Towards LLM-powered Assistive Drone for Blind and Low Vision Users

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Authors: Yize Wei, Ibnu Taimiyyah Bin Adam, Hanjun Wu, Moritz Alexander Messerschmidt, Wei Tsang Ooi, Christophe Jouffrais, Suranga Chandima Nanayakkara
Cited by: 1
References: 77

Abstract

Drones have gained traction as a versatile form of assistive robots for Blind and Low Vision (BLV) people. Nonetheless, novel interaction techniques are required to enable BLV people to communicate with drones naturally. In this work, we built an LLM-powered assistive drone for BLV users. We leverage an LLM to translate high-level user goals to step-by-step instructions for the drone and to extract visual information from the images. Through a formative study with BLV users (N=9), we identified envisioned use cases and desired interaction modalities. Then, we took a participatory and iterative approach to build a prototype, incorporating feedback received from 3 BLV users, as well as 5 domain experts. Finally, we conducted a user study with an additional 6 BLV participants to evaluate the iterated prototype, and received positive feedback. This work is contributing to a growing body of research on harnessing the power of LLMs to build a more inclusive world.

Fields of Study & Subjects

Social Robot Interaction and HRI Gaze Tracking and Assistive Technology Tactile and Sensory Interactions

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–18
Publication date
13 April 2026
Language
EN