Bacterial behavior-based cluster robot target search method and related device

Abstract

The invention discloses a bacterial behavior-based cluster robot target search method and a related device, and the method comprises the steps: sensing the current leakage concentration information through a cluster robot, including a concentration value and a position thereof; and if all the robots do not perceive the information, executing random search until the information is found. Once the robot senses the information, the current maximum concentration value and the position thereof are selected and compared with the concentration threshold value. If the current maximum concentration value reaches or exceeds the threshold value, the robot group moves to the position; and if the concentration value is lower than the threshold value, comparing the concentration value with the maximum concentration value at the previous moment. And according to the comparison result, the motion direction of the robot at the next moment is jointly determined by the group direction and the concentration gradient direction or is independently determined by the group direction. The invention aims to enhance the environment exploration capability by utilizing the cooperation of multiple robots, especially in the aspect of low-concentration information detection, so that the accuracy of environment information acquisition and the overall search efficiency are improved, and more efficient and accurate target search is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of swarm robot target search, and in particular relates to a swarm robot target search method based on bacterial behavior and related devices. Background Art

[0002] In recent years, the threat posed by hazardous chemical leakage has become increasingly severe. Especially when toxic, flammable, biochemical, radioactive and other hazardous substances leak, it will not only cause serious pollution to the air quality, but also may cause catastrophic consequences such as fire, explosion, poisoning, etc., seriously threatening personal safety and public health. Therefore, being able to quickly and accurately locate the source of indoor hazardous chemical leakage is of vital importance to curbing the spread of pollution, reducing personal injury and ensuring public safety.

[0003] Currently, existing robot systems mainly rely on a single robot to conduct independent searches or multiple robots to conduct collaborative searches in different areas when performing leak source search tasks. These methods show high efficiency when facing high-concentration areas or areas with concentrated concentrations. However, in sparse environments with lower concentrations, their search success rate drops significantly, limiting their application in complex environments. Summary of the invention

[0004] In response to the problems existing in the prior art, the present invention provides a swarm robot target search method and related devices based on bacterial behavior. Its purpose is to utilize the collaborative cooperation ability of a multi-robot group based on a group collaborative search mechanism, which can effectively enhance the environmental exploration capability and improve the detection efficiency of low-concentration information, thereby improving the accuracy of environmental information acquisition and the overall search efficiency.

[0005] In order to solve the above technical problems, the present invention is implemented by the following technical solutions:

[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 leakage concentration information at the current moment, wherein the leakage concentration information includes the concentration value and the location of the concentration value;

[0008] If all robots do not sense the leakage concentration information at the current moment, the cluster robots perform random search until at least one robot senses the leakage concentration information at the current moment;

[0009] If at least one robot senses the leakage concentration information at the current moment, the maximum concentration value at the current moment and the location of the maximum concentration value are selected from the leakage concentration information sensed at the current moment, and the maximum concentration value at the current moment is compared with the concentration threshold;

[0010] If the maximum concentration value at the current moment is not less than the concentration threshold, the movement direction of the cluster robot at the next moment is to move towards the location of the maximum concentration value;

[0011] If the current maximum concentration value is less than the concentration threshold, the current maximum concentration value is compared with the previous maximum concentration value;

[0012] 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 cluster robot at the next moment is determined by the group direction and the concentration gradient direction, where 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, the movement direction of the cluster robot at the next moment is determined by the group direction.

[0014] In a possible implementation manner of the first aspect, the swarm robot performs a random search, specifically:

[0015] The swarm robots perform random search using a modified Levy flight method.

[0016] In a possible implementation of the first aspect, the swarm robot performs random search using an improved Levy flight method, 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) is the movement direction of robot i in the cluster robot at the next moment; d i self (t+1) is the control force direction of robot i in the cluster robot based on group interaction at the next moment; d i ran(t+1) is the control force direction of robot i in the swarm robot based on Levy flight at the next moment; w align is the weight of speed coordination; w pos is the weight of position coordination; is the velocity synergy force; f i is the position synergistic force; v i is the current velocity vector of robot i in the swarm robot; v j is the current velocity vector of robot j in the swarm robot; N i is the neighbor set of robot i in the swarm robot; |N i | is the number of neighbors of robot i in the swarm robot; unit(·) represents the vector normalization function, defined as F ij is the force between robot i and robot j in the cluster robot; n ij is the unit direction vector of robot i pointing to robot j in the cluster robot; w rep is the repulsive force weight; w att is the attraction weight; d rep is the distance of action of the repulsive force in position coordination; d sen is the distance of attraction in positional synergy; d ij is the distance between robot i and robot j in the swarm robot; r ij is the relative position vector between robot i and robot j in the cluster robot; p i is the position vector of robot i in the cluster robot; p j is the position vector of robot j in the cluster robot; x i (t) is the current position of robot i in the swarm robot; α is the step length control parameter; S is the random step length parameter for generating Levy flight; u is the basic noise variable in Levy flight, which obeys the normal distribution u~N(0,σ 2 );v is the scale used to control the step size generation, which obeys the normal distribution u~N(0,1);σ is the standard deviation of Levy flight;Γ is the Gamma function;β is the long tail of the control step size;t is the current moment;t+1 is the next moment.

[0023] In a possible implementation of the first aspect, the movement direction of the swarm robot at the next moment is to move toward a position where the maximum concentration value is located, specifically:

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

[0025] Where, d i con (t+1) is the control force generated by robot i in the cluster robot based on the direction of the concentration gradient.

[0026] In a possible implementation of the first aspect, the movement direction of the swarm robot at the next moment is jointly determined by 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) is the weight that determines the direction of the group and the direction of the concentration gradient; η is the adjustment coefficient that controls the sensitivity of the concentration value to the weight change; c is the difference between the concentration value at the current moment and the concentration value at the previous moment.

[0030] In a possible implementation of the first aspect, the movement direction of the swarm robot 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] A perception module, used for each robot in the cluster robot to perceive the leakage concentration information at the current moment, wherein the leakage concentration information includes the concentration value and the location of the concentration value;

[0034] A random search module, used for, if all robots do not sense the leakage concentration information at the current moment, the cluster robots perform a random search until at least one robot senses the leakage concentration information at the current moment;

[0035] A first comparison module is used for selecting a maximum concentration value and a location of the maximum concentration value at the current moment from the leakage concentration information sensed at the current moment, and comparing the maximum concentration value at the current moment with a concentration threshold value if at least one robot senses leakage concentration information at the current moment;

[0036] The first movement direction determination module is used to determine that if the maximum concentration value at the current moment is not less than the concentration threshold, the movement direction of the cluster robot at the next moment is to move towards the location of the maximum concentration value;

[0037] A second comparison module is used to compare the maximum concentration value at the current moment with the maximum concentration value at the previous moment if the maximum concentration value at the current moment is less than the concentration threshold;

[0038] The second movement direction determination module is used for, 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 cluster robot at the next moment is determined by the group direction and the concentration gradient direction, and the concentration gradient direction is the direction vector from the position of the maximum concentration value at the previous moment to the position of the maximum concentration value at the current moment;

[0039] The third movement direction determination module is used to determine the movement direction of the cluster robot at 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, there is provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the bacterial behavior-based swarm robot target search method when executing the computer program.

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

[0042] According to a fifth aspect of the present invention, a computer program product is provided, which, when executed by a processor, implements the 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] The present invention provides a cluster robot target search method based on bacterial behavior. Through the collaborative cooperation of cluster robots, it is possible to more effectively explore complex environments, especially in sparse environments with low-concentration leaks. This collaborative search mechanism not only expands the search range, but also improves the meticulousness of the search, thereby ensuring that the information of the leak source can be accurately captured even under low-concentration conditions. The present invention uses the inspiration of bacterial behavior to enable the cluster robot to dynamically adjust the direction of movement according to the real-time perceived concentration information during the search process. This adaptive search strategy improves the detection efficiency of low-concentration information, allowing the robot to locate the leak source more quickly, thereby taking timely measures to curb the spread of pollution. By comparing the maximum concentration values ​​at the current moment and the previous moment, and combining the group direction and the concentration gradient direction to jointly determine the robot's movement path, the present invention can more accurately determine the location of the leak source. This comprehensive judgment mechanism reduces the possibility of misjudgment and missed judgment, and improves the reliability of search results.

[0045] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the specific implementation modes of the present invention, the drawings required for use in the description of the specific implementation modes will be briefly introduced below. Obviously, the drawings described below are some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 The present invention is a flowchart of a swarm robot target search method based on bacterial behavior according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, the embodiment of the present invention provides a swarm robot target search method based on bacterial behavior, which aims to improve the search efficiency and accuracy in complex environments, especially in low-concentration leakage environments, and specifically includes the following steps:

[0050] S1. Each robot in the cluster robot senses the leakage concentration information at the current moment, where the leakage concentration information includes the concentration value and the location of the concentration value.

[0051] Specifically, before the search mission begins, all cluster robots need to be initialized, including setting the initial position, configuring sensors (such as gas sensors) to sense the concentration of leaks, and setting initial motion parameters (such as speed, steering angle, etc.). In addition, each robot must be equipped with a wireless communication module to enable real-time sharing of perception data and collaborative decision-making. Each robot uses a gas sensor at its current position to collect real-time information on the concentration of leaks in the surrounding environment, including the specific concentration value and the geographical location corresponding to the concentration value.

[0052] S2. If all robots do not sense the leakage concentration information at the current moment, the cluster robots perform a random search until at least one robot senses the leakage concentration information at the current moment.

[0053] Specifically, when all robots in the cluster do not sense any leakage concentration information, it indicates that there is no concentration information in the current environment. At this time, the cluster robots will adopt a random search strategy to explore the unknown area by randomly changing the movement direction until at least one robot senses the leakage concentration information.

[0054] In one possible implementation, the cluster robot uses an improved Levy flight method to perform random search. The robot can use the improved Levy flight model to achieve random walk of the robot group in 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) is the movement direction of robot i in the cluster robot at the next moment; d i self(t+1) is the control force direction of robot i in the cluster robot based on group interaction at the next moment; d i ran (t+1) is the control force direction of robot i in the swarm robot based on Levy flight at the next moment; w align is the weight of speed coordination; w pos is the weight of position coordination; is the velocity synergistic force; f i is the position synergistic force; v i is the current velocity vector of robot i in the swarm robot; v j is the current velocity vector of robot j in the swarm robot; N i is the neighbor set of robot i in the swarm robot; |N i | is the number of neighbors of robot i in the swarm robot; unit(·) represents the vector normalization function, defined as F ij is the force between robot i and robot j in the cluster robot; n ij is the unit direction vector of robot i pointing to robot j in the cluster robot; w rep is the repulsive force weight; w att is the attraction weight; d rep is the distance of action of the repulsive force in position coordination; d sen is the distance of attraction in positional synergy; d ij is the distance between robot i and robot j in the swarm robot; r ij is the relative position vector between robot i and robot j in the cluster robot; p i is the position vector of robot i in the cluster robot; p j is the position vector of robot j in the cluster robot; x i (t) is the current position of robot i in the swarm robot; α is the step length control parameter; S is the random step length parameter for generating Levy flight; u is the basic noise variable in Levy flight, which obeys the normal distribution u~N(0,σ 2 );v is the scale used to control the step size generation, which obeys the normal distribution u~N(0,1);σ is the standard deviation of Levy flight;Γ is the Gamma function;β is the long tail of the control step size;t is the current moment;t+1 is the next moment.

[0061] In detail, Lévy flight is an effective robot target search strategy that can improve search efficiency and coverage, adapt to complex environments and uncertain information, and enhance group intelligence and collaboration capabilities. It takes advantage of the heavy-tailed characteristics of stable distributions, allowing robots to jump out of local areas with a higher probability and be more evenly distributed throughout the space. It does not require prior knowledge of the structure of the environment and the location of the target, nor does it require precise path planning and coordination, but only relies on the robot's own perception ability and random motion strategy. The improved Lévy flight can adjust the distance between robots and expand the search area for different search tasks to better meet the needs of specific tasks, making the completion of search tasks more efficient and accurate.

[0062] In detail, the advantages of Levy flight in robot search are mainly reflected in its ability to effectively simulate the non-uniform and random characteristics of species search behavior in nature. Through the combination of long-distance jumps and short-distance exploration, Levy flight can cover the search space more efficiently, avoid the local optimal dilemma in the search process, and enhance the adaptability and robustness of the robot in a dynamic environment. Especially in complex target search tasks, Levy flight enables robots to quickly respond to environmental changes and optimize collective collaboration without prior knowledge of the environmental structure and target location, thereby significantly improving the overall efficiency of group search. In addition, the improved Levy flight strategy enables robots to flexibly adjust the distance between robots according to the specific requirements of the task when performing search tasks, meeting different search task requirements. It can be seen that 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 leakage concentration information at the current moment, the maximum concentration value at the current moment and the location of the maximum concentration value are selected from the leakage concentration information sensed at the current moment, and the maximum concentration value at the current moment is compared with the concentration threshold.

[0064] Specifically, once a robot senses the concentration information of the leak, the cluster immediately enters the centralized search mode. First, the maximum concentration value and its location at the current moment are screened out from all the sensed concentration information. The current maximum concentration value is compared with the preset concentration threshold.

[0065] Exemplarily, 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, the movement direction of the cluster robot at the next moment is to move toward the location of the maximum concentration value.

[0067] Specifically, if the maximum concentration value within the current perception range reaches or exceeds the concentration threshold, indicating that it is close to the leakage source, the swarm robot will move directly toward the location of the maximum concentration value to locate the leakage source as soon as possible.

[0068] In one achievable manner, the movement direction of the cluster robot at the next moment is to move toward the location of the maximum concentration value, specifically:

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

[0070] Where, d i con (t+1) is the control force generated by robot i in the cluster 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, 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, the concentration change trend needs to be further analyzed.

[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 cluster 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 position of the maximum concentration value at the previous moment to the position 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 means that the robot is moving towards the leakage source. At this time, the movement direction of the cluster robot at the next moment is determined by two parts: one is based on the guidance of the concentration gradient (i.e. the direction vector from the maximum concentration point at the previous moment to the current maximum concentration point), and the other is the group coordination direction, which ensures that the robots maintain a certain formation and communication connection to avoid being dispersed too far.

[0075] In one possible implementation, the movement direction of the swarm robot at the next moment is determined by the group direction and the concentration gradient direction, 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 group direction and the concentration gradient direction, and determines the robot's dependence on group behavior and individual behavior; η is the adjustment coefficient that controls the sensitivity of concentration value and weight change; c is the difference between the concentration value at the current moment and the concentration value at the previous moment.

[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 cluster robot at the next moment is determined by the group direction.

[0080] Specifically, if the current maximum concentration value decreases compared to the previous moment, it means that the robot is not moving in the direction of high concentration. At this time, the cluster robot relies more on the group direction to move in order to find possible higher concentration areas while maintaining the integrity and coordination of the cluster.

[0081] Swarm robots can achieve efficient coordinated movement by sensing the relative position and movement speed of their neighbors. Specifically, the position coordination mechanism is to gather robots and effectively avoid collisions with each other, which is achieved by introducing two forces: repulsion and attraction. The role of repulsion is to prevent robots from getting too close to each other, thereby avoiding collisions. The attraction forces robots to gather together and enhance the cohesion of the group. In addition, during the movement process, the introduction of speed coordination ensures the consistency of the movement direction of robots within the group. By adjusting the weights of each of these coordination mechanisms, different group behavior characteristics can be demonstrated, allowing cluster robots to flexibly respond to various environmental changes and task requirements. In general, cluster robots rely on the coordination of position and speed to achieve effective coordinated movement and ensure the safety and consistency of movement within the group.

[0082] In one possible implementation, the movement direction of the swarm robot at the next moment is determined by the group direction, specifically:

[0083]

[0084] It should be noted that during the entire search process, the cluster robot needs to continuously and dynamically adjust its motion strategy according to the latest concentration information and group status, including adjusting the speed, steering angle, and whether to switch the search mode. In addition, by sharing data in real time through the wireless communication module, the search path can be further optimized, repeated searches can be reduced, and the overall search efficiency can be improved. When the cluster robot successfully locates the leak source (that is, it reaches or exceeds the preset concentration threshold and continues to be stable within a certain range), or reaches the preset search time limit and fails to find the leak source, the search task ends. At this point, the cluster robot will summarize the data during the search process, including the location of the leak source, the concentration distribution map, etc., and transmit it to the control center wirelessly for subsequent analysis.

[0085] The bacterial behavior-based swarm robot target search method proposed in the present invention can realize efficient and accurate leakage source positioning in complex and changeable indoor environments, especially under low-concentration leakage conditions.

[0086] It should be understood that swarm robots are composed of multiple homogeneous robots and adopt a distributed architecture. In swarm robots, each robot can make its own decisions. Swarm robots have the following characteristics:

[0087] (1) Simple structure

[0088] A swarm robot is composed of multiple homogeneous robots with simple structures and compact sizes, that is, the individual robots in the swarm robot have the same structure.

[0089] (2) Perception and local communication capabilities

[0090] The communication range between individual robots is limited. Individual robots can only communicate with other robots within a limited range to exchange target signal detection information and environmental information. The range of the sensors carried by individual robots to detect the environment is limited, and they can only detect target information within the sensor's range.

[0091] (3) Positioning capability

[0092] In indoor environments, cluster robots can exchange position information with each other through wireless communication, and can use their own sensors, positioning assistance systems or the known position data of other robots in the group to assist in positioning, thereby realizing local relative positioning function.

[0093] (4) Movement coordination ability

[0094] By controlling the speed and direction of the robots, obstacle avoidance between individual robots and position and speed coordination of cluster robots can be achieved.

[0095] In one embodiment, in layman's terms, (1) during the actual execution process, the surrounding environment can be sensed by ultrasonic sensors and the like to obtain the robot's position information. The robot is equipped with a sensing module that can detect the concentration information within the sensor's detection range. Each individual in the cluster robot can communicate and exchange the known information. (2) Target discovery phase: When the robot does not detect the concentration information, it performs a random search based on the principle of sensing the concentration information as quickly as possible. The robot is allowed to move randomly in the search area in an efficient manner until the concentration information is detected. (3) Target tracking phase: 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 changes in the detected concentration value, enhances the individual's retention of favorable directions and adaptability to unfavorable directions, and finally searches for the target. (4) Target confirmation phase: When the concentration value at the robot's location is greater than the set concentration threshold, it means that the robot has searched for the target.

[0096] The embodiment of the present invention provides a swarm robot target search device based on bacterial behavior, which specifically includes the following modules:

[0097] The perception module is used for each robot in the cluster robot to perceive the leakage concentration information at the current moment, and the leakage concentration information includes the concentration value and the location of the concentration value.

[0098] The random search module is used to, if all robots have not sensed the leakage concentration information at the current moment, cause the cluster robots to perform a random search until at least one robot senses the leakage concentration information at the current moment.

[0099] The first comparison module is used to select the maximum concentration value and the position 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 if at least one robot senses the leakage concentration information at the current moment.

[0100] The first movement direction determination module is used to determine that if the maximum concentration value at the current moment is not less than the concentration threshold, the movement direction of the cluster robot at the next moment is to move towards the position where the maximum concentration value is located.

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

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

[0103] The third movement direction determination module is used to determine the movement direction of the cluster robot at 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 contents of each step involved in the aforementioned embodiment of a cluster robot target search method based on bacterial behavior can be referred to the functional description of the functional module corresponding to a cluster robot target search device based on bacterial behavior in the embodiment of the present invention, and will not be repeated here. The division of modules in the embodiment of the present invention is schematic, which is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present invention can be integrated into a processor, or it can exist physically separately, or two or more modules can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0105] In another embodiment of the present invention, a computer device is provided, the computer device includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute 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 (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of a cluster robot target search method based on bacterial behavior.

[0106] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. 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-mentioned embodiment of a cluster robot target search method based on bacterial behavior.

[0107] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented 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] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0109] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0110] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0111] The present invention also provides a computer program product, which is used to execute any of the above-mentioned methods for searching a target by a swarm robot based on bacterial behavior. Since the computer program product provided by the present invention and the above-mentioned method for searching a target by a swarm robot based on bacterial behavior belong to the same inventive concept, the computer program product provided by the present invention has all the advantages of the above-mentioned method for searching a target by a swarm robot based on bacterial behavior, and therefore the beneficial effects of the computer program product provided by the present invention will not be described one by one here.

[0112] In the present invention, the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the described specific features, structures, materials or characteristics may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0113] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A swarm robot target search method based on bacterial behavior, characterized in that: include: Each robot in the swarm robot senses the leakage concentration information at the current moment, wherein the leakage concentration information includes the concentration value and the location of the concentration value; If all robots do not sense the leakage concentration information at the current moment, the cluster robots perform random search until at least one robot senses the leakage concentration information at the current moment; If at least one robot senses the leakage concentration information at the current moment, the maximum concentration value at the current moment and the location of the maximum concentration value are selected from the leakage concentration information sensed at the current moment, and the maximum concentration value at the current moment is compared with the concentration threshold; If the maximum concentration value at the current moment is not less than the concentration threshold, the movement direction of the cluster robot at the next moment is to move towards the location of the maximum concentration value; If the current maximum concentration value is less than the concentration threshold, the current maximum concentration value is compared with the previous maximum concentration value; 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 cluster robot at the next moment is determined by the group direction and the concentration gradient direction, where 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, the movement direction of the cluster robot at the next moment is determined by the group direction.

2. The target search method of a swarm robot based on bacterial behavior according to claim 1, characterized in that: The cluster robot performs random search, specifically: The swarm robots perform random search using a modified Levy flight method.

3. The target search method of a swarm robot based on bacterial behavior according to claim 2, characterized in that: The swarm robot performs random search using an improved Levy flight method, specifically: d ij ＝||r ij || r ij =p j -p i In the formula, u i (t+1) is the movement direction of robot i in the swarm robot at the next moment; is the control force direction of robot i in the swarm robot based on group interaction at the next moment; is the control force direction of robot i in the swarm robot based on Levy flight at the next moment; w align is the weight of speed coordination; w pos is the weight of position coordination; for the speed synergy force; f i is the position synergistic force; v i is the current velocity vector of robot i in the swarm robot; v j is the current velocity vector of robot j in the swarm robot; N i is the neighbor set of robot i in the swarm robot; |N i | is the number of neighbors of robot i in the swarm robot; unit(·) represents the vector normalization function, defined as F ij is the force between robot i and robot j in the cluster robot; n ij is the unit direction vector of robot i pointing to robot j in the cluster robot; w rep is the repulsive force weight; w att is the attraction weight; d rep is the distance of action of the repulsive force in position coordination; d sen is the distance of attraction in positional synergy; d ij is the distance between robot i and robot j in the swarm robot; r ij is the relative position vector between robot i and robot j in the cluster robot; p i is the position vector of robot i in the cluster robot; p j is the position vector of robot j in the cluster robot; x i (t) is the current position of robot i in the swarm robot; α is the step length control parameter; S is the random step length parameter for generating Levy flight; u is the basic noise variable in Levy flight, which obeys the normal distribution u~N(0,σ 2 );v is the scale used to control the step size generation, which obeys the normal distribution u~N(0,1);σ is the standard deviation of Levy flight;Γ is the Gamma function;β is the long tail of the control step size;t is the current moment;t+1 is the next moment.

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

5. The target search method of a swarm robot based on bacterial behavior according to claim 4, characterized in that: The movement direction of the cluster robot at the next moment is determined by the group direction and the concentration gradient direction, specifically: In the formula, w i (c) is the weight that determines the direction of the group and the direction of the concentration gradient; η is the adjustment coefficient that controls the sensitivity of the concentration value to the weight change; c is the difference between the concentration value at the current moment and the concentration value at the previous moment.

6. The target search method of a swarm robot based on bacterial behavior according to claim 3, characterized in that: The movement direction of the cluster robot at the next moment is determined by the group direction, specifically:

7. A swarm robot target search device based on bacterial behavior, characterized in that: include: A perception module, used for each robot in the cluster robot to perceive the leakage concentration information at the current moment, wherein the leakage concentration information includes the concentration value and the location of the concentration value; A random search module, used for, if all robots do not sense the leakage concentration information at the current moment, the cluster robots perform a random search until at least one robot senses the leakage concentration information at the current moment; A first comparison module is used for selecting a maximum concentration value and a location of the maximum concentration value at the current moment from the leakage concentration information sensed at the current moment, and comparing the maximum concentration value at the current moment with a concentration threshold value if at least one robot senses leakage concentration information at the current moment; The first movement direction determination module is used to determine that if the maximum concentration value at the current moment is not less than the concentration threshold, the movement direction of the cluster robot at the next moment is to move towards the location of the maximum concentration value; A second comparison module is used to compare the maximum concentration value at the current moment with the maximum concentration value at the previous moment if the maximum concentration value at the current moment is less than the concentration threshold; The second movement direction determination module is used for, 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 cluster robot at the next moment is determined by the group direction and the concentration gradient direction, and the concentration gradient direction is the direction vector from the position of the maximum concentration value at the previous moment to the position of the maximum concentration value at the current moment; The third movement direction determination module is used to determine the movement direction of the cluster robot at 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, the method for target searching of a swarm robot based on bacterial behavior as described in any one of claims 1 to 6 is implemented.

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

10. A computer program product, characterized in that When the computer program product is executed by a processor, it 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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