Konrad Urban
Papers
1
Total Citations
2
H-Index
1
About
Konrad Urban is a researcher in multirobot systems and cooperative path planning, with a focus on developing algorithms that enable teams of robots to efficiently coordinate and collaborate on complex tasks. His most-cited work, "Constraint Manifold Subsearch for multirobot path planning with cooperative tasks" (2015), addresses the challenge of simultaneously managing large-scale robot distribution across a workspace while tightly coordinating small teams for task-specific cooperation. This work introduces a novel approach to navigating the multi-scale coordination problem, balancing global path efficiency with local team dynamics. Although his citation count is modest, Urban's contributions are notable for tackling the intricate interplay between spatial distribution and cooperative task execution—a critical area for applications like warehouse automation, search-and-rescue, and autonomous construction. His research lays groundwork for scalable multirobot systems, offering insights into how robots can form temporary teams without sacrificing overall system performance. Urban's work is particularly relevant for students and researchers interested in the intersection of path planning, constraint satisfaction, and multi-agent coordination.
Research Focus
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Top Papers
- 1