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

2025-05-17

AI Summary

To address noise interference and motion instability encountered by blind and low-vision (BLV) users when deploying quadrupedal robots as guide dogs, this paper proposes the first hybrid gait–balance co-controller explicitly designed for acoustic comfort and motion smoothness. Methodologically, it integrates model predictive control (MPC) with impedance modulation to generate quiet, compliant gaits, and couples multi-sensor terrain perception with real-time stability margin optimization for robust balance control. Evaluated on the Unitree Go1 platform, the controller reduces walking noise by 50%, significantly improves slow-speed precise stepping, foot-end compliant contact, and stability on uneven terrains (e.g., stairs). Indoor user studies with BLV participants demonstrate markedly increased preference and enhanced natural navigation experience, validating a novel perception-aware human–robot interaction paradigm tailored to BLV users’ sensory needs.

Technology Category

• Intelligent Robots: Behavior Learning & Control
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

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.

Problem

• Reducing noise in quadruped robots for BLV users
• Improving motion smoothness in guide dog robots
• Enhancing stability on non-flat terrains like stairs

Innovation

• Novel quiet walking controller for quadruped robots
• Smooth foot swing and contact control
• Integrated perception for non-flat terrains