Ruediger Schmedding
Papers
1
Total Citations
11
H-Index
1
About
Ruediger Schmedding is a robotics researcher whose work focuses on enabling robots to perceive, model, and physically interact with deformable objects in unstructured environments. His key research areas include deformable object modeling, mobile robot navigation, and manipulation using depth cameras. Schmedding’s major contribution lies in developing a robotic system that can autonomously learn models of deformable objects through direct physical interaction—a critical step toward making robots more adaptable in real-world settings like homes or hospitals. His most-cited paper, "Learning Deformable Object Models for Mobile Robot Navigation using Depth Cameras and a Manipulation Robot" (2010), has garnered 11 citations and demonstrates how a robot can combine depth sensing with manipulation to build object models on the fly. This work is notable for bridging perception and action, allowing robots to navigate environments filled with soft, changing objects rather than assuming a rigid world. Schmedding’s research has practical implications for service robotics, where safe and effective interaction with everyday objects is essential. His approach continues to influence work in interactive perception and robot learning.
Research Focus
Key Achievements
Top Papers
- 1