Papers

3

Total Citations

8

H-Index

2

About

Abror Shavkatovich Buriboev is a researcher advancing the frontier of autonomous mobile robotics, with a focused expertise in path planning and exploration within unknown environments. His work directly addresses the fundamental challenge of enabling robots to navigate and map spaces without prior knowledge—a critical capability for applications in search-and-rescue, industrial inspection, and planetary exploration. Buriboev’s major contributions center on developing novel frontier-based exploration algorithms. His 2021 paper introduced an internal and external frontier-based method to optimize exploration efficiency, while his 2022 work, "Rmap+," refined previous algorithms by modifying exploration submodules to reduce operational overhead. Most notably, his 2024 paper presents the TAD (Trapezoid, Adjacent, and Distance) algorithm, a pioneering approach that leverages frontier characteristics to dramatically improve path planning. Though his citation counts (2–3 per paper) reflect an emerging career, the conceptual innovation in his algorithms—particularly the TAD method—positions his work as a building block for future autonomous systems. Buriboev’s research is essential reading for students and engineers tackling the core problem of efficient, real-time robot exploration in unstructured environments.

Research Focus

Key Achievements

2
H-Index
3
Papers
8
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Optimized Frontier-Based Path Planning Using the TAD Algorithm for Efficient Autonomous Exploration
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Gachon University, Konkuk University, Tashkent University of Information Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago