Numerical Simulation and Analysis of Fish-Like Robots Swarm

• Published in: Applied sciences Vol. 9; no. 8; p. 1652
• Main Authors: Li, Shuman, Li, Chao, Xu, Liyang, Yang, Wenjing, Chen, Xucan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2019
• Subjects: Collaboration; Computational fluid dynamics; Computer simulation; Configurations; Efficiency; fish schooling; Fluid flow; Fluids; hydrodynamics; Hydrology; Incompressible flow; Kinematic viscosity; Kinematics; Mathematical models; Methods; Numerical analysis; Open source software; Researchers; robot controlling; Robots; robots swarm; Simulation; Swimming; swimming efficiency; Two dimensional flow; Underwater; Underwater robots; Velocity; Viscosity
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app9081652

Artificial fish-like robot is an important branch of underwater robot research. At present, most of fish-like robot research focuses on single robot mechanism behavior, some research pays attention to the influence of the hydro-environment on robot crowds but does not reach a unified conclusion on the efficiency of fish-like robots swarm. In this work, the fish-like robots swarm is studied by numerical simulation. Four different formations, including the tandem, the phalanx, the diamond, and the rectangle are conducted by changing the spacing between fishes. The results show that at close spacing, the fish in the back can obtain a large wake from the front fish, but suffers large lateral power loss from the lateral fish. On the contrary, when the spacing is large, both the wake and pressure caused by the front and side fishes become small. In terms of the average swimming efficiency of fish swarms, we find that when the fish spacing is less than 1.25 L (L is the length of the fish body), the tandem swarm is the best choice. When the spacing is 1.25 L , the tandem, diamond and rectangle swarms have similar efficiency. When the spacing is larger than 1.25 L , the rectangle swarm is more efficient than other formations. The findings will provide significant guidance for the control of fish-like robots swarm.