A path planning method for aquaculture cage cleaning robotic arm

Through the three-level architecture of regional blocking and clustering optimization, the problems of high computational complexity and poor adaptability of the traditional ant colony optimization algorithm in aquaculture cage cleaning are solved, efficient path planning and multi-robotic arm collaborative operation are achieved, and cleaning efficiency is improved.

CN120503218BActive Publication Date: 2025-09-26SANYA SCI & EDUCATION INNOVATION PARK WUHAN UNIV OF TECH
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Patent Information

Application Number
CN202511007151.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-07-22
Publication Date
2025-09-26
Estimated Expiration
2045-07-22

AI Technical Summary

Technical Problem

In the existing technology, the traditional ant colony optimization algorithm (ACO) has high computational complexity, many iterations, and poor adaptability in aquaculture cage cleaning. It is difficult to find the optimal path within a reasonable time, especially in large-scale areas and uneven distribution.

Method used

A three-level architecture of regional partitioning, cluster optimization and global integration is adopted. The large-scale area to be cleaned is divided into multiple sub-areas through K-means clustering. Ant colony optimization is performed independently, and the global path is generated by combining the pheromone positive feedback mechanism and the state transition probability formula.

Benefits of technology

It significantly reduces the computational complexity and number of iterations, improves the accuracy and efficiency of path planning, enhances adaptability, supports collaborative operation of multiple robotic arms, and improves cleaning efficiency by 20%-30%.

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Abstract

The present invention provides a path planning method for a cage cleaning robot arm, the method comprising: S11, obtaining three-dimensional coordinate data of an area to be cleaned and performing two-dimensional mapping to obtain a two-dimensional area to be cleaned; S12, if the number of two-dimensional areas to be cleaned is less than or equal to a preset threshold, directly performing path planning for the two-dimensional areas to be cleaned using an ant colony optimization algorithm; if the number of two-dimensional areas to be cleaned is greater than the preset threshold, then dividing the two-dimensional areas to be cleaned into blocks using a clustering algorithm to obtain several two-dimensional sub-areas to be cleaned, and then performing path planning for the several two-dimensional sub-areas to be cleaned using an ant colony optimization algorithm; S13, integrating the optimal paths of the two-dimensional areas to be cleaned / two-dimensional sub-areas to be cleaned to generate a global path; S14, inversely mapping the global path to obtain a three-dimensional spatial path planning diagram. The present invention systematically solves the problem of balanced task allocation during collaborative operation of multiple robot arms through a three-level architecture of regional block division, cluster optimization, and global integration.
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