Sunghoon Ivan Lee – VEMI Lab /vemi University of Maine Thu, 19 Mar 2026 16:03:56 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.5 GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant for Blind Travelers /vemi/publication/guidenav-user-informed-development-of-a-vision-only-robotic-navigation-assistant-for-blind-travelers/ Mon, 16 Mar 2026 16:03:02 +0000 /vemi/?post_type=publication&p=5478 While commendable progress has been made in user-centric research on mobile assistive systems for blind and low-vision (BLV) individuals, references that directly inform robot navigation design remain rare. To bridge this gap, we conducted a comprehensive human study involving interviews with 26 guide dog handlers, four white cane users, nine guide dog trainers, and one O&M trainer, along with 15+ hours of observing guide dog–assisted walking. After de-identification, we open-sourced the dataset to promote human-centered development and informed decision-making for assistive systems for BLV people. Building on insights from this formative study, we developed GuideNav, a vision-only, teach-andrepeat navigation system. Inspired by how guide dogs are trained and assist their handlers, GuideNav autonomously repeats a path demonstrated by a sighted person using a robot. Specifically, the system constructs a topological representation of the taught route, integrates visual place recognition with temporal filtering, and employs a relative pose estimator to compute navigation actions—all without relying on costly, heavy, power-hungry sensors such as LiDAR. In field tests, GuideNav consistently achieved kilometer-scale route following across five outdoor environments, maintaining reliability despite noticeable scene variations between teach and repeat runs. A userstudy with 3 guide dog handlers and 1 guide dog trainer further confirmed the system’s feasibility, marking, to our knowledge, the first demonstration of a quadruped mobile system guiding a route in a manner comparable to guide dogs.

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