Daniel Eriksson

Host institutions and supervisors

Karlsruher Institut für Technologie, Prof. Geimer

 LIEBHERR- Werk Bischofshofen GmbH, Dr. Bös

Research project

Automatic Bucket Filling for Wheel Loaders Using Machine Learning Techniques – ESR 6

Scientific backgroud

Master of Science in System, Control and Robotics from the Royal Institute of Technology (KTH), Sweden (2019) with the title of thesis: Underwater Change Detection by Fusing Multiple Sonar Images. Bachelor of Electrical Engineering from KTH, Sweden (2017).


  • Eriksson, D., & Ghabcheloo, R. (2023). Comparison of machine learning methods for automatic bucket filling: An imitation learning approach. Automation in Construction150, 104843. https://doi.org/10.1016/j.autcon.2023.104843

Conference proceedings

  • Eriksson, D., & Geimer, M. (2023). Optimizing a Bucket Filling Strategy for Wheel Loaders Inside a Dream Environment. In Proceedings of the 18th Scandinavian International Conference on Fluid Power (SICFP’23), 30.5.-1.6. 2023, Tampere, Finland. Ed.: T. Minav (p. 239). https://urn.fi/URN:ISBN:978-952-03-2911-2
  • Machado, T., Fassbender, D., Taheri, A., Eriksson, D., Gupta, H., Molaei, A., Forte,  P., Rai, P. K., Ghabcheloo, R., Mäkinen, S., Lilienthal,  A. J., Andreasson, H., Geimer, M. (2021). Autonomous Heavy-Duty Mobile Machinery: A Multidisciplinary Collaborative Challenge. In 2021 IEEE International Conference on Technology and Entrepreneurship (ICTE). https://doi.org/10.1109/ICTE51655.2021.9584498 Proceeding of the International Conference on Technology and Entrepreneurship (ICTE) 2021.

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