Simplified self-organizing diffusion method and system for perception-limited swarm robots

Abstract

The application is a kind of self-organizing diffusion method and system for perception-limited cluster robots, belonging to the field of robot technology. The method steps are as follows: installing each single computer perception module; starting diffusion instruction, triggering the motion execution module according to the signal sent by the perception module on the control center of the single computer; the motion execution module performs motion according to the simplified self-organizing diffusion model P=(v o ,ω o ,v l ,L) until there is no perception target within the perception distance of all robots in the cluster, i.e. the diffusion is completed. The application solves the self-organizing diffusion problem of cluster robots in complex environments such as water, which cannot communicate, has no global positioning ability, has very low perception ability, and has very low robot computing power. Whether there is a perception target in the range is used as the diffusion execution condition, which simplifies communication and control equipment, shortens response time, and ensures uniform coverage in the target area and the timeliness of diffusion.

Description

Technical Field

[0001] This invention belongs to the field of robotics technology, specifically relating to a simplified self-organizing diffusion method and system for perception-limited swarm robots. Background Technology

[0002] Robotics is a high-tech field that integrates multiple disciplines such as computer science, cybernetics, mechanics, information and sensing technology, artificial intelligence, and bionics. In particular, multi-robot collaboration has become an effective way to improve the efficiency of solving complex tasks. Traditional centralized control methods plan the behavior of all robots uniformly. However, when the scale of collaborative robots is large, the fault tolerance of centralized control methods is insufficient, making it difficult to respond promptly to unexpected factors. The rapid development of swarm robot research has provided a feasible solution to these difficulties.

[0003] In the research of swarm robots, some basic behaviors of swarm robots, such as aggregation, diffusion, and obstacle avoidance, are fundamental research problems in the control of swarm robot systems. Studying some basic swarm behavior algorithms of robot swarms is a prerequisite or foundational work for the application of swarm robot systems. Furthermore, in the application of swarm robot systems, the diffusion behavior of the robot swarm is often a prerequisite or important foundational work for completing other tasks. For example, when a group of robots is airdropped into an unfamiliar area to perform reconnaissance or information gathering tasks, diffusion is necessary at the beginning. Therefore, in swarm robot systems, studying how to facilitate the diffusion of swarm robots is essential.

[0004] Underwater wireless communication is extremely difficult, primarily because commonly used communication frequencies fall within the absorption range of water molecules. Water is a polar molecule, with its positive and negative charge centers not coinciding, allowing it to change direction under the influence of an electric field in electromagnetic waves. When the frequency of an electromagnetic wave approaches the inherent vibrational frequencies of water molecules, the water molecules absorb most of the energy from the electromagnetic wave, converting it into their own vibrations. Since the frequencies of commonly used communication electromagnetic waves are almost entirely within the absorption range of water molecules, electromagnetic waves attenuate very rapidly in water. Furthermore, underwater noise, multipath effects, and the complexity of the underwater environment also negatively impact the reliability of underwater wireless communication. Therefore, solving the problem of underwater communication has always been a significant challenge for fields such as ocean exploration and marine resource development. Consequently, due to the severe limitations of underwater communication, the self-organizing control methods for swarm robots used on land and in the air cannot be perfectly applied to complex underwater environments, significantly increasing the cost and complexity of the control center when applying swarm robot systems to complex underwater environments.

[0005] In conventional scenarios, swarm robot systems require each robot to be simple and low-cost. Therefore, swarm robots cannot be equipped with high-cost, high-power, high-performance positioning, communication, sensing, and computing devices. When swarm robots are applied in complex environments such as water, the sensing, communication, and computing capabilities of individual robots are very limited. Thus, they can only collaborate to complete global tasks using their limited sensing, communication, and computing capabilities. Therefore, it is essential to research simplified self-organizing diffusion methods for swarm robots in complex environments with limited perception, where mutual communication and global position information are lacking. Summary of the Invention

[0006] The technical problem to be solved:

[0007] To overcome the shortcomings of existing technologies, this invention provides a simplified self-organizing diffusion method for swarm robots with limited perception. This method is applicable to swarm robots in complex environments such as water, land, and air, and is suitable for swarms ranging from a few to hundreds of robots. This method does not require global positioning information or inter-robot communication. Each robot only needs a perception module to detect its surrounding environment and determine the presence of other robots within its designated range. Based on the determination, it outputs execution commands, thereby achieving self-organizing diffusion of the robot swarm. This significantly reduces the demands on the robots' computing and perception capabilities. This invention solves the problem of self-organizing diffusion for swarm robots in complex environments such as water, where information exchange is impossible, global positioning capabilities are lacking, perception capabilities are extremely low (only able to distinguish the presence of other individuals in a certain direction), and robot computing capabilities are extremely limited. By using the presence of a target within the measurement range as the diffusion execution condition, this method simplifies communication and control equipment, shortens response time, and allows each robot to adjust its position promptly, ensuring uniform coverage and timely diffusion within the target area.

[0008] The technical solution of this invention is: a simplified self-organizing diffusion method for perception-limited swarm robots, characterized by the following specific steps:

[0009] Step 1: Install each standalone sensing module;

[0010] The sensing module's sensing direction is the negative direction of the speed of the installed stand-alone device, and the sensing distance is... ;

[0011] Step 2: Initiate the diffusion command. The control center on the standalone unit triggers the motion execution module based on the signal sent by the sensing module.

[0012] Step 3: The motion execution module is based on the simplified self-organizing diffusion model. P = ( The robots in the cluster move until there are no more target objects within the sensing range of all robots in the cluster, and the target area is evenly covered by robots, thus completing the diffusion process; among which, This represents the linear velocity of the robot when it performs circular motion. This represents the angular velocity of the robot when it performs circular motion. This indicates the forward speed of the robot as it moves in a straight line.

[0013] During the movement, the robot determines its own state according to the set sampling period size; when the signal indicates that there is a target within the sensing distance, the motion execution module controls the robot to move in a straight line along the velocity direction, away from the target; when the signal indicates that there is no target within the sensing distance, the motion execution module controls the robot to make uniform circular motion along a counterclockwise circular trajectory, monitoring targets in other directions.

[0014] A further technical solution of the present invention is as follows: In step 2, the sensing module converts the signal indicating whether a sensing target exists within the sensing distance into an electrical signal and sends it to the control center. The absence of a target is calibrated as I=0, and the presence of a target is calibrated as I=1. The signal calibrated as I=1 is associated with the motion command for linear motion along the velocity direction, and the signal calibrated as I=0 is associated with the motion command for uniform circular motion along a counterclockwise circular trajectory.

[0015] A further technical solution of the present invention is: the radius of the circular trajectory is .

[0016] A further technical solution of the present invention is: when I=0, there are no other robots within the range of the robot's own sensing module, and its linear velocity... Setting it to 0 means the robot moves counter-clockwise. The rotational motion in place.

[0017] A further technical solution of the present invention is: the sensing module is a distance sensor, and the sensing distance L is a threshold set by the sensor. When the distance sensor measures a distance less than the threshold, it is determined that a sensing target exists within the sensing distance; when the distance sensor measures a distance greater than the threshold, it is determined that no sensing target exists within the sensing distance.

[0018] A further technical solution of the present invention is as follows: the specific algorithm of the diffusion model in step 3 is as follows:

[0019] S3.1 Establish a coordinate system;

[0020] In coordinates Center of the circle A small circle with a radius represents an individual robot. Its linear velocity and angular velocity are respectively and At this time, the individual robot speed of movement The direction is the opposite direction of the X-axis, while the sensing direction of the sensing module is the positive direction of the X-axis; with Center of the circle A small circle with a radius represents an individual robot. or robot swarms ;

[0021] S3.2 Establish a mathematical model of the presence of a sensing target within the sensing distance;

[0022] make Individual robots The sensing module's sensing direction is the positive X-axis, and it can sense individual robots. The expression is as follows:

[0023]

[0024] In the formula, From individual robots The center point is exactly where the individual robot is perceived. The distance;

[0025] in The expression is,

[0026]

[0027] In the formula, This represents the individual robot before the movement. Center of mass and individual robots / Robot swarm The distance between the centers of mass, m is the distance required for individual i to move to the point where it can no longer perceive individual j;

[0028] S3.3 in individual robots When a target is present within the perceived distance, calculate the change in distance between the object and the target after movement.

[0029] Individual robots Sensing individual robots / Robot swarm At that time, it moves in the opposite direction of the X-axis to , The coordinates are as follows:

[0030] ;

[0031] Substituting the above formula into the following equation:

[0032]

[0033] In the formula, Represents individual robots after exercise Center of mass and individual robots / Robot swarm The distance between the centers of mass; > It is stated that after each movement away from the robot, the individual robot All will be far from individual robots / Robot swarm ;

[0034] The combined results are:

[0035]

[0036] Simplified results:

[0037]

[0038] Therefore, we arrive at the individual robot. The movement trajectory is always far away from the individual robot / Robot swarm Until the diffusion mission is completed.

[0039] A simplified self-organizing diffusion system for perception-limited swarm robots is characterized by comprising a swarm robot consisting of several individual robots, each individual robot being equipped with a control center, a sensing module, and a motion execution module; the control center is used to receive signals from the sensing module and send motion commands to the motion execution module.

[0040] A further technical solution of the present invention is that the sensing module is a TOF laser ranging sensor, a visual sensor, or an acoustic sensor used in water, such as a microphone array or transducer.

[0041] A further technical solution of the present invention is that the robot is a common two-wheeled differential robot, E-puck.

[0042] An application of a simplified self-organizing diffusion system for perception-limited swarm robots is provided, characterized in that: the swarm robots are used in various fields to perform tasks that require uniform and comprehensive coverage of a target area.

[0043] Beneficial effects

[0044] The beneficial effects of this invention are as follows:

[0045] 1) The technical problem addressed by this method is a purely distributed self-organizing diffusion method for swarm robots that cannot communicate between individuals, lack global positioning capabilities (GPS information), have extremely low perception capabilities (can only distinguish the presence or absence of other individuals in a certain direction, and many sensors do not have threshold settings, so their resolution is fixed; this method proposes setting thresholds to control the distribution density of the final diffusion result), have extremely low robot computing power, and are universal (no requirements on robot motion capabilities; both fully actuated and underactuated robots can be used). The complex environments and underwater environments involved in this technical problem (stable interaction between underwater robot swarms and the difficulty of perceiving high amounts of information) are common.

[0046] 2) The diffusion method and system of the present invention do not require global positioning information and mutual communication between robots. The robot only needs to be equipped with a sensing module (range sensor) to detect the surrounding environmental information and determine whether there are other robots within the sensor range. This enables the self-organized diffusion of the robot group, greatly reducing the demand on the robot's computing power and sensing capabilities.

[0047] 3) The diffusion method and system of this invention involve fewer parameters during the diffusion process. By changing key parameters such as the sensing range threshold of the sensing sensor, diffusion effects at different densities can be achieved, demonstrating excellent robustness and scalability. Furthermore, the diffusion results of the robot swarm can be distributed relatively uniformly in space and exhibit certain dynamic characteristics, making it valuable for engineering applications. Attached Figure Description

[0048] Figure 1 Diagram of robot sensor fixing method.

[0049] Figure 2 : A diffusion principle diagram between two robots or between one robot and a group of other robots

[0050] Explanation of the attached labels: 1 is the epuck robot, 2 is the robot's revolver, 3 is the robot's revolver, and 4 is the TOF laser rangefinder sensor mounted on the robot. Detailed Implementation

[0051] The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0052] Since existing swarm robot self-organized diffusion methods are not applicable to complex environments such as water, this invention proposes a simplified self-organized diffusion method for swarm robots with limited perception. This method is designed for weak connectivity among robots in complex environments. It does not require communication and positioning information between robots, but only a single sensor to detect the surrounding environment and determine whether there are other robots within the sensor's range, thereby achieving self-organized diffusion of the swarm robots.

[0053] This embodiment presents a simplified self-organizing diffusion method for perception-limited swarm robots, and the specific implementation process is as follows:

[0054] In this embodiment, the common two-wheeled differential robot E-puck is selected as the method implementation example. The robot's direction of motion is... The direction, while the sensing sensor senses the direction relative to the direction of motion. Conversely (at a 180° angle), the perceptible range is a distance of The included angle is The fan-shaped shape is used in this example, employing a TOF laser rangefinder as the sensing sensor. The sensing angle is... The angle is close to 0°, meaning the perceived sector can be approximated as a straight line. Furthermore, E-puck is a two-wheeled robot, so the linear and angular velocities in the model need to be converted into the speed of the E-puck's right wheel. Revolver speed The formula is shown below:

[0055]

[0056]

[0057] The specific diffusion execution process is as follows:

[0058] Step 1: The TOF laser rangefinder fixed on the robot senses the direction of the robot's movement. In the opposite direction, and set the threshold for the sensing range of the robot's sensing sensors. L That is, the range within which a sensing sensor can distinguish the presence or absence of a sensed object.

[0059] Step 2: The robot uses its fixed TOF ranging sensor to detect whether there are other robots in the vicinity. Define state I = 0 as the absence of other robots within the robot's own sensor range, and state I = 1 as the presence of other robots within the robot's own sensor range; the other robots refer to one or more robots in a group of robots that are self-organizing and spreading.

[0060] Step 3: The robot uses a simplified self-organizing diffusion model. P =( The robot moves, and during the movement, it determines its own state based on the set sampling period size.

[0061] Wherein: When the robot is in state I=0, that is, there are no other robots within the robot's sensor range, the robot moves forward along a counterclockwise circular trajectory at a uniform speed, with linear velocity and angular velocity respectively. and The radius of the circular trajectory is When the robot is in state I=1, meaning there are other robots within the sensor's sensing range, the robot moves forward at a speed of... Linear motion.

[0062] Example:

[0063] The actual motion process of this simplified self-organizing diffusion method for perception-limited swarm robots, as described in this embodiment, is as follows:

[0064] Reference Figure 2 As shown, on the left is Center A small circle with a radius represents an individual. It moves in a uniform circular motion in a counter-clockwise forward direction (the trajectory is based on...). Center (A solid circle with radius [missing information]), the sensing sensor fitted to the individual senses the direction opposite to the velocity, and the sensing distance is [missing information]. When the individual's binarized sensing sensor just detects the individual ,individual Maintaining the current direction of movement, continue straight forward, moving a distance of m, until the individual... Just when the individual is not visible ;individual It continues to move in a uniform circular motion in a clockwise direction (the trajectory is based on...). Center (A dashed circle with radius ).

[0065] The following quantitatively presents the motion algorithm for achieving self-organized diffusion using the above method:

[0066] like Figure 2 The diagram shown illustrates the principle of robot self-organized diffusion. We first prove that using the algorithm in this paper, a moving robot will always gradually move away from another robot or another group of robots.

[0067] Establish as Figure 2 Coordinate system, left side Center A small circle with a radius represents an individual. The linear velocity and angular velocity are respectively and At this time, the individual's speed The direction is opposite to the X-axis, while the sensing sensor detects the positive X-axis direction. To the right... Center A small circle with a radius represents an individual. (or a group of robots) ).

[0068] make ,individual The sensing direction of the sensor is horizontal to the right (positive x-axis direction), and it just senses the individual. The following expression can be obtained:

[0069]

[0070] In the formula, From the individual The center point is just where you can see the robot. The distance, m, is the distance required for individual i to move to a point where it can no longer perceive individual j. This is calculated... The expression:

[0071]

[0072] according to Figure 2 The geometric relationship can be calculated. The coordinates are as follows:

[0073]

[0074] Substituting the above formula into the following equation:

[0075]

[0076] By combining the two equations, we can obtain:

[0077]

[0078] Simplified results:

[0079]

[0080] In the formula, This represents the distance between the center of mass of the individual and the center of mass of another individual (or group of robots) before the motion. This represents the distance between the center of mass of this individual and the center of mass of another individual (or group of robots) after the motion. > This means that each time a robot moves away from another object, it will move away from another individual (or group of robots).

[0081] Individuals can be derived The trajectory of movement is always far away from the individual In other words, the individual Each cycle of exercise will move the individual away from the body. One point. When both individuals move, in each cycle of movement, the individual... The circular trajectory of the motion will move away from the individual A circular trajectory, meaning two moving individuals will continuously move away from each other. If we consider... Figure 2 China and Israel If we consider the black circle with the center as a group of individuals, we can see that a moving individual is always moving away from another stationary group.

[0082] robot and robots The robots will continue to move away, but they won't drift apart indefinitely. Once they reach a certain distance, they will maintain a dynamically stable state. The key to this algorithm's self-organized diffusion lies in the switching between two robot motion states. However, when the distance between the robots is greater than or equal to the detection range of the robots' sensors, the two robots will not drift away. In other words, when the distance between the robots is greater than or equal to the sensor distance, the robots will no longer drift away from each other and will maintain a dynamically stable state.

[0083] This embodiment presents a simplified self-organizing diffusion system for perception-limited swarm robots, comprising a swarm robot consisting of several individual robots. Each individual robot is equipped with a control center, a sensing module, and a motion execution module. The control center receives signals from the sensing module and sends motion commands to the motion execution module.

[0084] Preferably, the robot distance sensor can be a visual sensor such as a TOF laser rangefinder, a camera module, or an acoustic device such as a microphone array or transducer.

[0085] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A simplified self-organizing diffusion method for perception-constrained swarm robots, characterized in that... The specific steps are as follows: Step 1: Install each standalone sensing module; The sensing module's sensing direction is the negative direction of the speed of the installed stand-alone device, and the sensing distance is... ; Step 2: Initiate the diffusion command. The control center on the standalone unit triggers the motion execution module based on the signal sent by the sensing module. Step 3: The motion execution module is based on the simplified self-organizing diffusion model. P = ( The robots in the cluster move until there are no more target objects within the sensing range of all robots in the cluster, and the target area is evenly covered by robots, thus completing the diffusion process; among which, This represents the linear velocity of the robot when it performs circular motion. This represents the angular velocity of the robot when it performs circular motion. This indicates the forward speed of the robot as it moves in a straight line. During the movement, the robot determines its own state according to the set sampling period size; when the signal indicates that there is a target within the sensing distance, the motion execution module controls the robot to move in a straight line along the velocity direction, away from the target; when the signal indicates that there is no target within the sensing distance, the motion execution module controls the robot to make uniform circular motion along a counterclockwise circular trajectory, monitoring targets in other directions.

2. The simplified self-organizing diffusion method for perception-constrained swarm robots according to claim 1, characterized in that: In step 2, the sensing module converts the signal indicating whether a target exists within the sensing distance into an electrical signal and sends it to the control center. The absence of a target is calibrated as I=0, and the presence of a target is calibrated as I=1. The signal calibrated as I=1 is associated with a motion command for linear motion along the velocity direction, and the signal calibrated as I=0 is associated with a motion command for uniform circular motion along a counterclockwise circular trajectory.

3. The simplified self-organizing diffusion method for perception-constrained swarm robots according to claim 2, characterized in that: The radius of the circular trajectory is .

4. The simplified self-organizing diffusion method for perception-constrained swarm robots according to claim 2, characterized in that: When I=0, there are no other robots within the robot's own sensing module range, and its linear velocity... Setting it to 0 means the robot moves counter-clockwise. The rotational motion in place.

5. The simplified self-organizing diffusion method for perception-constrained swarm robots according to claim 1, characterized in that: The sensing module is a distance sensor. The sensing distance L is a threshold set by the sensor. When the distance sensor measures a distance less than the threshold, it is determined that a sensing target exists within the sensing distance. When the distance sensor measures a distance greater than the threshold, it is determined that no sensing target exists within the sensing distance.

6. The simplified self-organizing diffusion method for perception-constrained swarm robots according to claim 1, characterized in that: The specific algorithm for the diffusion model in step 3 is as follows. S3.1 Establish a coordinate system; In coordinates Center of the circle A small circle with a radius represents an individual robot. Its linear velocity and angular velocity are respectively and At this time, the individual robot speed of movement The direction is the opposite direction of the X-axis, while the sensing direction of the sensing module is the positive direction of the X-axis; with Center of the circle A small circle with a radius represents an individual robot. or robot swarms ; S3.2 Establish a mathematical model of the presence of a sensing target within the sensing distance; make Individual robots The sensing module's sensing direction is the positive X-axis, and it can sense individual robots. The expression is as follows: In the formula, From individual robots The center point is just enough to sense the individual robot The distance; in The expression is, In the formula, This represents the individual robot before the movement. Center of mass and individual robots / Robot swarm The distance between the centers of mass, m is the distance required for individual i to move to the point where it can no longer perceive individual j; S3.3 in individual robots When a target is present within the perceived distance, calculate the change in distance between the object and the target after movement; Individual robots Sensing individual robots / Robot swarm At that time, it moves in the opposite direction of the X-axis to , The coordinates are as follows: ； Substituting the above formula into the following equation: In the formula, Representing individual robots after exercise Center of mass and individual robots / Robot swarm The distance between the centers of mass; > It is stated that after each movement away from the robot, the individual robot All will be far from individual robots / Robot swarm ; The combined results are: Simplified results: Therefore, we arrive at the individual robot. The movement trajectory is always far away from the individual robot / Robot swarm Until the diffusion mission is completed.

7. An implementation system for the simplified self-organizing diffusion method for perception-constrained swarm robots as described in any one of claims 1-6, characterized in that: The system comprises a cluster of individual robots, each equipped with a control center, a sensing module, and a motion execution module. The control center receives signals from the sensing module and sends motion commands to the motion execution module.

8. The implementation system according to claim 7, characterized in that: The sensing module is a TOF laser rangefinder, a visual sensor, or an acoustic sensor used in a microphone array or transducer.

9. The implementation system according to claim 7, characterized in that: The robot in question is the common two-wheeled differential robot, E-puck.

10. An application of the system according to claim 7, characterized in that: The swarm robots are used in various fields to perform tasks that require uniform and comprehensive coverage of a target area.

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