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English(EN) Drone-Assisted UAV-UGV Collaboration for Autonomous Navigation in Snow-Covered Terrain

雪地地形无人机与地面机器人导航系统

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的导航框架，用于在具有挑战性的雪地地形中运行的无人机和地面机器人。该系统利用高效的U-Net架构进行实时道路分割，通过合成雪数据增强实现了96.5%的准确率。无人机采用扩展卡尔曼滤波器集成GPS和IMU数据进行定位，最大位置误差为0.5米。地面机器人的位置通过无人机的RGB-D摄像头数据和YOLOv5对象检测进行跟踪，从而能够进行考虑雪堆的动态路径规划。 AI

影响 这项研究可以提高在极端天气条件下的自主导航能力，可能对极地或山区地区的物流和探索产生影响。

排序理由 该集群包含一篇详细介绍新颖技术方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

雪地地形无人机与地面机器人导航系统

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该集群包含一篇详细介绍新颖技术方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Shreyam Gupta (Robotics Research Group, Indian Institute of Technology), P. Agrawal (University of Colorado, Boulder, USA), Priyam Gupta (Intelligent Field Robotic Systems), R. Gautam (Robotics Research Group, Indian Institute of Technology) ·

    无人机辅助无人机-地面机器人协同在积雪地形中的自主导航

    arXiv:2608.07797v1 Announce Type: cross Abstract: This paper presents a collaborative UAV-UGV navigation framework for high-altitude, snow-covered terrain, where reduced visibility and unstable ground render conventional methods ineffective. We introduce a custom efficient U-Net …

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