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On Coordinated Control of Multiple Bio-mimetic Robotic Fish

Author: ZhangYeMeng
Tutor: WangYiJing
School: Tianjin University
Course: Detection Technology and Automation
Keywords: Biomimetic robotic fish Coordinated control Fuzzy Control Artificial Potential Field Reinforcement learning algorithm
CLC: TP242
Type: Master's thesis
Year: 2010
Downloads: 128
Quote: 2
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Abstract


In the near future, the bionic robotic fish in a very complex underwater environment for marine life observation, the hard work of the seabed resource exploration, military reconnaissance and underwater construction. Therefore, for groups of robotic fish developed efficient, flexible, and and strong robust coordinated control method is an important research direction. Due to the complexity of the underwater environment, as well as a special robotic fish propulsion, general coordination control method is difficult to be applied directly in the body of the robot fish. Therefore, the coordinated control of multi-robot fish is a challenging research topic. Inspired by biological intelligence support as a basis for the successful development of the hardware platform of the robotic fish by the multi-robot coordination and control technology, the paper launched a multi bionic robotic fish coordinated control method. The first introduces the research background bionic robotic fish and its coordinated control method, the relevant research results at home and abroad, and briefly describes the main work. Then, the the polyarticular ROBOFISH kinetic model, the use of a common the robotic fish performance optimization method, we use three joint robotic fish straight Tour performance optimization. In addition, we have also fuzzy control basic idea is applied to speed coordinated control of multiple robotic fish. And then study the presence of coordinated control of two robotic fish in the environment of a plurality of obstacles. Artificial potential field method, to virtual robotic fish run space into an existing force field, and to establish a the mechanical relationship model between the robotic fish and the target points and obstacles between the robot fish. Using our method, two robotic fish can be done starting from their starting point, avoid obstacles and each other, smooth the task of reaching the target point. This method is based on robotic fish will effectively perform tasks underwater complex environment. The article also using reinforcement learning algorithm to design a two-machine fish turn vias task. Try different actions in different states, the machine fish obtain the return according to the results obtained, and guide the next action, according to the return value to eventually be able to independently choose the better the action strategy implemented in different states. Finally, some concluding remarks, and pointed out the need for further work in the future.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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