Page 91 - Read Online

Page 189 Yu et al. Intell Robot 2022;2:180-99 https://dx.doi.org/10.20517/ir.2022.10

Table 3. Research methods to study the swimming mechanism of robot fishes
Research methods Strengths Weaknesses
Theoretical analysis Very adaptable Mathematically challenging
Experimental observation Highly accurate Poor universality
Numerical simulation Low cost Solving a limited number of problems
Accurate

fin oscillation . It is frequently necessary to construct special experimental platforms in order to meet the
[24]
measurement of specific physical quantities. As shown in Figure 8, the robot fish was immersed in a tank
and the swimming speed was measured .
[27]
3.3. Numerical simulation
In recent years, computer technology, computational fluid dynamics (CFD), and other disciplines have
advanced rapidly. New iterations of computers have led to a significant increase in computing power,
allowing some complex swimming problems to be solved. The calculation model is continuously improved
in practice, resulting in increasing accuracy of the calculation. Thus, numerical simulation has made it
possible to acquire accurate answers to some complex swimming problems. Currently, many research
results are available. The hydrodynamic performance of fish of different shapes near the water surface using
CFD was studied by Zhan et al. . Using an incompressible Navier-Stokes flow solver based on the
[39]
[40]
immersion boundary method, Liu et al. studied the body-fin and fin-fin interactions . Han et al. used the
same solver as Liu et al. to simulate the swimming of the fish on the static cartesian grid [40,41] . The
interactions between the intermediate fins were analyzed in detail. The CFD method was used by Macias et
al. to simulate the swimming process of the fish in undisturbed water flow . Zhu et al. combined the
[42]
immersed boundary-lattice Boltzmann method in numerical simulation with a deep recurrent Q-network to
[43]
simulate the behavior of fish . It provided an effective method for researching fish adaptation behaviors in
complex environments. All of the above swimming problems require a massive amount of computation,
which was previously extremely difficult to achieve. From the results of the calculations, all of the authors
considered that the accuracy of the calculations met the requirements. We believe that numerical simulation
as a method will have considerable potential in the future.

3.4. Multiple research methods
Using multiple research methods to analyze a problem, each research method can not only complement
each other’s strengths but also verify the results of the others, which increases the convincingness of the
research. Korkmaz et al. established kinematic and dynamic models of the robot fish using the Denavit-
Hartenberg method and Lagrange method, respectively . The swimming of the robot fish was simulated
[2]
using MATLAB/Simulink. Experiments in the pool validated the simulation results. Behbahani et al.
established the dynamic model of robot fishes using the rigid body dynamics theory . The hydrodynamic
[44]
force acting on the pectoral fin was solved by the blade element theory. The kinetic model was evaluated
[45]
experimentally. The dynamic equation of the fish in autonomous swimming was established by Xin et al. .
The steering motion of fish was simulated using three-dimensional (3D) CFD software. Liu et al. established
a kinematic model by simplifying the caudal fin to a rigid hydrofoil and the caudal peduncle to a rigid
plate . The caudal fin propulsion mechanism was analyzed using CFD to determine the principle of
[46]
generating propulsive power. It can be anticipated that this method will be used by more and more
researchers and become a new research trend.

4. MOTION COORDINATION AND COMMUNICATION OF MULTIPLE ROBOT FISHES
The research of multiple robot fishes emerged in recent years and is now a hot research field. When