Anne Driemel
Papers
1
Total Citations
14
H-Index
1
About
Anne Driemel is a leading researcher in computational geometry and robotics, with a focus on developing algorithms for motion planning, trajectory analysis, and human-robot interaction. Her work bridges theoretical foundations and practical applications, particularly in enabling robots to navigate complex, dynamic environments while adapting to individual human preferences. In her notable 2023 paper, "Learning Depth Vision-Based Personalized Robot Navigation From Dynamic Demonstrations in Virtual Reality," Driemel introduces a novel learning framework that uses depth vision and virtual reality demonstrations to train navigation controllers tailored to user-specific behaviors. This work, already garnering 14 citations, exemplifies her contribution to personalized robotics, where robots learn from human demonstrations to optimize safety and comfort. Beyond this, Driemel is recognized for her advances in approximate nearest neighbor search and curve simplification, which have influenced fields from data analysis to autonomous systems. Her research, widely cited in top venues like SoCG and ICRA, continues to shape how robots perceive and move through the world, making her a pivotal figure in the intersection of geometry and intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1