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The success of accelerating and embedding robotics and autonomous systems within horticulture relies on a capable and robust navigation system for the robotic system to traverse and operate in a variety of agricultural/horticultural environments. This project aims to develop and deploy a low-cost, low-maintenance, yet reliable multi-session simultaneous localisation and mapping (SLAM) solution for robotic systems that face specific agricultural-related challenges.

We are seeking to appoint a passionate and highly qualified Postdoctoral Research Associate in Mobile Robotics to join the Loughborough University Centre for Autonomous Systems (LUCAS). This post is associated to a UKRI funded project on Precision Orchard Management for Environment (POME). You will work in a well-connected and diverse research team at LUCAS with state-of-the-art facility for robotic research. The post will provide an excellent opportunity to develop your knowledge and skills on autonomous mobile robotics with impactful applications in agricultural and horticultural industries.

To work efficiently in a project consortium and conduct research in the area of mobile robotics, you will manage own academic research and administrative activities, adapt existing and develop new methodologies in robotics, design working algorithms from theories, deploy and test algorithms on hardware as appropriate, and analyse data from a variety of sources and field trails. In addition, the more specific duties in this project require you to expand and augment existing graph-based SLAM methods to enable multi-session SLAM to be preformed in complex feature sparce agricultural environment. This is to enable consistent robotic operation and mapping throughout the year within an everchanging environment. Enabled through the use of IMU, Visual data or LiDAR sensors.

You must hold or close to complete a Doctorate degree in Control Engineering, Computer Science, Robotics, Autonomous systems or a related technical field, or a MSc/MRes degree with substantial working experience in relevant fields. Demonstrated ability to program in C/C++, Python and/or MATLAB to a high standard, experience with state estimation and factor-graph algorithms and working experience with the Robotic Operating System (ROS), track record of publications preferably in robotics or control engineering themed journals are essential. Experience in the use of inertial measurement units, Simultaneous Localisation and Mapping (SLAM) and Visual Inertial Odometry (VIO) and experience of field trials of mobile robotic systems would be desirable.

For more information refer to theJob Description and Person Specification.

From £35,116. Specialist and Supporting Academic Research grade 6. Subject to annual pay award.