A full PhD studentship is offered at the Department of Engineering, Lancaster University, UK to create a novel training paradigm of human sensorimotor augmentation (HSA) system tailored to personalised needs in extreme environment tasks such as: deep-sea exploration and nuclear decontamination and decommissioning, which demonstrates intuitive assistance for training less-experienced users (LEU) through new human-robot collaboration techniques.
The primary objective of HSA is to enhance the perception and motion capabilities of LEU with minimized training efforts. Reducing the need of LEU to enter hazardous environments has been more widely recognised. Nevertheless, many interactive teleoperation tasks highly rely on prior knowledge and skills of expert workers, resulting in operational obstacles for LEU to take over. New multi-resource feedback information fusion and arbitration techniques accessible to LEU are demanding. In addition, current tele-robotic technology is developed to deliver simple, repetitive and “one-size-fits-all” tasks, with limited parametrization and limited to specific needs. Although such devices are helpful, they lead to “reinventing the wheel” for every application scenario, at high development costs and slow innovation cycles that struggle to integrate novel technologies. As a result, extending the scope of interactive human-robot collaboration to overcome these challenges calls for tele-robotic systems building on human factors analysis and AI technologies.
The HSA project offers PhD students a multidimensional, highly integrated training programme. Critically, HSA will enable PhD students to build a network of peers across the Engineering School and beyond to enhance career prospects, which will contribute greatly to the innovation capacity of the Engineering School by creating new and improved collaborative links between different groups. This studentship may also present opportunities for testing and demonstration of the outputs of the research at Lancaster Intelligent, Robotic and Autonomous (LIRA) Systems Centre, Bristol Robotics Laboratory and Hamlyn Centre (Imperial College), based at Bristol and London, respectively.
The HSA project will largely foster the effective utilization of ML to maximize tailored training efficiency of the LEU in versatile interactive teleoperation tasks. The main objectives include:
· Develop a LEU training platform composed of Franka Emika Panda robots with local sensors and hybrid visual-haptic feedback provided to human-machine interfaces.
· Extract and analyse muscle motion and eye activity patterns of LEUs using multiple physiological signals such as EEG/EMG/temperature/gaze.
· Develop multisensory information-guided training strategy based on the extracted pattern
· Develop human-in-the-loop reinforcement learning framework considering the behaviour features of LEUs, e.g., suboptimal solution.
· Investigate inferred control from the interaction force and from eye gaze.
· Develop trustworthy AI model to arbitrate between
· Test the resulting algorithms and control in experiments involving graduate students.
Lancaster University has a world ranking of 146th out of more than 1,000 universities in the QS World University Rankings 2023. It is a strong and dynamic university with a very highly regarded Engineering Department. In the 2021 Research Excellence Framework, 95% of its research rated as world-leading or internationally excellent. Lancaster’s approach to interdisciplinary collaboration means that it has pre-eminent capacity and capability for the integration of Engineering with expertise in the areas of data science, autonomous and learning systems, intelligent automation, materials science, and cyber security. The University is developing an ambitious growth plan for Engineering, including investment in staff, doctoral students, equipment and a new building focused on research themes including robotics and AI. Lancaster University has been rated top in the region in the Times and The Sunday Times Good University Guide 2023 and sits 12th on the table nationally.
Qualifications and experience:
· Candidates should have a relevant degree at 2.1 minimum or an equivalent overseas degree in Mechanical Engineering Mechatronics/ Electrical Engineering/ Computer Science / Industrial Engineering/ Education. Applicants with a background in education, ergonomics or neuroscience are preferably welcome.
· A good background in robotics and computer programming such as MATLAB and Python is desirable.
· Excellent oral and written communication skills with ability to prepare presentations, reports, and journal papers to the highest levels of quality.
· Excellent interpersonal skill to work effectively in a team consisting of PhD students and postdoctoral researchers.
Non-UK students are welcomed to apply. Overseas applicants should submit IELTS results (minimum 6.5) if applicable.
Informal enquiries and how to apply
For informal enquiries, please contact Dr. Ziwei Wang ([Email Address Removed]). Candidates interested in applying should send a copy of their CV together with a cover letter addressing their background and suitability for this project to Dr. Ziwei Wang by the closing date: 1st March 2023.