GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant for Blind Travelers

Hochul Hwang1, Soowan Yang2, Jahir Sadik Monon1, Nicholas A. Giudice3, Sunghoon Ivan Lee1, Joydeep Biswas4, Donghyun Kim1
1University of Massachusetts Amherst, 2Daegu Gyeongbuk Institute of Science and Technology, 3University of Maine, 4The University of Texas at Austin,
arXiv Code Video GuideData

Summer can walk silently with half the noise of the default controller, offering a smoother and more comfortable experience for BLV individuals.

Abstract

Noise and jerky motion during walking are critical drawbacks of existing quadruped robots.

Acoustic and physical disturbances can be particularly disruptive for blind and low-vision individuals, who rely heavily on environmental sounds for navigation.

To address these issues, we developed a novel walking controller for slow stepping and smooth foot swing/contact while maintaining human walking speed, as well as robust and stable balance control. The controller integrates with a perception system to facilitate locomotion over non-flat terrains.

Our controller was extensively tested on the Unitree Go1 robot and, when compared with other control methods, demonstrated significant noise reduction – half of the default locomotion controller.

In this study, we adopt a mixed-methods approach to evaluate its usability with BLV individuals.

Results demonstrated superior acceptance of our controller, highlighting its potential to improve the user experience of guide dog robots.

Video

Control Framework

To develop a noise-suppressed guide-dog locomotion controller, our primary goal was to reduce the stepping frequencey and ensure gentle foot contacts by employing a combined NMPC+WBIC architecture.

NMPC (with full orientation representation) is solved by single-interation SQP, which allows 500 Hz update frequency, minimizing latency and enhancing over-all robot stability.

Default vs. Ours

(Need to update) Go1 default controller exhibits excessive roll, whereas our controller achieves superior balance control, resulting in lower noise levels.

User-study

(Need to update) We employed a mixed-methods approach to evaluate the walking and stair-climbing experience enabled by our controller with four BLV individuals.

BibTeX

@article{hwang2025guidenav,
      title={GuideNav: User-Informed Development of a Vision-Only Robotic Navigation Assistant For Blind Travelers},
      author={Hwang, Hochul and Yang, Soowan and Monon, Jahir Sadik and Giudice, Nicholas A and Lee, Sunghoon Ivan and Biswas, Joydeep and Kim, Donghyun},
      booktitle={2026 21st ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
      year={2026}
    }