Stability and Comfort in Mobile Robot-Pedestrian Interactions
2026-07-20 • Robotics
Robotics
AI summaryⓘ
The authors studied how mobile robots with movement limits (called Nonholonomic Mobile Robots) can move around people comfortably in public. They created new algorithms based on social behavior models to help these robots avoid bothering or scaring pedestrians. They showed that their approach is stable and tested it with experiments, where people reported feeling more comfortable around these robots compared to other methods. Their work focuses on making robot navigation safer and more pleasant for people nearby.
Nonholonomic Mobile RobotsSocial Force ModelTime-to-collisionRobot navigationPedestrian comfortDynamic obstaclesStability analysisHuman-robot interactionCost function
Authors
Alireza Jafari, Hong-Son Nguyen, Yen-Chen Liu
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.