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Claudio Fantacci

Post Doc
R&D Engineer

Research Line

Humanoid Sensing and Perception


IIT Central Research Labs Genova


Via Morego 30, 16163, Genoa, Italy
+39 010 2898 216
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I'm an engineer and developer with knowledge sharing and problem solving attitudes.

I have 6 years experience in recursive Bayesian filtering and software developing, including R&D collaboration with Selex ES (Finmeccanica) and a Ph.D. in computer science and automation engineering from University of Florence (Italy). I was recipient of the 2014 Australia Award Endeavour Research Fellowship (granted by the Australian Government, Department of Education) under which I have been an R&D collaborator at the Advanced Signal Processing Group of Curtin University of Technology (Perth, Australia).

From January 2016, I'm a post-doc at the Istituto Italiano di Tecnologia (Genoa, Italy) in the iCub Facility, Humanoid Sensing and Perception, for studying, researching and developing new augmented reality-based visual tracking systems and visual servoing controllers for the humanoid robotic platform iCub.

I actively contribute to the development of the free and open source YARP and iCub software as a member of the robotology group.
I also contribute to and develop other open source project during my research activities, which can be found in my GitHub page.


Recursive Bayesian filtering Recursive Bayesian tracking Kalman filters Particle filters Visual tracking Visual servoing Augmented-reality Multi-object multi-sensor tracking Random Finite Set algorithms (PHD - CPHD - Labeled Multi-Bernoulli filters) Distributed information fusion


Visual tracking project

Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms

Link to the paper

Link to the code

This work addresses recursive markerless estimation of a robot’s end-effector using visual observations from its cameras. We formulate the problem into the Bayesian framework and address it using Sequential Monte Carlo (SMC) filtering (also known as particle filtering). We use a 3D rendering engine and Computer Aided Design (CAD) schematics of the robot to virtually create images from the robot’s camera viewpoints (likewise in augmented reality contexts). These images are then used to extract information and estimate directly the 6D pose of the end-effector. To this aim, we developed a particle filter for estimating the position and orientation of the robot’s end-effector using the Histogram of Oriented Gradient (HOG) descriptors to capture robust characteristic features of shapes in both cameras and rendered images. We implemented the algorithm on the iCub humanoid robot and employed it in a closed-loop reaching scenario. We demonstrate that the tracking is robust to clutter, allows compensating for errors in the robot kinematics and servoing the arm in closed loop using vision.


Visual servoing project

Markerless visual servoing on unknown objects for humanoid robot platforms

Link to the paper

Link to the code

To precisely reach for an object with a humanoid robot, it is of central importance to have good knowledge of both end-effector, object pose and shape. In this work we propose a framework for markerless visual servoing on unknown objects, which is divided in four main parts:

  1. a leastsquares minimization problem is formulated to find the volume of the object graspable by the robot’s hand using its stereo vision;
  2. a recursive Bayesian filtering technique, based on Sequential Monte Carlo (SMC) filtering, estimates the 6D pose (position and orientation) of the robot’s end-effector without the use of markers;
  3. a nonlinear constrained optimization problem is formulated to compute the desired graspable pose about the object;
  4. an image-based visual servo control commands the robot’s end-effector toward the desired pose.

The pipeline prove to be effective and robust and has been tested on the iCub humanoid robot platform, achieving real-time computation, smooth trajectories and subpixel precisions.


2018 - KUKA Innovation Award

Award to the CoAware team of the Istituto Italiano di Tecnologia for developing a “Robot adapting to task variations and human states to promote ergonomic human-robot collaboration”.

2016 - Florence University Press Special mention for Ph.D. thesis

The Ph.D. thesis "Distributed multi-object tracking over sensor networks: a random finite set approach" has been evaluated to be a significant scientific contribution by the Florence University Press (FUP) judging committee.

2014 - Australia Award - Endeavour Research Fellowship

Issued by the Department of Industry of the Australian Government. The Endeavour Research Fellowship provides financial support for postgraduate students and postdoctoral fellows to undertake short-term research (up to 6 months) towards a Masters or Ph.D. or postdoctoral research in any field of study in Australia.

2013 - Jean-Pierre Le Cadre Award for Best Paper

16th International Conference on Information Fusion (FUSION), award for the paper: "A new approach for Doppler-only target tracking".

2012 - Student Travel Grant Award

15th International Conference on Information Fusion (FUSION), award for the paper: "Multiple-model Algorithms for Distributed Tracking of a Maneuvering Target".


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I numeri di IIT

L’Istituto Italiano di Tecnologia (IIT) è una fondazione di diritto privato - cfr. determinazione Corte dei Conti 23/2015 “IIT è una fondazione da inquadrare fra gli organismi di diritto pubblico con la scelta di un modello di organizzazione di diritto privato per rispondere all’esigenza di assicurare procedure più snelle nella selezione non solo nell’ambito nazionale dei collaboratori, scienziati e ricercatori ”.

IIT è sotto la vigilanza del Ministero dell'Istruzione, dell'Università e della Ricerca e del Ministero dell'Economia e delle Finanze ed è stato istituito con la Legge 326/2003. La Fondazione ha l'obiettivo di promuovere l'eccellenza nella ricerca di base e in quella applicata e di favorire lo sviluppo del sistema economico nazionale. La costruzione dei laboratori iniziata nel 2006 si è conclusa nel 2009.

Lo staff complessivo di IIT conta circa 1440 persone. L’area scientifica è rappresentata da circa l’85% del personale. Il 45% dei ricercatori proviene dall’estero: di questi, il 29% è costituito da stranieri provenienti da oltre 50 Paesi e il 16% da italiani rientrati. Oggi il personale scientifico è composto da circa 60 principal investigators, circa 110 ricercatori e tecnologi di staff, circa 350 post doc, circa 500 studenti di dottorato e borsisti, circa 130 tecnici. Oltre 330 posti su 1400 creati su fondi esterni. Età media 34 anni. 41% donne / 59 % uomini.

Nel 2015 IIT ha ricevuto finanziamenti pubblici per circa 96 milioni di euro (80% del budget), conseguendo fondi esterni per 22 milioni di euro (20% budget) provenienti da 18 progetti europei17 finanziamenti da istituzioni nazionali e internazionali, circa 60 progetti industriali

La produzione di IIT ad oggi vanta circa 6990 pubblicazioni, oltre 130 finanziamenti Europei e 11 ERC, più di 350 domande di brevetto attive, oltre 12 start up costituite e altrettante in fase di lancio. Dal 2009 l’attività scientifica è stata ulteriormente rafforzata con la creazione di dieci centri di ricerca nel territorio nazionale (a Torino, Milano, Trento, Parma, Roma, Pisa, Napoli, Lecce, Ferrara) e internazionale (MIT ed Harvard negli USA) che, unitamente al Laboratorio Centrale di Genova, sviluppano i programmi di ricerca del piano scientifico 2015-2017.

IIT: the numbers

Istituto Italiano di Tecnologia (IIT) is a public research institute that adopts the organizational model of a private law foundation. IIT is overseen by Ministero dell'Istruzione, dell'Università e della Ricerca and Ministero dell'Economia e delle Finanze (the Italian Ministries of Education, Economy and Finance).  The Institute was set up according to Italian law 326/2003 with the objective of promoting excellence in basic and applied research andfostering Italy’s economic development. Construction of the Laboratories started in 2006 and finished in 2009.

IIT has an overall staff of about 1,440 people. The scientific staff covers about 85% of the total. Out of 45% of researchers coming from abroad 29% are foreigners coming from more than 50 countries and 16% are returned Italians. The scientific staff currently consists of approximately 60 Principal Investigators110 researchers and technologists350 post-docs and 500 PhD students and grant holders and 130 technicians. External funding has allowed the creation of more than 330 positions . The average age is 34 and the gender balance proportion  is 41% female against 59% male.

In 2015 IIT received 96 million euros in public funding (accounting for 80% of its budget) and obtained 22 million euros in external funding (accounting for 20% of its budget). External funding comes from 18 European Projects, other 17 national and international competitive projects and approximately 60 industrial projects.

So far IIT accounts for: about 6990 publications, more than 130 European grants and 11 ERC grants, more than 350 patents or patent applications12 up start-ups and as many  which are about to be launched. The Institute’s scientific activity has been further strengthened since 2009 with the establishment of 11 research nodes throughout Italy (Torino, Milano, Trento, Parma, Roma, Pisa, Napoli, Lecce, Ferrara) and abroad (MIT and Harvard University, USA), which, along with the Genoa-based Central Lab, implement the research programs included in the 2015-2017 Strategic Plan.