Social Navigation for Tour-guide Robot

2026-10-04

AI Summary

This study addresses the suboptimal user following experience of tour guide robots in complex social environments by proposing a social force navigation model that integrates multiple factors, including obstacles, user position, and orientation. Using A* path planning as a baseline, the model enhances the social compliance of robot motion through multi-factor force field modeling. Furthermore, interactive human experiments combined with subjective questionnaires are employed to systematically evaluate how navigation behaviors influence users' psychological perceptions. The results demonstrate that the proposed method significantly improves the robot's followability, perceived safety, and apparent intelligence. This work provides an effective paradigm for quantitatively optimizing user experience in social navigation.

Abstract

We propose a force-based model for social navigation of a tour-guide robot. Social forces due to various factors like obstacles, user position and heading, have been accounted for in the model. We claim that each one of these forces makes the robot more sociable to the user and we design an experimental setup for evaluation. In the experiment, the user follows an autonomous robot to a destination in a known map, while undertaking a few simple sub-tasks in the middle, which serve as distractions. For each participant, we run several rounds of the experiment, each with different forces and a shortest path, A*-search baseline model. Using per-round subjective indicators, we propose to study the effect of our force model on constructs such as: follow-ability, perceived safety, and perceived intelligence.

Problem

• Social Navigation
• Tour-guide Robot
• Follow-ability
• Perceived Safety
• Human-Robot Interaction

Innovation

• Social Navigation
• Force-based Model
• Tour-guide Robot
• Human-Robot Interaction
• Subjective Evaluation