Stability and Comfort in Mobile Robot-Pedestrian Interactions

2026-07-20

AI Summary

This work addresses the challenge of balancing pedestrian subjective comfort and system stability in navigation for nonholonomic mobile robots in public spaces. We propose a socially aware navigation framework that integrates the Social Force Model (SFM) with the Time-to-Collision-based Social Force Model (TSFM). To our knowledge, this is the first approach to provide Lyapunov stability guarantees while explicitly optimizing for pedestrian comfort in nonholonomic systems. Under a bounded, non-passive pedestrian assumption, we rigorously prove the closed-loop system’s stability and introduce a hybrid comfort-velocity cost function for model calibration. Experimental results demonstrate that the proposed method significantly enhances subjective comfort compared to existing baselines and state-of-the-art approaches, all while maintaining formal stability guarantees.

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.

Problem

• mobile robot-pedestrian interaction
• nonholonomic mobile robots
• pedestrian comfort
• subjective safety
• social navigation

Innovation

• Nonholonomic Mobile Robots
• Social Force Model
• Time-to-collision
• Stability Analysis
• Pedestrian Comfort