中文摘要：

具有嵌入式视觉的仿生机器鱼的摄像头往往安装在头部,为了获取稳定的图像数据,研究了游动过程中头部的平稳性控制问题.首先,基于牛顿-欧拉方法对仿生机器鱼的水动力学进行建模.然后,基于动力学模型,比较了两种鱼体波模型下的机器鱼头部摆动情况.进一步地采用遗传算法对输入到运动关节的参数进行优化,实现机器鱼头部的最小摆动.最后,在自主设计的具有嵌入式视觉的仿生机器鱼上进行了实验.结果表明,在平稳性控制后,头部的摆动幅度明显减小,采集到的图像的稳定性与连续性有较大改进,但游动速度有所降低.该方法为基于嵌入式视觉的运动控制与任务执行提供了有效保障.

英文摘要：

The camera is generally installed in the head of a biomimetic robotic fish with embedded vision. The issue of stability control of the head is explored to guarantee the steady acquisition of image data. Specifically, hydrodynamics of the biomimetic robotic fish is modeled based on the Newton-Euler method, which is applied to comparing the head swing status in the cases of different body models. In addition, a genetic algorithm is developed to optimize parameters for multiple moving joints, intended to minimize the swing of the robotic fish＇s head. Finally, experiments are conducted on a self- designed biomimetic robotic fish equipped with an embedded vision system. The results indicate that the swing of the head is decreased and the imaging stability and continuity are greatly improved by the stability control. However, it is inevitable that the swimming velocity decreases. This method lays the foundation for locomotion control and task execution based on embedded vision.