Li, Mickey; Richards, Arthur G; Sooriyabandara, Mahesh; (2024) Experimental Validation of the Reliability-Aware Multi-UAV Coverage Path Planning Problem. In: AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics

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Abstract

Unmanned aerial vehicles (UAVs) have become crucial for various applications, necessitating reliable and time-constrained performance. Multi-UAV solutions offer advantages but require effective coordination. Traditional coverage path planning methods overlook uncertainties and individual UAV failures. To address this, reliability-aware multi-UAV coverage path planning methods optimise task allocation to maximise mission completion probabilities given a failure model. This paper presents an experimental validation of the reliability-aware approach, specifically an approach using a Greedy Genetic Algorithm (GGA). We evaluate the GGA performance in real-world environments, comparing mission reliability to computed reliability and comparing it against a traditional multi-UAV methods. The experimental validation demonstrates the practical viability and effectiveness of the reliability-aware approach, showing significant improvement in mission reliability despite the inevitable mismatch between real and assumed failure models.

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