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Underwater robot is a new research field which is emerging quickly in recent years.Previous researches in this field focuson Remotely Operated Vehicles(ROVs),Autonomous Underwater Vehicles(AUVs),underwater manipulators,etc.Fish robot,which is a new type of underwater biomimetic robot,has attracted great attention because of its silence in moving and energyefficiency compared to conventional propeller-oriented propulsive mechanism.However,most of researches on fish robots have been carried out via empirical or experimental approaches,not based ondynamic optimality.In this paper,we proposed an analytical optimization approach which can guarantee the maximum propulsivevelocity of fish robot in the given parametric conditions.First,a dynamic model of 3-joint(4 links)carangiform fishrobot is derived,using which the influences of parameters of input torque functions,such as amplitude,frequency and phasedifference,on its velocity are investigated by simulation.Second,the maximum velocity of the fish robot is optimized bycombining Genetic Algorithm(GA)and Hill Climbing Algorithm(HCA).GA is used to generate the initial optimal parametersof the input functions of the system.Then,the parameters are optimized again by HCA to ensure that the final set of parametersis the“near”global optimization.Finally,both simulations and primitive experiments are carried out to prove the feasibility ofthe proposed method.
Underwater robot is a new research field which is emerging quickly in recent years. Previous researches in this field focus on Remotely Operated Vehicles (ROVs), Autonomous Underwater Vehicles (AUVs), underwater manipulators, etc. Fish robot, which is a new type of underwater biomimetic robot, has attracted great attention because of its silence in moving and energyefficiency compared to conventional propeller-oriented propulsive mechanism. Yet, most of researches on fish robots have been carried out via empirical or experimental approaches, not based on dynamic optimality. In this paper , we proposed an analytical optimization approach which can guarantee the maximum propulsivevelocity of fish robot in the given parametric conditions. First, a dynamic model of 3-joint (4 links) carangiform fishrobot is derived, using which the influences of parameters of input torque functions , such as amplitude, frequency and phasedifference, on its velocity are investigated by simulation. Second, the maximum velocity of t he fish robot is optimized bycombining Genetic Algorithm (GA) and Hill Climbing Algorithm (HCA) .GA is used to generate the initial optimal parametersof the input functions of the system.Then, the parameters are optimized again by HCA to ensure that the final set of parametersis the “near ” global optimization. Finally, both simulations and primitive experiments are carried out to prove the feasibility ofthe proposed method.