Judith Haubner
Papers
1
Total Citations
10
H-Index
1
About
Judith Haubner’s research sits at the compelling intersection of human-robot interaction, virtual reality, and spatial cognition. Her most-cited work, “Evaluating the Effects of Virtual Reality Environment Learning on Subsequent Robot Teleoperation in an Unfamiliar Building” (2023, 10 citations), tackles a fundamental challenge in teleoperation: how humans can efficiently align allocentric map representations with egocentric views to navigate unfamiliar spaces. Haubner’s key contribution lies in demonstrating that immersive VR environment learning can significantly improve a user’s ability to later teleoperate a robot in a real, unknown building—effectively bridging the gap between virtual training and real-world performance. This work has immediate implications for search-and-rescue, remote inspection, and assistive robotics, where operators must quickly adapt to novel environments. By systematically evaluating how spatial knowledge transfers from VR to physical teleoperation, Haubner provides a rigorous, evidence-based framework for designing more intuitive human-robot interfaces. Her findings not only advance the field of teleoperation but also offer practical guidance for training operators in high-stakes scenarios, making her research both theoretically insightful and directly applicable to real-world robotics challenges.
Research Focus
Key Achievements
Top Papers
- 1