Thermal RGB Fusion for Micro-UAV Wildfire Perimeter Tracking with Minimal Comms
Ercan Erkalkan, Vedat Topuz, Ay\c{c}a Ak

TL;DR
This paper presents a lightweight, thermal RGB fusion method for micro-UAV wildfire perimeter tracking that operates efficiently under limited communication and computational resources, ensuring rapid deployment and stable navigation.
Contribution
The study introduces a novel fusion technique combining thermal and RGB data for wildfire perimeter tracking on micro-UAVs with minimal communication and computational demands.
Findings
Reduces boundary jitter and path length compared to baseline methods.
Achieves sub 50 ms latency on embedded platforms.
Maintains environmental coverage with minimal communication.
Abstract
This study introduces a lightweight perimeter tracking method designed for micro UAV teams operating over wildfire environments under limited bandwidth conditions. Thermal image frames generate coarse hot region masks through adaptive thresholding and morphological refinement, while RGB frames contribute edge cues and suppress texture related false detections using gradient based filtering. A rule level merging strategy selects boundary candidates and simplifies them via the Ramer Douglas Peucker algorithm. The system incorporates periodic beacons and an inertial feedback loop that maintains trajectory stability in the presence of GPS degradation. The guidance loop targets sub 50 ms latency on embedded System on Chip (SoC) platforms by constraining per frame pixel operations and precomputing gradient tables. Small scale simulations demonstrate reductions in average path length and…
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Taxonomy
TopicsFire Detection and Safety Systems · Advanced Optical Sensing Technologies · UAV Applications and Optimization
