提出新评估指标，量化人机交互中的合作与责任分配。
Spotting the Unfriendly Robot -- Towards better Metrics for Interactions
- 引入冲突强度与责任度两个新指标，衡量交互质量。
- 可识别谁主动避让、谁应承担冲突责任，避免误判。
- 适合研究人机协作导航的学者与工程师参考。
构建标准化的社交机器人导航（SRN）评估指标对提升机器人行为质量与社会合规性至关重要。当前常用指标难以量化智能体在人际互动中的合作程度。例如，在正面接近场景中，无法判断双方是否协同避让，或是否存在一方持续碰撞而另一方被迫规避。为此，本文提出冲突强度指标与责任指标，能够评估算法在降低冲突中的贡献，并明确冲突解决的责任归属。该工作旨在推动建立全面、统一的SRN评估体系，最终提升机器人在人本环境中的安全性、效率与社会接受度。
原文摘要 · Abstract (English)
Establishing standardized metrics for Social Robot Navigation (SRN) algorithms for assessing the quality and social compliance of robot behavior around humans is essential for SRN research. Currently, commonly used evaluation metrics lack the ability to quantify how cooperative an agent behaves in interaction with humans. Concretely, in a simple frontal approach scenario, no metric specifically captures if both agents cooperate or if one agent stays on collision course and the other agent is forced to evade. To address this limitation, we propose two new metrics, a conflict intensity metric and the responsibility metric. Together, these metrics are capable of evaluating the quality of human-robot interactions by showing how much a given algorithm has contributed to reducing a conflict and which agent actually took responsibility of the resolution. This work aims to contribute to the development of a comprehensive and standardized evaluation methodology for SRN, ultimately enhancing the safety, efficiency, and social acceptance of robots in human-centric environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。