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

Abstract

A quadruped robot is a promising system that can offer assistance comparable to that of guide dogs 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. To evaluate the usability, workload, and perceived noise of the developed system from a user's perspective, we conducted indoor walking experiments. In these tests, participants compared our controller with the robot's default controller. The results demonstrated higher user acceptance of our controller, highlighting its potential to improve the overall user experience of robotic guide dogs. Video demonstration (best viewed with audio) available at: https://guidedogrobot-stairclimbing.github.io.