Alexander M. Schmidts
Technical University of Munich, KUKA (Germany), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Papers
3
Total Citations
53
H-Index
3
About
Alexander M. Schmidts is a roboticist whose research lies at the intersection of imitation learning and physical human-robot interaction, with a particular focus on how robots can acquire and refine dexterous manipulation skills. His most influential work, "Imitation learning of human grasping skills from motion and force data" (2011, 41 citations), pioneered the integration of force information into Programming by Demonstration, moving beyond purely kinematic approaches to enable robots to learn the nuanced force profiles required for stable, human-like grasping. This contribution is foundational for teaching robots complex tasks that demand both precision and compliance. Schmidts further advanced the field with his work on interaction force decomposition (2016), which provides a principled framework for separating forces that maintain grasp robustness from those that drive motion—a critical insight for controlling manipulation under real-world physical constraints. His research has direct applications in assistive robotics and industrial automation, where robots must safely and effectively handle objects alongside humans. By bridging the gap between kinematic imitation and force-aware control, Schmidts has helped define a more holistic approach to robot skill acquisition.
Research Focus
Key Achievements
Top Papers
- 1Imitation learning of human grasping skills from motion and force data41 citations · 2011
- 2
- 3Imitation learning of human grasping skills from motion and force data6 citations · 2011