Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor...

Area of Science:

• Robotics
• Wireless Sensor Networks
• Energy Efficiency

Background:

• Mobile data collection in robot networks using unmanned aerial vehicles (UAVs) presents energy constraints.
• Cluster heads (CH) manage data collection within robot clusters, posing challenges for UAVs with limited battery capacity.

Purpose of the Study:

• To develop an energy-efficient data collection strategy for a mobile sink (UAV) in a clustered robot network.
• To minimize total UAV energy consumption and data collection costs by optimally selecting CH robots to visit.
• To analytically derive an optimal approach considering the UAV's constant battery capacity.

Main Methods:

• Formulating an optimization problem to minimize UAV energy consumption and data transmission costs.
• Developing a strategy for the UAV to select a subset of CH robots based on location and battery constraints.
• Incorporating data transmission path optimization for CH robots not visited by the UAV.
• Deriving an analytical solution for the energy-efficient data collection problem.

Main Results:

• The proposed strategy effectively minimizes UAV energy consumption and associated data collection costs.
• The analytical approach provides an optimal solution considering the UAV's finite battery capacity.
• Numerical simulations demonstrate superior performance compared to existing methods in terms of total energy consumed by CH robots.

Conclusions:

• The developed strategy significantly enhances energy efficiency in UAV-based data collection within robot networks.
• The approach contributes to extending network lifetime by optimizing energy usage among CH robots.
• This work offers a novel analytical solution for energy-constrained mobile data collection in clustered robotic systems.