Obstacle Avoidance Algorithm of Bionic Robots in Fluid Based on IB-LBM

This study implements a coupled Immersed Boundary-Lattice Boltzmann Method (IB-LBM) to numerically investigate the propulsion mechanisms and motion control strategies in tadpole swimming. The computational framework establishes a periodic flow field within a straight channel using the Lattice Boltzmann Method (LBM), while resolving fluid-structure interactions between the tadpole's body and surrounding flow through the Immersed Boundary (IB) formulation. By introducing an angular compensation parameter to generate asymmetric tail undulation, we achieved precise directional control of tadpole locomotion, thereby implementing a bio-inspired "sensing-control" strategy. Numerical results demonstrate that the proposed methodology successfully achieves stable trajectory correction and environmental adaptability, providing new insights into bio-mechanism-inspired underwater robotic control systems.