外观
论文arXiv 2610.1641116 天前
估计走廊场景中社交导航信号的因果影响
原文链接：Estimating the Causal Impact of Social Navigation Signals in Corridor Scenarios（arXiv 2610.16411 · 发布日期：2026-10-12）
Estimating the Causal Impact of Social Navigation Signals in Corridor Scenarios
研究走廊人机交互中社交导航信号是否提升通行成功，用因果DAG对比干预与观测估计并验证。
核心要点
- 动机是共享环境中机器人需判断何时发出社交信号，观测推断可能受混杂误导。
- 方法将交互表示为因果DAG，包含机器人动作、行人占用、可用空间、结果和静态障碍。
- 实验对比干预估计与仅按机器人动作条件化的观测估计，二者结论相反。
- 结果显示观测估计误判信号有害，因果估计认为有益，强调混杂控制的重要性。
验证范围与局限：验证范围为走廊人机交互场景，摘要未说明仿真或真机设置。
英文摘要 (Abstract)
Deploying robots in human-shared environments requires deciding not only how to navigate, but also when dedicated social signals are worth emitting. Classic observation-based inference can be misleading in such settings: confounding factors may bias the estimated relationship between a signal and the task outcome, leading to incorrect decisions. Causal inference provides a framework for disentangling these relationships by modelling the mechanisms linking observations, actions, and outcomes, and by estimating interventional effects after accounting for confounding paths. We study a human-robot interaction scenario in a corridor and use a causal model to estimate whether a social navigation signal causally improves transit success. We represent the interaction as a causal DAG involving robot action, pedestrian occupancy, available space, task outcome, and a controlled confounder (static obstacles). We compare the interventional estimate with the observational estimate obtained by conditioning only on the robot action, which does not explicitly model interventions. Our results show that accounting for confounding variables can reverse the conclusions drawn from naive observational analysis: the observational estimate wrongly suggests that the social signal is detrimental, whereas the causal estimate shows that it is beneficial. This discrepancy highlights how failing to account for confounding can lead to incorrect conclusions and demonstrates the importance of causal models for context-aware signalling decisions in social robot navigation.
作者：Francesco Baldo, Luca Castri, Gloria Beraldo, Nicola Bellotto
来源
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