Papers

28

Total Citations

455

H-Index

12

About

Leopoldo Armesto is a leading researcher in robotics, control systems, and sensor fusion, with a career defined by bridging theoretical rigor and practical application. His most impactful work, the 2004 paper "Multi-rate fusion with vision and inertial sensors" (63 citations), established a foundational framework for combining visual and inertial data at different sampling rates, a critical contribution to egomotion estimation for robot navigation and augmented reality. Armesto has also made seminal advances in motion planning, notably developing a real-time technique for Clothoid path approximation using Rational Bezier curves (46 citations), enabling smoother, more efficient trajectories for mobile robots. His work extends to vehicle stability control, where he designed hybrid controllers for industrial forklifts (40 citations), and to education, with his "Low-cost Printable Robots" project (37 citations) democratizing access to robotics learning. Further contributions include a generalization of the Iterative Closest Point algorithm for 3D scan matching (37 citations) and constraint-aware policy learning from demonstrations (18+ citations). With over 330 total citations across his top ten papers, Armesto’s research consistently addresses real-world challenges, from autonomous navigation to human-robot interaction, making him a pivotal figure in modern robotics.

Research Focus

Key Achievements

12
H-Index
28
Papers
455
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Multi-rate fusion with vision and inertial sensors
63 citations · 2004
📈 Most Prolific Year: 2011 (4 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: Universitat Politècnica de València, Universitat de València

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago