Communication and Energy-Aware Multi-UAV Coverage Path Planning for Networked Operations

TL;DR

This paper introduces a multi-UAV coverage path planning method that balances energy consumption and communication connectivity, validated through simulations and real-world experiments, enhancing cooperative search and surveillance missions.

Contribution

It proposes a novel algorithm that integrates energy and communication constraints into coverage path planning for multi-UAV systems, addressing a gap in existing solutions.

Findings

Achieves 99% accuracy in communication range estimation.

Effectively balances energy use and connectivity in complex environments.

Validated through extensive simulations and real-world UAV experiments.

Abstract

This paper presents a communication and energy-aware multi-UAV Coverage Path Planning (mCPP) method for scenarios requiring continuous inter-UAV communication, such as cooperative search and rescue and surveillance missions. Unlike existing mCPP solutions that focus on energy, time, or coverage efficiency, the proposed method generates coverage paths that minimize a specified combination of energy and inter-UAV connectivity radius. Key features of the proposed algorithm include a simplified and validated energy consumption model, an efficient connectivity radius estimator, and an optimization framework that enables us to search for the optimal paths over irregular and obstacle-rich regions. The effectiveness and utility of the proposed algorithm is validated through simulations on various test regions with and without no-fly-zones. Real-world experiments on a three-UAV system demonstrate the remarkably high 99% match between the estimated and actual communication range requirement.