Papers
14
Total Citations
164
H-Index
9
About
Ivan Zelinka is a leading figure in swarm robotics, evolutionary computation, and complex systems. His research centers on developing bio-inspired algorithms for autonomous robot navigation and control. Zelinka is best known for his pioneering work with the Self-Organizing Migrating Algorithm (SOMA), which he has adapted for critical real-world tasks such as obstacle avoidance and path planning for swarm robots. His 2019 paper on SOMA-based obstacle avoidance (33 citations) and his 2021 work introducing the iSOMA variant with a narrowing search space strategy (14 citations) demonstrate his sustained impact in the field. He has also made significant contributions to symbolic regression through Analytic Programming, applying it to optimize robot trajectories. Beyond his algorithmic innovations, Zelinka has edited influential volumes like "AETA 2015: Recent Advances in Electrical Engineering" (25 citations) and organized the Interdisciplinary Symposium on Complex Systems, cementing his role as a key voice in complex systems research. His work, spanning optimal control with phase constraints to dynamic multi-robot target capture, consistently bridges theoretical evolution with practical robotics, making him a vital resource for students and researchers in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2AETA 2015: Recent Advances in Electrical Engineering and Related Sciences25 citations · 2016
- 3ISCS 2013: Interdisciplinary Symposium on Complex Systems17 citations · 2014
- 4
- 5
- 6Investigation on Evolutionary Synthesis of Movement Commands12 citations · 2009
- 7
- 8
- 9
- 10