Enhancing Danger and Hazard Perception in Robotic Guide Dogs Kingston University in United Kingdom

This PhD project at Kingston University focuses on advancing the capabilities of robotic guide dogs, aiming to enhance their danger and hazard perception for visually impaired individuals. Traditional guide dogs provide invaluable support, but their training and maintenance are resource-intensive, and not all individuals can care for a living animal. Robotic guide dogs offer a promising alternative, combining the reliability of technology with the benefits of conventional guide dogs.

Recent developments in robotics have led to significant improvements in obstacle avoidance and autonomous navigation, particularly with quadruped robots capable of guiding humans through complex environments. However, current robotic guide dogs lack sophisticated hazard perception and effective user feedback systems for hazard response. This project seeks to address these gaps by developing advanced sensor fusion techniques for real-time hazard detection, integrating machine learning algorithms to predict and react to dynamic hazards, and utilizing simulated environments powered by generative AI and physics simulators for robust training scenarios. Additionally, the project will focus on creating a user feedback system to facilitate effective communication between the robot and its human user during hazard events.

The research will have a substantial impact on assistive robotics, providing safer and more reliable mobility solutions for people with vision impairments. It will also contribute to the broader fields of autonomous systems and human-robot interaction. The successful candidate will join the Faculty of Engineering, Computing and the Environment, working under the supervision of Dr. Miftahur Rahman. Funding is available through the Graduate School studentships competition for October 2026 entry, with details provided on the Kingston University PhD Studentships page.

Applicants should possess a strong academic background in robotics, computer science, engineering, or related fields, with skills in machine learning, sensor fusion, and programming. International candidates may need to demonstrate English language proficiency. The application deadline is March 4, 2026. For further information or queries, contact Dr. Miftahur Rahman at [email protected]. Interested candidates should review the studentships information and faculty research pages and submit their application via the university portal.