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CPG-based autonomous swimming control for multi-tasks of a biomimetic robotic fish

机译:基于CPG的仿生机器人鱼多任务自动游泳控制

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This work emphasizes the artificial intelligent control of the developed biomimetic robotic fish (i-RoF) based on sensory feedback Central Pattern Generator (CPG) approach. In order to obtain rhythmic, robust and adaptable closed loop control performance, a novel control mechanism, composed of two subsystems; as a biological based CPG network and a Fuzzy Logic controller, is proposed. The CPG network behaves as an artificial spinal cord, inspired by Lampreys. It is constructed as unidirectional chained network with Sensory Neurons (SNs) which can perceive the external stimulus. The Fuzzy Logic control structure is also designed as a decision-making mechanism and a Finite State Machine (FSM) algorithm is proposed to perform the given missions autonomously. In the experimental studies, different scenarios are created for both situations as autonomous swimming and encountering obstacles while taking on a primary task, which is determined with yaw control. Autonomous swimming ability is performed in the real pool environment with proposed scenarios that are likely to be encountered in a real environment. It is observed that autonomous swimming performance is excellent and yaw control is quite good even in the presence of obstacles. It is also proved that the escape performance of the robot is very fast.
机译:这项工作强调了基于感官反馈中央模式发生器(CPG)方法的仿生机器人鱼(i-RoF)的人工智能控制。为了获得有节奏,鲁棒和适应性强的闭环控制性能,一种新颖的控制机制由两个子系统组成。提出了一种基于生物的CPG网络和模糊逻辑控制器。 CAMP网络的行为就像是受Lampreys启发的人工脊髓。它被构造为具有感觉神经元(SN)的单向链接网络,可以感知外部刺激。模糊逻辑控制结构还被设计为决策机制,并提出了一种有限状态机(FSM)算法来自主执行给定任务。在实验研究中,针对两种情况都创建了不同的场景,例如自主游泳和在执行主要任务时遇到障碍,这由偏航控制确定。在真实的泳池环境中使用可能在真实环境中遇到的建议方案执行自主游泳能力。据观察,即使在有障碍物的情况下,自主游泳性能也很出色,并且偏航控制也非常好。还证明了机器人的逃生性能非常快。

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