About

Diego B. Haddad is a leading researcher in autonomous robotics, specializing in the control, coordination, and cognitive architectures of unmanned aerial vehicles (UAVs) and multi-robot systems. His major contributions include developing a fuzzy-tuned cascaded-PID control method for stabilizing UAV flight, which addresses the challenge of nonlinear dynamics without exhaustive parameter tuning (30 citations). He has also pioneered heterogeneous multi-robot collaboration strategies for coverage path planning in dynamic environments, integrating UAVs and unmanned ground vehicles (UGVs) for real-world tasks (24 citations). Haddad’s work on vision-assisted target tracking for autonomous UAVs in offshore mooring operations demonstrates his focus on industrial applications (18 citations). Notably, he created ARCog-NET, an advanced cognitive network architecture enabling UAV swarms to autonomously coordinate, allocate tasks, and plan paths—a framework validated beyond simulation (10 citations). His research extends to soft robotics, with novel activation mechanisms for multi-legged robots. With over 95 total citations, Haddad’s work bridges theoretical control and practical swarm autonomy, making significant impacts on aerial robotics and multi-agent systems.

Research Focus

Key Achievements

5
H-Index
7
Papers
95
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Unmanned Aerial Vehicles Motion Control with Fuzzy Tuning of Cascaded-PID Gains
30 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Federal Center for Technological Education of Minas Gerais, Federal Center for Technological Education Celso Suckow da Fonseca

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago