
Research on Cooperative Search and Dynamic Target Encirclement of Unmanned Surface Vehicle Swarms Based on Improved Pheromone Algorithm
Author(s) -
Antong Zhang,
Yunfan Yang,
Zhuo Chen,
Tao Bao,
Yu Guo,
Xu Liu,
Wenhui Yin
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3596844
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Concentrating on the practical needs of effective collaborative search and encirclement techniques for unmanned surface vehicles (USVs). This study proposes a collaborative search technique, focusing on enhancing the efficiency, preventing early pheromone accumulation, and achieving local optimality, in response to challenges in the regional coverage search of USVs in unfamiliar settings. The system creates a technique for revising hazardous grids and identifying adjacent locations. Global guidance is provided by the primary grid, while the sub-grid serves the purpose of local optimization. The efficiency of searching sub-grids is enhanced by dynamically modifying their search density via the mechanism of pheromone decay or enhancement. A method of dynamically distributed encirclement is suggested to address the challenge of dynamically allocating encirclement roles and preserving the stability of formation during the encirclement of dynamic targets. Encirclement occurs through the creation of encirclement contracts and the creation of potential points for encirclement, while the potential points for encirclement in dynamic targets are judiciously distributed, facilitating rapid formation of an encirclement by several USVs. Following this, simulations are conducted to test the aforementioned algorithms, leading to the optimization of their control parameters. A total of six USVs were employed to conduct a search for coverage with in a 400 m×400 m zone. The outcomes of the simulations revealed that a single USV located the target in 53.5 seconds, while the rest ceased their search swiftly, created an encirclement at 85.3 seconds, attained the threshold in 101.3 seconds, autonomously avoid obstacles, and finished the encirclement task. Ultimately, the lake study was confirmed using four USVs, which located the target upon achieving 64% area coverage, smoothly transitioned from search to encirclement mode, and ultimately accomplished the encirclement task. The effectiveness and rationality of this method were successfully confirmed through simulations and experiments.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom