轻量视觉系统让机器人快速识别关键探索区域
L-VITeX: Light-weight Visual Intuition for Terrain Exploration
- 基于FOMO架构，用极低资源实现高精度兴趣区检测
- 峰值内存低于50KB，推理延迟小于200毫秒，准确率超99%
- 适合嵌入式机器人和无人机群，提升复杂地形探索效率
本文提出L-VITeX，一种专为资源受限机器人与集群设计的轻量级视觉直觉系统，用于地形探索中快速提示感兴趣区域（RoIs），避免高成本计算。该系统采用FOMO tinyML架构，在仅需<50 KB峰值内存下实现>99%的检测准确率，近实时推理时间低于200毫秒。论文在山地、水下沉船残骸区及火星岩石表面等多种地形上评估其性能，并展示了其在小型移动机器人（ESP32-Cam）结合Gaussian Splats（GS）进行3D建图中的应用，验证了其在提升探索效率与决策能力方面的潜力。
原文摘要 · Abstract (English)
This paper presents L-VITeX, a lightweight visual intuition system for terrain exploration designed for resource-constrained robots and swarms. L-VITeX aims to provide a hint of Regions of Interest (RoIs) without computationally expensive processing. By utilizing the Faster Objects, More Objects (FOMO) tinyML architecture, the system achieves high accuracy (>99%) in RoI detection while operating on minimal hardware resources (Peak RAM usage < 50 KB) with near real-time inference (<200 ms). The paper evaluates L-VITeX's performance across various terrains, including mountainous areas, underwater shipwreck debris regions, and Martian rocky surfaces. Additionally, it demonstrates the system's application in 3D mapping using a small mobile robot run by ESP32-Cam and Gaussian Splats (GS), showcasing its potential to enhance exploration efficiency and decision-making.
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