Flight Planning Optimization of Multiple UAVs for Internet of Things

Area of Science:

• Robotics and Automation
• Computer Science
• Aerospace Engineering

Background:

• Unmanned Aerial Vehicles (UAVs) are increasingly used as mobile data collectors in Internet of Things (IoT) networks.
• Efficient flight planning is crucial for maximizing data collection while managing UAV operational constraints such as battery life and data storage.
• Existing methods may not adequately address the complexities of multi-UAV coordination and energy-aware path optimization for extensive IoT deployments.

Purpose of the Study:

• To develop an autonomous flight planning approach for single and multiple UAVs acting as IoT data collectors.
• To enhance the operational range and data acquisition capabilities of UAVs by optimizing flight paths.
• To integrate energy consumption models and data storage considerations into the UAV flight planning process.

Main Methods:

• A novel autonomous flight planning model for UAVs, applicable to both single and multiple aircraft scenarios.
• Implementation of a clustering technique to extend the coverage of visited IoT devices (nodes).
• Energy consumption modeling based on specific aerodynamic characteristics of UAVs.
• Consideration of data storage limitations as a critical planning parameter.

Main Results:

• The developed model generates optimized flight routes that prioritize battery life to maximize the number of visited IoT nodes.
• Simulations demonstrated the algorithm's effectiveness in generating reliable and efficient routes for UAV data collection missions.
• The approach successfully addresses the challenge of preventing mission failures due to battery exhaustion.

Conclusions:

• The proposed autonomous flight planning approach enhances the efficiency and reliability of UAVs in IoT data collection.
• The model provides a robust solution for managing energy consumption and data storage, crucial for extended autonomous operations.
• This work contributes to the advancement of intelligent drone navigation and data management in IoT environments.