移动机器人人行道相遇中行人舒适度的实证预测
Empirical Prediction of Pedestrian Comfort in Mobile Robot Pedestrian Encounters
AI总结：
本文通过实验证明移动机器人与行人交互运动学与主观舒适度之间的关联，设计了三种舒适度估计器，其中复合估计器在预测性能和分类表现上最佳，具有3.67的比值。
摘要：
移动机器人进入公共空间如人行道必须考虑行人舒适度。许多研究关注行人客观安全，如开发避障算法，但很少研究考虑行人主观安全或舒适度。量化舒适度是移动机器人理解并响应人类情绪的主要挑战。我们实证研究了移动机器人-行人交互运动学与主观舒适度的关系。我们进行一对一实验，每项实验涉及移动机器人和志愿者。对行人报告的舒适度与运动学变量的统计分析显示，大多数变量有中等但显著的相关性。基于这些实证发现，我们设计了三种舒适度估计器/预测器，分别来自最小距离、最小投影碰撞时间以及复合估计器。复合估计器使用所有研究的运动学变量，在预测性能和分类表现上最佳。复合预测器的比值为3.67。简单来说，当它识别行人为舒适时，行人实际上是舒适的概率是不舒适的4倍。本研究为将行人感受纳入路径规划器中，以实现更符合社会规范的机器人提供了舒适度量化工具。
英文摘要：
Mobile robots joining public spaces like sidewalks must care for pedestrian comfort. Many studies consider pedestrians' objective safety, for example, by developing collision avoidance algorithms, but not enough studies take the pedestrian's subjective safety or comfort into consideration. Quantifying comfort is a major challenge that hinders mobile robots from understanding and responding to human emotions. We empirically look into the relationship between the mobile robot-pedestrian interaction kinematics and subjective comfort. We perform one-on-one experimental trials, each involving a mobile robot and a volunteer. Statistical analysis of pedestrians' reported comfort versus the kinematic variables shows moderate but significant correlations for most variables. Based on these empirical findings, we design three comfort estimators/predictors derived from the minimum distance, the minimum projected time-to-collision, and a composite estimator. The composite estimator employs all studied kinematic variables and reaches the highest prediction rate and classifying performance among the predictors. The composite predictor has an odds ratio of 3.67. In simple terms, when it identifies a pedestrian as comfortable, it is almost 4 times more likely that the pedestrian is comfortable rather than uncomfortable. The study provides a comfort quantifier for incorporating pedestrian feelings into path planners for more socially compliant robots.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
