Gerald Steinbauer-Wagner
Papers
11
Total Citations
80
H-Index
5
About
Gerald Steinbauer-Wagner is an accomplished robotics researcher whose work spans autonomous systems, human-robot interaction, and mobile robot navigation in challenging environments. His research is particularly distinguished by its real-world applicability, addressing some of the most demanding scenarios in modern robotics — from extraterrestrial analog missions to wildfire disaster response. Steinbauer-Wagner's most impactful contribution to date integrates Belief-Desire-Intention agents with large language models to enable more reliable and explainable human-robot interaction, a timely advance that has already garnered 38 citations since its 2024 publication. His work on off-road navigation is equally notable, combining locomotion experiments, earth observation data, and convolutional neural networks to produce traversability and cost maps for ground robots operating in unstructured terrain — research that directly contributed to the AMADEE-20 Mars analog field mission in Israel's Negev Desert. Beyond navigation, Steinbauer-Wagner has explored robot autonomy architecture, energy-efficient path planning, explainable AI for motion planning failures, and trust-building frameworks for disaster response robotics. His EASIER project further underscores a recurring theme across his portfolio: making autonomous systems dependable, transparent, and genuinely useful to human operators in high-stakes environments. With a growing citation record and contributions bridging theory and field deployment, he represents a significant voice in applied robotics research.
Research Focus
Key Achievements
Top Papers
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- 5The AMADEE-20 Robotic Exploration Cascade: An Experience Report5 citations · 2022
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- 7The Need for a Meta-Architecture for Robot Autonomy2 citations · 2022
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