate position of underwater targets in three coordinate axes; Indicates the actual position of the underwater target.

[0030] 2. Constraint representation of cross-domain collaborative systems.

[0031] In the underwater target search and tracking mission, the three unmanned systems must meet specific constraints to ensure safe and reliable communication between heterogeneous systems. Comprehensively considering various constraints, the following analysis is given: 201. Feasible space constraints: Considering issues such as air traffic control, the hovering height of drones Limited to the allowed range In addition, in order to prevent underwater targets from escaping from the searched sea area, the center of the search range formed by the underwater target and the three unmanned systems of UAV-USV-AUV satisfies the following relationship: ; in, Indicates the distance between the underwater target position and the center of the search range; Indicates the position coordinates of the underwater target in the sea space; Represents the center of the cross-domain collaborative search range.

[0032] 202. Terminal distance constraints: At the end time, the AUV system should be as close to the target as possible. The distance between the AUV system and the target must be less than a certain threshold to meet the mission requirements, which is specifically expressed as follows: ; in, Respectively represent the terminal time, the spatial state information of the underwater target and the AUV, It represents the distance threshold that the AUV and the underwater target should meet at the terminal moment.

[0033] 203. Constraints on cross-domain heterogeneous information connection: UAV-USV information connection constraints: Due to the strong mobility and strong electromagnetic interference of UAVs, in order to ensure the cross-domain coordination of the three unmanned systems of UAV, USV and AUV, the information connection between UAV and USV needs to meet .

[0034] USV-AUV information connection constraints: ; in, represents the number of autonomous underwater vehicles AUV; Indicates unmanned system Communication connection index; constant Represents the requirements of unmanned systems for information connectivity.

[0035] 204. Energy consumption constraints: In the cross-domain heterogeneous collaborative planning process of three unmanned systems, UAV, USV, and AUV, the goal is to minimize the total energy consumption value. The energy consumption problem of establishing a cross-domain heterogeneous collaborative planning system is as follows: ; in, represents the number of autonomous underwater vehicles AUV; Indicates unmanned system Communication connection index; constant Indicates the requirements of unmanned systems for information connectivity; In addition, if the difference in residual energy inside the AUV system is too large, it will cause the target search mission to fail. Therefore, the energy inside the AUV system should be balanced and meet the following conditions: ; in, represents the energy consumption of the autonomous underwater vehicle AUV system; represents underwater information connectivity; Respectively represent the position information of UAV, USV, AUV and underwater targets; Respectively represent the speed information of UAV, USV, AUV and underwater target; For the The energy value inside the autonomous underwater vehicle AUV, constant It represents the requirements of the cross-domain collaborative system on the internal energy balance of the autonomous underwater vehicle (AUV).

[0036] 3. Optimization indicators in the search and tracking phase.

[0037] In the search and tracking phase, the search space of the three unmanned systems, UAV, USV, and AUV, should be expanded as much as possible to increase the probability of detecting underwater targets; in addition, the total energy consumption of the cross-domain heterogeneous system should be reduced as much as possible. The optimization goal of the search and tracking phase is established as follows: ; in, They represent the search space ranges of three unmanned systems: UAV, USV, and AUV. Indicates the underwater space range, , They represent the optimization objective functions of the target search phase and the tracking phase respectively.

[0038] 4. Asynchronous collaborative planning strategy.

[0039] Since the path planning process of the unmanned system is determined in a distributed form, an asynchronous planning strategy is adopted so that they work in a certain order at each sampling time.

[0040] 401. First, the AUV performs path planning: At each sampling moment, the AUV that detects the underwater target broadcasts the current position of the target. Since the target tracking task is actually implemented by the AUV, the fewer constraints imposed on the AUV path, the better the path planning effect. Therefore, the communication restrictions between the USV and the AUV are not considered in this stage. The AUV determines the optimal path based on the predicted position and the optimization target of the third stage.

[0041] 402. Secondly, USV performs path planning: The USV conducts path planning based on the actions of the AUV. Unlike the AUV path planning, the USV needs to consider the limitations of communication between the USV and the AUV. The optimization index of the USV can be expressed as: ; in, Indicates that the unmanned surface vehicle USV and the underwater target are in the The distance of time; Represents the motion optimization function of the unmanned surface vehicle USV.

[0042] 403. Finally, UAV performs path planning: The UAV performs path planning at the end of each sampling moment. Similar to the USV, the distance constraint between the UAV and the USV needs to be considered during the path planning process. The optimization index of the UAV decision is also the distance to the target at the next moment: ; in, Indicates that UAV and underwater targets are The distance of time; Represents the motion optimization function of the UAV.

[0043] It is worth noting that the contents not elaborated in detail in the present invention are all prior art and are well known to those skilled in the art.

[0044] Therefore, the present invention adopts the above-mentioned sea-air integrated cross-domain heterogeneous collaborative planning method, which has a more complete collaborative planning framework and performance advantages, is suitable for complex underwater environments, and can effectively overcome the problems of weak search capability and low communication efficiency in the prior art.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A cross-domain heterogeneous collaborative planning method for sea and air, characterized in that: The following steps are involved: Step S1, modeling unmanned systems and underwater targets, including modeling unmanned aerial vehicles (UAVs), unmanned surface vessels (USVs), autonomous underwater vehicles (AUVs), and underwater targets; Step S2: Based on the modeling results in step S1, the feasible space constraints, terminal distance constraints, cross-domain heterogeneous information connection constraints, and energy consumption constraints are comprehensively considered to set boundary conditions and restrictions for cross-domain heterogeneous collaborative planning; Step S3: Under the constraints of step S2, according to the characteristics of the unmanned system and the task requirements, establish the optimization goal of the search and tracking phase; Step S4: Under the guidance of the optimization goal of step S3, an asynchronous planning strategy is adopted to sequentially plan the paths of the autonomous underwater vehicle AUV, the unmanned surface vessel USV and the unmanned aerial vehicle UAV.

2. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 1 is characterized in that: In step S1, the UAV model is as follows: At each time step, the UAV adjusts its range radius by adjusting the path loss To complete the search mission, since the UAV can always see the USV, the communication connection between the UAV and the USV is modeled as a line-of-sight LOS path, and the height of the UAV and range radius The relationship between them is expressed as: ； in, Represents the communication loss index under the LOS path, which is determined by the loss of the LOS path.

3. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 2 is characterized in that: In step S1, the unmanned surface vehicle USV is modeled as follows: As a relay for wireless communication, the USV operates randomly at sea to ensure the transmission of information between the USV and the UAV. The success rate of communication between the unmanned surface vessel USV and the unmanned aerial vehicle UAV is as follows: ； in, represents the signal to interference plus noise ratio, express The threshold value of express probability.

4. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 3 is characterized in that: In step S1, the autonomous underwater vehicle AUV is modeled as follows: Each AUV is modeled as a target tracker, whose information communication and energy constraints must be met, acoustic path loss and carrier frequency , Propagation distance The relationship is as follows: ； in, represents the expansion factor in the geometric propagation process; It represents the acoustic path loss during the communication process of the autonomous underwater vehicle AUV; represents the propagation loss coefficient; Total energy consumption of autonomous underwater vehicle AUV It is expressed as: ； in, Indicates the energy consumption of exercise. Indicates the communication energy consumption.

5. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 4 is characterized in that: In step S1, the underwater target model is as follows: When the underwater target enters the search area, the search mission begins. It is assumed that the underwater target can sense the approach of the autonomous underwater vehicle AUV and escape at a speed of represents the random initial velocity of the underwater target, represents the direction vector from the AUV cluster center to the underwater target, The underwater target safety area with radius Defined as: ； in, Indicates O- xyz The approximate position of the underwater target received by the unmanned surface vehicle USV from the autonomous underwater vehicle AUV in the coordinate system; Respectively x,y,z Approximate position of underwater targets in three coordinate axes; Indicates the actual position of the underwater target.

6. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 5 is characterized in that: In step S2, the feasible space constraints are as follows: ； in, Indicates the distance between the underwater target position and the center of the search range; Indicates the position coordinates of the underwater target in the sea space; Represents the center of the cross-domain collaborative search scope; The terminal distance constraints are as follows: ； in, They represent the terminal moment, the spatial state information of the underwater target and the autonomous underwater vehicle AUV respectively; It represents the distance threshold that the autonomous underwater vehicle AUV should meet with the underwater target at the terminal time; Cross-domain heterogeneous information connection constraints include UAV-USV information connection constraints and USV-AUV information connection constraints; The UAV-USV information connection constraints are as follows: ； The USV-AUV information connection constraints are as follows: ； in, represents the number of autonomous underwater vehicles AUV; Indicates unmanned system Communication connection index; constant Indicates the requirements of unmanned systems for information connectivity; The energy consumption constraint formula of the autonomous underwater vehicle AUV system is as follows: ； ； in, represents the energy consumption of the autonomous underwater vehicle AUV system; represents underwater information connectivity; Respectively represent the position information of UAV, USV, AUV and underwater targets; Respectively represent the speed information of UAV, USV, AUV and underwater target; For the The energy value inside the autonomous underwater vehicle AUV, constant It represents the requirements of the cross-domain collaborative system on the internal energy balance of the autonomous underwater vehicle (AUV).

7. The method for cross-domain heterogeneous collaborative planning for sea-air integration according to claim 6 is characterized in that: In step S3, the optimization objectives are as follows: ； in, They represent the search space ranges of three unmanned systems: UAV, USV, and AUV. Indicates the underwater space range, , They represent the optimization objective functions of the target search phase and the tracking phase respectively.

8. The method for cross-domain heterogeneous collaborative planning of sea-air integration according to claim 7 is characterized in that: In step S4, under the guidance of the optimization goal of step S3, an asynchronous planning strategy is adopted to sequentially plan the paths of the autonomous underwater vehicle AUV, the unmanned surface vehicle USV and the unmanned aerial vehicle UAV as follows: At each sampling moment, the autonomous underwater vehicle AUV that detects the underwater target first determines the optimal path based on the target's predicted position and optimization objectives; The USV conducts path planning based on the actions of the AUV, where the USV needs to consider the limitations of communication with the AUV; The optimization indicators of the unmanned surface vehicle USV are as follows: ； in, Indicates that the unmanned surface vehicle USV and the underwater target are in the The distance of time; represents the motion optimization function of the unmanned surface vehicle USV; The UAV performs path planning, and the distance constraint between the UAV and the unmanned surface vessel USV needs to be considered during the process; The optimization indicators for UAV decision-making are as follows: ； in, Indicates that UAV and underwater targets are The distance of time; Represents the motion optimization function of the UAV.

Images