Optimizing maximum velocity of fish robot using Hill Climbing Algorithm and Genetic Algorithm

Recently, the robotics research has been developed very fast in some kinds of robot such as: mobile robot, vision robot, humanoid robot and especially underwater robot. In the field of underwater robot, most of the researches focus mainly on ROV (Remotely Operated Vehicle), AUV (Autonomous Underwater Vehicle) or UUV (Unmanned Underwater Vehicle). In this field, the research about one kind of autonomous robot called fish robot still remain at low level of technology and there are many thing need to be done in this type of robot. In this paper, we present a model of 4-link (3 joints) fish robot. This fish robot´s maximum velocity is then optimized by using the combination of Hill Climbing Algorithm (HCA) and Genetic Algorithm (GA). We use HCA to generate the good initial population for GA and then use GA to find the optimal parameters that give maximum propulsion power in order to make fish robot swim at the fastest velocity. Finally, some simulation results are presented to prove this application.