Dr Alireza Rastegarpanah MEng, PhD

Dr Alireza Rasregarpanah

School of Metallurgy and Materials
Senior Robotic Scientist at UoB and the Faraday Institution
Co-Founder of Extreme Robotics Lab
Co-Founder of the National Robotic Centre at the Birmingham Energy Innovation Centre

Contact details

Telephone
+44 (0)121 415 9989
Email
a.rastegarpanah@bham.ac.uk
View my research portal
Address
Extreme Robotics Lab
Metallurgy and Materials
The University of Birmingham
Edgbaston
Birmingham, B15 2SE

Dr Alireza Rastegarpanah is a Senior Robotic Scientist who wears many hats; he is Co-I of €5M REBLION project, Co-Founder of Extreme Robotics Lab, Robotic Scientist at the Faraday Institution, Senior automation consultant, Co-Founder of National Robotic Test bed at the Birmingham Energy Innovation Centre. He is a leading expert with more than a decade of experience in robotics and artificial intelligence, and half a decade of experience in applying his knowledge in reuse and recycling of EV batteries.

Alireza's research interests are broadly centred on human-robot interface, machine learning, advanced robotics, medical robotics, and robotic disassembly. He obtained his PhD in Robotics from the University of Birmingham and has conducted extensive research in leading universities and research organizations such as the University of Birmingham, University College London, and the Faraday Institution.

Dr Rastegarpanah has led numerous research projects throughout his career, and he is currently involved in multiple projects aimed at advancing robotics and artificial intelligence technologies. Dr. Rastegarpanah has a distinguished publication record of over three dozen technical papers in robotics and has organized numerous national and international conferences and workshops, showcasing his expertise and significant contributions to the field.

Dr Rastegarpanah's work is aimed at creating sustainable and efficient solutions to real-world problems by transferring knowledge from academia to industry. He has several funded collaborations with various industries, such as the Manufacturing Technology Centre and Direct Line Insurance Group. He also provides consultancy services in robotics and automation for various industries, including start-up companies. 

Further information can be found on my LinkedIn profile and YouTube channel.

Qualifications

  • Research scientist - Faraday Institution 2018-present
  • Research Fellow at the University College London 2017-2018
  • Research Fellow at the University of Birmingham 2017-2017
  • PhD in Robotics, University of Birmingham 2016
  • MEng in Biomechanics, University of Birmingham 2011

Biography

Faraday Institution Recycling Lithium Ion batteries project
Scanning and constructing 3D model of EV battery pack
Reuse and Recycling Lithium Ion batteries
Robotic Grasping of Moving Objects by dynamic re-planning

Dr Alireza Rastegarpanah is an interdisciplinary engineer with diverse research interests, although mainly focusses on robotics. His main interests include vision and sensing, robotic manipulation, human-robot interaction, AI and machine learning.

He is the Co-founder of Extreme Robotics Lab (ERL); ERL includes a 1,000m2 research lab on the university campus (more than15 different robot arms, dexterous hands, a variety of advanced vehicles, sensors and in-house super-computing), with an additional 500m2 industrial space off campus which houses extremely large heavy duty industrial robot arms (can manipulate half-tonne objects) and other equipment.

Dr Rastegarpanah leads the ERL Control and Manipulation team, and currently supervising eight PhD students along with several MScs and interns. His team's primary focus is on developing learning-based robotic systems for automating the testing, disassembly, and sorting of complex products, such as EV batteries, electric motors, and wind turbines, to extract critical materials (such as Lithium, magnet, Nickel, and cobalt) to contribute to the circular economy.

Dr Rastegarpanah graduated in robotics from the University of Birmingham in 2016. His PhD focused on developing an assistive-resistive robotic system for the rehabilitation of post-stroke people. His developed robotic system is made by a combination of an actuated parallel robot in conjunction with a passive platform. The motion signatures of the healthy leg attached to the passive platform  will be mapped to the affected one attached to the active parallel robot. The mapping between two legs is developed based on kinematic relationship between two legs during a normal gait.  His developed system is showed case in various clinics and rehabilitation centres. He has extensive knowledge medical robotics and parallel robots.

Dr Alireza Rastegarpanah is an accomplished Scientist who has received more than £1.6 million in grant income (as of April 2023). He has led numerous research projects throughout his career, and he is currently involved in multiple projects aimed at advancing robotics and artificial intelligence technologies. He is a Co-Investigator of the €5M REBLION project, an EU initiative that aims to develop next-generation robots for the reuse and recycling of complex products, with a particular focus on EV batteries.

Dr Alireza Rastegarpanah also oversees the automation of the RELIB project (Reuse and Recycling of Lithium-ion Batteries), funded by the Faraday Institution. In addition, he is the Co-Founder of the National Robotic Testbed at the Birmingham Energy Innovation Centre, located in Tyseley Energy Park. This testbed is equipped with heavy-duty industrial robots and advanced sensors to demonstrate high Technology Readiness Level (TRL) robotic disassembly for extracting critical materials in an industrial-scale setting.

Beyond academia, he is also committed to disseminating his research to the wider public. He has conducted TV interviews, written news articles, and published scientific papers to share his research findings with a broader audience. Additionally, Dr Rastegarpanah has been actively involved in organizing and running STEM outreach events, aimed at inspiring young learners to pursue higher education in science, technology, engineering, and mathematics. His dedication to education and outreach has earned him high praise and recognition, both within the academic community and beyond.

Teaching

Dr Alireza Rastegarpanah has a broad range of teaching experience, from extensive tutoring, individual mentoring to designing and delivering engineering modules to undergraduate/postgraduate students such as:

  • Applied Mathematics,
  • Computer-aided drawing and finite element analysis,
  • Artificial Intelligence,
  • Mechanical design B,
  • Electronics and Computer Systems,
  • Operations Management,
  • Advanced Mechanics

Postgraduate supervision

Dr Rastegarpanah has a track record of supervising and mentoring undergraduate and postgraduate students throughout his career. Currently, he leads the Control and Manipulation team at the Extreme Robotics Lab, University of Birmingham, supervising 8 PhD students and several interns and MSc students.

Dr Rastegarpanah's funded research grants and collaborations with industry have directly funded some of his students. His team's research is focused on developing adaptive control strategies for the disassembly of complex products, including EV batteries, electric motors, and wind turbines.

The list of his current PhD students is as follows:

  • Ali Aflakian
  • Jamie Hathaway
  • Abdelaziz Sharaway
  • Cansu Akdenaiz
  • Irum Mehboob
  • Eesa Mohammed Asif
  • Minhao Yang
  • Cesar Contreras

Dr Alireza Rastegarpanah welcomes self-funded PhD students who are interested in the fields of robotics, machine vision, and artificial intelligence.

Research

Research interests

  • Human-Robot-Interaction
  • Machine Vision
  • AI and Machine Learning
  • Robot manipulation
  • Adaptive Control Theories
  • Medical Robotics
  • Rehabilitation Robotics
  • Robotic Disassembly
  • Reinforcement Learning
  • EV Batteries

 Current projects

  • REBELION : €5-Million HORIZON-CL5-2022-D2-01-10; Research and development of a highly automated and safe streamlined process for increased Lithium-ion battery repurposing and recycling.
  • Funded project with Manufacturing Technology Centre:
    Developing a multi-robot task planner for robotic disassembly of Lithium-ion battery disassembly in an industrial scale.
  • Natural Environment Research Council (NERC):
    Overcoming legal obstacles to facilitate the safe and effective robotic disassembly of lithium-ion batteries
  • Funded project by Direct Line Insurance Group
  • Faraday Institution PhD Studentship: Developing a hierarchical task execution framework for automatic disassembly of electrical vehicle battery pack.

Other activities

  • Trained roboticist by KUKA Robotics Ltd.:
    • KRC4 Programming
    • Robot Programming 1 KSS 8.x (KR C4)
    • Robot Programming 2 KSS 8.x (KR C4)
    • Mechanical Servicing QUANTEC
    • LBR iiwa - Robot Operation Sunrise OS 1
    • KMP/KMR – Commissioning and Programming Sunrise OS
  • Professional musician: Bağlama, Tanbour, Tar, Setar, Daf

Publications

Selected papers

  1. Hathaway, J., Rastegarpanah, A. and Stolkin, R. (2023) ‘Learning robotic milling strategies based on passive variable operational space interaction control’, arXiv preprint arXiv:2304. 01000.
  2. Rastegarpanah, A., Hathaway, J., et al. (2021) ‘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. SAGE Publications Sage UK: London, England, 235(3), pp. 330–346.
  3. Aflakian, A., Rastegarpanah, A. and Stolkin, R. (2023) ‘Boosting Performance of Visual Servoing using Deep Reinforcement Learning from Multiple Demonstrations’, IEEE Access. IEEE.
  4. Marturi, N. et al. (2019) ‘Dynamic grasp and trajectory planning for moving objects’, Autonomous Robots. Springer US, 43, pp. 1241–1256.
  5. Hathaway, J. et al. (2023) ‘Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries’, arXiv preprint arXiv:2304. 01065.
  6. Rastegarpanah, A., Ahmeid, M., et al. (2021) ‘Towards robotizing the processes of testing lithium-ion batteries’, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. SAGE Publications Sage UK: London, England, 235(8), pp. 1309–1325.
  7. Azizi, M. R., Rastegarpanah, A. and Stolkin, R. (2021) ‘Motion planning and control of an omnidirectional mobile robot in dynamic environments’, Robotics. MDPI, 10(1), p. 48.
  8. Rastegarpanah, A., Gonzalez, H. C. and Stolkin, R. (2021) ‘Semi-autonomous behaviour tree-based framework for sorting electric vehicle batteries components’, Robotics. MDPI, 10(2), p. 82.
  9. Rastegarpanah, A., Aflakian, A. and Stolkin, R. (2022) ‘Optimized hybrid decoupled visual servoing with supervised learning’, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. SAGE Publications Sage UK: London, England, 236(2), pp. 338–354.
  10. Rastegarpanah, A., Hathaway, J. and Stolkin, R. (2021) ‘Vision-guided mpc for robotic path following using learned memory-augmented model’, Frontiers in Robotics and AI. Frontiers Media SA, 8, p. 688275.
  11. Rastegarpanah, A., Howard, R. and Stolkin, R. (2022) ‘Tracking linear deformable objects using slicing method’, Robotica. Cambridge University Press, 40(4), pp. 1188–1206.
  12. Rastegarpanah, A., Ner, R., et al. (2021) ‘Nut unfastening by robotic surface exploration’, Robotics. MDPI, 10(3), p. 107.
  13. Rastegarpanah, A., Aflakian, A. and Stolkin, R. (2021) ‘Improving the Manipulability of a Redundant Arm Using Decoupled Hybrid Visual Servoing’, Applied Sciences. MDPI, 11(23), p. 11566.
  14. Scone, T. et al. (2023) ‘Effects of Variations in Hemiparetic Gait Patterns on Improvements in Walking Speed’, IRBM. Elsevier Masson, 44(1), p. 100733.
  15. Harper, G. et al. (2022) ‘Roadmap for a sustainable circular economy in lithium-ion and future battery technologies’, Journal of Physics: Energy.
  16. Marturi, N. et al. (2016) ‘Towards advanced robotic manipulation for nuclear decommissioning: A pilot study on tele-operation and autonomy’, in 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA). IEEE, pp. 1–8.
  17. Rastegarpanah, A., Marturi, N. and Stolkin, R. (2017) ‘Autonomous vision-guided bi-manual grasping and manipulation’, in 2017 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO). IEEE, pp. 1–7.
  18. Marturi, N. et al. (2017) ‘Towards advanced robotic manipulations for nuclear decommissioning’, Robots Operating in Hazardous Environments. InTech Vienna, Austria.
  19. Rastegarpanah, A., Wang, Y. and Stolkin, R. (2022) ‘Predicting the Remaining Life of Lithium-ion Batteries Using a CNN-LSTM Model’, in 2022 8th International Conference on Mechatronics and Robotics Engineering (ICMRE). IEEE, pp. 73–78.
  20. Joshi, P., Rastegarpanah, A. and Stolkin, R. (2021a) ‘A training free technique for 3D object recognition using the concept of vibration, energy and frequency’, Computers & Graphics. Pergamon, 95, pp. 92–105.
  21. Joshi, P., Rastegarpanah, A. and Stolkin, R. (2021b) ‘An Efficient Technique for Filtering of 3D Cluttered Surfaces’, in Artificial Intelligence and Soft Computing: 20th International Conference, ICAISC 2021, Virtual Event, June 21--23, 2021, Proceedings, Part II 20. Springer International Publishing, pp. 36–43.
  22. Joshi, P., Rastegarpanah, A. and Stolkin, R. (2020a) ‘A survey on training free 3D texture-less object recognition techniques’, in 2020 Digital Image Computing: Techniques and Applications (DICTA). IEEE, pp. 1–3.
  23. Joshi, P., Rastegarpanah, A. and Stolkin, R. (2020b) ‘Are Current 3D Descriptors Ready for Real-time Object Recognition?’, in 2020 8th International Conference on Control, Mechatronics and Automation (ICCMA). IEEE, pp. 217–221.
  24. Saadat, M. et al. (2018) ‘Path’s slicing analysis as a therapist’s intervention tool for robotic rehabilitation’, in Advances in Service and Industrial Robotics: Proceedings of the 26th International Conference on Robotics in Alpe-Adria-Danube Region, RAAD 2017. Springer International Publishing, pp. 901–910.
  25. Rastegarpanah, A., Rakhodaei, H., et al. (2018) ‘Path-planning of a hybrid parallel robot using stiffness and workspace for foot rehabilitation’, Advances in Mechanical Engineering. SAGE Publications Sage UK: London, England, 10(1), p. 1687814017754159.
  26. Rastegarpanah, A., Scone, T., et al. (2018) ‘Targeting effect on gait parameters in healthy individuals and post-stroke hemiparetic individuals’, Journal of Rehabilitation and Assistive Technologies Engineering. SAGE Publications Sage UK: London, England, 5, p. 2055668318766710.
  27. Maddalena, M. et al. (2017) ‘An optimized design of a parallel robot for gait training’, in 2017 International Conference on Rehabilitation Robotics (ICORR). IEEE, pp. 418–423.
  28. Rastegarpanah, A. (2016) A methodology for the lower limb robotic rehabilitation system. University of Birmingham.
  29. Rastegarpanah, A. and Saadat, M. (2016) ‘Lower limb rehabilitation using patient data’, Applied Bionics and Biomechanics. Hindawi, 2016.
  30. Borboni, A. et al. (2016) ‘Kinematic performance enhancement of wheelchair-mounted robotic arm by adding a linear drive’, in 2016 IEEE international symposium on medical measurements and applications (MeMeA). IEEE, pp. 1–6.
  31. Rastegarpanah, A. et al. (2016) ‘Application of a parallel robot in lower limb rehabilitation: A brief capability study’, in 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA). IEEE, pp. 1–6.
  32. Rakhodaei, H. et al. (2016) ‘Path planning of the hybrid parallel robot for ankle rehabilitation’, Robotica. Cambridge University Press, 34(1), pp. 173–184.
  33. Rakhodaei, H., Saadat, M. and Rastegarpanah, A. (2014) ‘Motion simulation of a hybrid parallel robot for ankle rehabilitation’, in Engineering Systems Design and Analysis. American Society of Mechanical Engineers, p. V003T17A008.
  34. Rakhodaei, H. R. et al. (2013) ‘Free singularity path planning of hybrid parallel robot’, in. Cranfield University.
  35. Rastegarpanah, A., Saadat, M. and Rakhodaei, H. (2012) ‘Analysis and simulation of various Stewart Platform configurations for lower limb rehabilitation’, in BEAR conference, University of Birmingham, Birmingham-UK.

View all publications in research portal