Matthias Teschner
Papers
8
Total Citations
231
H-Index
6
About
Matthias Teschner is a leading researcher in mobile manipulation and autonomous navigation, with a particular focus on environments containing deformable objects. His work bridges the gap between rigid-body robotics and the real-world challenges posed by non-rigid obstacles such as curtains, plants, and other flexible materials. Teschner’s major contributions include developing methods to learn the elasticity parameters of deformable objects through physical interaction with a manipulator robot, enabling robots to model and predict how such objects will behave. He has also pioneered the integration of symbolic and geometric planning for mobile manipulation, allowing robots to decompose complex tasks into high-level symbolic actions and low-level geometric motions. His work on learning deformable object models using depth cameras and manipulation robots has been cited over 75 times, demonstrating significant impact in the field. Teschner’s research has advanced the state of the art in path planning through deformable environments, showing that robots can navigate more effectively when they leverage information about object deformability. His notable achievements include developing systems that combine probabilistic roadmaps with learned cost functions for real-world robot navigation among deformable obstacles.
Research Focus
Key Achievements
Top Papers
- 1
- 2Integrating symbolic and geometric planning for mobile manipulation72 citations · 2009
- 3Learning object deformation models for robot motion planning41 citations · 2014
- 4
- 5Real-world robot navigation amongst deformable obstacles14 citations · 2009
- 6
- 7
- 8Collision Handling and its Applications2 citations · 2006