Obstacle avoidance learning for biomimetic robot fish

被引：0

作者：

Shen, Zhizhong ^{[1
]}

Tan, Min ^{[1
]}

Cao, Zhiqiang ^{[1
]}

Wang, Shuo ^{[1
]}

Hou, Zengguang ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2006年

关键词：

D O I：

10.1142/9789812774118_0101

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Biomimetic robot fish can play an important role in underwater object reconnaissance and tracking. In order to fulfill more complex tasks, the capability of obstacle avoidance is an indispensable one for robot fish. The design of biomimetic robot fish with multiple ultrasonic and infrared sensors is presented in the paper. An obstacle avoidance strategy based on the reinforcement learning is proposed. State-behavior pairs are obtained. Computer simulation shows the validity of the learning results.

引用

页码：719 / +

页数：2

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