Cephalopods can propel their bodies underwater, steer them in the desired directions, and physically explore the surrounding environment, effectively combining mobility and exploration; one crucial component to support these intelligent behaviours is the capability to sense both the water flow and the physical contacts with tactile receptors in the tentacles. Underwater robots with comparable skills can have a tremendous impact on our ability to explore large regions of the sea, supporting many defence operations. Although different prototypes of a robotic cephalopods have been developed, they lack water flow sensing and tactile sensing capabilities, and therefore the precise steering of the motion and the ability to generate and control physical contacts with the surrounding environment is hindered.
Therefore, in this project we will develop an innovative octopus-inspired underwater robot that can swim, locomote and explore its surroundings effectively, leveraging on tactile capabilities offered by novel highly sensitive tactile sensors. We will explore methods for developing miniature tactile sensors that can seamlessly integrate into a soft robot octopus, enabling independent control of the motion of its tentacles. We will also investigate how Machine Learning/Artificial Intelligence techniques can be used to encode the tactile information so that we can develop an automatic control policy for steering the robot motion and exploring the environment. Finally, the developed tactile soft octopus robot will be tested in a water tank to autonomously perform a number of tasks, including swimming from point A to point B, as fast as possible, while avoiding obstacles in the way (that will be detected by touch), and locomoting on the ground (underwater) while detecting objects with the “free” tentacles.
Candidates should have a first-class honours degree (minimum 2(i) honours) or equivalent or a good MSc/MRes Degree, in mechanical or electrical engineering, computer science, or a field closely related to robotics. Strong motivation and a commitment to achieving excellence are essential. Proficiency in programming languages such as Python, C/C++, MATLAB is also necessary. Applicants with advanced knowledge in robotics (especially soft robotics), control systems, machine learning, artificial intelligence, tactile sensing, and/or prior research experience in these areas are highly encouraged to apply.
About Queen Mary University of London (QMUL) and The Centre for Advanced Robotics @ Queen Mary (ARQ):
This project will be conducted in collaboration between ARQ at Queen Mary University of London and the Defence Science and Technology Laboratory (DSTL). ARQ is a multidisciplinary research centre situated in Mile End Campus, QMUL. It operates across faculties and focuses on various research areas including robot design and mechatronics, human-robot interaction, bio-inspired robotics, social robotics, control and systems engineering, autonomous systems, field robotics, and sensing and biomedical mechatronics. QMUL is a research-intensive institution, ranked 2nd in the UK for the quality of its engineering research outputs in the REF2021 exercise.
ARQ - Centre for Advanced Robotics at QMUL
http://www.qmul.ac.uk/robotics
Eligibility
- UK home students are preferred for this application (See: http://www.welfare.qmul.ac.uk/money/feestatus/ for details of UK Home status)
- The minimum requirement for this studentship opportunity is a good Honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
- If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).
- Candidates are expected to start from Sept/Oct 2023
Supervisors Contact Details:
For informal enquiries about this position, please contact Thilina Dulantha Lalitharatne E-mail: [Email Address Removed] or Lorenzo Jamone E-mail: [Email Address Removed]
Application Method:
To apply for this studentship and for entry on to the PhD Full-time the Mechanical Engineering - Semester 1 (September Start), please follow the instructions detailed on the following webpage:
Research degrees in Engineering:
http://www.qmul.ac.uk/postgraduate/research/subjects/engineering.html
Further Guidance: http://www.qmul.ac.uk/postgraduate/research/
Please be sure to include a reference to ‘SEMS-PHD-524’ to associate your application with this studentship opportunity.
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