Papers

5

Total Citations

105

H-Index

3

About

Marcelo Jacinto is a robotics researcher specializing in autonomous vehicle control, multi-robot coordination, and simulation technologies. His work bridges theory and practice, with a focus on path following strategies for marine, ground, and aerial vehicles. His most cited paper, a comprehensive review of path following control strategies (2022, 66 citations), provides a foundational framework for stabilizing error dynamics across diverse robotic platforms, establishing him as a key contributor to this field. Jacinto also developed the Pegasus Simulator (2024, 29 citations), an Isaac Sim-based framework for multi-aerial vehicle simulation, enabling researchers to test control and motion planning algorithms in realistic 3D environments. His notable achievements include a distributed cooperative approach for chemical spill encircling using quadrotors and autonomous surface vehicles (2022), demonstrating practical applications in environmental cleanup. Additionally, his work on underwater geophysical navigation via particle filter multi-sensor fusion (2021) advances autonomous underwater vehicle localization using bathymetric data. With a growing citation impact and contributions spanning simulation, control theory, and multi-robot systems, Jacinto is a rising figure in autonomous robotics, offering tools and insights that empower both students and researchers to push the boundaries of intelligent vehicle autonomy.

Research Focus

Key Achievements

3
H-Index
5
Papers
105
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
A review of path following control strategies for autonomous robotic vehicles: Theory, simulations, and experiments
66 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: INESC TEC, University of Lisbon, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago