Motion Control of a Guide Dog Robot Adapted to the Intentions of Visually Impaired Individuals and Dynamic Environmental Conditions

To enhance the mobility and quality of life of visually impaired individuals, this paper proposed a guide dog robot by improving navigation and interaction capabilities under dynamic environments. Integrating with existing navigation technologies, two user-operated buttons are equipped to the robot to accelerate or decelerate the speed, temporarily stop or restart the robot, according to the will and operations of the user. The moving speed of the robot is finally calculated by combing the will of the user and the situation of the environment to ensure the safety of the user. Additionally, a voice interaction system is proposed to generate real-time environmental descriptions based on LSTM neural networks, conveyed through speech synthesis. Experiments demonstrate that the robot effectively responds to user commands, as well as ensuring safety, and interacts well with the user.

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Publication Details

Published
2025-06-27
DOI
https://doi.org/10.1109/icras65818.2025.11108859
Primary Topic
Human-Animal Interaction Studies
Type
article
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article

Motion Control of a Guide Dog Robot Adapted to the Intentions of Visually Impaired Individuals and Dynamic Environmental Conditions

Bin Zhang, Yuhui Gao
Human-Animal Interaction Studies
article

Motion Control of a Guide Dog Robot Adapted to the Intentions of Visually Impaired Individuals and Dynamic Environmental Conditions

Bin Zhang, Yuhui Gao
article en

Abstract

To enhance the mobility and quality of life of visually impaired individuals, this paper proposed a guide dog robot by improving navigation and interaction capabilities under dynamic environments. Integrating with existing navigation technologies, two user-operated buttons are equipped to the robot to accelerate or decelerate the speed, temporarily stop or restart the robot, according to the will and operations of the user. The moving speed of the robot is finally calculated by combing the will of the user and the situation of the environment to ensure the safety of the user. Additionally, a voice interaction system is proposed to generate real-time environmental descriptions based on LSTM neural networks, conveyed through speech synthesis. Experiments demonstrate that the robot effectively responds to user commands, as well as ensuring safety, and interacts well with the user.

Kanagawa University (JP)
Life in Land
Openalex Percentile: Top 77%
Human-Animal Interaction Studies
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