Towards Decentralized Importance-based Multi-UAS Path Planning for Wildfire Monitoring
S M Towhidul Islam, Xiaolin Hu · 2022
For area monitoring tasks, Unmanned Aircraft Systems (UASs) is one of the common considerations by the researchers and practitioners. When monitoring a small and spatially static area of interest, a single UAS might be adequate for the monitoring task. However, when monitoring a large area of interest that is evolving dynamically in space, such as a dynamical wildfire, efficient and optimized use of multiple UASs is required. Many of the existing works in UAS-based wildfire monitoring adopt a centralized approach for the path planning of the UASs. However, the use of centralized approaches is often limited in terms of applicability and adaptability. In addition, many of the applications do not consider the uneven nature of wildfire spread and thus the uneven importance of the fire boundary. To address these concerns, previously we developed a importance-based on-board path planning algorithm considering a single UAS. In this work, we extend our single UAS on-board path planning algorithm towards a decentralized and importance-based multi-UAS path planning algorithm. The design of the algorithm has been described in detail and preliminary results have been presented for a simulated wildfire spread scenario.