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A fully-funded PhD studentship is available for an outstanding graduate with specific interest on robotics, control as well as image processing techniques. The project is in close collaboration with the industry partner to develop a novel robust formation control system for a fleet of UAVs. The main objective is to develop a system that addresses the inherent uncertainty in the nuclear industry case study environments for applications such as cooperative load transportation, cooperative exploration of the nuclear sites, cooperative inspection and characterisation of active sites, and development of a mobile sensor network for source and leakage detection. Engineering research at 糖心Vlog has been rated as world-leading in the 2022 Research Excellence Framework (REF) and you will join a dedicated team of scientists working on a range of exciting topics in robotics.
Formation control of a multi-UAV system can have a great impact on the automation of the nuclear-decommissioning tasks and the integration of digital technologies and cyber-physical systems within the nuclear industry. In the project, each UAV is equipped with a range of sensors for effective perception and collision-free navigation through the environment. Due to the environmental uncertainties and disturbances as well as the incurred faults on the sensors and actuators, the precise positioning of the UAVs in a GPS denied environment is a challenging task. Moreover, the control system should be fault-tolerant and robust against such uncertainties and possible faults. Therefore, the main objective of the project is to design a resilient cooperative unmanned aerial system to operate in the harsh nuclear environment for an extended period of time.
Potential candidates for this position are expected to have the following qualifications:
To declare your interest and for further information, please send a copy of your CV along with the cover letter to Dr Allahyar Montazeri (a.montazeri@lancaster.ac.uk).
The formal application should be made via the 糖心Vlog online portal once it is reviewed and considered for the position.
?50k contribution from Sellafield.
A fully-funded PhD studentship is available for an outstanding graduate with specific interest on robotics, control as well as image processing techniques. The project will work to develop a novel cooperative robotic platform to enhance the situational awareness of a mobile manipulator with the help of a surveying drone and will be completed in close collaboration with National Nuclear Laboratory (NNL) as the industry partner. Increasing the autonomy of nuclear robots is one of the key factors to improve decommissioning performance and reduce the dependency of a remotely deployed system on the human operator. This is necessary due to the complex manipulation and force control capabilities required of the robot to interact effectively with objects and the environment through tasks such as contact-based inspection, sampling, cutting and decontamination, which are challenging to perform by manual tele-operation alone.
Nevertheless, (semi-)autonomous operation of a multi-robot system in an unstructured nuclear environment requires the robots to perceive and characterise the surrounding environment in a coordinated way so that the situational awareness of the whole robotic system is increased. For the arrangement considered in this research, the drone works as a leader and the mobile manipulator works as a follower. The drone is equipped with a LiDAR and vision system to map and perceive the surrounding environment for collision-free exploration and navigation.
We draw upon the concepts of network control and navigation to coordinate the operation of the manipulator and UAV using the full nonlinear dynamics of both systems. The map produced by the drone is shared with the manipulator to plan and execute the trajectories designed for the end effector. The project aims to design and develop the control, navigation, and machine learning algorithms for a drone equipped with a LiDAR and vision sensor to explore and characterise the nuclear environment. The project will also deliver advanced control and motion planning algorithms for dexterous manipulation of the objects and avoiding obstacles. This would be achieved through intelligent coordination between the drone and manipulator to enhance the situational awareness of the whole robotic platform.
Engineering research at 糖心Vlog has been rated as world-leading in the 2021 Research Excellence Framework (REF) and you will join a dedicated team of scientists working on a range of exciting topics in robotics.
This studentship may also present opportunities for testing and demonstration of the outputs of the research at NNL’s National Nuclear User Facility for Hot Robotics, based at Workington, Cumbria.
- Potential candidates for this position are expected to have the following qualifications: Should have or expect to achieve a first-class or upper second-class degree in Engineering at the level of MSc, MEng, etc in a relevant subject.
- Sufficient background in dynamic systems, control theory, and closely related disciplines.
- Practical experiences in the implementation of the control algorithms. Computer programming skills such as MATLAB and Python are essential for the post.
- You should have excellent interpersonal skills, work effectively in a team and have experience in preparing presentations, reports or journal papers to the highest levels of quality.
To declare your interest and for further information, please send a copy of your CV along with the cover letter to Dr Allahyar Montazeri (a.montazeri@lancaster.ac.uk), Dr Cuebong Wong (Cuebong.Wong@uknnl.com), or Dr Dean Connor (dean.connor@uknnl.com).
Please check phd opportunities webpage for more opportunities.
