Human-Centered Development of Guide Dog Robots: Quiet and Stable Locomotion Control

TL;DR

This paper presents a novel quadruped robot locomotion controller designed to reduce noise and improve stability, making guide dog robots more suitable for blind and low-vision users through extensive testing and user feedback.

Contribution

The paper introduces a new walking controller that achieves quieter, smoother, and more stable locomotion for quadruped robots, addressing key challenges for guide dog applications.

Findings

Significant noise reduction compared to default controllers

Higher user acceptance among BLV individuals

Effective locomotion over non-flat terrains

Abstract

A quadruped robot is a promising system that can offer assistance comparable to that of dog guides due to its similar form factor. However, various challenges remain in making these robots a reliable option for blind and low-vision (BLV) individuals. Among these challenges, noise and jerky motion during walking are critical drawbacks of existing quadruped robots. While these issues have largely been overlooked in guide dog robot research, our interviews with guide dog handlers and trainers revealed that acoustic and physical disturbances can be particularly disruptive for BLV 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, such as stairs. 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. In our indoor walking experiments, participants compared our controller to the robot's default controller. Results demonstrated superior acceptance of our controller, highlighting its potential to improve the user experience of guide dog robots. Video demonstration (best viewed with audio) available at: https://youtu.be/8-pz_8Hqe6s.