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U-Shaped Obstacle Avoidance for a Bionic Robotic Fish: A Virtual Sentinel Obstacle Strategy Based on the Artificial
Yijin Tong1, Zhenping Wan1, Ruolin Wang1
1School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China.
Sensors (Basel, Switzerland)
|August 13, 2026
Summary
This study introduces a virtual sentinel obstacle strategy to prevent robotic fish from getting trapped in U-shaped obstacles. The method enhances path planning for reliable underwater navigation and obstacle avoidance.
Area of Science:
- Robotics
- Artificial Intelligence
- Control Systems
Background:
- Bionic robotic fish require reliable obstacle avoidance for complex underwater operations.
- Traditional artificial potential field (APF) methods struggle with local minima, leading to failure near U-shaped obstacles.
Purpose of the Study:
- To develop a novel strategy for U-shaped obstacle avoidance in bionic robotic fish.
- To overcome the limitations of traditional APF methods in preventing entrapment.
Main Methods:
- Proposed a virtual sentinel obstacle strategy deployed near U-shaped obstacle entrances to prevent local minima entrapment.
- Implemented a two-stage fuzzy controller to optimize heading rotation and cruising step size for improved path planning.
- Validated the approach through numerical simulations and physical experiments with a bionic robotic fish prototype.
Main Results:
- The virtual sentinel obstacle strategy successfully prevented robotic fish entrapment in U-shaped obstacles.
- Fuzzy control significantly shortened paths and enhanced trajectory smoothness.
- Physical experiments confirmed the strategy's feasibility in 2D underwater obstacle avoidance scenarios.
Conclusions:
- Combining virtual sentinel obstacles with APF-based planning offers a robust solution for U-shaped obstacle avoidance in bionic robotic fish.
- The proposed method enhances navigation safety and efficiency in challenging underwater environments.
