Papers
2
Total Citations
11
H-Index
2
About
Max Breitmeyer is a researcher at the forefront of human-robot interaction (HRI), pioneering methods to overcome the scalability challenges that have long hindered robotics research. His work centers on integrating virtual reality and photogrammetry to create highly reproducible, simulated environments for studying how humans and robots interact. Breitmeyer’s key contribution lies in demonstrating that high-fidelity virtual settings can replace physical robots and prepared labs, dramatically reducing system failures and participant bottlenecks. His most-cited paper, “Virtual Reality and Photogrammetry for Improved Reproducibility of Human-Robot Interaction Studies” (8 citations), establishes a framework for collecting robust HRI data without the logistical overhead of real hardware. In related work, “Learning from human-robot interactions in modeled scenes” (3 citations), he addresses the critical data bottleneck in machine learning for robotics by leveraging simulated interactions to generate training data. Though early in his career, Breitmeyer’s innovative approach promises to accelerate progress in HRI by making large-scale, reproducible studies accessible—a vital step toward robots that learn seamlessly from human behavior.
Research Focus
Key Achievements
Top Papers
- 1
- 2Learning from human-robot interactions in modeled scenes3 citations · 2019