TRISTAR：用于搜索救援微型无人机的三重信号楼梯识别与仅视觉室内导航
TRISTAR: Triple-Signal Stair Recognition and Vision-Only Indoor Navigation for Search-and-Rescue Micro-UAVs
AI总结：
研究为低成本无人机提出仅基于单目视觉的室内导航框架。结合深度估计、传统计算机视觉和轻量级深度学习模型。核心方法是TRISTAR三重传感器融合，贡献是实现可靠室内探索与楼梯穿越，无需特殊测距硬件。
摘要：
室内搜索救援行动常需快速态势感知，多数自主航空系统依赖激光雷达等增加成本。本文提出仅基于单目视觉的低成本无人机室内导航框架，在DJI Tello平台实现，结合多种技术。框架含走廊探索和基于TRISTAR的自主楼梯上升两行为，评估表明该方案可行。
英文摘要：
Indoor search-and-rescue (SAR) operations often require rapid situational awareness where GNSS signals are unavailable and human access is difficult or hazardous. While most autonomous aerial systems rely on LiDAR, stereo vision, or specialized depth cameras, such solutions increase both hardware complexity and deployment costs. This paper presents a complete autonomous indoor navigation framework for low-cost unmanned aerial vehicles based exclusively on monocular vision. Implemented on a DJI Tello platform, the system combines monocular depth estimation using Depth Anything V2 with classical computer vision and lightweight deep learning models for scene understanding, victim detection, and hazard recognition. The framework consists of two independent behaviors: (i) corridor exploration with automatic door detection, room entry, OCR-based room identification, and victim inspection; and (ii) autonomous stair ascent based on TRISTAR (TRI-Signal STair Ascent Recognition), a novel triple-sensor fusion method that integrates structural cues (Sobel filtering), texture analysis (multi-scale Gabor filtering), and geometric depth from monocular depth estimation. Evaluation used real indoor flights in a university building. Depth calibration reduced relative depth error from 27.4% to below 10%, while the door detection algorithm reached a precision of 0.93 and an F1-score of 0.91. A dedicated ablation study shows that multi-sensor fusion significantly improves stair-recognition robustness compared to individual sensing modalities, and a failure-case analysis delineates the limits of monocular perception under challenging lighting and reflective surfaces. The results demonstrate that reliable indoor exploration and stair traversal are achievable on resource-constrained platforms without specialized ranging hardware, a practical, cost-effective solution for rapid SAR deployment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
