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Soft Robotic Fish Actuated by Bionic Muscle With Embedded Sensing for Self-Adaptive Multiple Modes Swimming

Ruiqian Wang, Wenjun Tan, Yiwei Zhang, Lianchao Yang, Wenyuan Chen, Feifei Wang, Jiandong Tian, Lianqing Liu

Year
2025
Citations
17

Abstract

Fish can adaptively adjust their body kinematics and swimming modes by sensing to realize optimal propulsion. However, most soft robotic fish have an unchangeable swimming mode through simple structure design, making them difficult to adapt to dynamic and complex fluid environments. Here, inspired by the multiple muscle synergy and lateral line sensing function of fish, we developed a soft robotic fish with multiple actuating units and embedded sensing elements. By collaboratively controlling the amplitude and phase of excitation from the multiple flexible actuating units, the soft robotic fish can successfully realize various swimming modes very similar to those of natural fish. Additionally, the embedded flexible sensing elements enable the robotic fish to sense the swimming state and the surrounding fluid environment in real time. The multiple actuation and embedded sensing allow the soft robotic fish to adaptively switch to an optimal swimming mode in a certain fluid environment. The multimode swimming and perception capabilities proposed in this work not only make soft robotic fish more intelligent and adaptable to complex fluid environments, but also contribute to the future implementation of autonomous control capabilities for robotic fish.

Keywords

Soft roboticsComputer scienceBiomimeticsRobotControl engineeringArtificial intelligenceControl theory (sociology)Engineering

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