Real-time autonomous path planning for dynamic wildfire monitoring with uneven importance

Unmanned Aircraft Systems (UASs) offer many benefits in wildfire monitoring when compared to traditional wildfire monitoring technologies. Wildfire spread is a highly heterogeneous process with non-uniform spreading speed and fireline intensity in both space and time. When planning the path of a UAS for monitoring a dynamically growing wildfire, it is important to consider the uneven spread of the fire because different parts of the fire boundary would need different levels of monitoring attention. This paper presents a real-time path planning algorithm for a UAS to autonomously monitor the perimeter of a spreading wildfire with uneven importance. The proposed path planning algorithm allows the UAS to focus on the most active regions of a wildfire while still covering the entire fire perimeter. The design and implementation of this algorithm are described, and an in-depth analysis of the performance of the algorithm is provided. Experiment results based on simulated wildfires demonstrate the effectiveness and robustness of the proposed algorithm for monitoring dynamic wildfires.