Autonomous Water Quality Monitoring and Water Surface Cleaning for Unmanned Surface Vehicle

Area of Science:

• Environmental Science
• Robotics
• Sensor Technology

Background:

• Industrial development has led to critical water pollution issues.
• Effective water quality monitoring and surface cleaning are essential for water resource protection.
• Unmanned Surface Vehicles (USVs) offer potential solutions for aquatic environmental management.

Purpose of the Study:

• To develop a multi-function unmanned surface vehicle (MF-USV) integrating sensor fusion technology.
• To enable autonomous obstacle avoidance, water quality monitoring, and water surface cleaning capabilities.
• To validate the effectiveness of the MF-USV and its algorithms in real-world scenarios.

Main Methods:

• Development of a modular MF-USV incorporating a control unit, locomotion, positioning, obstacle avoidance, water quality monitoring, and cleaning systems.
• Implementation of sensor fusion for autonomous navigation, obstacle detection, and precise positioning.
• Integration of water surface detection and cleaning mechanisms with remote control and real-time data display.

Main Results:

• The MF-USV achieved 100% success rates in detecting floating garbage within a -30° to 30° visual angle at 40 and 70 cm distances.
• Floating garbage collection success rates varied from 70% to 95% depending on location and distance, with optimal performance directly in front of the vehicle.
• Experimental results confirmed the efficacy of the MF-USV and its algorithms for obstacle avoidance, water quality monitoring, and surface cleaning.

Conclusions:

• The developed MF-USV is an effective platform for addressing water pollution challenges.
• Sensor fusion technology significantly enhances the autonomous capabilities of the MF-USV for environmental monitoring and cleaning.
• The MF-USV demonstrates practical applicability in improving water resource management and protection.