In order to study the adaptability of a multi-redundancy and multi-degree-of-freedom snake-like robot to underwater motion, a two-dimensional (2-D) obstacle avoidance control algorithm for a snake-like robot based on immersed boundary-lattice Boltzmann method (IB-LBM) and improved artificial potential field (APF) is proposed in this paper. Firstly, the non-linear flow field model is established under the framework of LBM, and the IB method is introduced to establish a fluid solid coupling of a 2-D soft snake-like robot. Then, the obstacle avoidance of a snake-like robot in a flow field is realized by optimizing the curvature equation of the serpentine curve and eliminating the local minimum in APF method. Finally, the effects by exerted different control parameters on a snake-like robot’s obstacle avoidance capability are analyzed via MATLAB simulation experiment, by which we can find the optimal parameter of the obstacle avoidance and testify the validity of the proposed control algorithm.

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Aiming at the problem of trajectory tracking between joints of the multi-joint snake-like robot in the flow fields, a trajectory tracking control law proposed based on the improved snake-like curve of a multi-joint snake-like robot to avoid obstacles in the flow fields is studied. Firstly, considering the external disturbance that the fluid environment may impose on the multijoint snake-like robot system, from the point of view of probability, the fluid-solid coupling models of the obstacle channel and multi-joint snake-like robot are established in the flow field by using immersed boundary-lattice Boltzmann method algorithm, which solves the problem of nonlinear fluid motion that cannot be explained by solving the Navier-Stokes (N-S) equation. Then, a potential function is applied to the multi-joint snake-like robot so that the head of the robot can avoid obstacles in the fluid smoothly. By improving the snake-like motion equation, the snake-like curve trajectory tracking function of each joint of the multi-joint snake-like robot with time variation is obtained, which enables the tail joints of the snake-like robot to track the motion trajectory of the head joints. Finally, the effects of different flow field density, velocity, and Reynolds numbers on trajectory tracking of the multi-joint snake-like robot are studied by MATLAB simulations and experiments. The theoretical analysis and numerical simulation show that the designed trajectory tracking control law can make the multi-joint snake-like robot track the trajectory of the front joint when the robot encounters obstacles and make the robot stabilize the lateral distance, longitudinal distance, and direction angle, so as to effectively avoid obstacles. The simulation and experimental results verify the effectiveness of the trajectory tracking control law.

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