Papers
31
Total Citations
334
H-Index
11
About
Michael Hofbaur is a leading researcher at the intersection of robotics, artificial intelligence, and quantum computation. His work primarily focuses on human-robot interaction (HRI), collaborative robotics, and model-based reasoning for autonomous systems. Hofbaur’s major contributions include developing novel methodologies to measure and predict situation awareness in HRI using probabilistic attention models and gaze features, a breakthrough that enhances real-time robot responsiveness. He has also pioneered model-based fault diagnosis and reconfiguration for mobile robot drives, significantly improving system robustness and autonomy. His research extends to quantum computation’s applications in robotics, a forward-looking area with 40 citations, and collaborative robots like ABB’s YuMi, demonstrated in a tangram puzzle task (25 citations). With a total of over 230 citations across his top ten papers, Hofbaur’s impact is evident in his work on safe human-robot collaboration, including collision-force mapping and radar-based speed control for fenceless environments. He has also contributed to space exploration through reactive programming for cooperative Mars rovers. His achievements include editing the volume *New Trends in Medical and Service Robots*, reflecting his influence on applied robotics. Hofbaur’s research continues to shape safer, more intuitive, and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Quantum Computation in Robotic Science and Applications40 citations · 2019
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- 3Improving Robustness of Mobile Robots Using Model-based Reasoning30 citations · 2006
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- 5Model-based fault diagnosis and reconfiguration of robot drives23 citations · 2007
- 6Model-based Reactive Programming of Cooperative Vehicles for Mars Exploration22 citations · 2001
- 7New Trends in Medical and Service Robots18 citations · 2017
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