Papers
5
Total Citations
37
H-Index
4
About
Aryo Jamshidpey’s research lies at the intersection of swarm robotics, multi-robot coordination, and decentralized intelligence, with a particular focus on balancing efficiency and scalability in coverage and perception tasks. His most cited work, “Multi-robot Coverage Using Self-organized Networks for Central Coordination” (2020, 12 citations), introduces a novel framework that leverages self-organized communication networks to achieve centralized-like coordination without sacrificing the robustness of decentralized systems. This theme of centralization versus decentralization is further explored in his 2025 paper (10 citations), which examines sweep coverage using heterogeneous teams of ground robots and UAVs, offering practical insights for real-world deployment. Jamshidpey also contributes to foundational swarm behaviors, as seen in his 2015 work on explicit communication for task allocation (8 citations), and addresses uncertainty in collective perception through self-organizing hierarchy (2023, 3 citations). His work is notable for systematically identifying the trade-offs between speed, accuracy, and fault tolerance in swarm systems, providing both theoretical frameworks and actionable design principles. For students and researchers, Jamshidpey’s research offers a clear roadmap for engineering scalable, resilient multi-robot systems that can adapt to dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Multi-robot Coverage Using Self-organized Networks for Central Coordination12 citations · 2020
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