外观
论文arXiv 2607.176043 个月前
移动机器人-行人交互中的稳定性与舒适性
原文链接：Stability and Comfort in Mobile Robot-Pedestrian Interactions（arXiv 2607.17604 · 发布日期：2026-07-20）
Stability and Comfort in Mobile Robot-Pedestrian Interactions
针对公共空间NMR与行人交互舒适性不足，提出基于SFM/TSFM的社会感知导航，并在仿真与行人实验中验证。
核心要点
- 公共空间移动机器人需保障行人舒适，但主观安全实证研究较少，且非完整机器人研究不足。
- 提出面向NMR的框架，结合SFM与投影Time-to-collision SFM，形式化人、障碍交互。
- 在有界非被动行人假设下证明系统稳定性，并用舒适与速度混合代价在仿真中标定模型。
- 行人-机器人实验比较SFM、TSFM与遥控基线，统计问卷显示模型稳定且提升行人舒适。
验证范围与局限：验证范围包括仿真标定和行人-机器人交互实验，场景为NMR穿越行人群。
英文摘要 (Abstract)
Mobile robots in public spaces must ensure pedestrians' comfort, and yet empirical studies of walkers' subjective safety are rare. Many classical navigation algorithms do not distinguish the walkers from dynamic obstacles and do not explicitly model subjective human factors. Moreover, most studies focus on holonomic mobile robots, whereas applications demand Nonholonomic Mobile Robots (NMR). This paper develops socially aware algorithms for NMRs, proves the stability, verifies the performance experimentally, and statistically analyzes the reported comfort. We design a framework for NMRs using Social Force Model (SFM) and the projected Time-to-collision Social Force Model (TSFM). We formalize the NMR-pedestrians' and NMR-obstacles' interactions and prove the system's stability, assuming boundedly nonpassive pedestrians. Simulations calibrate the models by maximizing a hybrid cost function of comfort and speed. Pedestrian-robot interaction experiments compare SFM and TSFM to two remote-controlled baselines and collect walkers' reported comfort. Statistical tools analyze survey results collected during the experiments. Benchmarking the algorithms against previous studies highlights the proposed methods' advantage with respect to the studied metrics. Overall, the models are stable and improve pedestrian comfort when an NMR navigates through a pedestrian crowd.
作者：Alireza Jafari, H S. Nguyen, Yen-Chen Liu
来源
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