Autonomous Mission of Multi-UAV for Optimal Area Coverage

Area of Science:

• Robotics and Automation
• Aerospace Engineering
• Computer Science

Background:

• Commercial drone services face limitations in operational autonomy and require significant human intervention.
• Existing systems often lack efficient decision-making capabilities for complex missions like area coverage.

Purpose of the Study:

• To develop a comprehensive hardware and software architecture for autonomous area coverage missions using multiple unmanned aerial vehicles (UAVs).
• To enhance the efficiency and autonomy of drone operations by optimizing waypoint allocation.

Main Methods:

• Designed an optimization problem to allocate waypoints for comprehensive area coverage.
• Developed an integrated hardware and software architecture from operator input to motor command.
• Conducted extensive simulations for quantitative analysis and real-world hardware experiments for validation.

Main Results:

• Achieved efficient and non-overlapping area coverage by multiple UAVs.
• Demonstrated minimal mission completion time through optimized waypoint allocation.
• Validated the system's performance through both simulation and practical outdoor experiments.

Conclusions:

• The proposed architecture significantly improves autonomy and efficiency in multi-UAV area coverage missions.
• The developed methodologies are adaptable for various applications utilizing UAVs with specialized sensors.
• This work advances the capabilities of autonomous drone operations for diverse real-world tasks.