Towards Robotic Companions: Understanding Handler-Guide Dog Interactions for Informed Guide Dog Robot Design

要旨

Dog guides are favored by blind and low-vision (BLV) individuals for their ability to enhance independence and confidence by reducing safety concerns and increasing navigation efficiency compared to traditional mobility aids. However, only a relatively small proportion of BLV people work with dog guides due to their limited availability and associated maintenance responsibilities. There is considerable recent interest in addressing this challenge by developing legged guide dog robots. This study was designed to determine critical aspects of the handler-guide dog interaction and better understand handler needs to inform guide dog robot development. We conducted semi-structured interviews and observation sessions with 23 dog guide handlers and 5 trainers. Thematic analysis revealed critical limitations in guide dog work, desired personalization in handler-guide dog interaction, and important perspectives on future guide dog robots. Grounded on these findings, we discuss pivotal design insights for guide dog robots aimed for adoption within the BLV community.

受賞
Best Paper
著者
Hochul Hwang
University of Massachusetts Amherst, Amherst, Massachusetts, United States
Hee-Tae Jung
Indiana University Indianapolis, Indianapolis, Indiana, United States
Nicholas A. Giudice
University of Maine, Orono, Maine, United States
Joydeep Biswas
University of Texas at Austin, Austin, Texas, United States
Sunghoon Ivan. Lee
University of Massachusetts Amherst, Amherst, Massachusetts, United States
Donghyun Kim
University of Massachusetts Amherst, Amherst, Massachusetts, United States
論文URL

https://doi.org/10.1145/3613904.3642181

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Human-Robot Interaction C

324
4 件の発表
2024-05-16 20:00:00
2024-05-16 21:20:00