About the Project
About the project: Reuse and Recycling of Lithium-ion batteries (RELIB): Introducing robotics into the waste and recycling sector, will boost productivity, stabilize the existing jobs market and could also draw jobs into the UK by providing valuable raw materials to feed in further up manufacturing supply chains. The ReLiB project, funded by The Faraday Institution, will have a significant impact on the safety, economics and efficiency of battery recycling whilst minimizing the environmental impact of these processes.
About the Extreme Robotics Lab (ERL): The University of Birmingham Extreme Robotics Lab, is one of the leading university robotics labs in Europe dedicated to practical applications of robotics and AI to extreme environments:
http://www.birmingham.ac.uk/research/activity/metallurgy-materials/robotics/index.aspx
About the PhD position: The ERL team is collectively working on robotic grasping and manipulation; planning and reasoning for fixed and/or mobile manipulators; robotic vehicles and navigation; robot dynamics and control and Computer Vision, machine learning and AI. The PhD student should demonstrate strong expertise in at least one of these areas. This PhD project is set to address key challenges in robotizing the procedure of dismantling Electrical Vehicle`s batteries. The objectives of the project include:
-- To develop an automated framework for disassembly of Lithium-ion batteries (from pack level to cell level)
-- To develop novel learning-based AI-driven methods for manipulating the robot using sensory feedback (e.g. point cloud obtained by RGBD camera, Force/Torque sensor etc)
-- To develop and demonstrate novel robotic processes (i.e. cutting, unbolting etc) based on Machine learning methods in both simulation and real world
Required knowledge, skills, qualifications:
-- 1st class degree in robotics, AI, machine learning, control engineering, computer engineering or a relevant discipline, at Masters level, or an equivalent overseas degree
-- Strong programming skills in C++ and Python
-- Demonstrated expertise in ROS
-- Demonstrable knowledge of mathematics and algorithms for computer vision
-- Demonstrable knowledge of AI and relevant machine learning methods
-- Demonstrable knowledge of control systems, kinematics and dynamics of robot
-- Experience of working with Solidworks and Matlab(Simulink) will be an advantage
-- A driven, professional and self-dependent work attitude is essential
-- Experience of working within industry will be an advantage
-- The ability to produce high quality presentations, technical papers and written reports
This is an excellent opportunity to work on a novel robotics system with strong links to industrial applications and key skills and knowledge in preparation for a high-impact, high-technology research or industrial career.
To apply:
Please share your CV, cover letter and one recommendation letter (ideally from your MSc supervisor(s)) over a cloud (i.e. Dropbox, OneDrive etc) and email the shared link to Dr Alireza Rastegarpanah: [Email Address Removed]
*********PLEASE DO NOT ATTACH THE REQUESTED FILES TO YOUR EMAIL*********
Start Date: Starting as early as possible
References
Harper, G., Sommerville, R., Kendrick, E., Driscoll, L., Slater, P., Stolkin, R., Walton, A., Christensen, P., Heidrich, O., Lambert, S. and Abbott, A., 2019. Recycling lithium-ion batteries from electric vehicles. Nature, 575(7781), pp.75-86.
Rastegarpanah, A., Hathaway, J., Ahmeid, M., Lambert, S., Walton, A. and Stolkin, R., 2020. A rapid neural network–based state of health estimation scheme for screening of end of life electric vehicle batteries. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, p.0959651820953254.
Marturi, N., Kopicki, M., Rastegarpanah, A., Rajasekaran, V., Adjigble, M., Stolkin, R., Leonardis, A. and Bekiroglu, Y., 2019. Dynamic grasp and trajectory planning for moving objects. Autonomous Robots, 43(5), pp.1241-1256.