Stefano Geluardi

Alumni of the Department Human Perception, Cognition and Action
Alumni of the Group Cybernetics Approach to Perception and Action

Main Focus

I am leading the research group. Within this group, we use the principles of  Cybernetics, Control Theory and System Identification to further our understanding of human manual control. In particular, we investigate  Haptic Support Systems, Neuromuscular Identification Methods and  Helicopter Augmentation Systems. For more details, please visit our .

I obtained my M.Sc. in Automation Engineering from University of Pisa, in Italy. Between 2012 and 2016, I worked in a collaborative research project between University of Pisa and Max Planck Institute for Biological Cybernetics, resulting in a PhD for my work on "".

Since December 2016, I work as project leader of the research group.

My research interests include System Identification, Robust Control Theory, effect on Handling Qualities of System Augmentation and Haptic Support Systems.

PhD thesis - Identification and augmentation of a civil light helicopter: transforming helicopters into Personal Aerial Vehicles

The research described in this thesis was inspired by the results of the , a European project funded by the European Commission in 2011. The myCopter project's aim was to identify new concepts for air transport that could be used to achieve a Personal Aerial Transport (PAT) system in the second half of the 21st century. Although designing a new vehicle was not among the project's goal, it was considered important to assess vehicle response types and handling qualities that Personal Aerial Vehicles (PAVs) should have to be part of a PAT. In this thesis it is proposed to consider civil light helicopters as possible PAVs candidates. The goal of the thesis is to investigate whether it is possible to transform civil light helicopters into PAVs through the use of system identification methods and control techniques. The transformation here is envisaged in terms of vehicle dynamics and handling qualities.

To achieve this goal, three main steps are considered. The first step focuses on the identification of a Robinson R44 Raven II helicopter model in hover. The second step consists of augmenting the identified helicopter model to achieve response types and handling qualities defined for PAVs. The third step consists of assessing the magnitude of discrepancy between the two implemented augmented systems and the PAV reference model. An experiment was conducted for this purpose, consisting of piloted closed-loop control tasks performed in the by participants without any prior flight experience.

Results, evaluated in terms of objective and subjective workload and performance, showed that the augmented helicopter is able to resemble PAVs handling qualities and response types in piloted closed-loop control tasks. This result demonstrates that it is possible to transform helicopter dynamics into PAVs dynamics.

Curriculum Vitae

Stefano Geluardi is currently project leader of the research group at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.


Jun '12 - Jul '16

Ph.D. Candidate at Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany (in co-operation with University of Pisa, Italy).


Supervisors: Prof. Heinrich H. Bülthoff, Prof. Lorenzo Pollini

Sep '08 - Mar '12

Master's Degree in Automation Engineering, University of Pisa, Italy.

Thesis: Path following of an underwater glider vehicle with actuated and independently controllable hydrodynamic wings

Supervisors: Prof. Andrea Caiti, Prof. Mario Innocenti, Eng. Vincenzo Calabrò.

Final mark: cum laude

Sep '05 - Sep '08

Bachelor's Degree in Computer Engineering, University of Pisa, Italy.

Thesis: Implementation of algorithms for the analysis of components and main paths in networks of patents citations.

Supervisors: Prof. Carlo Alberto Avizzano, Prof. Lorenzo Pollini, Eng. Emanuele Ruffaldi

Final mark: cum laude

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