Ilja Rausch

About

Ilja Rausch investigates the intersection of collective behaviour, swarm robotics, and complex systems, with a focus on how decentralised groups—from simulated locusts to robot swarms—achieve coherent decision-making and adaptive foraging. His major contributions include demonstrating that balancing social feedback with noise can produce coherent collective behaviour without central control (32 citations), and showing that scale-free interaction networks enhance adaptability in dynamic environments (12 citations). Rausch’s work on scale-free features in collective robot foraging (9 citations) and construction task allocation through collective perception (9 citations) reveals how natural principles like scalability and rapid information exchange can be engineered into robotic systems. By challenging traditional local-interaction models, he has advanced understanding of how minimal, decentralised rules yield robust group outcomes. His research is notable for bridging theoretical models with real-world swarm applications, offering insights for designing resilient, self-organising systems in uncertain settings.

Research Focus

Key Achievements

Top Papers

1. 1
   Coherent collective behaviour emerging from decentralised balancing of social feedback and noise

   32 citations · 2019
2. 2
   The Impact of Interaction Models on the Coherence of Collective Decision-Making: A Case Study with Simulated Locusts

   13 citations · 2018
3. 3
   Adaptive Foraging in Dynamic Environments Using Scale-Free Interaction Networks

   12 citations · 2020
4. 4
   Scale-Free Features in Collective Robot Foraging

   9 citations · 2019
5. 5
   Construction Task Allocation Through the Collective Perception of a Dynamic Environment

   9 citations · 2020

Key Collaborators

Contact & Links