Volume 128, Number 5, December 2019
|Number of page(s)||6|
|Published online||03 February 2020|
The role of visual angle in pattern phase transition of collective motions
1 School of Artificial Intelligence and Automation, the State Key Lab of Digital Manufacturing Equipment and Technology, and the Key Lab of Image Processing and Intelligent Control, Huazhong University of Science and Technology - Wuhan 430074, PRC
2 Department of Electronic Engineering, City University of Hong Kong - Kowloon, Hong Kong
3 China-EU Institite for Clean and Renewable Energy, Huazhong University of Science and Technology Wuhan 430074, PRC
(a) firstname.lastname@example.org (corresponding author)
Received: 8 November 2019
Accepted: 13 December 2019
Abundant collective motion patterns of animal groups have different kinds of functions like migration, predator avoidance and foraging. To explore the phase transition mechanism behind such charming collective behaviors, some self-propelled particle models have been proposed, most of which however have isotropic inter-particle interactions and hence could not reproduce sophisticated natural collective patterns. As a remedy, this letter develops an anisotropic self-propelled particle model. By slightly tweaking the vision range and inter-particle attraction, the proposed model demonstrate transitions between four distinct collective motion patterns, i.e., torus, dumbbell, twist, and worm. To investigate more insightfully into the phase transition nature, quantitative analysis is carried out, revealing the relationship of visual angle-based inter-agent interactions and abundant pattern transitions existing in large numbers of natural, social and artificial grouping behaviors. From the industrial application point of view, the present study can help adjust the formation of multiple unmanned systems by simply tweaking a couple of vision-related parameters in their models.
PACS: 05.65.+b – Self-organized systems / 45.70.Qj – Pattern formation / 64.60.-i – General studies of phase transitions
© EPLA, 2020
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