D. Kuhner
Papers
6
Total Citations
107
H-Index
5
About
D. Kuhner is a roboticist whose work sits at the intersection of autonomous service robotics, human-robot interaction, and accessible control interfaces. Their research focuses on making complex robotic systems usable by a broad range of people, including those with limited communication skills. Kuhner’s most impactful contribution is the development of a service assistant that integrates autonomous robotics with deep-learning-based brain–computer interfacing (BCI) and flexible goal formulation, enabling users to control robots through thought alone (49 citations). This work, along with their exploration of BCI control for robotic assistants (7 citations), represents a significant step toward assistive technologies for individuals with severe motor impairments. Kuhner has also advanced practical robot cleaning through Poisson-driven dirt maps (18 citations), which model dirt distribution dynamics to compute efficient cleaning paths. Additional contributions include closed-loop task planning using referring expressions (7 citations) and augmenting action model learning with non-geometric features (3 citations). With a total of over 100 citations across their most-cited works, Kuhner’s research demonstrates a commitment to making autonomous robots more accessible, intelligent, and responsive to human needs—a vision that promises to reshape how we interact with machines in everyday environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Poisson-driven dirt maps for efficient robot cleaning18 citations · 2013
- 4Closed-Loop Robot Task Planning Based on Referring Expressions7 citations · 2018
- 5
- 6Augmenting Action Model Learning by Non-Geometric Features3 citations · 2019