DRAGON: A Dialogue-Based Robot for Assistive Navigation with Visual Language Grounding

Shuijing Liu, Aamir Hasan, Kaiwen Hong, Runxuan Wang, Peixin Chang, Zachary Mizrachi, Justin Lin, D Livingston McPherson, Wendy Rogers, Katherine Rose Driggs-Campbell

Keywords: Human centered robotics, natural dialogue for human-robot interaction, visual language grounding

TL;DR: We design a guiding robot that can hold conversations and exchange semantic information with blind users.

Abstract: Persons with visual impairments (PwVI) have difficulties understanding and navigating spaces around them. Current wayfinding technologies either focus solely on navigation or provide limited communication about the environment. Motivated by recent advances in visual-language grounding and semantic navigation, we propose DRAGON, a guiding robot powered by a dialogue system and the ability to associate the environment with natural language. By understanding the commands from the user, DRAGON is able to guide the user to the desired landmarks on the map, describe the environment, and answer questions from visual observations. Through effective utilization of dialogue, the robot can ground the user’s free-form descriptions to landmarks in the environment, and give the user semantic information through spoken language. We conduct a user study with blindfolded participants in an everyday indoor environment. Our results demonstrate that DRAGON is able to communicate with the user smoothly, provide a good guiding experience, and connect users with their surrounding environment in an intuitive manner. Videos and code are at https://sites.google.com/view/dragon-wayfinding/home.

Submission Number: 45