Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method

Area of Science:

• Robotics
• Autonomous Systems
• Marine Engineering

Background:

• Dynamic environments pose significant challenges for autonomous navigation due to motion uncertainty.
• Effective collision avoidance is critical for the safe and reliable operation of unmanned underwater vehicles (UUVs).

Purpose of the Study:

• To develop and validate a dynamic collision avoidance method for UUVs operating in environments with uncertain moving obstacles.
• To improve the adaptability and effectiveness of UUV navigation systems in complex, real-world scenarios.

Main Methods:

• Fusion optimization of forward-looking sonar data to accurately determine obstacle position, size, and velocity.
• Development of a collision risk assessment model based on minimum meeting time and distance.
• Implementation of an improved velocity obstacle method incorporating UUV motion characteristics to calculate reachable velocity sets and optimize UUV speed and heading.

Main Results:

• The proposed method effectively reduces data redundancy from sonar sensors.
• The collision risk assessment model successfully identifies and prioritizes key obstacles for avoidance.
• Simulations demonstrate superior collision avoidance performance and adaptability in dynamic, uncertain environments compared to existing methods.

Conclusions:

• The integrated approach of collision risk assessment and improved velocity obstacle method provides a robust solution for UUV dynamic collision avoidance.
• The method exhibits strong adaptability to unknown dynamic environments, enhancing UUV operational safety and reliability.