Recently, the number of jellyfish has been rapidly grown because of the global warming,
the increase of marine structures, pollution, and etc. The increased jellyfish is a threat to the marine
ecosystem and induces a huge damage to fishery industries, seaside power plants, and beach
industries. To overcome this problem, a manual jellyfish dissecting device and pump system for
jellyfish removal have been developed by researchers. However, the systems need too many human
operators and their benefit to cost is not so good. Thus, in this paper, the design, implementation, and
experiments of autonomous jellyfish removal robot system, named JEROS, have been presented. The
JEROS consists of an unmanned surface vehicle (USV), a device for jellyfish removal, an electrical
control system, an autonomous navigation system, and a vision-based jellyfish detection system. The
USV was designed as a twin hull-type ship, and a jellyfish removal device consists of a net for
gathering jellyfish and a blades-equipped propeller for dissecting jellyfish. The autonomous
navigation system starts by generating an efficient path for jellyfish removal when the location of
jellyfish is received from a remote server or recognized by a vision system. The location of JEROS is
estimated by IMU (Inertial Measurement Unit) and GPS, and jellyfish is eliminated while tracking the
path. The performance of the vision-based jellyfish recognition, navigation, and jellyfish removal was
demonstrated through field tests in the Masan and Jindong harbors in the southern coast of Korea.