Papers
13
Total Citations
237
H-Index
10
About
Stefan Zickler is a roboticist whose work spans computer vision, motion planning, and multi-robot systems, with a particular focus on enabling robots to perceive, reason about, and act in complex, dynamic environments. His major contributions include developing robust methods for detecting and localizing multiple objects—both rigid and highly deformable—in real-time video using PCA-SIFT and clustered voting schemes, a foundational capability for humanoid robots and autonomous agents. In motion planning, Zickler advanced physics-based planning beyond simple collision avoidance, introducing efficient sampling search algorithms that allow robots to achieve physical goals in unpredictable settings. He also pioneered RSS-based relative localization and tethering for robots in unknown environments, enabling teams to track and follow each other using only wireless signal strength. Zickler’s work on the CMDragons robot soccer team at Carnegie Mellon is particularly notable; the team won the RoboCup Small-Size League in 2006 and 2007 without losing a single game, demonstrating the practical impact of his research in dynamic passing, strategy, and real-time coordination. With over 220 citations across his most influential papers, Zickler’s research continues to influence fields from autonomous navigation to multi-agent activity analysis.
Research Focus
Key Achievements
Top Papers
- 1Detection and Localization of Multiple Objects37 citations · 2006
- 2
- 3
- 4Analyzing Multi-agent Activity Logs Using Process Mining Techniques27 citations · 2009
- 5CMDragons: Dynamic passing and strategy on a champion robot soccer team21 citations · 2008
- 6Detection of multiple deformable objects using PCA-SIFT17 citations · 2007
- 7
- 8CMDragons 2007 Team Description13 citations · 2007
- 9A TEAM OF HUMANOID GAME COMMENTATORS10 citations · 2008
- 10CMDragons 2009 Extended Team Description10 citations · 2009