一线救援人员对机器人语义信息提升态势感知的评价
First Responders' Perceptions of Semantic Information for Situational Awareness in Robot-Assisted Emergency Response
- 通过跨国问卷调研22名救援人员,分析其对语义信息的态度
- 平均3.6分(满分5)认为语义信息有助于态势感知,需74.6%准确率才信任
- 揭示了实战中语义信息需求与实验室能力间的差距,适合人机协同研究者
本研究调查了一线救援人员(FRs)在应急任务中对机器人系统使用语义信息及态势感知(SA)的态度。通过向来自八个国家的22名救援人员发放结构化问卷,收集其人口统计信息、对机器人的总体态度以及对语义增强型态势感知的经验。结果显示,大多数救援人员对机器人持积极态度,对语义信息提升态势感知的作用平均评分达3.6/5。语义信息在预测突发状况方面的价值也获高评,均值为3.9。参与者表示,需达到平均74.6%的准确性才愿意信任语义输出,67.8%的准确率即认为其有用,反映出对不完美但具信息量的AI辅助工具的接受意愿。据我们所知,这是首个在跨国背景下直接调研救援人员对基于语义的态势感知态度的研究。研究揭示了现场最被重视的语义信息类型,如物体身份、空间关系和风险背景,并将其偏好与受访者角色、经验及教育水平相关联。研究还暴露了实验室机器人能力与实际部署现实之间的关键差距,强调了救援人员与机器人研究人员之间更深入协作的必要性。这些发现有助于开发更符合用户需求、更具情境感知能力的应急响应机器人系统。
原文摘要 · Abstract (English)
This study investigates First Responders' (FRs) attitudes toward the use of semantic information and Situational Awareness (SA) in robotic systems during emergency operations. A structured questionnaire was administered to 22 FRs across eight countries, capturing their demographic profiles, general attitudes toward robots, and experiences with semantics-enhanced SA. Results show that most FRs expressed positive attitudes toward robots, and rated the usefulness of semantic information for building SA at an average of 3.6 out of 5. Semantic information was also valued for its role in predicting unforeseen emergencies (mean 3.9). Participants reported requiring an average of 74.6\% accuracy to trust semantic outputs and 67.8\% for them to be considered useful, revealing a willingness to use imperfect but informative AI support tools. To the best of our knowledge, this study offers novel insights by being one of the first to directly survey FRs on semantic-based SA in a cross-national context. It reveals the types of semantic information most valued in the field, such as object identity, spatial relationships, and risk context-and connects these preferences to the respondents' roles, experience, and education levels. The findings also expose a critical gap between lab-based robotics capabilities and the realities of field deployment, highlighting the need for more meaningful collaboration between FRs and robotics researchers. These insights contribute to the development of more user-aligned and situationally aware robotic systems for emergency response.
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