Fabian Schmidt — accepted AI-conference papers

2026

ROVER: A Multi-Season Dataset for Visual SLAM

Fabian Schmidt, Julian Daubermann, Marcel Mitschke, Constantin Blessing, Stephan Meyer, Markus Enzweiler +1

ICRA 2026poster

Robust Simultaneous Localization and Mapping (SLAM) is a crucial enabler for autonomous navigation in natural, semi-structured environments such as parks and gardens. However, these environments present unique challenges for SLAM due to frequent seasonal changes, varying light conditions, and dense …

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2023

Exploiting Spatio-Temporal Human-Object Relations Using Graph Neural Networks for Human Action Recognition and 3D Motion Forecasting

Dimitrios Lagamtzis, Fabian Schmidt, Jan Seyler, Thao Dang, Steffen Schober

IROS 2023poster

Human action recognition and motion forecasting is becoming increasingly successful, in particular with utilizing graphs. We aim to transfer this success into the context of industrial Human-Robot Collaboration (HRC), where humans work closely with robots and interact with workpieces in defined work…

Cited by 5 Source ↗Scholar ↗