用热成像与可见光融合追踪火线，低带宽下实时稳定飞行
Thermal RGB Fusion for Micro-UAV Wildfire Perimeter Tracking with Minimal Comms
- 热图粗筛热点，可见光补边缘，规则融合选边界
- 路径长度缩短23%，边界抖动减少41%，延迟低于50毫秒
- 适合微型无人机群紧急侦察，通信少、功耗低
本研究提出一种轻量级火线追踪方法，适用于在带宽受限环境下运行的微型无人机集群。热图像通过自适应阈值和形态学处理生成粗略高温区域掩码，可见光图像则利用梯度滤波提供边缘线索并抑制纹理导致的误检。采用规则级融合策略筛选边界候选点，并通过Ramer-Douglas-Peucker算法简化。系统结合周期性信标与惯性反馈回路，在GPS信号下降时保持轨迹稳定。通过限制每帧像素操作并预计算梯度表，实现嵌入式SoC平台下子50毫秒延迟。小规模仿真显示，相比纯边缘追踪基线，平均路径长度减少23%，边界抖动降低41%，且通过交集-并集分析保持环境覆盖率。电池消耗与计算利用率验证了在标准微平台上实现10~15 m/s前进速度的可行性。该方法支持快速野外部署，具备鲁棒感知与极低通信需求，适用于应急侦察场景。
原文摘要 · Abstract (English)
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 boundary jitter compared to a pure edge tracking baseline, while maintaining environmental coverage measured through intersection merge analysis. Battery consumption and computational utilization confirm the feasibility of achieving 10, 15 m/s forward motion on standard micro platforms. This approach enables rapid deployment in the field, requiring robust sensing and minimal communications for emergency reconnaissance applications.
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