Papers

18

Total Citations

169

H-Index

8

About

David Alejo is a robotics researcher whose work spans autonomous systems, robot localization, and multi-robot coordination, with particular expertise in the challenging domain of underground infrastructure inspection and unmanned aerial vehicles. His most recognized contribution is the development of SIAR, a ground robot platform designed for semi-autonomous inspection of urban sewer networks — a critical yet notoriously difficult environment for autonomous operation. His localization work, including RGBD-based Monte Carlo methods for sewer navigation, has garnered over 50 citations across multiple publications, establishing him as a leading voice in subterranean robotics. Alejo has also made significant strides in tethered UAV-UGV marsupial systems, pioneering trajectory planning methods for physically linked aerial-ground robot pairs — work that has quickly attracted 25 citations since 2023. His broader contributions extend to multi-UAV ground control systems, conflict resolution in aerial traffic management, and heterogeneous robot teams for urban firefighting, the latter demonstrated in the prestigious MBZIRC 2020 competition. Through publicly released sewer network datasets and optimization-based planning frameworks, Alejo has consistently provided the robotics community with both foundational tools and practical solutions for real-world deployment challenges.

Research Focus

Key Achievements

8
H-Index
18
Papers
169
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A Robust Localization System for Inspection Robots in Sewer Networks
29 citations · 2019
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 25
🏛 Institutions: Universidad Pablo de Olavide, Universidad de Sevilla

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago