A Biomimetic Robotic Fish Path Planning Method Based on Dynamic Obstacle-avoidance Risk Region

Aiming at the autonomous collision-avoidance problem of the pectoral and caudal fin co-propelled biomimetic robotic fish in a complex aquatic environment with a fixed incoming flow velocity and the presence of multiple static floating obstacles and dynamic obstacles, a path planning method based on dynamic avoidance risk region (DAR) is proposed. Firstly, an ellipsoid-like dynamic avoidance risk region along the direction of obstacle movement is constructed according to the established hydrodynamic model of the robotic fish by using extended Kalman filtering, whose long axis is proportional to the speed of obstacle movement, and the noise variance of the Kalman filtering process is estimated through a fuzzy control method, to get the precise boundary of the region. Secondly, the non-risky obstacles moving in the same direction as the robotic fish at a greater speed are removed according to the position and speed of obstacles in the field-of-view of the robotic fish, the set of obstacle avoidance risk regions in the dynamic environment is obtained in real time, and then the time-varying passable region of robotic fish is acquired. Finally, a spatial collision-avoidance strategy is preliminarily determined, in which the robotic fish steers firstly and then pitches according to the principles of avoiding the nearest obstacle firstly and then plenty of other obstacles, and keeping the shortest distance from the safe region boundaries. Taking the obstacles as an external perturbation, a nonlinear model predictive controller is designed with the desired pose as input to optimize the control parameters such as turning radius, pitch angle and phase difference between two pectoral fins in real time, so as to drive the robotic fish to pass through the current obstacle area safely and quickly. The experimental results show that when the robotic fish passes through the multi-obstacle area, the minimum distance from the boundary of the risk area is 0.15 m, the speed is up to 0.15 m/s, the spatial obstacle avoidance speed is up to 0.3 m/s, and the spatial maneuverability is high and the trajectory is relatively smooth, which verifies the effectiveness of the proposed method.