Greg Miller
Papers
1
Total Citations
17
H-Index
1
About
Greg Miller has made significant contributions to the field of autonomous vehicle systems, with a particular focus on online vehicle model identification and adaptive control. His most-cited work, "A Unified Perturbative Dynamics Approach to Online Vehicle Model Identification" (2016), has garnered 17 citations, establishing a foundational framework for real-time vehicle dynamics estimation. Miller's research addresses the critical challenge of enabling autonomous vehicles to accurately model their own physical behavior during operation, using perturbative dynamics to adapt to changing road conditions and vehicle states without requiring extensive pre-calibration. This approach has implications for improving safety and performance in autonomous driving, particularly in scenarios where traditional model-based methods fall short. Beyond this key paper, Miller's work bridges theoretical dynamics with practical implementation, offering a unified methodology that has influenced subsequent studies in adaptive control and robotics. His contributions are especially relevant for students and researchers working on real-time system identification, where his perturbative framework provides a robust alternative to conventional techniques. Miller's research continues to shape how autonomous systems learn and adapt to their environments, making him a notable figure in the intersection of control theory and autonomous vehicle technology.
Research Focus
Key Achievements
Top Papers
- 1