Online Velocity Estimation of a Robotic Fish Using Artificial Lateral Line System With Velocity-Decoupling Sensing Ability

The robotic fish has attracted widespread research interest over the past few decades, due to its outstanding agility and environmental friendliness. And the sensing ability of underwater environments is crucial for the robotic fish to accomplish various underwater tasks. Inspired by the lateral line of real fish, many types of artificial lateral line (ALL) sensors have been proposed, including pressure-based sensors and deformation-based sensors. However, currently these types of ALL sensors mounted on robotic fish are susceptible to the interference from robotic fish's self-motions such as yaw motion and pitch motion, as well as the unavoidable vortices around the robotic fish. To address the above issues, a deformation-based magnetic ALL sensor capable of flow velocity-decoupling sensing is proposed, which can be used to measure the swimming speed of the robotic fish while suppressing the aforementioned noise. Besides, an ALL array is designed and mounted on both sides of a robotic fish, enabling the measurement of its swimming speed under both rectilinear and turning motion, with a mean absolute error (MAE) of 0.0153 m/s and 0.0125 m/s, respectively. Based on this, the ALL array is applied for trajectory estimation of the robotic fish, and the MAE of trajectory estimation under rectilinear and turning motion is 0.0600 m and 0.0730 m, respectively.