Cooperative Optimal Collision Avoidance Laws for a Hybrid-Tailed Robotic Fish

避碰 碰撞 控制理论(社会学) 执行机构 计算机科学 法学 模拟 人工智能 控制(管理) 计算机安全 政治学
作者
Vishwamithra Sunkara,Animesh Chakravarthy,Xiongfeng Yi,Wenyu Zuo,Zheng Chen
出处
期刊:IEEE Transactions on Control Systems and Technology [Institute of Electrical and Electronics Engineers]
卷期号:28 (4): 1569-1578 被引量:21
标识
DOI:10.1109/tcst.2019.2910478
摘要

This brief addresses the problem of collision avoidance by robotic fish that have a single caudal fin. The fish is hybrid-tailed in that the caudal fin is driven by a double-jointed mechanism. One joint is driven by a servomotor and the second joint is driven by an ionic polymer-metal composite (IPMC) actuator, which is often called an artificial muscle. For this type of robotic fish, collision avoidance is performed by employing a collision cone approach. Within the framework of the collision cone approach, Lyapunov-based methods are employed to determine analytical expressions of nonlinear guidance laws with which cooperative collision avoidance can be achieved. It is shown how these cooperative collision avoidance laws can be made optimal in the sense of minimizing an energy-like performance index. The conditions under which the developed guidance laws are robust to sensor measurement errors are determined. Simulations and experiments are performed to validate the guidance laws.
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