Papers
2
Total Citations
21
H-Index
2
About
Martin Stotz is a researcher whose work lies at the intersection of robot vision, object recognition, and automated manipulation. His primary contributions focus on enabling robots to perceive and interact with their environment, particularly through the use of depth-sensing technologies. Stotz’s most-cited paper, “Grasping in Depth maps of time-of-flight cameras” (2008, 18 citations), addresses the fundamental challenge of recognizing and localizing objects in space—a critical capability for service robots and human-robot interaction. This work demonstrates how time-of-flight cameras can provide robust depth information for grasping tasks. His related research, “A novel approach to object recognition and localization in automation and handling engineering” (2008, 3 citations), targets industrial applications such as bin picking, where robots must reliably grasp work pieces from cluttered containers. While his citation counts are modest, Stotz’s contributions are notable for their practical focus on bridging the gap between computer vision algorithms and real-world robotic manipulation. His work has particular relevance for automation and handling engineering, where reliable object recognition remains a persistent challenge.
Research Focus
Key Achievements
Top Papers
- 1Grasping in Depth maps of time-of-flight cameras18 citations · 2008
- 2