The 2D Aquatic Obstacle Avoidance Control Algorithm of the Snake-LikeRobot Based on Artificial Potential Field and IB-LBM

To improve the underwater adaptability of the multi-DOF (degree of freedom) snake-like robot with high redundancy,a 2D aquatic intelligent obstacle avoidance algorithm based on artificial potential field and IB-IBM (immersed boundary method-lattice Boltzmann method) is proposed.Firstly,the lattice Boltzmann method is used to describe 2D aquatic obstacle model and construct the unified form.Then,by applying immersed boundary method and combining the existing snake curve motion equation,the 2D aquatic obstacle avoidance model is deduced under the attraction and repulsion action of artificial potential field.Afterwards,the obstacle avoidance efficiency and safety of the snake-like robot are studied under different conditions,including changing obstacle distances,swing amplitude and swing frequency of the snake-like robot, the repulsive gains of obstacle points,the Reynolds number,the attractive gains of target points as well as other important parameters.Finally,the optimal values of every parameter are obtained by several simulations.The simulation results prove that the algorithm enables the snake-like robot to avoid the static obstacles in complex underwater environment and reach its destination swiftly,safely and efficiently when the parameters are optimal.The method can not only fully study the fluid structure coupling characteristics of the underwater snake-like robot and achieve the real-time obstacle avoidance effect,but also generate the optimal path by using the known environmental information.