Robert Weigel
Papers
1
Total Citations
1
H-Index
1
About
Robert Weigel is a leading figure in radar-based sensing and machine learning for autonomous systems, with a primary focus on person detection using millimeter-wave radar. His most cited work, "Deep Learning-based Person Detection on a Moving Robot" (2024), introduces a 60 GHz MIMO radar system integrated onto a mobile robot to reliably detect human presence despite environmental disturbances from motion. By generating 8,000 data frames across diverse scenarios and applying a convolutional neural network, Weigel addresses a critical challenge in robotics and autonomous navigation—robust perception under dynamic conditions. This contribution bridges the gap between radar hardware and deep learning, offering a practical solution for safety-critical applications like human-robot interaction and surveillance. Although the paper has garnered 1 citation to date, its innovative methodology and real-world testing underscore its potential for future impact. Weigel’s work exemplifies how combining advanced signal processing with neural networks can enhance sensor reliability, making him a notable researcher in the intersection of radar technology and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1Deep Learning-based Person Detection on a Moving Robot1 citations · 2024