Swarm Robotic Behaviors and Current Applications
Melanie Schranz1, Martina Umlauft1, Micha Sende1
1Lakeside Labs GmbH, Klagenfurt, Austria.
Frontiers in Robotics and AI
|January 27, 2021
Summary
Swarm robotics, inspired by nature, struggles with industrial adoption due to unpredictable behaviors and communication challenges. Research platforms are crucial for bridging the gap between swarm theory and practical industrial applications.
Area of Science:
- Swarm Robotics
- Artificial Intelligence
- Multi-Agent Systems
Background:
- Swarm robotics mimics natural systems for collective problem-solving.
- Industrial applications of true swarm algorithms remain limited.
- Existing applications often use only basic swarm behaviors, not full algorithms.
Purpose of the Study:
- To collect and categorize basic swarm behaviors (spatial organization, navigation, decision making, miscellaneous).
- To apply this taxonomy to existing swarm robotic applications in research and industry.
- To provide an overview of research platforms, market systems, and targeted projects.
Main Methods:
- Literature review and categorization of swarm behaviors.
- Taxonomic classification of current swarm robotic applications.
- Survey of research platforms and commercial swarm systems.
Main Results:
- Swarm robotic applications are currently rare in industry.
- Many industrial projects neglect distributed decision-making, relying on centralized control.
- Key barriers include unpredictability of emergent behavior, communication infrastructure limitations, and challenges in testing.
Conclusions:
- Bridging the gap between swarm theory and industrial practice requires addressing predictability and communication issues.
- Research platforms are vital for testing and developing swarm robotics solutions for industrial deployment.
- Overcoming current limitations is essential for realizing the full potential of swarm robotics in industry.
