Papers
2
Total Citations
80
H-Index
2
About
Alexander Narr is a leading researcher in autonomous 3D modeling and active machine learning for spatial data. His foundational work on next-best-scan planning, published in 2012 and cited over 55 times, introduced a pioneering approach that enables robotic systems to autonomously complete 3D models of complex objects by iteratively selecting optimal scanning positions based on previously acquired data. This work has been instrumental in advancing autonomous inspection and digital twinning. Narr further extended his impact into the domain of intelligent data acquisition with his 2016 study on stream-based active learning for 3D point cloud classification. Garnering 25 citations, this research tackles the critical challenges of non-uniform class distributions and imbalanced sample sizes in real-time data streams, demonstrating that standard online methods fall short and proposing adaptive, efficient alternatives. Together, his contributions bridge the gap between perception and decision-making, equipping autonomous systems with the ability to both understand and efficiently explore their environments. Narr’s work remains essential reading for researchers in robotics, computer vision, and intelligent sensing.
Research Focus
Key Achievements
Top Papers
- 1Next-best-scan planning for autonomous 3D modeling55 citations · 2012
- 2