Methods, apparatus, systems, devices, and storage media for optimizing cluster formation structure

Abstract

This application provides a method, apparatus, system, device, and storage medium for optimizing cluster formation structure, relating to the field of unmanned systems technology. The solution includes: acquiring the current communication position of a sensing device and the current communication positions of multiple sensed devices; determining the target travel speed and target communication position of the sensing device based on the current communication positions of the sensing device, the multiple sensed devices, and an optimal communication distance; the optimal communication distance being the distance with the highest communication efficiency between the sensing device and any sensed device; and the target communication position being the position where the communication efficiency between the sensing device and any sensed device is highest. The sensing device then travels from the current communication position to the target communication position at the target travel speed. This solution addresses the technical problem of how to optimize the formation structure in a timely manner when the structure of a cluster changes, thereby improving the communication efficiency of the cluster.

Description

Technical Field

[0001] This application relates to the field of unmanned systems technology, and in particular to a method, apparatus, system, device, and storage medium for optimizing cluster formation structure. Background Technology

[0002] With the continuous advancement and development of information and electronic technologies, unmanned systems technology has been widely applied in agriculture, industry, and the military. When conducting swarm operations, formation control is required. Existing swarm formation algorithms typically employ direct control methods. For example, in some aquatic scenarios, path planning can calculate the optimal formation structure, thus assigning commands to each unmanned surface vessel (USV). However, in complex scenarios, such as those with high real-time communication data requirements, direct control methods struggle to cope with complex and dynamic situations. This results in the inability to promptly optimize the formation structure when changes occur, leading to technical problems such as poor communication efficiency in swarm formations. Summary of the Invention

[0003] This application provides a method, apparatus, system, device, and storage medium for optimizing cluster formation structure. This solution addresses the technical problem of how to optimize the formation structure in a timely manner when the structure of a cluster changes, thereby improving the communication efficiency of the cluster formation.

[0004] In a first aspect, embodiments of this application provide a method for optimizing cluster formation structure. The method includes: acquiring the current communication position of a sensing device and the current communication positions of multiple sensed devices; determining the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of the multiple sensed devices, and an optimal communication distance; the optimal communication distance being the distance with the highest communication efficiency between the sensing device and any sensed device; and the target communication position being the position where the communication efficiency between the sensing device and any sensed device is highest; and traveling from the current communication position to the target communication position at the target travel speed.

[0005] This application provides a method for optimizing cluster formation structure. By determining the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensing devices, and the optimal communication distance, the sensing device can obtain the position information of the sensing device and the surrounding sensing devices in a timely manner, thereby determining the target travel speed and target communication position of the sensing device in a timely manner. By adjusting the sensing device to travel towards the target communication position according to the target travel speed, the formation structure can be optimized in a timely manner when the cluster formation structure changes, thereby improving the communication efficiency of the cluster formation.

[0006] In one possible implementation of this application, before determining the target travel speed of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensed devices, and the optimal communication distance, the method further includes: determining the maximum travel speed that the sensing device can travel. Determining the target travel speed based on the current communication position of the sensing device, the current communication positions of the multiple sensed devices, and the optimal communication distance includes: determining a first distance between the sensing device and the multiple sensed devices based on the current communication position of the sensing device and the current communication positions of the multiple sensed devices; determining the absolute value of the difference between the optimal communication distance and each of the first distances; determining a target coefficient based on the absolute values ​​of the differences by comparing the optimal communication distance with the multiple first distances, the target coefficient being used to determine the target travel speed; and finally, determining the target travel speed based on the target coefficient and the maximum travel speed.

[0007] In one possible implementation of this application, determining the target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensed devices, and the optimal communication distance includes: determining multiple angular directions of the sensing device relative to any one of the sensed devices based on the current communication position of the sensing device and the current communication positions of the multiple sensed devices; determining multiple first communication positions of the sensing device relative to any one of the sensed devices based on the multiple angular directions, the optimal communication distance, and the current communication position of the sensing device, where each first communication position is the position with the highest communication efficiency between the sensing device and each sensed device; determining multiple second distances based on the multiple first communication positions and the current communication position of the sensing device, where each second distance is the extension distance between the current communication position and the first communication position; determining the second distance with the largest extension distance between the current communication position and the first communication position as the target extension distance; and determining the first communication position corresponding to the target extension distance as the target communication position.

[0008] In one possible implementation of this application, before moving from the current communication location to the target communication location at the target speed, the method further includes: determining whether there are obstacles on the path between the current communication location and the target communication location of the sensing device. If obstacles are detected on the path, the path for the sensing device to move to the target communication location is redefined.

[0009] In one possible implementation of this application, redetermining the trajectory of the sensing device toward the target communication location includes: determining a third distance between the sensing device and an obstacle. Based on the third distance, the sensing device is adjusted to a second communication location with the obstacle as the center, in a predetermined direction (clockwise or counterclockwise), provided that there are no obstacles on the path of the sensing device from the second communication location to the target communication location. Correspondingly, traveling from the current communication location to the target communication location at a target speed includes: traveling from the second communication location to the target communication location at the target speed.

[0010] In one possible implementation of this application, any of the sensed devices in the cluster system can serve as a sensing device and / or a sensing device for other sensed devices.

[0011] Secondly, embodiments of this application provide an apparatus for optimizing cluster formation structures. This apparatus can implement the method in the first aspect or any possible implementation of the first aspect, and therefore can also achieve the beneficial effects of the first aspect or any possible implementation of the first aspect. The apparatus for optimizing cluster formation structures can be a sensing device, or an apparatus that supports the sensing device in implementing the method in the first aspect or any possible implementation of the first aspect, such as a chip or control circuit applied in a sensing device. The apparatus for optimizing cluster formation structures can implement the above method through software, hardware, or hardware executing corresponding software.

[0012] As an example, this application provides an apparatus for optimizing cluster formation structure. This apparatus is a sensing device or a chip applied within a sensing device. The apparatus includes an acquisition unit and a processing unit. The acquisition unit acquires the current communication position of the sensing device and the current communication positions of multiple sensed devices. The processing unit determines the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of the multiple sensed devices, and an optimal communication distance. The target communication position is the position where the communication efficiency between the sensing device and any sensed device is highest, and the optimal communication distance is the distance between the sensing device and any sensed device where the communication efficiency is highest. The processing unit is further configured to travel from the current communication position to the target communication position at the target travel speed.

[0013] In one possible implementation of this application, the processing unit is also used to determine the maximum travel speed of the sensing device.

[0014] In one possible implementation of this application, the processing unit is further configured to determine a first distance between the sensing device and the multiple sensing devices based on the current communication location of the sensing device and the current communication locations of the multiple sensing devices, determine the absolute value of the difference between the optimal communication distance and the multiple first distances respectively, determine a target coefficient by comparing the magnitude of the optimal communication distance and the multiple first distances based on the multiple absolute values ​​of the difference, the target coefficient is used to determine the target travel speed, and the target travel speed is determined based on the target coefficient and the maximum travel speed.

[0015] In one possible implementation of this application, the processing unit is further configured to determine multiple angular directions of the sensing device relative to any one of the sensing devices based on the current communication position of the sensing device and the current communication positions of multiple sensing devices; determine multiple first communication positions of the sensing device relative to any one of the sensing devices based on the multiple angular directions, the optimal communication distance, and the current communication position of the sensing device, wherein the first communication position is the position with the highest communication efficiency between the sensing device and each sensing device; determine multiple second distances based on the multiple first communication positions and the current communication position of the sensing device, wherein the second distance is the extension distance between the current communication position and the first communication position; determine the second distance with the largest extension distance between the current communication position and the first communication position as the target extension distance; and determine the first communication position corresponding to the target extension distance as the target communication position.

[0016] In one possible implementation of this application, the processing unit is further configured to determine whether there is an obstacle on the travel path between the current communication location of the sensing device and the target communication location, and if an obstacle is detected on the travel path, to redetermine the path for the sensing device to travel to the target communication location.

[0017] In one possible implementation of this application, the processing unit is further configured to determine a third distance between the sensing device and the obstacle, and based on the third distance, adjust the sensing device to a second communication position with the obstacle as the center and in a set direction, wherein the set direction is clockwise or counterclockwise, and there are no obstacles on the path of the sensing device traveling from the second communication position to the target communication position.

[0018] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program or instructions that, when executed on a computer, cause the computer to perform a method for optimizing cluster formation as described in any of the possible implementations of the first aspect.

[0019] Fourthly, embodiments of this application provide a computer program product including instructions that, when executed on a computer, cause the computer to perform a cluster formation optimization method described in the first aspect or various possible implementations of the first aspect.

[0020] Fifthly, embodiments of this application provide a chip including a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run computer programs or instructions to implement a cluster formation optimization method described in the first aspect or various possible implementations of the first aspect. The communication interface is used to communicate with other modules outside the chip.

[0021] In a sixth aspect, embodiments of this application provide a cluster system for optimizing cluster formation structure. The cluster system includes a sensing device and multiple sensing devices. The cluster system is applied to a cluster system based on a wireless mesh network. The sensing device is used to perform a cluster formation structure optimization method described in the first aspect or various possible implementations of the first aspect. Attached Figure Description

[0022] Figure 1 This application provides a cluster system with optimized cluster formation structure as an embodiment.

[0023] Figure 2 This is a schematic diagram of the structure of a sensing device provided in an embodiment of this application;

[0024] Figure 3 A flowchart illustrating a method for optimizing cluster formation structure provided in an embodiment of this application;

[0025] Figure 4 A schematic diagram illustrating the principle of cluster formation optimization provided in this application embodiment;

[0026] Figure 5 A graph showing the relationship between communication distance and communication efficiency is provided for an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of a device for optimizing group formation structure provided in an embodiment of this application. Detailed Implementation

[0028] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0029] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or sets of devices.

[0030] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0031] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0032] With the continuous advancement and development of information and electronic technologies, unmanned systems technology has been widely applied in agriculture, industry, and the military. For example, in some aquatic scenarios, unmanned systems composed of unmanned surface vessels (USVs) can perform tasks. USVs are unmanned surface vessels primarily used for dangerous tasks unsuitable for manned vessels, such as reconnaissance, search, detection, and mine clearance. Their key feature is their ability to perform long-duration, autonomous, and covert operations. When performing tasks, unmanned systems composed of USVs need to be grouped and formed into a specific formation to coordinate their operations.

[0033] Swarm formation algorithms are divided into two categories: direct control and indirect control. Existing technologies typically employ direct control algorithms. For example, in complex aquatic scenarios, receiving data and using path planning, the optimal swarm formation can be calculated, assigning tasks to each unmanned surface vessel (USV) to achieve swarm actions such as obstacle avoidance, formation, and group movement. However, direct control algorithms struggle to handle complex and dynamic scenarios, resulting in the inability to promptly optimize the formation when its structure changes, leading to poor communication efficiency and other technical problems.

[0034] The method provided in this application employs an indirect control algorithm. It transfers formation decision-making power from the control center to each unmanned surface vessel (USV) in the swarm system. Each USV acts as a sensing device, and surrounding USVs act as sensed devices. Based on the current communication positions of the sensed surrounding USVs, the sensing devices autonomously adjust their communication positions within the swarm formation, thereby achieving dynamic optimization of the formation. In the algorithm provided in this application, the indirect control algorithm for formation grants each sensing device independent decision-making capabilities, such as reconnaissance, cognition, decision-making, and action capabilities. A dynamic communication network is constructed within the swarm, and through the autonomous decision-making of the sensing devices, the swarm formation achieves self-organization capabilities in complex aquatic scenarios.

[0035] Therefore, embodiments of this application provide a method, apparatus, system, device, and storage medium for optimizing cluster formation structure. This solution addresses the technical problem of how to optimize the formation structure in a timely manner when the structure of a cluster formation changes, thereby improving the communication efficiency of the cluster formation.

[0036] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0037] like Figure 1 As shown, Figure 1 This application provides an architecture diagram of a cluster system with optimized cluster formation structure, which includes: a sensing device 100 and multiple sensing devices 200.

[0038] The sensing device 100 and the multiple sensing devices 200 can be devices that can be executed by a preset program without human operation, such as unmanned surface vessels, drones, etc. This application embodiment does not impose specific limitations on this.

[0039] As an example, by communicating wirelessly with multiple sensed devices 200, the sensing device 100 can obtain the current communication location of the surrounding sensed devices 200, their distance from itself, etc., thereby adjusting the position and speed of the sensing device 100.

[0040] Since the method provided in this application embodiment is an indirect control algorithm, it endows each sensing device with the ability to make independent decisions. When optimizing the cluster formation structure, the main body is the sensing device 100. Therefore, the sensing device 100 can adjust its own formation position according to the communication position of other sensing devices 200 in the cluster system, thereby optimizing the cluster formation structure. At the same time, since the sensing device 100 can make independent decisions, the total amount of data communication with the control center is reduced, the formation efficiency of the cluster formation is improved, and the self-organizing generation capability and structural optimization capability of the cluster formation structure are realized.

[0041] In one possible embodiment of this application, the cluster system described in this application consists of a sensing device 100 and multiple sensed devices 200 automatically formed through a wireless mesh network. The increase or decrease in the number of devices in the cluster system does not affect the communication of the cluster system.

[0042] It's important to explain that a wireless mesh network is a type of wireless local area network (WLAN). In a cluster system composed of wireless mesh networks, all devices (sensing devices and sensed devices) are interconnected, such as... Figure 1 The diagram shows the architecture of the cluster system. Each device has multiple connection channels, forming a unified network structure, where each device can dynamically maintain communication with other devices. When a connection channel between two devices becomes unresponsive, the wireless mesh network can select other connection channels for data propagation as needed. The failure of any one device will not affect network access to other devices. Therefore, the cluster system provided in this embodiment is applied to a wireless mesh network. When the communication distance between the sensing device 100 and the sensed device 200 is appropriate, devices within the area automatically form a communication network. Even if any device loses network access, the overall communication efficiency of the cluster system does not decrease, thus ensuring uninterrupted network communication during device movement. Furthermore, the number of devices can be dynamically increased or decreased, thereby improving the robustness of the cluster network.

[0043] Optional, such as Figure 2 As shown, Figure 2 This is a schematic diagram of the structure of a sensing device 100 provided in an embodiment of this application. The sensing device 100 includes a wireless communication module, a processing module, and a storage module. The processing module is connected to both the wireless communication module and the storage module. The wireless communication module is used to establish a wireless communication connection between the sensing device 100 and the sensed device 200, and to acquire the current communication positions of the sensing device 100 and the sensed device 200. The processing module is used to determine the target travel speed and target communication position of the sensing device 100, and to move the sensing device 100 towards the target communication position.

[0044] For example, the wireless communication module in the sensing device 100 and the sensed device 200 can be an LR-WiFi (Long Range Wireless Fidelity) chip or a Bluetooth chip; this application embodiment does not limit this. Generally, LR-WiFi chips have the characteristics of long transmission distance, networking capability, strong anti-interference ability, and high sensitivity.

[0045] In this application embodiment, the specific structure of the execution subject of the cluster formation structure optimization method is not particularly limited, as long as it can communicate according to the cluster formation structure optimization method of this application embodiment by running a program that records the code of the cluster formation structure optimization method of this application embodiment. For example, the execution subject of the cluster formation structure optimization method provided in this application embodiment can be a functional module in a sensing device that can call and execute a program, or a device applied in a sensing device, such as a chip. This application does not limit this. The following embodiments describe a cluster formation structure optimization method with a sensing device as the execution subject.

[0046] like Figure 3 As shown, Figure 3 This application provides a flowchart illustrating a method for optimizing cluster formation structure, comprising:

[0047] Step 310: The sensing device obtains the current communication location of the sensing device and the current communication location of multiple sensed devices.

[0048] It should be noted that both the sensing device and the sensed device can be unmanned equipment, such as unmanned surface vessels.

[0049] The current communication position of the sensing device and the current communication position of the sensed device can be represented by two-dimensional coordinates.

[0050] As an example, let's illustrate this with three sensed devices, see, for example... Figure 4 Figure (a) shows the optimization principle diagram of the cluster formation structure: the current communication position coordinates of the sensing device are (X0, Y0), the current communication position coordinates of the sensed device 1 are (X1, Y1), the current communication position coordinates of the sensed device 2 are (X2, Y2), and the current communication position coordinates of the sensed device 3 are (X3, Y3). It can be understood that in Figure (a), sensed devices 1 to 3 are relatively stationary, and the communication distance between sensed devices 1 and 3 is sufficient to enable communication between the devices. Therefore, sensed devices 1 to 3 achieve a stable formation structure.

[0051] Step 320: The sensing device determines the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensed devices, and the optimal communication distance.

[0052] The target speed is the real-time speed that the sensing device needs to update.

[0053] It should be explained that the target travel speed is the real-time travel speed determined based on the current communication position of the sensing device in the cluster formation structure and the communication distance between it and other sensed devices. The closer the communication distance between the sensing device and the sensed devices is to the optimal communication distance, the smaller the real-time travel speed becomes, until the cluster formation structure stabilizes and the real-time travel speed of the sensing device is 0.

[0054] The method for the sensing device to obtain the target's speed can be referred to the description in the following embodiments, and will not be repeated here.

[0055] The optimal communication distance is the distance at which communication efficiency is highest between the sensing device and any sensed device, such as... Figure 4 The diagram shows the optimization principle of the cluster formation structure: In the stable state shown in diagram (a), the communication distance between the sensed device 1 and the sensed device 2 is the optimal communication distance; In the target stable state shown in diagram (c), the communication distance between the sensed device and the sensed device 2 is the optimal communication distance.

[0056] As an example, see, for example Figure 5 The graph shows the relationship between communication distance and communication efficiency. Communication distance represents the distance between the sensing device and any sensed device, measured in kilometers (km). Communication efficiency is expressed as a percentage, with higher percentage values ​​indicating higher efficiency. The graph shows that communication distance and efficiency follow a normal distribution; that is, the closer the communication distance between the sensing device and the sensed device is to the optimal communication distance, the higher the communication efficiency. Therefore, from... Figure 5 It can be concluded that the optimal communication distance between the sensing device and the sensed device is 10km, at which point the communication efficiency between the sensing device and the sensed device is 100%.

[0057] It should be explained that, considering the non-linear relationship between communication distance and communication efficiency, when the communication distance between the sensing device and the sensed device is between 9km and 11km, a communication efficiency of 95% to 100% can still be guaranteed. In this case, the communication distance between the sensing device and the sensed device can also be considered the optimal communication distance. Figure 4 As shown in Figure (c), when the sensing device and the sensed device 1 to sensed device 3 reach the target stable state, the communication distance between the sensing device and the sensed device 3 is maintained within the range of communication efficiency of 95% to 100%. Therefore, the communication distance between the sensing device and the sensed device 3 is the optimal communication distance.

[0058] The target communication location is the location where the communication efficiency between the sensing device and any sensed device is highest. For example, such as... Figure 4 Figure (c) of the cluster formation optimization principle diagram shows that when the devices in the cluster system reach the target stable state, the coordinate position (X0', Y0') of the sensing device is the target communication position. At this time, the communication distance between the sensing device and the sensing device 1 to sensing device 3 reaches the optimal communication distance.

[0059] Step 330: The sensing device travels from the current communication location to the target communication location at the target travel speed.

[0060] As an example, see, for example Figure 4 The diagram shows the optimization principle of the cluster formation structure. In Figure (b), the cluster system is in an unstable state. At this time, when the sensing device obtains the target's travel speed and target communication position, the sensing device moves from the current communication position (X0, Y0) to the target communication position (X0', Y0'). When the sensing device and the sensed device 1 to sensed device 3 reach relative stillness and the communication distance between the devices can enable mutual communication between the devices, the cluster system shown in Figure (c) is in the target stable state.

[0061] This application provides a method for optimizing cluster formation structure. By determining the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensing devices, and the optimal communication distance, the sensing device can obtain the position information of the sensing device and the surrounding sensing devices in a timely manner, thereby determining the target travel speed and target communication position of the sensing device in a timely manner. Since the sensing device travels from the current communication position to the target communication position according to the target travel speed, the formation structure can be optimized in a timely manner when the cluster formation structure changes, thereby improving the communication efficiency of the cluster formation.

[0062] As one possible approach, since the sensing device and the sensed device may be in motion in a cluster system, and the sensing device needs to obtain the current communication position of the sensed device in real time, the following description is based on the sensing device and three sensed devices around it. The autonomous decision-making of the sensing device in optimizing the cluster formation includes the following stages:

[0063] Phase 1: Reconnaissance Phase.

[0064] As an example, the sensing device needs to perceive the scene situation in the surrounding environment in real time and obtain the current communication positions of the three closest sensing devices in real time, thereby determining the first distance and angular direction between the sensing device and these three sensing devices. The method for the sensing device to determine the first distance and angular direction can be referred to the description in the following embodiments, and will not be repeated here.

[0065] Phase 2: Cognitive Phase.

[0066] As an example, the sensing device determines the optimal communication position for the next moment by determining the initial distance and angular direction between the sensing device and the three sensed devices. The method by which the sensing device determines the optimal communication position can be found in the description of the following embodiments, and will not be repeated here.

[0067] Phase 3: Decision-making phase.

[0068] As an example, the sensing device needs to determine whether its current communication location conforms to the optimal communication distance principle. The optimal communication distance principle can be referenced as follows: Figure 5 The diagram showing the relationship between communication distance and communication efficiency illustrates that when the communication distance between the sensing device and the sensed device is between 9km and 11km, and communication efficiency can be guaranteed, the current communication position of the sensing device conforms to the optimal communication distance principle. If the current communication position of the sensing device does not conform to the optimal communication distance principle, the sensing device needs to determine the target communication position and target travel speed, and then travel towards the target communication position at the target travel speed. It should be explained that since both the sensing device and the sensed device are in motion, the target communication position and target travel speed determined by the sensing device at this time are the target communication position and target travel speed after a preset time, based on the current communication positions of the three closest sensed devices. This preset time can be a manually preset value or a preset value determined by the sensing device based on the current scene situation.

[0069] Phase 4: Action Phase.

[0070] As an example, since there may be obstacles on the path from the current communication location to the target communication location, the sensing device needs to determine whether there are obstacles on the path to the target communication location. If an obstacle is detected, the sensing device needs to redetermine the path to the target communication location. This ensures the possibility of the sensing device's movement. The methods for the sensing device to determine obstacles and redetermine its path are described in the following embodiments and will not be repeated here.

[0071] As one possible approach, the autonomous decision-making process of sensing devices, encompassing the reconnaissance, cognition, decision-making, and action phases, needs to be executed cyclically in practical scenarios, i.e., the OODA loop (Observation, Orientation, Decision, Action loop). Through the OODA loop, sensing devices can fine-tune their real-time positions within the cluster system, optimizing the cluster formation and thus improving communication efficiency.

[0072] As one possible approach, if the number of sensed devices around the sensed device is less than a preset number, the sensed device determines a preset target location for the cluster system. The sensed device then moves towards the target location.

[0073] The preset quantity can be a manually set value or a preset value determined by the sensing device based on the current scene situation. For example, if the preset quantity is 3, the sensing device needs to move towards the target location.

[0074] The target location can be the position where the sensing device needs to move when the number of devices in the cluster system decreases or the sensing device detects too few sensing devices in the vicinity. This target location can be a manually preset location in the cluster system, or it can be the center location within the communication range of the devices in the cluster system. This application embodiment does not limit this.

[0075] In one possible embodiment of this application, prior to step 320, the method provided in this application further includes: the sensing device determining the maximum travel speed of the sensing device.

[0076] It should be explained that the maximum speed of the sensing device depends on the performance of the sensing device itself, such as the performance of the engine unit configured with the sensing device.

[0077] In one possible embodiment of this application, the method for determining the target traveling speed of the sensing device in step 320 includes the following steps:

[0078] Step 3211: The sensing device determines the first distance between itself and the multiple sensing devices based on its current communication location and the current communication locations of the multiple sensing devices.

[0079] As an example, see, for example Figure 4Figure (b) of the cluster formation optimization principle diagram shows: The current communication position coordinates of the sensing device are (X0, Y0), the current communication position coordinates of the sensed device 1 are (X1, Y1), the current communication position coordinates of the sensed device 2 are (X2, Y2), and the current communication position coordinates of the sensed device 3 are (X3, Y3). For example, the sensing device can calculate the distance formula based on the coordinates between the two devices, obtaining: the first distance d1 between the sensing device and the sensed device 1, the first distance d2 between the sensing device and the sensed device 2, and the first distance d3 between the sensing device and the sensed device 3. Specifically:

[0080]

[0081]

[0082]

[0083] As one possible implementation, the sensing device can optionally be equipped with a distance sensing module. Based on the current communication position of the sensing device and the current communication positions of the sensed devices 1 to 3, the sensing device senses the first distances d1, d2, and d3 between itself and the sensed devices 1 to 3 through the distance sensing module. The distance sensing module can be an optical distance sensing module, an infrared distance sensing module, or an ultrasonic distance sensing module. Taking an optical distance sensing module as an example: the distance sensing module in the sensing device emits laser pulse signals to the sensed devices 1 to 3 respectively. Based on the time it takes for the laser pulse signals to reach the sensed devices 1 to 3 and to be reflected back to the distance sensing module, and based on the emission speed of the laser pulse signals, the sensing device determines the first distances d1, d2, and d3 between itself and the sensed devices 1 to 3. Typically, the emission speed of the optical pulse signal is 3 * 10^5 km / s.

[0084] Step 3212: The sensing device determines the absolute value of the difference between the optimal communication distance and multiple first distances.

[0085] As an example, by Figure 5 The graph shown illustrates the relationship between communication distance and communication efficiency, determining the optimal communication distance as d. t =10km. Therefore, the absolute values ​​of the differences between the optimal communication distance and multiple first distances determined by the sensing device are respectively: |d1-d t |、|d2-d t | and |d3-d t |

[0086] Step 3213: The sensing device determines the target coefficient by comparing the optimal communication distance with multiple first distances and based on the absolute values ​​of the multiple differences. The target coefficient is used to determine the target's travel speed.

[0087] It should be noted that, typically, the value of this target coefficient is less than or equal to 1.

[0088] As an example, the sensing device needs to compare the optimal communication distance with multiple first distances to determine the target coefficient. Taking the sensed devices as sensed device 1 to sensed device 3, the first distances as d1, d2, and d3, and the target coefficient as δ, the following example illustrates this: when d1 < 0.9d... t Or d1 > 1.1d t In the case of , the target coefficient δ is 1; in 0.9d t ≤d1≤1.1d t and in d2 < 0.9d t Or d2 > 1.1d t In this case, the target coefficient δ is At 0.9d t ≤d1, d2≤1.1d t and in d3 < 0.9d t Or d3 > 1.1d t In this case, the target coefficient δ is At 0.9d t ≤d1, d2, d3≤1.1d t In this case, the target coefficient δ is By organizing the information, we can obtain the formula for calculating the target coefficient of the sensing device:

[0089]

[0090] Step 3211: The sensing device determines the target speed based on the target coefficient and the maximum speed.

[0091] It is understandable that, since the target coefficient is no greater than 1, the target speed determined by the sensing device is less than or equal to the maximum speed.

[0092] As an example, the sensed devices are sensed device 1 to sensed device 3, the first distances are d1, d2 and d3, the target coefficient is set as δ, the target speed is set as V, and the maximum target speed is set as V. max For example, when d1 < 0.9d t Or d1 > 1.1d t In the case where the target coefficient δ is 1, the target speed V is V. max ; at 0.9dt ≤d1≤1.1d t and in d2 < 0.9d t Or d2 > 1.1d t In this case, the target coefficient δ is The target's speed V is At 0.9d t ≤d1, d2≤1.1d t and in d3 < 0.9d t Or d3 > 1.1d t In this case, the target coefficient δ is The target's speed V is At 0.9d t ≤d1, d2, d3≤1.1d t In this case, the target coefficient δ is The target's speed V is By organizing the data, we can obtain the formula for calculating the target speed of the sensing device:

[0093]

[0094] Since the sensing device needs to determine its target communication position at the next moment based on its relative position in the cluster formation to ensure that the sensing device achieves relative optimization of the cluster formation when it reaches the target communication position, in one possible embodiment of this application, the method for determining the target communication position of the sensing device in step 320 includes the following steps:

[0095] Step 3221: The sensing device determines multiple angular directions relative to any one of the sensing devices based on the current communication position of the sensing device and the current communication positions of the multiple sensing devices.

[0096] Wherein, the angular direction of the sensing device relative to any sensed device is the angle by which the sensed device is offset from the sensing device in the vertical direction relative to the sensing device, with the position of the sensing device as a reference. For example, as Figure 4 Figure (b) of the cluster formation optimization principle diagram shows: the angle α1 of the sensing device 1 relative to the sensing device in the vertical direction based on the position of the sensing device, the angle α2 of the sensing device 2 relative to the sensing device in the vertical direction based on the position of the sensing device, and the angle α3 of the sensing device 2 relative to the sensing device in the vertical direction based on the position of the sensing device.

[0097] Since the angle of offset of the sensed device relative to the sensing device is generally represented as a positive value, the angular direction of the sensed device cannot be determined solely by the offset angle. Therefore, as an example, the sensing device can obtain the angular direction based on trigonometric functions (such as the arctangent function).

[0098] As an example, such as Figure 4 The diagram (b) shows the optimization principle of the cluster formation structure. The sensing device's current communication position coordinates are (X0, Y0), the current communication position coordinates of sensing device 1 are (X1, Y1), the current communication position coordinates of sensing device 2 are (X2, Y2), and the current communication position coordinates of sensing device 3 are (X3, Y3). The sensing device determines the angle directions α1, α2, and α3 based on the arctangent function. Specifically:

[0099]

[0100]

[0101]

[0102] Step 3222: The sensing device determines multiple first communication positions relative to any sensed device based on multiple angular directions, the optimal communication distance, and the current communication position of the sensing device.

[0103] The first communication position is the position where the communication efficiency between the sensing device and each sensed device is highest. It is understandable that, since the communication efficiency between the sensing device and each sensed device cannot be guaranteed to be the same, the optimal communication position of the sensing device relative to each sensed device may also be different.

[0104] As an example, such as Figure 4 The diagram (b) shows the optimization principle of the cluster formation structure. The current communication position coordinates of the sensing device are (X0, Y0), the current communication position coordinates of the sensed device 1 are (X1, Y1), the current communication position coordinates of the sensed device 2 are (X2, Y2), and the current communication position coordinates of the sensed device 3 are (X3, Y3). The angular directions of sensed devices 1 to 3 are α1, α2, and α3, respectively. Assume the first communication position of the sensing device relative to sensed device 1 is (X0, Y0). 01 Y 01 The first communication position of the sensing device relative to the sensed device 2 is (X). 02 Y 02 The first communication position of the sensing device relative to the sensed device 3 is (X). 03Y 03 Specifically:

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] Step 3223: The sensing device determines multiple second distances based on multiple first communication locations and the current communication location of the sensing device.

[0112] The second distance is the extended distance between the current communication location and the first communication location.

[0113] As an example, the current communication location of the sensing device is (X0, Y0), and the first communication location of the sensing device relative to the sensed device 1 is (X0, Y0). 01 Y 01 The first communication position of the sensing device relative to the sensed device 2 is (X). 02 Y 02 The first communication position of the sensing device relative to the sensed device 3 is (X). 03 Y 03 The sensing device can calculate the distance formula based on the coordinates between the current communication location and the first communication location to determine the second distance d1′ based on the sensing device 1, the second distance d2′ based on the sensing device 2, and the second distance d3′ based on the sensing device 3. Specifically:

[0114]

[0115]

[0116]

[0117] Step 3224: The sensing device determines the second distance with the largest extension distance between the current communication location and the first communication location as the target extension distance.

[0118] It is understandable that the second distance, which has the largest extension distance between the current communication location and the first communication location, is the extension distance with the highest communication efficiency for the sensing device relative to any other sensing device.

[0119] As an example, as can be seen from the above embodiments, the sensing device takes the maximum value as the target extension distance among the second distance d1′ based on the sensing device 1, the second distance d2′ based on the sensing device 2, and the second distance d3′ based on the sensing device 3.

[0120] Step 3225: The sensing device determines the first communication location corresponding to the target extension distance as the target communication location.

[0121] Since there may be obstacles on the path from the current communication location to the target communication location for the sensing device, in order to ensure the possibility of the sensing device's movement, in one possible embodiment of this application, before step 330, the method provided by this embodiment further includes:

[0122] The sensing device determines whether there are obstacles on the path between its current communication location and the target communication location. If an obstacle is detected, the sensing device redetermines its path to the target communication location.

[0123] The obstacles may be static obstacles such as reefs or islands, or dynamic obstacles such as other organisms or ships that are moving.

[0124] It should be explained that the algorithm used by the sensing device to redetermine the trajectory of the sensing device toward the target communication location can be applied to any obstacle avoidance strategy algorithm. For example, it can be a dynamic obstacle avoidance algorithm based on the principle of bacterial walking, obstacle avoidance and foraging, or it can be a heuristic search algorithm based on grid modeling. This application does not limit this.

[0125] In the following description of the embodiments of this application, the sensing device adopts a dynamic obstacle avoidance algorithm strategy based on the principle of bacterial walking, obstacle avoidance and foraging, to redetermine the path of the sensing device to the target communication location, thereby correcting the walking path of the sensing device.

[0126] In one possible embodiment of this application, redetermining the trajectory of the sensing device toward the target communication location includes the following steps:

[0127] The sensing device determines a third distance between the sensing device and the obstacle.

[0128] The third distance is the straight-line distance between the sensing device and the obstacle.

[0129] Based on the third distance, the sensing device adjusts to the second communication position with the obstacle as the center and in a set direction.

[0130] The direction is set to either clockwise or counterclockwise, and there are no obstacles on the path along which the sensing device travels from the second communication position to the target communication position.

[0131] Accordingly, in one possible embodiment of this application, step 330 includes the following steps: the sensing device travels from the second communication location to the target communication location at a target travel speed.

[0132] As an example, a sensing device can be based on the principle of bacterial movement, obstacle avoidance, and foraging to set up a rotational obstacle avoidance strategy. This strategy includes: when the sensing device detects an obstacle on its path to the target communication location, it activates the rotational obstacle avoidance strategy to determine a third distance between the sensing device and the obstacle, and establishes a sensing situation. Situational awareness is an environment-based, dynamic, and holistic ability to understand the surrounding environment and security risks. The sensing device marks the real-time planned path to determine if there are obstacles on it. Based on the third distance, the sensing device rotates in a set direction around the obstacle, marking each position. The sensing device travels along the real-time planned path, collecting and updating the sensing situation, while simultaneously correcting its obstacle avoidance trajectory. This continues until the sensing device reaches a second communication position, where there are no obstacles on the path from the second communication position to the target communication position. The sensing device then terminates the rotational obstacle avoidance strategy and travels from the second communication position to the target communication position at the target speed.

[0133] In one possible embodiment of this application, any of the sensed devices in the cluster system can serve as a sensed device and / or a sensed device for other sensed devices.

[0134] It should be explained that the sensing device can be a newly added device in the cluster system, which adjusts its own communication position to reach the target position and maintain the communication efficiency between devices in the cluster system; or it can be due to changes in the structure of the cluster system, such as one or more devices in the cluster system losing network access, or obstacles in the scene that need to be autonomously changed in shape. In such cases, the sensing device needs to update its real-time communication position, so the cluster structure in the cluster system needs to be optimized.

[0135] Any sensing device in the cluster system can also act as a sensing device, adjusting its own position by obtaining the current communication position of other sensing devices in the vicinity, thereby achieving cluster structure optimization of the cluster system.

[0136] As one possible approach, the method provided in this application embodiment is used to solve cluster roaming problems, and is also applicable to the situational distribution problem when devices in a cluster system are at a stationary speed.

[0137] The above mainly describes the solutions of the embodiments of this application from the perspective of interaction between various network elements. It is understood that each device, such as a sensing device, includes corresponding structures and / or software modules to perform the above functions in order to achieve them. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0138] This application embodiment can divide the sensing device into functional units according to the above-described method example. For example, each function can be divided into its own functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0139] The above combination Figures 1 to 5 The methods described in the embodiments of this application have been explained. The apparatus for executing the above methods, provided in the embodiments of this application, is described below. Those skilled in the art will understand that the methods and apparatus can be combined with and referenced in relation to each other. The apparatus for optimizing cluster formation structure provided in the embodiments of this application can execute the steps performed by the sensing device in the above-described method for optimizing cluster formation structure.

[0140] When using integrated units Figure 6 The apparatus for optimizing cluster formation structure involved in the above embodiments is shown. The apparatus for optimizing cluster formation structure can be a sensing device or a device applied in a sensing device, such as a chip or processing circuit. The apparatus for optimizing cluster formation structure can include: an acquisition unit 410 and a processing unit 420.

[0141] In one alternative implementation, the cluster formation optimization apparatus may further include a storage unit for storing the program code and data of the cluster formation optimization apparatus.

[0142] In one example, the device for optimizing the cluster formation structure is a sensing device, or a chip applied to a sensing device. The acquisition unit 410 is used to acquire the current communication position of the sensing device and the current communication positions of multiple sensed devices. The processing unit 420 is used to determine the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of the multiple sensed devices, and the optimal communication distance. The target communication position is the position where the communication efficiency between the sensing device and any sensed device is highest, and the optimal communication distance is the distance at which the communication efficiency between the sensing device and any sensed device is highest. The processing unit 420 is also used to travel from the current communication position to the target communication position at the target travel speed.

[0143] In one possible implementation of this application, the processing unit 420 is also used to determine the maximum travel speed of the sensing device.

[0144] In one possible implementation of this application, the processing unit 420 is further configured to determine a first distance between the sensing device and the multiple sensing devices based on the current communication position of the sensing device and the current communication positions of the multiple sensing devices, determine the absolute value of the difference between the optimal communication distance and the multiple first distances respectively, determine a target coefficient by comparing the magnitude of the optimal communication distance and the multiple first distances based on the multiple absolute values ​​of the difference, the target coefficient is used to determine the target travel speed, and the target travel speed is determined based on the target coefficient and the maximum travel speed.

[0145] In one possible implementation of this application, the processing unit 420 is further configured to determine multiple angular directions of the sensing device relative to any one of the sensing devices based on the current communication position of the sensing device and the current communication positions of multiple sensing devices; determine multiple first communication positions of the sensing device relative to any one of the sensing devices based on the multiple angular directions, the optimal communication distance, and the current communication position of the sensing device, wherein the first communication position is the position with the highest communication efficiency between the sensing device and each sensing device; determine multiple second distances based on the multiple first communication positions and the current communication position of the sensing device, wherein the second distance is the extension distance between the current communication position and the first communication position; determine the second distance with the largest extension distance between the current communication position and the first communication position as the target extension distance; and determine the first communication position corresponding to the target extension distance as the target communication position.

[0146] In one possible implementation of this application, the processing unit 420 is further configured to determine whether there is an obstacle on the travel path between the current communication location of the sensing device and the target communication location, and if an obstacle is detected on the travel path, to redetermine the path for the sensing device to travel to the target communication location.

[0147] In one possible implementation of this application, the processing unit 420 is further configured to determine a third distance between the sensing device and the obstacle, and based on the third distance, adjust the sensing device to a second communication position with the obstacle as the center and in a set direction, wherein the set direction is either clockwise or counterclockwise, and there are no obstacles on the path of the sensing device traveling from the second communication position to the target communication position.

[0148] The processing unit 420 may be a processor or controller, such as a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, etc. The storage module may be a memory.

[0149] Optional, such as Figure 2 The structure of the sensing device 100 shown may further include a memory, which may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processor via a communication line. Alternatively, the memory may be integrated with the processor.

[0150] The memory stores computer execution instructions for implementing the scheme of this application, and the execution is controlled by the processor. The processor executes the computer execution instructions stored in the memory, thereby implementing the code writing method provided in the following embodiments of this application.

[0151] Optionally, the computer execution instructions in the embodiments of this application may also be referred to as application code, and the embodiments of this application do not specifically limit this.

[0152] On the one hand, a computer-readable storage medium is provided, in which instructions are stored, which, when executed, implement as follows: Figure 3 The functions performed by the sensing devices.

[0153] On the one hand, a computer program product including instructions is provided, wherein the computer program product includes instructions that, when executed, implement such... Figure 3 The functions performed by the sensing devices.

[0154] On one hand, embodiments of this application provide a chip used in a sensing device. The chip includes at least one processor and a communication interface, with the communication interface coupled to the at least one processor. The processor is used to execute instructions to achieve, for example... Figure 3 The functions performed by the sensing devices.

[0155] This application provides a cluster system with optimized cluster formation structure. The cluster system includes: a sensing device and multiple sensed devices. The cluster system is applied to a wireless mesh network. The sensing device and the sensed devices have a wireless communication connection. The sensing device is used to perform... Figure 3 Functions performed by sensing devices.

[0156] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid-state drive (SSD).

[0157] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, the disclosure, and the appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0158] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of this application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and modifications.

Claims

1. A method for optimizing cluster formation structure, characterized in that, include: Obtain the current communication location of the sensing device and the current communication location of multiple sensed devices; Based on the current communication position of the sensing device, the current communication positions of multiple sensing devices, and the optimal communication distance, the target travel speed and target communication position of the sensing device are determined. The optimal communication distance is the distance at which the communication efficiency between the sensing device and any of the sensing devices is the highest, and the target communication position is the position where the communication efficiency between the sensing device and any of the sensing devices is the highest. Travel from the current communication location to the target communication location at the target travel speed; Before determining the target travel speed of the sensing device based on the current communication location of the sensing device, the current communication locations of the multiple sensed devices, and the optimal communication distance, the method further includes: Determine the maximum travel speed of the sensing device; Determining the target travel speed of the sensing device based on its current communication location, the current communication locations of multiple sensed devices, and the optimal communication distance includes: Based on the current communication location of the sensing device and the current communication locations of the multiple sensed devices, a first distance is determined between the sensing device and the multiple sensed devices. Determine the absolute value of the difference between the optimal communication distance and each of the first distances; By comparing the optimal communication distance with a plurality of first distances, a target coefficient is determined based on the absolute values ​​of the plurality of differences, and the target coefficient is used to determine the target travel speed; The target speed is determined based on the target coefficient and the maximum speed.

2. The method according to claim 1, characterized in that, Determining the target communication location of the sensing device based on the current communication location of the sensing device, the current communication locations of multiple sensed devices, and the optimal communication distance includes: Based on the current communication position of the sensing device and the current communication positions of the multiple sensed devices, the sensing device is determined to have multiple angular directions relative to any one of the sensed devices. Based on the multiple angular directions, the optimal communication distance, and the current communication position of the sensing device, multiple first communication positions of the sensing device relative to any of the sensed devices are determined, and the first communication position is the position where the communication efficiency between the sensing device and each sensed device is the highest. Based on multiple first communication locations and the current communication location of the sensing device, multiple second distances are determined, wherein the second distance is the extended distance between the current communication location and the first communication location; The second distance, which has the largest extension distance between the current communication location and the first communication location, is determined as the target extension distance; The first communication location corresponding to the target extension distance is determined as the target communication location.

3. The method according to claim 1, characterized in that, Before traveling from the current communication location to the target communication location at the target travel speed, the method further includes: Determine whether there are obstacles on the travel path between the current communication location of the sensing device and the target communication location; If an obstacle is detected in the travel path, the path for the sensing device to travel to the target communication location is redefined.

4. The method according to claim 3, characterized in that, Redetermining the trajectory of the sensing device toward the target communication location includes: Determine a third distance between the sensing device and the obstacle; Based on the third distance, with the obstacle as the center, the sensing device is adjusted to the second communication position in a set direction, either clockwise or counterclockwise. There are no obstacles on the path the sensing device travels from the second communication position to the target communication position. Correspondingly... Traveling from the current communication location to the target communication location at the target travel speed includes: Travel from the second communication location to the target communication location at the target travel speed.

5. The method according to any one of claims 1-4, characterized in that, Any of the sensed devices can serve as the sensing device and / or the sensing device of the other sensed devices.

6. A device for optimizing cluster formation structure, characterized in that, include: The acquisition unit is used to acquire the current communication location of the sensing device and the current communication location of multiple sensed devices. The processing unit is configured to determine the target travel speed and target communication position of the sensing device based on the current communication position of the sensing device, the current communication positions of multiple sensing devices, and the optimal communication distance. The target communication position is the position where the communication efficiency between the sensing device and any of the sensing devices is the highest, and the optimal communication distance is the distance where the communication efficiency between the sensing device and any of the sensing devices is the highest. The processing unit is further configured to travel from the current communication location to the target communication location at the target travel speed; The processing unit is also used to determine the maximum travel speed of the sensing device; The processing unit is also used for: Based on the current communication location of the sensing device and the current communication locations of the multiple sensed devices, a first distance is determined between the sensing device and the multiple sensed devices. Determine the absolute value of the difference between the optimal communication distance and each of the first distances; By comparing the optimal communication distance with a plurality of first distances, a target coefficient is determined based on the absolute values ​​of the plurality of differences, and the target coefficient is used to determine the target travel speed; The target speed is determined based on the target coefficient and the maximum speed.

7. A cluster system with optimized cluster formation structure, characterized in that, include: The system comprises a sensing device and multiple sensing devices, wherein the cluster system is applied to a cluster system based on a wireless mesh network, and the sensing device is used to perform the cluster formation optimization method according to any one of claims 1 to 5.

8. A sensing device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the method as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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