| 英文摘要 | The Center Pattern Generator (CPG) based locomotion control methods applied to biomimetic swimming robots, i.e., robotic fish and robotic dolphin, pose new opportunities and challenges. This paper has proposed a CPG-coupled hydrodynamic model for the bio-inspired robotic fish on the basis of fish swimming mechanisms. The influence of varying CPG parameters on the robotic fish’s behaviors has also been explored. A nearest-coupling limit-cycle-based CPG model for multi-link robotic fish with pectoral fins has been proposed, which solves the multimodal locomotion control problem. With a combination of sensory signals and descending commands from the mesencephalic locomotor region located in the midbrain, the robotic fish acquires enhanced adaptation and higher maneuverability. The CPG-based model of robotic fish has further been extended to the locomotion control of robotic dolphin. It successfully combines discrete motions with rhythmic motions, which builds the foundation of designing a versatile controller capable of producing multimodal motions for bio-inspired robots. This paper mainly deals with the CPG modeling, CPG-based multimodal locomotion control, dynamic modeling, path planning, mechanism design, system integration, coordination control, etc. The technical contributions of this paper are summarized below. Firstly, we present a CPG-coupled dynamic model of bio-inspired robotic fish. Since the robotic fish has been constructed with a rigid anterior head, a flexible rear body and an oscillating caudal fin, it is reasonable to simplify swimming robotic fish as a moving multi-link rigid body in fluids. Considering that the thrust of fish mainly results from the force of trailing vortex, additional lateral pressure and leading-edge suction force, the dynamic equations of the swimming robotic fish have been derived by summing up the longitudinal force, lateral force and yaw moment on each propulsive component. Using the CPG output signals from Ijspeert’s phase oscillator-based CPG model as robotic fish’s link driven stimulus, the estimated propulsive characteristics, such as motion trajectory, propulsive resultant force, link oscillating angle, can then be obtained by solving the ordinary differential equations in Mathematica environment. The effect of CPG parameters has been analyzed. The simulation results show the validity of the CPG-coupled dynamic model. Secondly, by integrating nonlinear oscillators together with nearest-coupling ... |
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