Gabriel Arpino

Carnegie Mellon University

Papers

2

Total Citations

4

H-Index

2

About

Gabriel Arpino’s research focuses on the theoretical foundations of multi-robot systems, particularly the distinction between swarm algorithms and general multi-robot coordination. His key contributions center on using information invariants—a framework that quantifies the type and locality of information available to robots—to rigorously compare these two paradigms. In his most-cited works (2018), Arpino demonstrates that robotic swarms rely on decentralized, local information from proximal neighbors to produce emergent collective behaviors, while general multi-robot systems can leverage global or all-to-all communication. By formalizing these differences, he provides a powerful lens for understanding when swarm intelligence is sufficient versus when more centralized control is necessary. Though his citation counts are modest (2 each), these papers represent foundational steps in a critical area of robotics theory. Arpino’s work is notable for bridging the gap between swarm engineering and broader multi-robot coordination, offering researchers a clear vocabulary to compare algorithms. For students and scholars, his contributions are essential reading for anyone designing or analyzing distributed robotic systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
4
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms
2 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago