In context
In July 2024, autonomous underwater vehicles, particularly biomimetic robotic fish, were gaining attention for their superior propulsion efficiency and maneuverability compared to propeller-driven craft. However, navigating unstructured underwater environments with dynamic obstacles remained a key challenge for autonomous operation.
What was reported
A team from Lanzhou Jiaotong University, Dalian University of Technology, and North China Institute of Aerospace Engineering published a study in the journal Robot proposing a path planning method based on dynamic obstacle-avoidance risk regions (DAR) for a pectoral and caudal fin co-propelled biomimetic robotic fish.
The method constructs an ellipsoid-like risk region around each moving obstacle using extended Kalman filtering, with the long axis proportional to obstacle speed. Fuzzy control estimates noise variance to refine region boundaries. Obstacles moving in the same direction and faster than the fish are filtered out, yielding a time-varying passable region.
A spatial collision-avoidance strategy—steer first, then pitch—is determined by principles of avoiding nearest obstacles first and maintaining shortest distance to safe boundaries. A nonlinear model predictive controller (NMPC) optimizes turning radius, pitch angle, and pectoral fin phase difference in real time.
Experiments in a multi-obstacle environment showed a minimum distance of 0.15 m from risk region boundaries, speeds up to 0.15 m/s, and spatial obstacle avoidance speeds up to 0.3 m/s, with smooth trajectories and high maneuverability.
Why it mattered
This work addressed the challenge of dynamic obstacle avoidance in underwater robotics by integrating risk region prediction with NMPC, potentially improving autonomous navigation for inspection, exploration, and environmental monitoring in cluttered aquatic settings.
"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, and the spatial obstacle avoidance speed is up to 0.3 m/s."
Source: 《机器人》期刊 (robot.sia.cn) · Published 2024-07-20 · “基于动态避障风险区域的仿生机器鱼路径规划方法”