测试软体藤蔓机器人在倒塌建筑中的探测能力，验证其在城市搜救中的实用性。
Field Insights for Portable Vine Robots in Urban Search and Rescue
- 通过真实坍塌结构测试藤蔓机器人的生长与导航能力。
- 可在狭小缝隙、拐角和空腔中穿行，但传感与控制仍需优化。
- 适合应急搜救人员评估废墟内部结构，为小型探测设备设计提供参考。
柔性生长型藤蔓机器人非常适合探索杂乱未知环境，理论上在地震、火灾、爆炸及材料缺陷引发的结构坍塌事件中表现优异。这类机器人从顶端生长，可轻松穿越堆叠瓦砾的通道。现有先进藤蔓机器人已在考古等场景测试，但其在城市搜索与救援（USAR）中的实际应用潜力尚不明确。为此，本文开展一系列实验，评估名为软路径导航观测单元（SPROUT）的藤蔓机器人系统在人工模拟坍塌结构中的表现。测试基于搜救人员在空隙空间中面临的挑战构建难度分类体系。初步实验验证了藤蔓机器人形态的可行性，包括理想设计与实际实现，并考察了系统的控制与传感能力。后续实验引入领域专用设计改进，以提升系统的便携性与可靠性。结果表明，SPROUT能够穿过狭窄孔洞、绕过拐角并进入空腔，但仍需加强传感以提升操控性与态势感知能力。
原文摘要 · Abstract (English)
Soft, growing vine robots are well-suited for exploring cluttered, unknown environments, and are theorized to be performant during structural collapse incidents caused by earthquakes, fires, explosions, and material flaws. These vine robots grow from the tip, enabling them to navigate rubble-filled passageways easily. State-of-the-art vine robots have been tested in archaeological and other field settings, but their translational capabilities to urban search and rescue (USAR) are not well understood. To this end, we present a set of experiments designed to test the limits of a vine robot system, the Soft Pathfinding Robotic Observation Unit (SPROUT), operating in an engineered collapsed structure. Our testing is driven by a taxonomy of difficulty derived from the challenges USAR crews face navigating void spaces and their associated hazards. Initial experiments explore the viability of the vine robot form factor, both ideal and implemented, as well as the control and sensorization of the system. A secondary set of experiments applies domain-specific design improvements to increase the portability and reliability of the system. SPROUT can grow through tight apertures, around corners, and into void spaces, but requires additional development in sensorization to improve control and situational awareness.
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