Prof. Dr. Philipp Beckerle

Chair of Autonomous Systems and Mechatronics

We develop technical systems that functionally support their users and provide them with a positive experience.Our research approach equally considers human factors and technical requirements based on a mixture of methods from engineering and human sciences. We demonstrate our findings on wearable systems such as prostheses or exoskeletons, cognitive systems such as collaborative or humanoid robots, and general applications with tight human-robot interaction.

Research projects

  • Fault diagnosis and tolerance for elastic actuation systems in robotics: physical human-robot interaction
  • Active transfer learning with neural networks through human-robot interactions (TRAIN)
  • EFFENDI – EFficient and Fast text ENtry for persons with motor disabilities of neuromuscular origin

Current projects

  • Learning Predictive Maintenance of Fleets of Networked Systems

    (Third Party Funds Single)

    Term: 1. September 2023 - 31. August 2026
    Funding source: Bayerische Forschungsstiftung

    The project aims at advancing predictive maintenance for networked device fleets using learning approaches and integrating expert knowledge. To this end, we will combine machine learning with physical models and analyze data flows between systems as well as integrate expertise on system behavior and failure modes. The resulting predictive maintenance approach for networked systems will be transferred to various classes of systems. Besides investigating industrial applications, we will create a fleet of mobile robots to demonstrate the capabilities of the predictive maintenance approach and make it available to academia, industry, and beyond.

Recent publications





Related Research Fields