CN107589743B - Self-organizing aggregation method of under-actuated robot based on binarization environment information - Google Patents

Abstract

The invention provides an under-actuated robot self-organizing gathering method based on binarization environment information. In the implementation process of the whole algorithm, the robot only needs one sensor to detect surrounding environment information to judge whether other robots exist in the range of the sensor, and therefore self-organization aggregation of group robots is achieved. The state of the sensor of the robot is simplified into two states, I-0 and I-1. I-0 represents that there are no other robots within the sensor range of the robot; i-1 represents that there are other robots within the sensor range of the robot. When the sensor state I of the robot is equal to 0, the robot makes uniform circular motion backwards along a clockwise circular track; when the sensor state I of the robot is 1, the robot moves forwards along a clockwise circular track to do uniform circular motion. The robot can realize self-organization aggregation of the robot through continuous switching of the two states. Meanwhile, the mathematical demonstration that the algorithm can realize self-organization aggregation is also provided, and the feasibility of the algorithm is theoretically demonstrated.

Description

Self-organizing aggregation method of under-actuated robot based on binarization environment information

Technical Field

The invention relates to a self-organizing clustering algorithm, which is particularly suitable for under-actuated group robots. Meanwhile, the algorithm is also suitable for the fully-driven robot.

Background

In the research of the group robot, the aggregation behavior as the basic behavior of the group organism is considered as the basic group behavior that the group robot system should have, and is also a basic research problem for researching the control of the group robot system. Many researchers are working on how to make population robots perform self-organizing aggregation motions. Studying the self-organizing aggregation of swarm robots is a prerequisite or fundamental work in swarm robot system applications. In a swarm robot system, it is necessary to study how to make swarm robots self-organize and gather, because of the following two reasons:

first, in the application of swarm robotic systems, robot aggregation is often a prerequisite or important fundamental task to accomplish other tasks. Because the sensing capability, the communication capability and the computing capability of the individual robots in the group robot system are very limited, they can only utilize the local sensing and communication capability to realize mutual cooperation to complete the global task, which requires the individual robots to communicate and cooperate within a close range to each other, so that robot aggregation often becomes a precondition or basic work in the application of the group robot system. For example, a group of small robots are scattered in a certain area to perform information exploration tasks, and after the exploration is completed, the robots need to be gathered together so as to be queued to jointly go to the next exploration area or facilitate the recovery work of the robots. Taking a military scene as an example, a group of robots are airdropped into a certain unfamiliar area to execute a task of detecting or collecting information, and diffusion is needed at the beginning; after the detection is completed, the robots need to be gathered.

Secondly, the core significance of the research is that a group robot system formed by coordinating and organizing a huge number of individuals can complete complex tasks which cannot be completed by a single robot, and the design cost of the group system formed by simple individuals is far lower than that of a single robot with the same capacity. Since the swarm robot system requires each robot to be simple in structure and low in cost, the robot does not need to be equipped with expensive positioning equipment like a GPS, and the acquisition of global position information is very difficult in an unknown environment such as deep sea. For example, in a certain area, the target search is performed, and the efficiency of using group robots is higher than that of using single robots; when information sampling is carried out, the efficiency of the group robot is much higher, and meanwhile, smooth completion of tasks can be guaranteed. Therefore, it is very important to study the aggregation of autonomous self-organization of population robots.

Disclosure of Invention

In order to solve the problems brought by various complex and changeable environments to the self-organizing motion control of the group robots, the invention provides a self-organizing aggregation algorithm of under-actuated robots based on binary environment information, communication and positioning information among the robots are not needed, and the robots only need one sensor to detect surrounding environment information in the implementation process of the whole algorithm to judge whether other robots exist in the range of the sensor, so that the self-organizing aggregation of the group robots is realized. Meanwhile, the algorithm does not need the mutual communication between the GPS positioning and the robot, and has good robustness and expansibility.

The technical scheme of the invention is as follows:

the self-organizing aggregation method of the under-actuated robot based on the binarization environment information is characterized in that: the method comprises the following steps:

step 1: the robot senses whether other robots are around through a sensor of the robot, the condition that the state I is 0 represents that no other robot exists in the range of the sensor of the robot, and the state I is 1 represents that other robots exist in the range of the sensor of the robot; the other robots refer to one or more robots of a population of robots performing self-organizing aggregation;

step 2: robot control model according to self-organizing aggregation

P＝(ν₀,ω₀,ν₁,ω₁)

And in the moving process, the robot judges the state I according to the set sampling period size:

wherein: when the robot is in the state I equal to 0, the robot makes uniform circular motion backwards along a clockwise circular track, and the linear velocity and the angular velocity are v respectively₀And ω₀(ii) a When the robot is in the state I equal to 1, the robot moves forwards to do uniform circular motion along a clockwise circular track, and the linear velocity and the angular velocity are respectively v₁And ω₁(ii) a And in the motion process of the robot in the state I being 0, the sensor of the robot can be in a certain positionAnd sensing other robots around at any moment, and converting the state of the robot into I1.

Advantageous effects

The invention does not need communication and positioning information among robots, and the robots only need one sensor to detect surrounding environment information in the whole algorithm realization process to judge whether other robots exist in the sensor range, thereby realizing the self-organization aggregation of group robots. Meanwhile, the invention has good robustness and expansibility because GPS positioning and mutual communication between robots are not needed.

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1: schematic diagram of the aggregation of two robots.

FIG. 2: aggregation strategy for two robots.

Detailed Description

The following detailed description of embodiments of the invention is intended to be illustrative, and not to be construed as limiting the invention.

The invention aims to provide a method which does not need communication and positioning information among robots, only needs a sensor to detect surrounding environment information and is used for judging whether other robots exist in the range of the sensor, and therefore self-organization aggregation of group robots is achieved.

The method comprises the following specific steps:

step 1: the robot senses whether other robots are around through a sensor of the robot, the condition that the state I is 0 represents that no other robot exists in the range of the sensor of the robot, and the state I is 1 represents that other robots exist in the range of the sensor of the robot; the other robots refer to one or more robots of a population of robots that perform self-organizing aggregation.

Step 2: robot control model according to self-organizing aggregation

P＝(ν₀,ω₀,ν₁,ω₁)

And in the moving process, the robot judges the state I according to the set sampling period size:

wherein: when the robot is in the state I equal to 0, the robot makes uniform circular motion backwards along a clockwise circular track, and the linear velocity and the angular velocity are v respectively₀And ω₀(ii) a When the robot is in the state I equal to 1, the robot moves forwards to do uniform circular motion along a clockwise circular track, and the linear velocity and the angular velocity are respectively v₁And ω₁(ii) a And in the motion process of the robot with the state I equal to 0, the sensor of the robot can sense other surrounding robots at a certain moment, so that the state of the robot is converted into the state I equal to 1.

The actual motion process is as follows:

the group robot starts to be in a dispersed state, the robot state I is 0, and the robot state I is set to be in a dispersed state according to the set linear speed v₀And angular velocity ω₀Starting to move backward along a clockwise circular track at a constant speed, wherein in the dispersed state of the group robots, in the circular track constant-speed circular motion corresponding to the state I equal to 0, the sensors of the robots can sense other surrounding robots at a certain moment, so that the state of the robots is converted into the state I equal to 1, and at the moment, the robots move backwards along the set linear speed v₁And angular velocity ω₁The robot moves forwards along a clockwise circular track at a constant speed, so that qualitative analysis shows that a moving robot can always approach a static robot by using the method.

The following theoretical proof that the above method can achieve self-organizing aggregation is given quantitatively:

fig. 1 is a schematic diagram of the robot self-organizing cluster. We first demonstrate that using the algorithm herein, a moving robot can always approach a stationary robot.

We establish an xy coordinate system as shown in FIG. 1, where p is_iIndicates the ith robot，p_jDenotes the j-th robot, the y-axis passing through c_iAnd o_iX-axis over p_jPerpendicular to the x-axis. From the figure we can show some important coordinates,

c_i＝[0,α₁]，c_i'＝[β₁-β₂,α₂]，p_j＝[β₁,0]，o_i＝[0,η]

we can easily obtain:

α₁＝||c_i-o_i||+η

α₂＝||c_i'-o_i||*cosθ+η

β₁＝β₂+||c_i'-o_i||*sinθ

wherein theta belongs to (0, pi/2) and | c_i'-o_i||＝||c_i-o_iI, so we can get from the above formula

α₁-α₂＞0

β₁-β₂＞0

d²＝||c_i-p_j||²＝α₁ ²+β₁ ²

d represents the center c of the motion track of the robot i_iThe distance from the robot j, d' is the circle center c of the motion track of the robot i after the robot moves for a period_i' distance to robot j.

∴d²＞d'²

By the above formula, we can obtain that the motion trail of the robot i is always close to the robot j. In other words, each time the robot i moves one cycle, it approaches the robot j a little. When the two robots move, the motion circular track of the robot i approaches the motion circular track of the robot j every time the robot moves for one period.

In the using process of the embodiment, since the E-puck robot is a four-wheel robot, the linear velocity and the angular velocity in the model need to be converted into the left and right wheel speeds of the E-puck robot, and the formula is as follows:

the E-puck robot adopts a front camera as a sensor and outputs a state I. In the uniform-speed circular motion of the circular track corresponding to the state I (0), the sensor of the robot can sense other robots around at a certain moment, so that the state of the robot is converted into the state I (1), and at the moment, the robot changes into the state I (1) according to the set linear velocity v₁And angular velocity ω₁The robot moves forwards along a clockwise circular track at a constant speed, so that the motion track of the robot always approaches to another robot.

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, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.

Claims (1)

1. An under-actuated robot self-organizing gathering method based on binarization environment information is characterized in that: the method does not require communication and positioning information between robots; the method comprises the following steps:

step 1: the robot senses whether other robots are around through a sensor of the robot, the condition that the state I is 0 represents that no other robot exists in the range of the sensor of the robot, and the state I is 1 represents that other robots exist in the range of the sensor of the robot; the other robots refer to one or more robots of a population of robots performing self-organizing aggregation;

step 2: robot control model according to self-organizing aggregation

P＝(ν₀,ω₀,ν₁,ω₁)

And in the moving process, the robot judges the state I according to the set sampling period size:

wherein: when the robot is in the state I equal to 0, the robot makes uniform circular motion backwards along a clockwise circular track, and the linear velocity and the angular velocity are v respectively₀And ω₀(ii) a When the robot is in the state I equal to 1, the robot moves forwards to do uniform circular motion along a clockwise circular track, and the linear velocity and the angular velocity are respectively v₁And ω₁(ii) a And in the motion process of the robot with the state I equal to 0, the sensor of the robot can sense other surrounding robots at a certain moment, so that the state of the robot is converted into the state I equal to 1.

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