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  • [ February 25, 2020]

    A Breakthrough of Artificial Lateral Line Based Trajectory Estimation of Fish Robot

  • Prof. Guangming Xie's group in College of Engineering has provided a novel way to evaluate the trajectory of underwater robot using fish lateral line inspired pressure sensor arrays. The related work has been published in the IEEE Transactions on Robotics, a flagship journal in robotics research.

    Lateral line system is a mechanoreceptive organ system that provides fish with flow-relative information. Inspired by this typical biological phenomenon, Xie’s group studies how a robotic fish uses its onboard artificial lateral line system (ALLS) to measure the pressure variations (PVs) around itself, then estimating the motion parameters including linear velocity, angular velocity, and motion radius of the robotic fish using the HPVs.

    Figure 1 Robotic Fish with Artificial Lateral Line System

    Specifically, a pressure variation (PV) model which links motion parameters to PVs surrounding the robotic fish is first built. Then, a nonlinear regression analysis method is used for determining the model parameters. Based on the acquired PV model, motion parameters mentioned above can be estimated by solving the PV model inversely using the PVs measured by ALLS. Finally, a trajectory estimation method is proposed for estimating trajectory of the robotic fish based on the ALLS-estimated motion parameters. The experimental results show that the robotic fish is able to estimate its trajectory in the above-mentioned multiple motions using ALLS, with small estimation errors.

    The work mentioned above has been published as Regular Paper in IEEE Transactions on Robotics. (X. Zheng, W. Wang, M. Xiong, & G. Xie, “Online State Estimation of a Fin-Actuated Underwater Robot Using Artificial Lateral Line System”, 2020). Link: https://ieeexplore.ieee.org/document/9004516

    Xingwen Zheng and Prof. Guangming Xie are the first author and corresponding author of the paper mentioned above, respectively. The work was supported in part by grants from the National Natural Science Foundation of China (NSFC, No. 91648120, 61633002, 51575005) and the Beijing Natural Science Foundation (No. 4192026). The collaborators are from Massachusetts Institute of Technology and Boya Gongdao (Beijing) Robot Technology Co., Ltd., China.

    Figure 2 Artificial Lateral Line Based Trajectory Estimation of Fish Robot in Multiple Motions (From the published paper)