仿生学习的机器鱼运动模式分析

Study on the fish robot locomotion based on biomimetic method

运动行为建模是机器鱼研究领域的重点和难点,研究将一种新颖的仿生学习方法应用到多关节机器鱼运动模式学习和生成上。首先,通过视频采集设备对鲤鱼的运动行为进行记录,并对记录的视频数据作离散化处理后进行分析,提取得到了鲤鱼的3个基本运动模式:"巡游"、"游动转弯"和"C形急转"。然后采用通用内部模型(general internal model,GIM)对鲤鱼的运动模式进行学习,利用其函数逼近能力和在时间、空间上的可伸缩性,机器鱼可以学习、修正和再现真鱼的运动模式。最后结合红外传感器及避障算法实现了机器鱼的自主避障行为,从而证实了该方法的有效性。

Locomotion behavior modeling is a key and difficult problem in the research field of robotic fish.In this paper,a novel biomimetic learning approach is applied to the movement patterns generation of a multi-joint robotic fish.Firstly,the real fish behaviors are recorded by video system.By analyzing the recorded data,three basic swimming patterns,＂cruise＂,＂cruise in turning＂and ＂C sharp turn＂,are extracted.Then the general internal model（GIM）is employed to learn the swimming patterns of carangiform fishes.Based on the approximation ability and the temporal-spatial scalabilities of GIM,robotic fish owns the capability of learning,modifying and regenerating the similar swimming patterns of the real fish.Finally,autonomous obstacle avoidance behavior of the robotic fish is realized by combining infrared sensors and obstacle avoidance algorithm.The experiment result verifies the validity of theproposed biomimetic learning approach.