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SUMMARYThis paper presents a model of a three-joint (four links) carangiform fish robot. The smooth gait or smooth motion of a fish robot is optimized by using a combination of the Genetic Algorithm (GA) and the Hill Climbing Algorithm (HCA) with respect to its dynamic system. Genetic algorithm is used to create an initial set of optimal parameters for the two input torque functions of the system. This set is then optimized by using HCA to ensure that the final set of optimal parameters is a “near” global optimization result. Finally, the simulation results are presented in order to demonstrate that the proposed method is effective.

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Recently, the underwater robotics research field has been developed quickly in some kinds of robot such as: ROV (Remotely Operated Vehicle), AUV (Autonomous Underwater Vehicle) or UUV (Unmanned Underwater Vehicle) and etc. These types of underwater robot mostly use propeller or thruster to generate the propulsion force in order to create the movement for robot. However, 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 robot type. Fish robot usually uses its body's oscillation or its fins' oscillation to create the movement for it self in underwater environment. In this paper, a model of 3-joint (4 links) fish robot type is presented. This fish robot's smooth gait or smooth motion is optimized by using the combination of Hill Climbing Algorithm (HCA) and Genetic Algorithm (GA). HCA is used to generate the good initial population for GA and then GA is used to find the optimal parameters set that make fish robot has a smooth gait or smooth motion. Finally, some simulation results are presented to prove this application.