Abstract
Experimental systems for analyzing robotic fish swimming play a crucial role in optimizing robotic fish, which prompted us to design an experimental system that combines information from multiple sensors to address the shortcomings of current experimental systems with a single measurement. Furthermore, we are interested in a multi-fin co-drive robotic fish. This paper presents the design of a robotic fish, LUO-V2, and an experimental system, MSPerception. The LUO-V2 represents a novel solution for developing multi-fin co-drive robotic fish. It also provides a controller for LUO-V2, which can synchronously control the multi-fin of the robotic fish. Furthermore, the MSPerception system has been designed based on the fusion of multi-sensor information, which can sense the average thrust, swimming speed, and flow field, which provides an effective tool for studying robotic fish swimming. MSPerception was employed to investigate the factors influencing the swimming performance of LUO-V2 and to compare it with the flow field around the caudal fin of a real fish. The experimental results demonstrated that the multi-fin co-drive significantly enhanced the robotic fish’s performance. This research can provide a theoretical foundation for developing multi-fin co-drive robotic fish and experimental systems.
Published Version
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