Ahmad Alsayed

University of Manchester, Umm al-Qura University

Papers

8

Total Citations

103

H-Index

6

About

Ahmad Alsayed is a researcher at the forefront of autonomous robotics and industrial metrology, specializing in stockpile volume estimation, fiducial marker localization, and swarm-based aerial mapping. His work bridges the gap between low-cost sensing and high-accuracy 3D reconstruction, particularly for confined and open environments. Alsayed’s most cited paper (2021, 32 citations) critically examines the accuracy of stockpile estimations for manufacturing process optimization, while his comprehensive review (2023, 31 citations) surveys traditional and advanced volume-estimation techniques using terrestrial and aerial platforms. He has pioneered real-time fiducial marker systems with full 6-DOF pose estimation (2023, 10 citations; 2022, 9 citations), enabling autonomous robots to reliably determine their position in cluttered spaces. His innovative approach to indoor stockpile reconstruction using drone-borne actuated single-point LiDARs (2022, 6 citations) offers a low-cost, accurate alternative for confined storage facilities. Alsayed has also contributed to autonomous aerial mapping with swarms of UAVs (2022, 9 citations) and real-time scan matching for indoor drone navigation (2022, 2 citations). His work has direct applications in inventory management, logistics, and industrial automation, demonstrating how affordable sensor systems can achieve professional-grade mapping and localization.

Research Focus

Key Achievements

6
H-Index
8
Papers
103
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
32 citations · 2021
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of Manchester, Umm al-Qura University

Top Papers

  1. 1
    32 citations · 2021
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago