BP neural network-based multimodal motion method and system of robot fish

A BP neural network and robot fish technology, applied in general control systems, control/regulation systems, instruments, etc., can solve problems such as the free movement of robot fish that are rarely studied, and achieve the goal of improving autonomy and adaptability, and improving the perception of the environment effect of ability

Active Publication Date: 2019-09-27
SHANDONG JIANZHU UNIV
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Problems solved by technology

Existing art rarely studies the free motion of robotic fish in nonlinear structu

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  • BP neural network-based multimodal motion method and system of robot fish
  • BP neural network-based multimodal motion method and system of robot fish
  • BP neural network-based multimodal motion method and system of robot fish

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[0040] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0041] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0042] Implementation example one

[0043] This embodiment discloses a multi-modal motion method for robotic fish based on BP ...

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Abstract

The invention provides a BP neural network-based multimodal motion method and system of robot fish. The method comprises the steps of building a CPG model; carrying out dynamic modeling on robot fish with pectoral fins at four joints, inhibiting pectoral fin CPGs by tail fin CPGs in a one-way manner, determining left and right input stimuluses, downlink and uplink phase coupling coefficients, uplink and downlink coupling coefficient weights and CPG frequencies corresponding to various joints by using nonlinear oscillator models as CPG neurons; building a BP neural network model; obtaining variations of joint angles on the basis of the CPG model, storing variation values of the joint angles as data packets for carrying out BP neural network training, and transmitting the trained data to a controller of the biomimetic robot fish; and driving swinging of various joints by using CPG signals and carrying out swimming and turning motions of the robot fish. According to the BP neural network-based multimodal motion method and system of the robot fish, multimodal motions of the robot fish are learned by using the BP neural network, so that the target of learning the multimodal motion processes of the robot fish through the BP neural network is finally achieved and the autonomy and the adaptability of a robot fish system are improved.

Description

technical field [0001] The present disclosure relates to the technical field of motion control, in particular to a multi-modal motion method and system for robotic fish based on BP neural network. Background technique [0002] In recent years, as the scarcity of land resources has become increasingly serious, people have paid more and more attention to the rich marine resources. Since the original underwater detection, operation, and delivery devices are difficult to meet the needs of complex underwater operations, the research and development of underwater robots has been accelerated. As the combination of fish propulsion mechanism and robot technology, the bionic robotic fish provides a new idea for the development of new underwater vehicles, and has important research value and application prospects. [0003] With the progress of society and the development of technology, the integration of artificial intelligence and control technology has created new research opportuni...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 汪明张燕鲁常征卫正逯广浩
Owner SHANDONG JIANZHU UNIV
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