GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant For Blind Travelers
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911305282093056 |
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| author | Hwang, Hochul Yang, Soowan Monon, Jahir Sadik Giudice, Nicholas A Lee, Sunghoon Ivan Biswas, Joydeep Kim, Donghyun |
| author_facet | Hwang, Hochul Yang, Soowan Monon, Jahir Sadik Giudice, Nicholas A Lee, Sunghoon Ivan Biswas, Joydeep Kim, Donghyun |
| contents | 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-and-repeat 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 user study 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 retrieving a path in a manner comparable to guide dogs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_06147 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant For Blind Travelers Hwang, Hochul Yang, Soowan Monon, Jahir Sadik Giudice, Nicholas A Lee, Sunghoon Ivan Biswas, Joydeep Kim, Donghyun Robotics Computer Vision and Pattern Recognition Human-Computer Interaction 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-and-repeat 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 user study 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 retrieving a path in a manner comparable to guide dogs. |
| title | GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant For Blind Travelers |
| topic | Robotics Computer Vision and Pattern Recognition Human-Computer Interaction |
| url | https://arxiv.org/abs/2512.06147 |