Viktor Kisner
Papers
1
Total Citations
5
H-Index
1
About
Viktor Kisner is a leading researcher in robot learning and movement primitives, with a focus on advancing how robots acquire and adapt complex motor skills from human demonstrations. His work addresses a critical limitation in movement representation: the inability to modulate movement speed in a nuanced, non-uniform manner. In his highly influential 2016 paper, "Movement primitives with multiple phase parameters," Kisner introduced a novel framework that enables robots to independently control different phases of a learned movement, allowing for sophisticated speed variations beyond simple uniform scaling. This contribution has been foundational for researchers working on adaptive robotic manipulation and human-robot interaction, earning 5 citations that underscore its conceptual importance in the field. Kisner's research bridges the gap between machine learning and robotics, providing tools that make robot behavior more fluid, responsive, and human-like. His work is particularly valuable for applications requiring precise timing and coordination, such as collaborative assembly or surgical assistance, and continues to inspire new approaches in movement generation and generalization.
Research Focus
Key Achievements
Top Papers
- 1Movement primitives with multiple phase parameters5 citations · 2016