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Advanced Control System Design for Enhancing the Situational Awareness of Robotic Platforms in the Nuclear Environment

   Faculty of Science and Engineering

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  Dr Allahyar Montazeri, Dr Cuebong Wong, Dr Dean Connor  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

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 Lancaster University 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.

Eligibility Criteria

  • 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 ([Email Address Removed]), Dr Cuebong Wong ([Email Address Removed]), or Dr Dean Connor ([Email Address Removed]).
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