Looking to list your PhD opportunities? Log in here.
About the Project
Robotic active perception is a key factor to develop autonomous systems capable of safely and intelligently interacting with humans and their surrounding environment. Active perception allows robots to not only make accurate decisions, but also to autonomously perform actions that will lead the robot to improve its own performance during a specific task, such as autonomous driving, wearable assistive robots and human-robot collaboration.
Even though state-of-the-art robots are equipped with multimodal sensors (e.g., vision, touch, audio, force, gyroscopes), the capability of accurately and reliably extracting and fusing this multimodal data remains a challenge. The lack of this capability in robotic systems limits robots’ potential for autonomous learning, control, decision-making and actions, which also reduces the capability of robots to behave safely and intelligently.
This project, which is aligned with the UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent Artificial Intelligence (ART-AI), involves the following key aspects required for the development of safe autonomous vehicles:
• Research and development of cognitive architecture for robot sensing, decision-making and control composed of high-level, middle-level, and low-level processes.
• Research and development of advanced machine learning methods capable of exploiting the benefits of multimodal sensor data for reliable and responsible decision-making processes in autonomous vehicles.
• Development of human-machine interfaces that allow the designer and user to verify the decisions made by the autonomous vehicle. This interface provides a component of transparency for validation and accountability of the actions performed by the robotic system.
The methods developed in this project will be implemented and tested in ROSbot mobile robots, and with the racing car developed by the Team Bath Racing Electric – AI (TBRe-AI).
The research to be undertaken in this project has a strong multidisciplinary nature. Therefore, the student is expected to collaborate with students and researchers from the ART-AI CDT, computer science, electronic and electrical engineering, mechanical engineering, and psychology. Furthermore, the student is expected to attend multiple events such as conferences, workshops and publish the results from the research work in international conferences and journals.
Candidates are expected to have or near completion of an MSc or MEng in Robotics, Computer Science, Electronics, Mechanics, Mathematics, Physics or related areas.
Informal enquiries about the project should be directed to Dr Uriel Martinez Hernandez: umh21@bath.ac.uk.
Formal applications should be accompanied by a research proposal and made via the University of Bath’s online application form. Enquiries about the application process should be sent to art-ai-applications@bath.ac.uk.
Start date: 2 October 2023.
Funding Notes
We also welcome applications from candidates who can source their own funding.
Email Now
Why not add a message here
The information you submit to University of Bath will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.

Search suggestions
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Bath, United Kingdom
Check out our other PhDs in United Kingdom
Start a New search with our database of over 4,000 PhDs

PhD suggestions
Based on your current search criteria we thought you might be interested in these.
Robust perception and decision making for autonomous vehicles
Kingston University
Robust perception, decision making and path prediction for autonomous vehicles
Kingston University
6G Wireless Communications for Connected and Autonomous Vehicles in Challenging Environments
University of York