A swarm robot target search method and related device based on bacterial behavior

Abstract

This invention discloses a swarm robot target search method and related apparatus based on bacterial behavior. The method involves swarm robots sensing the current concentration information of a leaked substance, including its concentration value and location. If none of the robots sense the information, a random search is performed until a target is found. Once a robot senses the information, it selects the current maximum concentration value and its location, and compares it with a concentration threshold. If the current maximum concentration value reaches or exceeds the threshold, the swarm of robots moves towards that location; if it is below the threshold, it compares it with the maximum concentration value from the previous moment. Based on the comparison result, the robot's next movement direction is determined by both the swarm direction and the concentration gradient direction, or solely by the swarm direction. The purpose of this invention is to enhance environmental exploration capabilities, particularly in the detection of low-concentration information, by utilizing multi-robot collaboration, thereby improving the accuracy of environmental information acquisition and overall search efficiency, and achieving more efficient and accurate target search.

Description

Technical Field

[0001] This invention belongs to the field of target search technology for swarm robots, specifically relating to a target search method and related apparatus for swarm robots based on bacterial behavior. Background Technology

[0002] In recent years, the threat posed by hazardous chemical leaks has become increasingly severe. Especially when toxic, flammable, biochemical, or radioactive substances leak, they not only cause serious air pollution but can also trigger catastrophic consequences such as fires, explosions, and poisoning, seriously threatening personal safety and public health. Therefore, the ability to quickly and accurately locate indoor hazardous chemical leak sources is crucial for containing the spread of pollution, reducing personal injury, and ensuring public safety.

[0003] Currently, existing robotic systems primarily rely on a single robot to search independently or multiple robots to search collaboratively in different areas when performing leak source searches. These methods demonstrate high efficiency when facing areas with high or concentrated concentrations. However, their search success rate drops significantly in sparse environments with low concentrations, limiting their application in complex environments. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a cluster robot target search method and related device based on bacterial behavior. Its purpose is to enhance environmental exploration capabilities and improve the detection efficiency of low-concentration information by utilizing the collaborative cooperation ability of multiple robot groups based on a group collaborative search mechanism, thereby improving the accuracy of environmental information acquisition and overall search efficiency.

[0005] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0006] According to a first aspect of the present invention, a swarm robot target search method based on bacterial behavior is provided, comprising:

[0007] Each robot in the swarm robot senses the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value;

[0008] If none of the robots detect the concentration of the leaked substance at the current moment, the cluster of robots will perform a random search until at least one robot detects the concentration of the leaked substance at the current moment.

[0009] If at least one robot senses the concentration information of the leaked substance at the current moment, then select the maximum concentration value and the location of the maximum concentration value at the current moment from the leaked substance concentration information sensed at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold.

[0010] If the maximum concentration value at the current moment is not less than the concentration threshold, then the swarm robot will move towards the location of the maximum concentration value in the next moment.

[0011] If the maximum concentration value at the current moment is less than the concentration threshold, then the maximum concentration value at the current moment is compared with the maximum concentration value at the previous moment.

[0012] If the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment, then the movement direction of the swarm robot at the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment.

[0013] If the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment, then the movement direction of the swarm robots at the next moment will be determined by the group's direction.

[0014] In one possible implementation of the first aspect, the cluster robots perform a random search, specifically:

[0015] The swarm robots use an improved Levy flight method to perform random searches.

[0016] In one possible implementation of the first aspect, the swarm robot performs a random search using a modified Levy flight pattern, specifically:

[0017] u i (t+1)=d i self (t+1)+d i ran (t+1)

[0018]

[0019] d ij =||r ij ||

[0020] r ij =p j -p i

[0021]

[0022] In the formula, u i (t+1) represents the direction of motion of robot i in the swarm robot at the next moment; d i self (t+1) represents the direction of the control force of robot i in the swarm robot at the next moment based on group interaction; d i ran(t+1) represents the direction of the control force of robot i in the swarm robot at the next moment based on Levi's flight; w align Weights for speed coordination; w pos Weights for location coordination; For velocity-coordinated force; f i For positional coordination force; v i v is the current velocity vector of robot i in the swarm of robots; j N is the current velocity vector of robot j in the swarm of robots; i It is the set of neighbors of robot i in the swarm robot; |N i | represents the number of neighbors of robot i in the swarm robot; unit(·) denotes the vector normalization function, defined as F ij n represents the interaction force between robot i and robot j in a swarm of robots. ij w is the unit direction vector pointing from robot i to robot j in a swarm of robots; rep For the repulsive force weight; w att For attractiveness weight; d rep d represents the effective distance of the repulsive force in positional coordination. sen d represents the effective distance of attraction in location coordination. ij r is the distance between robot i and robot j in a swarm of robots; ij p represents the relative position vector between robot i and robot j in a swarm of robots; i p is the position vector of robot i in the swarm of robots; j Let x be the position vector of robot j in the swarm of robots; i (t) represents the current position of robot i in the swarm; α is the step size control parameter; S is the random step size parameter generated according to the Lévy flight; u is the basic noise variable in the Lévy flight, which follows a normal distribution u~N(0,σ) 2 v is the scale used to control the generation of the step size, which follows a normal distribution u ~ N(0,1); σ is the standard deviation of the Lévy flight; Γ is the Gamma function; β is the long-tailed property of the control step size; t is the current time; t+1 is the next time.

[0023] In one possible implementation of the first aspect, the swarm robot's next movement direction is towards the location of the maximum concentration value, specifically:

[0024] u i (t+1)=d i self (t+1)+d i con (t+1)

[0025] In the formula, d i con (t+1) represents the control force generated by robot i in the swarm robot based on the direction of the concentration gradient.

[0026] In one possible implementation of the first aspect, the direction of motion of the swarm robot at the next moment is determined by both the group direction and the concentration gradient direction, specifically:

[0027] u i (t+1)=d i self (t+1)+(1-w i (c))·d i con (t+1)

[0028]

[0029] In the formula, w i (c) represents the weights that determine the population orientation and concentration gradient orientation; η is the adjustment coefficient that controls the sensitivity of the concentration value and weight changes; and c is the difference between the concentration value at the current time and the concentration value at the previous time.

[0030] In one possible implementation of the first aspect, the direction of motion of the swarm robots at the next moment is determined by the group direction, specifically:

[0031]

[0032] According to a second aspect of the present invention, a swarm robot target search device based on bacterial behavior is provided, comprising:

[0033] The sensing module is used by each robot in the swarm to sense the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value.

[0034] The random search module is used to perform a random search on the cluster robots if none of the robots have detected the concentration information of the leaked substance at the current moment, until at least one robot has detected the concentration information of the leaked substance at the current moment.

[0035] The first comparison module is used to select the maximum concentration value and the location of the maximum concentration value from the leakage concentration information sensed at the current moment if at least one robot senses the leakage concentration information at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold.

[0036] The first motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the concentration threshold.

[0037] The second comparison module is used to compare the current maximum concentration value with the previous maximum concentration value if the current maximum concentration value is less than the concentration threshold.

[0038] The second motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment. The motion direction of the cluster robot in the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment.

[0039] The third motion direction determination module is used to determine the motion direction of the swarm robots in the next moment by the group direction if the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment.

[0040] According to a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned method for searching a cluster robot target based on bacterial behavior.

[0041] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned method for swarm robot target search based on bacterial behavior.

[0042] According to a fifth aspect of the present invention, a computer program product is provided that, when executed by a processor, implements the aforementioned bacterial behavior-based swarm robot target search method.

[0043] Compared with the prior art, the present invention has at least the following beneficial effects:

[0044] This invention provides a target search method for swarm robots based on bacterial behavior. Through the collaborative cooperation of swarm robots, complex environments can be explored more effectively, especially in sparse environments with low concentrations of leaked materials. This collaborative search mechanism not only expands the search range but also improves the granularity of the search, thus ensuring accurate capture of leak source information even under low concentration conditions. Inspired by bacterial behavior, this invention enables swarm robots to dynamically adjust their movement direction based on real-time perceived concentration information during the search process. This adaptive search strategy improves the detection efficiency of low-concentration information, allowing robots to locate the leak source more quickly and take timely measures to curb the spread of pollution. By comparing the maximum concentration values ​​at the current and previous moments, and combining the swarm direction and concentration gradient direction to jointly determine the robot's movement path, this invention can more accurately determine the location of the leak source. This comprehensive judgment mechanism reduces the possibility of false positives and false negatives, improving the reliability of search results.

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the specific embodiments of the present invention, the drawings used in the description of the specific embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating a target search method for swarm robots based on bacterial behavior, as described in an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, this invention provides a target search method for swarm robots based on bacterial behavior, aiming to improve search efficiency and accuracy in complex environments, especially in environments with low concentrations of leaked materials. The method specifically includes the following steps:

[0050] S1. Each robot in the swarm of robots senses the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value.

[0051] Specifically, before the search mission begins, all swarm robots need to undergo initial setup, including setting their initial positions, configuring sensors (such as gas sensors) to detect the concentration of the leaked substance, and setting initial motion parameters (such as speed and turning angle). In addition, each robot needs to be equipped with a wireless communication module to share sensing data and make collaborative decisions in real time. Each robot, at its current location, uses gas sensors to collect real-time information on the concentration of the leaked substance in its surrounding environment, including the specific concentration value and the corresponding geographical location.

[0052] S2. If none of the robots have detected the concentration of the leaked substance at the current moment, the cluster of robots will perform a random search until at least one robot has detected the concentration of the leaked substance at the current moment.

[0053] Specifically, when none of the robots in the swarm detects any concentration information of the leaked substance, it indicates that there is no concentration information in the current environment. At this point, the swarm robots will adopt a random search strategy, exploring the unknown area by randomly changing their movement direction until at least one robot detects the concentration information of the leaked substance.

[0054] In one feasible approach, the swarm of robots performs random searches using a modified Lévy flight model. The robots can use this modified Lévy flight model to achieve random walks within the swarm during the random search phase, as follows:

[0055] u i (t+1)=d i self (t+1)+d i ran (t+1)

[0056]

[0057] d ij =||r ij ||

[0058] r ij =p j -p i

[0059]

[0060] In the formula, u i (t+1) represents the direction of motion of robot i in the swarm robot at the next moment; d i self(t+1) represents the direction of the control force of robot i in the swarm robot at the next moment based on group interaction; d i ran (t+1) represents the direction of the control force of robot i in the swarm robot at the next moment based on Levi's flight; w align Weights for speed coordination; w pos Weights for location coordination; For velocity-coordinated force; f i For positional coordination force; v i v is the current velocity vector of robot i in the swarm of robots; j N is the current velocity vector of robot j in the swarm of robots; i It is the set of neighbors of robot i in the swarm robot; |N i | represents the number of neighbors of robot i in the swarm robot; unit(·) denotes the vector normalization function, defined as F ij n represents the interaction force between robot i and robot j in a swarm of robots. ij w is the unit direction vector pointing from robot i to robot j in a swarm of robots; rep For the repulsive force weight; w att For attractiveness weight; d rep d represents the effective distance of the repulsive force in positional coordination. sen d represents the effective distance of attraction in location coordination. ij r is the distance between robot i and robot j in a swarm of robots; ij p represents the relative position vector between robot i and robot j in a swarm of robots; i p is the position vector of robot i in the swarm of robots; j Let x be the position vector of robot j in the swarm of robots; i (t) represents the current position of robot i in the swarm; α is the step size control parameter; S is the random step size parameter generated according to the Lévy flight; u is the basic noise variable in the Lévy flight, which follows a normal distribution u~N(0,σ) 2 v is the scale used to control the generation of the step size, which follows a normal distribution u ~ N(0,1); σ is the standard deviation of the Lévy flight; Γ is the Gamma function; β is the long-tailed property of the control step size; t is the current time; t+1 is the next time.

[0061] In detail, Lévy flight is an effective robot target search strategy that improves search efficiency and coverage, adapts to complex environments and uncertain information, and enhances swarm intelligence and collaborative capabilities. It utilizes the heavy-tailed characteristic of a stable distribution, enabling robots to escape localized areas with a higher probability and distribute themselves more evenly throughout space. It does not require prior knowledge of the environment's structure or the target's location, nor does it require precise path planning and coordination; it relies solely on the robot's own perception capabilities and stochastic motion strategies. Improved Lévy flight can adjust the distance between robots to expand the search area for different search tasks, better meeting the needs of specific tasks and making the search more efficient and accurate.

[0062] In detail, the advantages of Levy flight in robot search primarily lie in its ability to effectively simulate the non-uniform and random characteristics of species search behavior in nature. By combining long-distance jumps with short-distance exploration, Levy flight can more efficiently cover the search space, avoid local optima traps during the search process, and enhance the robot's adaptability and robustness in dynamic environments. Especially in complex target search tasks, Levy flight enables robots to quickly respond to environmental changes and optimize collective collaboration even without prior knowledge of the environmental structure and target location, thus significantly improving the overall efficiency of group search. Furthermore, the improved Levy flight strategy allows robots to flexibly adjust the distance between them according to the specific needs of the task, meeting different search requirements. Therefore, Levy flight, as a highly adaptable and efficient search strategy, can effectively perform search tasks in unknown environments.

[0063] S3. If at least one robot senses the concentration information of the leaked substance at the current moment, then select the maximum concentration value and the location of the maximum concentration value at the current moment from the leakage concentration information sensed at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold.

[0064] Specifically, once a robot detects information about the concentration of the leaked substance, the cluster immediately enters a centralized search mode. First, it filters out the maximum concentration value and its location from all detected concentration information. Then, it compares the current maximum concentration value with a preset concentration threshold.

[0065] For example, the concentration threshold is 0.9 to 0.95 of the maximum concentration.

[0066] S4. If the maximum concentration value at the current moment is not less than the concentration threshold, then the movement direction of the cluster robot at the next moment will be to move towards the location of the maximum concentration value.

[0067] Specifically, if the maximum concentration value within the current sensing range reaches or exceeds the concentration threshold, it indicates that the leak source is approaching. The swarm robot will move directly toward the location of the maximum concentration value in order to locate the leak source as soon as possible.

[0068] In one possible implementation, the swarm robot's next movement direction is towards the location of the maximum concentration value, specifically:

[0069] u i (t+1)=d i self (t+1)+d i con (t+1)

[0070] In the formula, d i con (t+1) represents the control force generated by robot i in the swarm robot based on the direction of the concentration gradient.

[0071] S5. If the maximum concentration value at the current moment is less than the concentration threshold, then the maximum concentration value at the current moment is compared with the maximum concentration value at the previous moment.

[0072] Specifically, if the current maximum concentration value is lower than the concentration threshold, further analysis of the concentration change trend is required.

[0073] S6. If the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment, the movement direction of the swarm robot at the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment.

[0074] Specifically, if the current maximum concentration value increases or remains unchanged compared to the previous moment, it indicates that the robot is moving towards the leak source. At this time, the next movement direction of the swarm robots is determined by two parts: one is the guidance based on the concentration gradient (i.e., the direction vector from the previous maximum concentration point to the current maximum concentration point), and the other is the group coordination direction, ensuring that the robots maintain a certain formation and communication connection, and avoid being too far apart.

[0075] In one possible implementation, the motion direction of the swarm robot at the next moment is determined by both the group orientation and the concentration gradient orientation, specifically:

[0076] u i (t+1)=d i self (t+1)+(1-w i (c))·d i con (t+1)

[0077]

[0078] In the formula, w i (c) is the weight that determines the direction of the group and the direction of the concentration gradient, and determines the degree of dependence of the robot on the group behavior and individual behavior; η is the adjustment coefficient that controls the sensitivity of the concentration value and weight changes; c is the difference between the concentration value at the current time and the concentration value at the previous time.

[0079] S7. If the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment, the movement direction of the swarm robot at the next moment will be determined by the group direction.

[0080] Specifically, if the current maximum concentration value has decreased compared to the previous moment, it means that the robot has not moved towards the direction of higher concentration. At this time, the swarm robots rely more on the group direction to move in order to find potentially higher concentration areas, while maintaining the integrity and coordination of the swarm.

[0081] Swarm robots can achieve efficient cooperative movement by sensing the relative positions and speeds of their neighbors. Specifically, the positional cooperation mechanism involves grouping robots together and effectively avoiding collisions, achieved by introducing both repulsive and attractive forces. Repulsive forces prevent robots from getting too close, thus avoiding collisions. Attractive forces encourage robots to huddle together, enhancing group cohesion. Furthermore, speed cooperation ensures consistency in the direction of movement among robots within the group. By adjusting the weights of these cooperative mechanisms, different group behavioral characteristics can be exhibited, allowing swarm robots to flexibly respond to various environmental changes and task requirements. In summary, swarm robots rely on positional and speed cooperation to achieve effective coordinated movement, ensuring both safety and consistency within the group.

[0082] In one possible implementation, the direction of motion of the swarm robots in the next moment is determined by the group orientation, specifically:

[0083]

[0084] It should be noted that throughout the search process, the swarm robots need to continuously and dynamically adjust their movement strategies based on the latest concentration information and group status, including adjusting speed, turning angle, and whether to switch search modes. Furthermore, real-time data sharing via wireless communication modules can further optimize the search path, reduce redundant searches, and improve overall search efficiency. The search task ends when the swarm robots successfully locate the leak source (i.e., the concentration reaches or exceeds the preset threshold and remains stable within a certain range), or when the preset search time limit is reached without finding the leak source. At this point, the swarm robots will summarize the data from the search process, including the leak source location and concentration distribution map, and transmit it wirelessly to the control center for subsequent analysis.

[0085] The bacterial behavior-based swarm robot target search method proposed in this invention can achieve efficient and accurate leakage source location in complex and variable indoor environments, especially under low concentration leakage conditions.

[0086] It should be understood that swarm robots consist of multiple homogeneous robots and employ a distributed architecture. Within a swarm robot system, each robot can autonomously decide its own behavior. Swarm robots possess the following characteristics:

[0087] (1) Simple structure

[0088] A swarm robot consists of multiple isomorphic robots with simple structures and small sizes, meaning that the individual robots in a swarm robot have the same structure.

[0089] (2) Sensing and local communication capabilities

[0090] Communication between individual robots is limited; an individual robot can only communicate with other robots within a limited range, exchanging target signal detection information and environmental information. The sensors carried by an individual robot have a limited range of environmental detection capabilities, only detecting target information within the sensor's effective range.

[0091] (3) Positioning capability

[0092] In indoor environments, swarm robots can exchange location information with each other via wireless communication. They can use their own sensors, positioning assistance systems, or known location data from other robots in the group to assist in local relative positioning.

[0093] (4) Motor coordination ability

[0094] By controlling the speed and direction of the robots, obstacle avoidance between individual robots and positional and speed coordination among robot swarms can be achieved.

[0095] In one embodiment, simply put, (1) during actual execution, the robot's position information can be obtained by sensing the surrounding environment through ultrasonic sensors, etc. The robot is equipped with a sensing module that can detect the concentration information within the sensor's detection range. Each individual in the swarm robot can communicate and exchange known information. (2) Target discovery stage: When the robot does not detect the concentration information, it performs a random search based on the principle of detecting the concentration information as quickly as possible. The robot moves randomly in an efficient manner in the search area until the concentration information is detected. (3) Target tracking stage: When the robot detects the concentration information, the robot dynamically adjusts the interaction weight according to the local environmental conditions, adjusts the group influence according to the detected concentration value changes, enhances the individual's maintenance of favorable directions and adaptability to unfavorable directions, and finally finds the target. (4) Target confirmation stage: When the concentration value at the location of the robot is greater than the set concentration threshold, it means that the robot has found the target.

[0096] This invention provides a target search device for swarm robots based on bacterial behavior, specifically comprising the following modules:

[0097] The sensing module is used by each robot in the swarm to sense the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value.

[0098] The random search module is used to perform a random search if none of the robots have detected the concentration of the leaked substance at the current moment, until at least one robot has detected the concentration of the leaked substance at the current moment.

[0099] The first comparison module is used to select the maximum concentration value and the location of the maximum concentration value from the leakage concentration information sensed at the current moment if at least one robot senses the leakage concentration information at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold.

[0100] The first motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the concentration threshold.

[0101] The second comparison module is used to compare the current maximum concentration value with the previous maximum concentration value if the current maximum concentration value is less than the concentration threshold.

[0102] The second motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment. The motion direction of the cluster robot in the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment.

[0103] The third motion direction determination module is used to determine the motion direction of the swarm robots in the next moment by the group direction if the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment.

[0104] All relevant content regarding the steps involved in the aforementioned embodiment of a bacterial behavior-based swarm robot target search method can be referenced from the functional description of the corresponding functional module of the bacterial behavior-based swarm robot target search device in this embodiment of the invention, and will not be repeated here. The module division in this embodiment of the invention is illustrative and merely a logical functional division; in actual implementation, there may be other division methods. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or have two or more modules integrated into one module. The integrated modules can be implemented in hardware or as software functional modules.

[0105] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a target search method for swarm robots based on bacterial behavior.

[0106] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the above embodiment regarding a swarm robot target search method based on bacterial behavior.

[0107] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0111] This invention also provides a computer program product for executing any of the aforementioned bacterial behavior-based target search methods for swarm robots. Since the computer program product provided by this invention belongs to the same inventive concept as the bacterial behavior-based target search method for swarm robots described above, it possesses all the advantages of the bacterial behavior-based target search method for swarm robots described above. Therefore, the beneficial effects of the computer program product provided by this invention will not be elaborated upon here.

[0112] In this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0113] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A target search method for swarm robots based on bacterial behavior, characterized in that, include: Each robot in the swarm robot senses the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value; If none of the robots detect the concentration of the leaked substance at the current moment, the cluster of robots will perform a random search until at least one robot detects the concentration of the leaked substance at the current moment. If at least one robot senses the concentration information of the leaked substance at the current moment, then select the maximum concentration value and the location of the maximum concentration value at the current moment from the leaked substance concentration information sensed at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold. If the maximum concentration value at the current moment is not less than the concentration threshold, then the swarm robot will move towards the location of the maximum concentration value in the next moment. If the maximum concentration value at the current moment is less than the concentration threshold, then the maximum concentration value at the current moment is compared with the maximum concentration value at the previous moment. If the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment, then the movement direction of the swarm robot at the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment. If the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment, then the movement direction of the swarm robots at the next moment will be determined by the group's direction.

2. The target search method for swarm robots based on bacterial behavior according to claim 1, characterized in that, The cluster robots perform random searches, specifically: The swarm robots use an improved Levy flight method to perform random searches.

3. The target search method for swarm robots based on bacterial behavior according to claim 2, characterized in that, The swarm robots employ an improved Levi flight method to perform random searches, specifically: d ij ＝||r ij || r ij =p j -p i In the formula, u i (t+1) represents the direction of motion of robot i in the swarm robot at the next moment; Let i be the direction of the control force of robot i in the swarm robot at the next moment based on the group interaction; Let w be the direction of the control force of robot i in the swarm robot at the next moment based on Levy's flight. align Weights for speed coordination; w pos Weights for location coordination; For velocity-coordinated force; f i For positional coordination force; v i v is the current velocity vector of robot i in the swarm of robots; j N is the current velocity vector of robot j in the swarm of robots; i It is the set of neighbors of robot i in the swarm robot; |N i | represents the number of neighbors of robot i in the swarm robot; unit(·) denotes the vector normalization function, defined as F ij n represents the interaction force between robot i and robot j in a swarm of robots. ij w is the unit direction vector pointing from robot i to robot j in a swarm of robots; rep For the repulsive force weight; w att For attractiveness weight; d rep d represents the effective distance of the repulsive force in positional coordination. sen d represents the effective distance of attraction in location coordination. ij r is the distance between robot i and robot j in a swarm of robots; ij p represents the relative position vector between robot i and robot j in a swarm of robots; i p is the position vector of robot i in the swarm of robots; j Let x be the position vector of robot j in the swarm of robots; i (t) represents the current position of robot i in the swarm; α is the step size control parameter; S is the random step size parameter generated according to the Lévy flight; u is the basic noise variable in the Lévy flight, which follows a normal distribution u~N(0,σ) 2 v is the scale used to control the generation of the step size, which follows a normal distribution u ~ N(0,1); σ is the standard deviation of the Lévy flight; Γ is the Gamma function; β is the long-tailed property of the control step size; t is the current time; t+1 is the next time.

4. The target search method for swarm robots based on bacterial behavior according to claim 3, characterized in that, The next movement direction of the swarm robot is towards the location of the maximum concentration value, specifically: In the formula, The control force generated by robot i in the swarm robot based on the direction of the concentration gradient.

5. The target search method for swarm robots based on bacterial behavior according to claim 4, characterized in that, The direction of motion of the swarm robot in the next moment is determined by both the group direction and the concentration gradient direction, specifically: In the formula, w i (c) represents the weights that determine the population orientation and concentration gradient orientation; η is the adjustment coefficient that controls the sensitivity of the concentration value and weight changes; and c is the difference between the concentration value at the current time and the concentration value at the previous time.

6. The target search method for swarm robots based on bacterial behavior according to claim 3, characterized in that, The direction of motion of the swarm robots in the next moment is determined by the group's direction, specifically:

7. A swarm robot target search device based on bacterial behavior, characterized in that, include: The sensing module is used by each robot in the swarm to sense the current concentration information of the leaked substance, which includes the concentration value and the location of the concentration value. The random search module is used to perform a random search on the cluster robots if none of the robots have detected the concentration information of the leaked substance at the current moment, until at least one robot has detected the concentration information of the leaked substance at the current moment. The first comparison module is used to select the maximum concentration value and the location of the maximum concentration value from the leakage concentration information sensed at the current moment if at least one robot senses the leakage concentration information at the current moment, and compare the maximum concentration value at the current moment with the concentration threshold. The first motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the concentration threshold. The second comparison module is used to compare the current maximum concentration value with the previous maximum concentration value if the current maximum concentration value is less than the concentration threshold. The second motion direction determination module is used to determine the motion direction of the cluster robot in the next moment if the maximum concentration value at the current moment is not less than the maximum concentration value at the previous moment. The motion direction of the cluster robot in the next moment is determined by the group direction and the concentration gradient direction. The concentration gradient direction is the direction vector from the location of the maximum concentration value at the previous moment to the location of the maximum concentration value at the current moment. The third motion direction determination module is used to determine the motion direction of the swarm robots in the next moment by the group direction if the maximum concentration value at the current moment is less than the maximum concentration value at the previous moment.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a cluster robot target search method based on bacterial behavior as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a swarm robot target search method based on bacterial behavior as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, When executed by a processor, the computer program product implements a swarm robot target search method based on bacterial behavior as described in any one of claims 1 to 6.

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