Trajectory Optimization of Laser-Charged UAVs for Charging Wireless Rechargeable Sensor Networks.

Area of Science:

• Wireless Power Transfer (WPT)
• Robotics and Automation
• Sensor Networks

Background:

• Battery-limited sensors in wireless rechargeable sensor networks (WRSNs) require continuous energy replenishment.
• Existing WPT systems face challenges in efficiently powering distributed sensors.
• Unmanned Aerial Vehicles (UAVs) offer a flexible platform for mobile energy transmission.

Purpose of the Study:

• To develop an optimized trajectory for laser-charged UAVs to ensure sustainable energy supply for WRSNs.
• To cooperatively optimize UAV flight paths and mobile unmanned vehicle (MUV) travel plans.
• To minimize the total working time of the UAV while maintaining sensor energy above a critical threshold.

Main Methods:

• Formulated the trajectory optimization of laser-charged UAVs for charging WRSNs (TOLC) problem.
• Proved the NP-hard nature of the TOLC problem.
• Developed the weighted centered minimum coverage (WCMC) algorithm for sensor clustering and weighted center computation.
• Proposed the TOLC algorithm (TOLCA) integrating UAV flight trajectories, hovering points, and MUV travel plans.

Main Results:

• The proposed TOLCA algorithm effectively designs UAV flight trajectories and MUV travel plans.
• Optimized hovering points and times for both sensor charging and UAV self-recharging.
• Demonstrated the system's capability to maintain sensor energy above the required threshold.
• Verified the efficiency of the cooperative trajectory optimization strategy.

Conclusions:

• The laser-powered UAV-enabled WPT system provides a sustainable energy solution for WRSNs.
• Cooperative trajectory optimization significantly minimizes UAV working time.
• The proposed algorithms (WCMC and TOLCA) offer an effective approach for managing energy in WRSNs.