DC2: Ensuring Runtime Safety: A Digital Twin Approach for ML-Based Controllers

Project: Ensuring Runtime Safety: A Digital Twin Approach for ML-Based Controllers (WP1)

Host institution: FGH-IESE (Germany)

Supervisor: Dr. R. Adler (FGH-IESE, Germany)

Co-supervisor(s): Davy Pissoort (KU Leuven), G. Lunzenfichter (Medisanté)

Objectives:

Create digital twin technology for individuals using assistive health technolgy devices to enhance real-time safety assurance of machine learning-based controllers; Assess the effectiveness of the developed methodology through a comprehensive evaluation in a single-use case study

Expected Results:

Establishment of a universal framework seamlessly integrating real-time safety assurance for machine learning-based controllers through digital twin technology; Demonstration of the digital twin technology for assisted individuals in simulation, focusing on a selected case study.

Planned secondment(s):

  1. KU Leuven (3 months, M22-M24) Study how to adapt and incorporate the run-time safety monitor framework with digital twin technology (3 months, M14-M16):, with Davy Pissort (KPI: joint conference paper)
  2. Medisanté (3 months, M38-M40) Application and evaluation – with respect to scientific criteria as well as practical applicability – of the platform in an industrial setting: with G. Lunzenfichter (KPI: joint journal paper)

Enrolment in Doctoral degree: Doctoral School of Technische Universität Kaiserslautern (Germany)

Required profile: Software Engineering

Desirable skills/interests: Safety, Digital Twins, Data Science

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