Steffen Knoop
Papers
19
Total Citations
1,249
H-Index
12
About
Steffen Knoop is a prominent robotics researcher whose work sits at the intersection of robotic manipulation, human-robot interaction, and machine learning. Best known for his groundbreaking 2004 paper "Automatic Grasp Planning Using Shape Primitives," which has accumulated over 715 citations, Knoop drew inspiration from human prehensile behavior to develop elegant solutions for one of robotics' most challenging problems — enabling robotic hands to intelligently grasp objects by decomposing them into manageable geometric primitives. Beyond grasping, Knoop made significant contributions to programming by demonstration, showing how robots can incrementally learn tasks from human guidance, vocal feedback, and prior experience — a vision captured in his 142-cited 2007 work on incremental task learning. His research on humanoid robots with five-fingered hands further bridged theoretical grasp planning with real-world visual perception in practical environments like kitchens. Knoop also advanced the field of human activity recognition and sensor fusion, developing robust methods for tracking articulated bodies and interpreting gestures in unconstrained human-robot interaction scenarios. His cumulative body of work reflects a coherent mission: creating robots that observe, understand, and adapt to humans with increasing sophistication and autonomy.
Research Focus
Key Achievements
Top Papers
- 1Automatic grasp planning using shape primitives715 citations · 2004
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- 5Feature Set Selection and Optimal Classifier for Human Activity Recognition38 citations · 2007
- 6Fusion of 2d and 3d sensor data for articulated body tracking33 citations · 2008
- 7Sensor fusion for model based 3D tracking22 citations · 2006
- 8Distribution and Recognition of Gestures in Human-Robot Interaction17 citations · 2006
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