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Page 195 Yu et al. Intell Robot 2022;2:180-99 https://dx.doi.org/10.20517/ir.2022.10

Table 4. Typical robot fishes and their performance parameters
Maximum swimming speed Frequency (hertz)
Reference -1 -1 Minimum turning radius (m) Caudal Swimming type Structural type
BL·s m·s Pectoral fins
fin
Ref. [19] 0.5(Ave) 0.23(Ave) 0.78(Ave) NA --- BCF Soft
Ref. [20] 0.25 0.037 NA 0.75 --- BCF Soft
Ref. [24] 4 1.02 NA 15 --- BCF Rigid-soft
Ref. [22] 2.5 0.25 NA NA --- BCF Rigid-soft
Ref. [25] 0.87 0.31 NA 2.9 --- BCF Rigid-soft
Ref. [26] 0.45 0.052 NA --- 1 MPF Soft
Ref. [28] 0.94 0.43 ≈0 --- NA MPF Rigid-soft
Ref. [27] NA 0.013 NA --- 4 MPF Rigid-soft
Ref. [30] 0.69 0.064 0.085 NA NA BCF-MPF Soft
Ref. [29] NA 0.062 0.234 NA NA BCF-MPF Soft
Ref. [32] 0.66 0.365 0.139 NA NA BCF-MPF Rigid-soft

Frequency (hertz) indicates the value at the maximum (or Ave) swimming speed. The ranking of the references is based on the magnitude of the
-1
maximum swimming speed (BL·s ) of the robot fish and is classified by swimming type and structural type. NA: Not available; Ave: average; BCF:
body and/or caudal fin; MPF: median and/or paired fin.

demonstrates the gap in swimming performance between robot fishes and fish, which is an urgent problem
to be solved. We believe there are several approaches to solve this problem. The first approach is to
investigate the effect of the vortices on the swimming efficiency of robot fishes. We believe that the high
propulsion efficiency of fish is closely related to the vortices they generate when they swim. It is possible to
improve the swimming efficiency of robot fishes by measuring the vortices generated when fish swim and
reproducing them in robot fishes. The second approach is to narrow the gap between the drive systems of
robot fishes and the muscles and skin of fish. Robot fishes simulate the swimming of fish by using multiple
rigid connecting rods. Fish have a flexible body made up of muscles and skin that allows them to swim
continuously and supplely. However, due to the rigidity of the connecting rod and the limitation of the
number of rods, the motion of robot fishes exhibits a discrete and unnatural movement. Attempts can be
made to flex the connecting rod to achieve continuous motion of robot fishes, thus improving
maneuverability. The third approach is to further reduce the water resistance of robot fishes when
swimming. Water resistance is currently decreased mostly by designing the shape of the robot fish to be
streamlined. Fish, on the other hand, have fish scales and mucous on their bodies, which can considerably
reduce resistance. However, the relevant design is rarely observed in the current robot fishes. The fourth
approach is to conduct an in-depth investigation of robot fishes in the BCF-MPF propulsion mode. Robot
fishes in BCF propulsion mode swim fast but have poor maneuverability. In contrast, robot fishes in MPF
propulsion mode have great maneuverability but slow swimming speed. The BCF-MPF propulsion mode
combines the above two propulsion modes, which can accurately imitate the swimming of fish. With a
reasonable design, it can achieve high swimming speed and great maneuverability and has wider application
prospects. This is a promising research direction. The final approach is to use sensor technology to create
close connections between robot fishes and fish. Replicating the swimming process of fish can improve the
swimming performance of robot fishes. Through the sensors, we obtain real-time feedback data (body
deformation, etc.) when fish swim, further completing the monitoring of the entire swimming process.
Finally, the collected data are applied to robot fishes. This allows robot fishes to make rhythmic movements
similar to fish, improving their swimming performance.

● The majority of studies have only used one research method to investigate the swimming mechanism of
robot fishes. Actually, each research method has its own strengths and weaknesses. Because of the