Pawel Kosicki
Papers
1
Total Citations
5
H-Index
1
About
Pawel Kosicki is a researcher whose work lies at the intersection of robotics, optimization, and dynamic systems, with a particular focus on real-time task allocation for multi-agent teams. His most-cited paper, "On-line task allocation for the robotic interception of multiple targets in dynamic settings" (2010), introduces a novel rolling-horizon methodology that enables a team of robotic pursuers to optimally intercept highly maneuverable mobile targets in real time. This contribution is significant for its practical approach to a computationally challenging problem—balancing online decision-making with the depth of search required for optimality in unpredictable environments. With 5 citations, this work has informed subsequent studies in multi-robot coordination and autonomous pursuit-evasion scenarios. Kosicki’s research addresses critical challenges in robotics, such as scalability, adaptability, and real-time performance, making his contributions valuable for applications ranging from surveillance to autonomous logistics. His work exemplifies the integration of control theory and optimization to solve complex, time-sensitive problems in dynamic settings.
Research Focus
Key Achievements
Top Papers
- 1