Papers
18
Total Citations
386
H-Index
10
About
R. Dillmann is a pioneering figure in robotics, whose work has fundamentally shaped how robots learn from and interact with humans. His primary research areas center on **Programming by Demonstration (PbD)** and the development of **anthropomorphic service robots**. Dillmann’s major contribution is establishing a framework that allows non-expert users to intuitively teach robots complex skills simply by showing them. His seminal 2002 paper, "Building elementary robot skills from human demonstration" (130 citations), introduced a general approach for acquiring sensor-based skills from human examples, crucially including a method for the robot to adapt these initially imperfect demonstrations. He further advanced this field by developing systems for understanding user intention during fine manipulation tasks (67 citations) and creating robust methods for visual object recognition and dynamic grasp recognition to support PbD. Beyond skill acquisition, Dillmann contributed to hardware design, most notably with the **ARMAR** anthropomorphic arm (25 citations), a key component for humanoid service robots. His work on the MORPHA project (19 citations) also explored communication and interaction with intelligent robot assistants. With over 300 total citations on his core PbD works, Dillmann’s legacy lies in democratizing robot programming, making it accessible to everyday users and paving the way for truly assistive robots in human environments.
Research Focus
Key Achievements
Top Papers
- 1Building elementary robot skills from human demonstration130 citations · 2002
- 2
- 3ARMAR-an anthropomorphic arm for humanoid service robot25 citations · 2003
- 4
- 5
- 6
- 7Reinforcement-learning For The Control Of An Autonomous Mobile Robot19 citations · 2005
- 8Integrating skills into multi-agent systems12 citations · 1998
- 9
- 103D-icon based user interaction for robot programming by demonstration10 citations · 2002