Arlind Rufi
Papers
2
Total Citations
6
H-Index
2
About
Arlind Rufi’s research centers on algorithmic path planning for autonomous robots operating under severe resource constraints, particularly limited memory and restricted communication. His major contribution lies in developing novel algorithms for the limited-buffer shortest path problem, where a robot must navigate from start to goal while collecting data—such as video feeds in monitoring scenarios—using only a small onboard storage capacity to minimize costs or prevent data overload. This work addresses a critical gap in robotics, balancing efficiency with real-world hardware limitations. Rufi’s most cited paper, “Algorithms for limited-buffer shortest path problems in communication-restricted environments” (2019), has garnered 4 citations, while an earlier version (2017) has 2, reflecting growing interest in his solutions. By tackling challenges in environments where communication is intermittent or unavailable, his research has implications for search-and-rescue missions, environmental monitoring, and planetary exploration. Rufi’s achievements include advancing theoretical foundations for memory-aware navigation, offering practical frameworks that enable robots to operate autonomously in data-intensive, bandwidth-limited scenarios—a vital step toward resilient, cost-effective autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2