Papers
7
Total Citations
61
H-Index
4
About
Dominik Krupke is a computational researcher whose work sits at the intersection of robotics, swarm intelligence, and algorithmic geometry. His research focuses primarily on the coordination, control, and optimization of robot swarms — systems of multiple agents that must collectively achieve complex tasks under significant constraints. Among his most recognized contributions is his work on distributed cohesive control, where he developed local algorithms enabling robot swarms to maintain connectivity even under external forces and node failures, garnering over 21 citations. He has also made meaningful advances in under-actuated swarm control, investigating how particles steered by uniform global inputs can be efficiently collected and concentrated — work with direct implications for targeted drug delivery in healthcare. His mapping and coverage research further extended these ideas to medical imaging of vascular systems using magnetic particles. More recently, Krupke has contributed to competitive computational geometry through the CG:SHOP Challenge 2021, focusing on collision-free trajectory planning for pixel-shaped robots, and has tackled near-optimal coverage path planning with turn costs — a practically vital problem spanning agriculture, surveillance, and autonomous cleaning. With a growing body of work accumulating over 60 citations, Krupke represents an emerging voice bridging theoretical algorithms with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Collecting a swarm in a grid environment using shared, global inputs14 citations · 2016
- 3Mapping and coverage with a particle swarm controlled by uniform inputs10 citations · 2017
- 4
- 5Near-Optimal Coverage Path Planning with Turn Costs4 citations · 2024
- 6A parallel distributed strategy for arraying a scattered robot swarm2 citations · 2015
- 7