CN-122015804-A - Full-area coverage path optimization method and system applied to water surface cleaning operation

CN122015804ACN 122015804 ACN122015804 ACN 122015804ACN-122015804-A

Abstract

The invention discloses a full-area coverage path optimization method and a full-area coverage path optimization system applied to water surface cleaning operation, which relate to the technical field of water surface cleaning path optimization, the method comprises the steps of cleaning data acquisition, water surface cleaning path analysis, water surface cleaning path optimization and early warning prompt, by constructing a problem base of a cleaning robot corresponding to the water surface cleaning operation and analyzing a cleaning problem set stored in the cleaning robot corresponding to a water area to be cleaned, further forming a high-efficiency associated optimal cleaning combination of the cleaning robot corresponding to cleaning, the method comprises the steps of obtaining a cleaning operation path, analyzing a cleaning result of the cleaning robot corresponding to a water area to be cleaned, knowing a problem influence factor when the cleaning has a problem, executing path optimization, and finally evaluating the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned, so that comprehensive analysis of the cleaning condition of the cleaning robot on the water surface is realized, effective cleaning under the coverage of the water surface corresponding to the whole area is realized, and the cleaning efficiency of the water surface is improved.

Inventors

CHEN ZHUOFEI
CHEN ZHIWEN
YUAN KUAN
Lv Linhuo
GONG HUI
SHI YINAN

Assignees

成都河宝机器人有限公司
东方水利智能科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260126

Claims (10)

1. The full-area coverage path optimization method applied to the water surface cleaning operation is characterized by comprising the following steps of: Step one, acquiring cleaning data, namely acquiring cleaning images of the cleaning robot in each historical water surface cleaning operation, constructing a problem base of the cleaning robot corresponding to the water surface cleaning operation, acquiring pollutant data corresponding to a current water area to be cleaned, and analyzing a cleaning problem set stored in the water area to be cleaned corresponding to the cleaning robot; Analyzing the cleaning operation path of the cleaning robot corresponding to the water area to be cleaned based on the cleaning problem set of the cleaning robot corresponding to the water area to be cleaned and each associable optimal cleaning combination for performing the cleaning operation of the cleaning robot corresponding to the water area to be cleaned; Monitoring a cleaning robot for performing cleaning operation on a water area to be cleaned according to the cleaning path, acquiring cleaning feedback data, analyzing a cleaning result of the cleaning robot corresponding to the water area to be cleaned, analyzing a covering path influence factor of the cleaning robot corresponding to the water area to be cleaned when the cleaning robot has a problem in cleaning the water area to be cleaned, performing path optimization of the cleaning robot corresponding to the water area to be cleaned, and evaluating cleaning coverage of the cleaning robot corresponding to the water area to be cleaned; And step four, early warning prompt is carried out when the cleaning robot has problems corresponding to the cleaning of the water area to be cleaned or the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned is not qualified.
2. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 1, wherein the construction of the problem base of the cleaning robot corresponding to the water surface cleaning operation comprises the following specific construction processes: based on the problem images with abnormal cleaning states of the cleaning robots, the cleaning abnormal characteristic data are extracted from the problem images, the cleaning abnormal characteristic images are constructed, meanwhile, specific abnormal manifestations of the cleaning abnormal characteristic images corresponding to various types of dirt are recognized, and the cleaning problems and the abnormal characteristic data when the problems occur when the cleaning robots are used for cleaning the various types of dirt are obtained, so that a problem base when the cleaning robots are used for cleaning the water surface is formed.
3. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 2, wherein the analyzing and cleaning robot corresponds to a cleaning problem set stored in a water area to be cleaned, and the specific analyzing process is as follows: The method comprises the steps of performing dual monitoring on a current water area to be cleaned by using water-entering type equipment and ground type equipment, respectively obtaining a water surface portrait and a water bottom portrait corresponding to the water area to be cleaned, respectively performing pollutant identification from the two portraits to obtain a pollutant type corresponding to the current water area to be cleaned, comparing the pollutant type corresponding to the current water area to be cleaned with a pollutant set of types corresponding to various cleaning problems in a problem library, and if the pollutant type corresponding to the current water area to be cleaned is contained in the pollutant set of types corresponding to certain cleaning problems in the problem library, taking the cleaning problems corresponding to the types of pollutants as the cleaning problems stored in the pollutant type corresponding to the current water area to be cleaned, thereby obtaining the cleaning problem set stored in the water area to be cleaned.
4. The method for optimizing a full-area coverage path for a water surface cleaning operation according to claim 3, wherein the specific analysis process is as follows: Based on a cleaning problem set stored in a water area to be cleaned corresponding to a cleaning robot, extracting abnormal performance characteristics of the cleaning robot when problems exist in cleaning various types of dirt corresponding to the cleaning robot, obtaining hierarchical association among pollution types, typical abnormalities and characteristic data, constructing a problem association library of the cleaning robot corresponding to various types of dirt according to the hierarchical association, extracting dirt problem hierarchical association of various types of dirt in the water area to be cleaned corresponding to the current cleaning robot, simultaneously extracting similar characteristic data among the dirt problem hierarchical association of various types of dirt in the water area to be cleaned corresponding to the current cleaning robot, establishing a problem offset characteristic library among specific abnormal directions of various types of dirt, and carrying out cleaning association combination of the two types of dirt when abnormal problem parameters are offset by cleaning problems among certain types of dirt and certain types of dirt, so that various associatable optimal cleaning combinations of the cleaning robot corresponding to the water area to be cleaned for performing cleaning operation are obtained through analysis.
5. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 4, wherein the cleaning operation path of the cleaning robot corresponds to the water area to be cleaned, and the specific analysis process is as follows: Based on the comprehensive characteristic data of the associatable excellent clear combination for extracting the cleaning operation of the cleaning robot corresponding to the water area to be cleaned, the comprehensive characteristic data is imported into a dirt combination high-quality evaluation model, the combination high-quality values corresponding to the associatable excellent clear combinations are output, the combination high-quality values corresponding to the associatable excellent clear combinations are arranged according to the sequence from high to low, the cleaning area division of the water area to be cleaned is executed according to the sequence from the first name to the last name of the high-quality values, and the cleaning operation path of the cleaning operation corresponding to the water area to be cleaned is ordered and executed according to the positive sequence corresponding to the high-quality values.
6. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 5, wherein the cleaning result of the cleaning robot corresponds to the water area to be cleaned is specifically analyzed as follows: Comparing the cleaning feedback data of the cleaning robot corresponding to the water area to be cleaned with a preset reference cleaning feedback data interval, judging that the cleaning path is not in full coverage of the area if one or more data of the cleaning feedback data of the cleaning robot corresponding to the water area to be cleaned are contained in the preset reference cleaning feedback data interval, judging that the cleaning of the water area under the residual path of the water area is not in problem if the cleaning feedback data of the cleaning robot corresponding to the water area to be cleaned are contained in the preset reference cleaning feedback data interval, and continuously executing the cleaning of the water area under the residual path of the water area according to the path if the cleaning path is in full coverage of the area.
7. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 1, wherein the coverage path influencing factors of the cleaning robot corresponding to the water area to be cleaned are analyzed, and the specific analysis process is as follows: The method comprises the steps of obtaining pollutant content of a cleaning robot corresponding to a water area to be cleaned when the cleaning of the water area to be cleaned is problematic, comparing the pollutant content of the cleaning robot corresponding to the water area to be cleaned with initial pollutant content corresponding to the water area, judging that the problem of cleaning is influenced by the change of the pollutant content if the pollutant content of the cleaning robot corresponding to the water area to be cleaned is larger than the initial pollutant content corresponding to the water area, extracting pollutant types exceeding the initial pollutant content, continuously comparing presentation characteristics corresponding to the pollutant types with reference pollutant type characteristic sets corresponding to all influence factors in a database, obtaining influence factors corresponding to the pollutant type content exceeding the standard, and predicting and obtaining final influence presentation values of the pollutants corresponding to all areas of the water area to be cleaned, including the exceeding amount and the used duration, based on change characteristic data between the initial time interval and the current time interval, of the influence factors corresponding to all influence factors.
8. The method for optimizing the coverage path of the whole area applied to the water surface cleaning operation according to claim 1, wherein the path optimization of the robot for performing the cleaning operation corresponding to the water area to be cleaned is specifically performed as follows: Comparing the final influence display value of the factors corresponding to the dirt in each region of the water area to be cleaned with the reference dirt influence offset value interval corresponding to the combined dirt in the problem offset feature library, if the final influence display value of the factors corresponding to the dirt in a certain region is contained in the reference dirt influence offset value interval corresponding to the combined dirt in the problem offset feature library, using the combination as a new cleaning association combination corresponding to the dirt cleaning of the water area, thus obtaining each new cleaning association combination corresponding to the dirt cleaning of the water area, extracting the reference quality value corresponding to each new cleaning association combination from the library, arranging the reference quality values of each new cleaning association combination in a sequence from high to low, using the new cleaning association combination with the quality value ranked first as a first station cleaning region, and constructing the path optimization corresponding to the water area to be cleaned by the cleaning robot in the sequence.
9. The method for optimizing the full-area coverage path for the water surface cleaning operation according to claim 1, wherein the specific evaluation process of evaluating the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned is as follows: The method comprises the steps of monitoring path cleaning after a cleaning robot is optimized corresponding to a water area to be cleaned, obtaining performance data of the water area under the condition of performing cleaning operation, importing the performance data into a full-coverage evaluation model of the water surface cleaning path, and outputting a cleaning performance characteristic value, wherein the cleaning performance characteristic value comprises data of 1 and 0; When the characteristic value of the cleaning performance of the cleaning robot corresponding to the water area to be cleaned is 1, the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned is judged to be qualified, and when the characteristic value of the cleaning performance of the cleaning robot corresponding to the water area to be cleaned is 0, the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned is judged to be unqualified.
10. A full area coverage path optimization system performing the full area coverage path optimization method applied to a water surface cleaning operation as set forth in any one of claims 1 to 9, comprising: The system comprises a cleaning data acquisition module, a cleaning robot, a cleaning data analysis module and a cleaning module, wherein the cleaning data acquisition module is used for acquiring cleaning images of the cleaning robot in each historical water surface cleaning operation, constructing a problem base of the cleaning robot corresponding to the water surface cleaning operation, acquiring pollutant data corresponding to a current water area to be cleaned, and analyzing a cleaning problem set stored in the water area to be cleaned corresponding to the cleaning robot; the water surface cleaning path analysis module is used for analyzing each associable optimal cleaning combination of the cleaning operation of the cleaning robot corresponding to the water area to be cleaned based on the cleaning problem set of the cleaning robot corresponding to the water area to be cleaned, and analyzing the cleaning operation path of the cleaning robot corresponding to the water area to be cleaned; the water surface cleaning path optimizing module is used for monitoring a cleaning robot which executes cleaning operation on a water area to be cleaned according to the cleaning path, acquiring cleaning feedback data, analyzing the cleaning result of the cleaning robot corresponding to the water area to be cleaned, analyzing the covering path influence factor of the cleaning robot corresponding to the water area to be cleaned when the cleaning of the cleaning robot corresponding to the water area to be cleaned is problematic, executing path optimization of the cleaning robot corresponding to the water area to be cleaned, and evaluating the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned; and the early warning terminal is used for carrying out early warning prompt when the cleaning of the cleaning robot corresponding to the water area to be cleaned has problems or the cleaning coverage of the cleaning robot corresponding to the water area to be cleaned is unqualified.

Description

Full-area coverage path optimization method and system applied to water surface cleaning operation Technical Field The invention relates to the technical field of water surface cleaning path optimization, in particular to a full-area coverage path optimization method and system applied to water surface cleaning operation. Background Along with the continuous development of society, various industrial construction and the movable range of crowds are also continuously expanded, and the phenomenon of discarding garbage without civilization is also more serious, wherein the phenomenon of damage of a water area is particularly remarkable, so that the full-area coverage path optimization method and system applied to the water surface cleaning operation are provided, thereby realizing full-area coverage cleaning and cleaning on the water surface by using the cleaning robot, reducing the damage influence of pollutants on the water surface, intelligently and efficiently ensuring the ecological health of the water area, and ensuring the full-coverage cleaning of the water area. According to the prior art, as disclosed in the application publication No. CN114721400A, a path optimization method and a water surface garbage collection path planning based on an ant colony algorithm are disclosed, wherein S1 is used for modeling water surface garbage to obtain node coordinates of each water surface garbage, S2 is used for initializing parameters, S3 is used for starting from a starting point, S4 is used for selecting the next node according to pheromone and heuristic information of each node, the transition probability S5 of the ants k from the node i to the node j is calculated, the pheromone global updating is carried out according to an updating rule, S6 is used for judging whether the ants traverse all the nodes or find out an ending point, if yes, the step S7 is executed, otherwise, the step S4-S5 is skipped to continue to find paths, S7 is used for storing the searching route and the length of each ant, if yes, the searching route with the minimum length is selected as the optimal route if no, and if no, the step S3 is skipped. The invention mainly aims at collecting the water surface suspended garbage and is not used for cleaning various garbage stored on the water surface, so that when the path is optimized, the two garbage types are different in the direction of the composition and the factors considered, the problem of full-area cleaning cannot be formed according to the current situation of pollution stored on the water surface, meanwhile, the problem of the cleaning robot when the cleaning robot is used for cleaning the water surface is effectively acquired, the problem of the cleaning robot is difficult to avoid to reoccur, the effectiveness and the full coverage rate of the cleaning on the water surface are reduced, the functions of the robot are damaged to a certain extent, the workability of the cleaning robot is reduced, the water surface dirt is of various types, the affected factors are different, and therefore, when the influence of the factors on the water surface dirt changes, the path of the cleaning on the water surface cannot be timely perceived, and the cleaning on the water surface is in full-coverage and high-efficiency. Disclosure of Invention Aiming at the technical defects, the invention aims to provide a full-area coverage path optimization method and system for water surface cleaning operation. The invention provides a full-area coverage path optimization method applied to water surface cleaning operation, which comprises the following steps of firstly, acquiring cleaning data, namely acquiring cleaning images of a cleaning robot in each historical water surface cleaning operation, constructing a problem base of the cleaning robot corresponding to the water surface cleaning operation, acquiring pollutant data corresponding to a current water area to be cleaned, and analyzing a cleaning problem set stored in the water area to be cleaned corresponding to the cleaning robot. And step two, analyzing the water surface cleaning path, namely analyzing each associable optimal cleaning combination of the cleaning robot corresponding to the cleaning water area based on the cleaning problem set of the cleaning robot corresponding to the cleaning water area, and analyzing the cleaning operation path of the cleaning robot corresponding to the cleaning water area. And step three, optimizing a water surface cleaning path, namely monitoring a cleaning robot which performs cleaning operation on a water area to be cleaned according to the cleaning path, acquiring cleaning feedback data, analyzing a cleaning result of the cleaning robot corresponding to the water area to be cleaned, analyzing a covering path influence factor of the cleaning robot corresponding to the water area to be cleaned when the cleaning result of the cleaning robot corresponding to the water area to be cleaned is problematic, performing