Papers

3

Total Citations

15

H-Index

2

About

Thomas Steinecker’s research focuses on the safety and autonomy of robotic systems, spanning physical human-robot interaction (pHRI) and autonomous navigation. His most impactful work introduces the “Mean Reflected Mass” metric, a physically interpretable tool for assessing collision safety and optimizing robot postures during human-robot interaction. This contribution, which has garnered 10 citations, provides a practical alternative to complex safety models by linking robot dynamics directly to injury risk, enabling safer collaborative robotics. Steinecker also developed a model-free path filtering algorithm that smooths noisy trajectory data without requiring intricate optimization or parameter tuning, offering a robust solution for real-time path reconstruction. His recent work on autonomous convoying presents a full-stack, perception-driven architecture for vehicle following in GNSS-denied environments, eliminating reliance on global localization or maps. This system integrates vehicle communication, localization, and object tracking to enable reliable convoy operations in challenging settings. With a growing citation record and contributions that bridge theoretical safety metrics with deployable autonomy, Steinecker is advancing practical, human-aware robotics and resilient navigation systems.

Research Focus

Key Achievements

2
H-Index
3
Papers
15
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Mean Reflected Mass: A Physically Interpretable Metric for Safety Assessment and Posture Optimization in Human-Robot Interaction
10 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Technical University of Munich, Universität der Bundeswehr München

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago