How Much is too Much: Exploring the Effect of Verbal Route Description Length on Indoor Navigation
Fathima Nourin N, Pradip Pramanick, Chayan Sarkar
TL;DR
The paper investigates how verbal route-description length affects indoor navigation performance by formalizing route segments as working-memory chunks and testing descriptions of four, six, and eight segments. Across a real-world experiment with AI-narrated videos and a recall-based navigation task, shorter descriptions yielded higher success rates and faster actual navigation times, supporting a four-segment optimal length. While some metrics did not show significant differences, the results consistently point to reduced cognitive load, higher confidence, and easier recall with shorter descriptions, suggesting practical guidance for designing robot-assisted wayfinding. The study lays a foundation for integrating chunk-based description strategies into indoor navigation systems and motivates further controlled experiments and richer measurements to refine optimal length and content.
Abstract
Navigating through a new indoor environment can be stressful. Recently, many places have deployed robots to assist visitors. One of the features of such robots is escorting the visitors to their desired destination within the environment, but this is neither scalable nor necessary for every visitor. Instead, a robot assistant could be deployed at a strategic location to provide wayfinding instructions. This not only increases the user experience but can be helpful in many time-critical scenarios e.g., escorting someone to their boarding gate at an airport. However, delivering route descriptions verbally poses a challenge. If the description is too verbose, people may struggle to recall all the information, while overly brief descriptions may be simply unhelpful. This article focuses on studying the optimal length of verbal route descriptions that are effective for reaching the destination and easy for people to recall. This work proposes a theoretical framework that links route segments to chunks in working memory. Based on this framework, an experiment is designed and conducted to examine the effects of route descriptions of different lengths on navigational performance. The results revealed intriguing patterns suggesting an ideal length of four route segments. This study lays a foundation for future research exploring the relationship between route description lengths, working memory capacity, and navigational performance in indoor environments.