Linus Nwankwo, M.Sc.


Short Bio

Mr. Linus Nwankwo started as a PhD student at the Chair of Cyber-Physical-Systems (CPS) in August 2021.  Prior to joining CPS, he worked as a research intern at the Department of Electrical and Computer EngineeringTechnische Universität Kaiserslautern, Germany.

In 2020, he obtained his M.Sc. degree in Automation and Robotics, a speciality in control for Green Mechatronics (GreeM) at the University of Bourgogne Franche-Comté (UBFC), France. In his M.Sc. thesis,  he implemented a stabilisation control for a mobile inverted pendulum robot and investigated the possibility of controlling and stabilising the robot via CANopen communication network.

Research Interests

  • Robotics
    • Simultaneous localization & mapping (SLAM)
    • Path planning & autonomous navigation
  • Machine Learning
    • Large language models (LLMs) and vision language models (VLMs) 
    • Supervised, unsupervised, and reinforcement learning
    • Probabilistic learning for robotics 
  • Human-Robot Interaction (HRI)
    • Intention-aware planning for social service robots
    • Social-aware and norm learning navigation
    • LLMs and VLMs for HRI

Research Videos

Contact & Quick Links

M.Sc. Linus Nwankwo
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert since August 2021.
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Phone:  +43 3842 402 – 1901 (Sekretariat CPS)
Web Work: CPS-Page
Web Private:



Nwankwo, Linus; Rueckert, Elmar

Understanding why SLAM algorithms fail in modern indoor environments Proceedings Article

In: International Conference on Robotics in Alpe-Adria-Danube Region (RAAD). , pp. 186 – 194, Cham: Springer Nature Switzerland., 2023.

Abstract | Links | BibTeX

Understanding why SLAM algorithms fail in modern indoor environments

Nwankwo, Linus; Fritze, Clemens; Bartsch, Konrad; Rueckert, Elmar

ROMR: A ROS-based Open-source Mobile Robot Journal Article

In: HardwareX, vol. 15, pp. 1–29, 2023.

Abstract | Links | BibTeX

ROMR: A ROS-based Open-source Mobile Robot