摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑-调查人员讨论机器人学的新发现。据NewsRx Corre Spondents从德国达姆施塔特发回的新闻报道，研究表明，“大量和大规模的自然和人为灾害导致了对提高搜索救援队伍安全和效率的技术的迫切需求。半自主救援机器人是一种有效的技术，特别是在搜索无法进入的地形或危险环境时。”这项研究的财政支持来自LOEWE倡议。我们的新闻记者从达姆施塔特技术大学(TU Darmstadt)的研究中获得了一句话：“对于在退化的视觉条件或非视线场景下的搜索和救援任务，基于雷达的方法可能有助于获得有价值的，否则无法获得的信息。本文介绍了一个完整的基于雷达的多人探测信号处理链，本文提出的方法在一个装备有商用通波雷达系统的半自主机器人上采集的具有挑战性的应急响应数据集上显示了良好的结果,该数据集由62个不同难度级别的场景组成,最多捕获5个不同姿态的人。角度和范围，包括阻挡雷达视线的木制和石头障碍物。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news originating from Darmstadt, Germany, by NewsRx corre spondents, research stated, “The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are ben eficial, especially when searching inaccessible terrains, or dangerous environme nts, such as collapsed infrastructures.” Financial support for this research came from LOEWE initiative. Our news journalists obtained a quote from the research from Technical Universit y Darmstadt (TU Darmstadt), “For search and rescue missions in degraded visual c onditions or non-line of sight scenarios, radar-based approaches may contribute to acquire valuable, and otherwise unavailable information. This article present s a complete signal processing chain for radar-based multi-person detection, 2D- MUSIC localization and breathing frequency estimation. The proposed method shows promising results on a challenging emergency response dataset that we collected using a semi-autonomous robot equipped with a commercially available through-wa ll radar system. The dataset is composed of 62 scenarios of various difficulty l evels with up to five persons captured in different postures, angles and ranges including wooden and stone obstacles that block the radar line of sight.”
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