About

Paolo Robuffo Giordano is a prominent robotics researcher whose work spans aerial robotics, multi-robot systems, teleoperation, and robot dynamics. Best known for his groundbreaking contributions to unmanned aerial vehicle (UAV) design, his 2014 paper introducing an overactuated quadrotor capable of full 6-degree-of-freedom control has accumulated nearly 400 citations, fundamentally challenging the conventional limitations of quadrotor platforms. His research into multi-robot coordination is equally influential, with seminal work on bilateral teleoperation of heterogeneous robot groups, decentralized connectivity maintenance, and bearing-based UAV formations reshaping how researchers approach scalable, fault-tolerant swarm control. Robuffo Giordano has also made significant contributions to human-robot interaction through shared control frameworks for UAV teams, and to visual servoing, particularly regarding feature depth estimation. His 2019 work on dynamic identification of the Franka Emika Panda robot — now cited over 300 times — has become an essential reference for researchers working with this widely adopted manipulator platform. His involvement in the development of Rollin' Justin, a sophisticated mobile humanoid research platform at DLR, further demonstrates the breadth of his expertise. Collectively, his body of work represents a sustained effort to bridge theoretical rigor with experimental validation across some of robotics' most challenging frontiers.

Research Focus

Key Achievements

32
H-Index
100
Papers
4,099
Total Citations
41
Avg Citations/Paper
🏆 Most Cited Paper
A Novel Overactuated Quadrotor Unmanned Aerial Vehicle: Modeling, Control, and Experimental Validation
394 citations · 2014
📈 Most Prolific Year: 2012 (10 Papers)
🤝 Key Collaborators: 134
🏛 Institutions: Centre National de la Recherche Scientifique, Max Planck Institute for Biological Cybernetics, Sapienza University of Rome, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Institut de Recherche en Informatique et Systèmes Aléatoires, Institut national de recherche en sciences et technologies du numérique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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