CN114839979A - SRP-based multi-robot plume source-finding relative navigation strategy - Google Patents
SRP-based multi-robot plume source-finding relative navigation strategy Download PDFInfo
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- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
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Abstract
The invention belongs to the technical field of source searching and positioning, and particularly relates to an SRP-based multi-robot plume source searching relative navigation strategy, which specifically comprises the following steps: in the process of plume sourcing by multiple robots, according to plume related parameter information, multi-robot Spatial distribution configuration and plume Spatial Relative Position (SRP) information, screening and priority determination are carried out on related information by using information entropy, and a decision is carried out on the related information by using a decision tree algorithm to determine a sourcing strategy, wherein the decision comprises the following steps: strategy A, slice random search, strategy B, fan-shaped divergent headwind search and strategy C, triangle formation source searching strategy.
Description
Technical Field
The invention belongs to the technical field of source searching and positioning, and particularly relates to a multi-robot plume source searching relative navigation strategy based on SRP.
Background
With the rapid development of industrial manufacturing industry, flammable, explosive and toxic chemical products such as petroleum, coal gas, natural gas and the like bring convenience to daily life of people, and meanwhile, people are more and more confronted with accidents such as leakage, discharge, poisoning and the like of flammable, explosive and toxic media, so that real harm is brought to the health and safety of people. Therefore, finding out the leakage source as soon as possible and eliminating risks in time are of great significance to the health and safety of people. However, there are the following drawbacks to the current multi-robot plume sourcing method.
(1) The plume historical motion information is rarely utilized, the relative pose relation between the geometric layout of multiple robots and the detected plume spatial distribution cannot be obtained, the prediction capability of the plume distribution and the motion trend of an undetected area is insufficient, the optimal motion trajectory of each robot at present is difficult to plan, and the source searching efficiency is low.
(2) The influence of the airflow variation parameters on the smoke plume, and the geometric and trend characteristics of the smoke plume distribution are not completely determined, so that the successful realization of multi-robot synergistic smoke plume sourcing still meets the challenge.
(3) The robot does not perform screening, priority determination, optimization and the like on rich plume information, so that the decision process in the source searching of the robot is longer, and the real-time performance is reduced.
Disclosure of Invention
In order to solve the problems of low plume source searching efficiency and low real-time performance, the invention provides a multi-robot plume source searching relative navigation strategy based on SRP, and the specific technical scheme is as follows.
A multi-robot plume source-finding relative navigation strategy based on SRP comprises the following specific steps.
And 2, if the source searching strategy is the strategy A, dividing the multiple robots into multiple areas according to the wind flow direction, and randomly searching each robot in each area until the plume is found.
And 3, if the source searching strategy is the strategy B, multiple robots adopt the fan-shaped divergent array type to carry out upwind search until trending plumes are found.
And 4, if the source searching strategy is the strategy C, searching by the multiple robots by adopting the improved triangular array until the plume source is found.
Optionally, the information on parameters related to the plume in step 1 may be obtained by sensors on multiple robots, and mainly include basic parameters (temperature, pressure, reynolds number, etc.) of the transport medium and the plume, visual parameters (texture, color difference, gray scale, etc.), motion parameters (diffusion rate, flow direction, flow velocity), and chemical parameters (concentration, component, etc.), and further determine the relative form and position (SRP) information of the plume space according to the detected spatial distribution of the plume.
Optionally, the source searching strategy in step (1) is divided into three types: strategy A, slice random search, strategy B, fan-shaped divergent headwind search and strategy C, triangle formation source searching strategy, wherein strategy A is enabled when no plume information exists, strategy B is enabled when no plume trends exist, and strategy C is enabled when plume trends exist.
Optionally, the policy a in step 2 divides the region to be sourced into n regions according to the number n of the robots, the robots perform random search in the respective regions, the sourcing path of each robot may be determined by an RRT algorithm (or other random algorithms, such as a PRM algorithm), when a plume is found, the trajectory is converted into a leader following policy, the robot that finds the information of the plume is the master robot M, and the rest are slave robots S.
Optionally, the policy B in step 3 is represented by formula 1: determining an included angle gamma between adjacent robots; from equation 2: determining a central angle omega of the sector; the position of the main robot M is used as the circle center of the sector, the slave robots are distributed on two sides of the main robot, the included angle between every two robots is gamma, the source searching range of the robots is in a sector, and the angular bisector of the sector is 180 degrees different from the wind direction.
Optionally, in the strategy C described in step 4, the robot located in the trending plume is the leader robot M, and the other robots are the slave robots S, wherein at least 2 slave robots are kept at the boundaries of the two sides of the plume, and if the number n of the multiple robots is greater than 3, the remaining robots are sourcing in the trending plume and are uniformly distributed on the two sides of the master robot, so that the matrix of the multiple robots is kept in a triangle. Determining a motion trajectory by using the historical discrete motion parameters and the current motion parameters of the leader robot M through weighted least squares; determining an optimal motion trajectory of the main robot through the robot spatial distribution configuration and the plume Spatial Relative Position (SRP); if the number n of the multiple robots is greater than 3, the method for determining the optimal motion trajectory from the robot motion trajectory in the trending plume to the main robot is consistent; the motion of the slave robot at the plume boundary is approximately consistent with the motion of the master robot, but fine-tuned based on the plume information at the robot to ensure that it is always at the plume boundary. And the main robot directly moves for a certain distance d along the optimal motion trajectory and then makes a decision again.
Drawings
The invention will be further understood from the following description in conjunction with the accompanying drawings.
FIG. 1 is a diagram of an SRP-based multi-robot plume-seeking relative navigation strategy model architecture.
FIG. 2 is a schematic diagram of strategy B-fan divergence headwind search.
FIG. 3 is a schematic diagram of strategy C-triangle formation source finding strategy.
FIG. 4 is a schematic diagram of the relative positions of the multi-robot spatial distribution configuration and the plume space.
Detailed Description
In order that the invention may be readily understood, the following description is further taken in conjunction with the examples. In the following detailed description, reference is made to the accompanying drawings, which form a part hereof.
Referring to fig. 1, a diagram of a multi-robot plume source-finding relative navigation strategy model based on SRP includes the following steps.
The number of multiple robots is set to 3, i.e., n = 3.
The information of parameters related to the plume can be obtained by sensors on multiple robots, and the information mainly comprises basic parameters (temperature, pressure, Reynolds number and the like) of the transport medium and the plume, visual parameters (texture, chromatic aberration, gray scale and the like), motion parameters (diffusion rate, flow direction, flow velocity) and chemical parameters (concentration, components and the like), and the information of relative form and position (SRP) of the plume space is further determined according to the detected spatial distribution of the plume.
It is assumed that the trend information of the plume distribution at the initial position where the multiple robots are located is no plume.
And determining to adopt the strategy A according to the trend information of the plume distribution.
And 2, the source searching strategy is a strategy A, the multiple robots are divided into 3 areas according to the wind flow direction, and the 3 robots perform random search in the respective areas until the plume is found.
The source finding path of each robot can be determined by an RRT algorithm (or other random algorithm, such as a PRM algorithm), when the robot a finds the plume, the method is converted into a leader following strategy, the robot a finding the information of the plume is the master robot M, and the rest are the slave robots S.
Assume that the plume found by the robot a is a non-trending plume.
And determining to adopt the strategy B according to the trend information of the plume distribution.
And 3, taking the source searching strategy as a strategy B, and carrying out upwind search by adopting a fan-shaped divergent array type by a plurality of robots until a trending plume is found.
The position of the master robot M is kept unchanged, and the slave robot S moves quickly to the master robot M.
From equation 1: determining an included angle γ = 60 ° between adjacent robots; from equation 2: determining the central angle ω =120 ° of the fan; the position of the main robot M is used as the circle center of the sector, the slave robots are distributed on two sides of the main robot, the included angle between every two robots is gamma, the source searching range of the robots is in a sector, and the angular bisector of the sector is 180 degrees different from the wind direction.
Assume that robot b finds a trending plume.
Robot b switches to master robot M, the remaining robots are slave robots, and strategy C is started.
And 4, taking the source searching strategy as a strategy C, and searching by adopting an improved triangular array by multiple robots until the plume source is found.
The position of the main robot M is kept unchanged, the auxiliary robots S1 and S2 quickly move to the two sides of the main robot until the plume boundary, and a motion trajectory is determined by using weighted least squares for the historical discrete motion parameters and the current motion parameters of the leader robot M; determining an optimal motion trajectory of the main robot through the robot spatial distribution configuration and the plume Spatial Relative Position (SRP); the slave robots S1, S2 motion is approximately consistent with the master robot, but fine-tuned to ensure that they are always located at the plume boundary based on the plume information at the robots.
Assuming the plume concentration of the slave robot S1 increases, the slave robot S1 will move in a direction away from the master robot M to ensure that it is always located at the plume boundary.
And assuming that the robot finds the plume source, ending the source searching.
The robots a, b and c used in this example do not represent a specific robot, but generally refer to a robot, and the robots that find changes in the trend information of the plume distribution in different steps may be the same or different.
It should be understood that the embodiments described in the detailed description, drawings, and claims for illustration purposes should not be construed as limiting the invention. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
The invention has the beneficial technical effects that.
1. The plume historical motion information, particularly the relative form and position (SRP) information of the multi-robot space configuration and the plume space is fully utilized, so that the detection capability of the robot is improved, the effective distance of motion of each decision step is increased, and the source searching efficiency is improved.
The main robot directly moves for a certain distance along the optimal motion trajectory and then makes a decision again, and does not need to make a decision constantly, so that the source searching speed is increased.
3. The information entropy is introduced to optimize the plume information, and the distribution and motion rule conditions of the plume are determined in an accelerated mode, so that the real-time performance of the robot decision is improved.
Claims (6)
1. A multi-robot plume source-finding relative navigation strategy based on SRP is characterized by comprising the following specific steps:
(1) in the plume sourcing process of multiple robots, according to plume related parameter information, Spatial Relative Position (SRP) information of a multi-robot Spatial distribution configuration and a plume space, screening and priority determining are carried out on related information by using information entropy, and a decision is carried out on the related information by using a decision tree algorithm to determine a sourcing strategy;
(2) if the source searching strategy is strategy A, the multiple robots are divided into a plurality of areas according to the wind flow direction, and each robot carries out random search in each area until a plume is found;
(3) if the source searching strategy is a strategy B, multiple robots adopt a fan-shaped divergent array type to carry out upwind search until a trending plume is found;
(4) if the source searching strategy is strategy C, the multiple robots search by adopting the improved triangular array until the plume source is found.
2. The SRP-based multi-robot plume source-seeking relative navigation strategy as claimed in claim 1, wherein the information of the parameters related to the plume in step (1) can be obtained by sensors on the multi-robot, and mainly includes transport medium, basic parameters (temperature, pressure, Reynolds number, etc.) of the plume, visual parameters (texture, color difference, gray level, etc.), motion parameters (diffusion rate, flow direction, flow velocity), and chemical parameters (concentration, composition, etc.), and the information of the relative position (SRP) of the plume space is determined according to the detected spatial distribution of the plume.
3. The SRP-based multi-robot plume sourcing relative navigation strategy of claim 1, wherein the sourcing strategy of step (1) is divided into three categories: strategy A, slice random search, strategy B, fan-shaped divergent headwind search and strategy C, triangle formation source searching strategy, wherein strategy A is enabled when no plume information exists, strategy B is enabled when no plume trends exist, and strategy C is enabled when plume trends exist.
4. The SRP-based multi-robot plume source-finding relative navigation strategy of claim 1, wherein the strategy A in step (2) is to divide the area to be source-found into n areas according to the wind flow direction according to the number n of robots, the robots perform random search in the respective areas, the source-finding path of each robot can be determined by RRT algorithm (or other random algorithm, such as PRM algorithm), when the plume is found, the strategy is converted into a leader following strategy, the robot which finds the information of the plume is the master robot M, and the rest are the slave robots S.
5. The SRP-based multi-robot plume sourcing relative navigation strategy of claim 1, wherein the strategy B of step (3) is represented by formula 1: determining an included angle gamma between adjacent robots; from equation 2: determining a central angle omega of the fan shape; the position of the main robot M is used as the circle center of the sector, the slave robots are distributed on two sides of the main robot, the included angle between every two robots is gamma, the source searching range of the robots is in a sector, and the angular bisector of the sector is 180 degrees different from the wind direction.
6. The SRP-based multi-robot plume sourcing relative navigation strategy of claim 1, wherein the robot in the trend plume in the strategy C in the step (4) is a leader robot M, and the other robots are slave robots S, wherein at least 2 slave robots are kept at the boundaries of two sides of the plume, and if the number n of the multi-robots is greater than 3, the remaining robots are sourcing in the trend plume and uniformly distributed on two sides of the master robot, so that the multi-robot array is kept in a triangle;
determining a motion trajectory by using weighted least squares for historical discrete motion parameters and current motion parameters of a leader robot M, determining the optimal motion trajectory of a main robot through the spatial distribution configuration and plume Spatial Relative Position (SRP) of the robots, wherein if the number n of the robots is greater than 3, the motion trajectory of the slave robot in the plume tendency is consistent with the method for determining the optimal motion trajectory of the main robot, the motion of the slave robot at the plume boundary is approximately consistent with that of the main robot, but fine adjustment is carried out according to plume information at the robot to ensure that the slave robot is always positioned at the plume boundary; and the main robot directly moves for a certain distance d along the optimal motion trajectory and then makes a decision again.
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| CN117138291A (en) * | 2023-10-27 | 2023-12-01 | 江苏庆亚电子科技有限公司 | Fire-fighting robot fire-extinguishing method and fire-extinguishing system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117138291A (en) * | 2023-10-27 | 2023-12-01 | 江苏庆亚电子科技有限公司 | Fire-fighting robot fire-extinguishing method and fire-extinguishing system |
| CN117138291B (en) * | 2023-10-27 | 2024-02-06 | 江苏庆亚电子科技有限公司 | Fire-fighting robot fire-extinguishing method and fire-extinguishing system |
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