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Since 2004, IAS-Lab of the University of Padova realized that the tools and the competencies it has been developing in the field of autonomous robots and artificial intelligence could be applied to industrial robotics. At that time, well in advance on the current trend of Industry 4.0, IAS-Lab understood more intelligence and more perception were needed for industrial robot. For this reason, in 2005, IAS-Lab founded the spin-off company called IT+Robotics srl. The expertise of IAS-Lab on intelligent industrial robots started to grow year after year and IAS-lab was able to win many industrial research grants in the competitive calls of the European Commission.



Fig. 1 - UNIPD-Mask



COVID-19 pandemic spread rapidly in Italy in early 2020, with over 200000 positive cases and more than 30000 deaths (Protezione Civile Update). Hospitals faced a shortage of Continuous Positive Airway Pressure (C- PAP) mechanical ventilation masks. This non-invasive treatment offers essential support in the treatment of patients with respiratory difficulties, such as COVID-19 ones, and can potentially avoid their admission to intensive care. Through an airtight connection with patients' airways, C-PAP devices create a constant positive pressure airflow while improving the patients breathing capacity. As a result, it is absolutely necessary to supply C-PAP devices, and this need led to the development of alternative solutions.


The Department of Information Engineering and the Department of Medicine of the University of Padova (Italy) developed UNIPD-Mask (see Fig. 1 and 2): a set of valves that allows converting EasyBreath, the snorkeling mask developed and marketed by Decathlon, into a C-PAP mask (patent pendant n. IT 1020200008305). This repository collects 3D models of the developed parts: They are freely accessible and replicable.


Fig. 2 - UNIPD-Mask real picture


The proposed invention follows the idea of Isinnova SRL (Brescia, Italy) in the development of Charlotte and solves Charlotte problems related to the limited section of its air inlet and outlet ducts: during inhalation, systems equipped with Charlotte valve are not able to compensate the volume of air inhaled by the patient, resulting in a pressure drop. Moreover, during exhalation, this configuration does not allow for rapid air evacuation, causing a feeling of fatigue in the patient. UNIPD-Mask, using a double-channel for the incoming airflow, is instead able to provide a greater volume of air to the patient, without a drop in pressure inside the mask during inhalation (see Fig. 2).


Fig. 2 - Confronto tra Charlotte (blu) e UNIPD-Mask (rosso) in termini di variazione di pressione / Comparison between Charlotte (blue) and UNIPD-Mask (red) in terms of pressure variation


Finally, UNIPD-Mask adds an anti-suffocation valve which, in the event of an accidental interruption of air and oxygen flow, allows the patient to continue breathing. It is also possible to connect an outgoing air filter.



Harvard and Padova Universities to prevent the risk of falling in the elderly


Instability is the maIn cause of falls for the elderly people, which increases the risk of fractures and therefore disability, with high health and social costs. Fall prevention is one of the targets of social and health policies for the promotion of active aging.

The SoftAct project aims to meet this need by developing an innovative neuromuscular controller integrated in a "soft exoskeleton" (exosuit: soft wearable robot) for the lower limb, that can detect the loss of stability during walking or standing by the integration of biomechanical, cerebral and muscular signals. This information will activate compensation systems integrated in the soft exoskeleton to prevent possible fall, with an integrated feedback-feedforward system.

The project will see the cooperation of two research groups: the Harvard University, which has an experience in gait and muscle signal analysis (EMG), and which created the prototype of the exosuit, and the University of Padua, with its deep knowledge in the field of brain signal analysis (EEG) and intelligent software for robotics. Prof. Alessandra Del Felice of the Neuroscience Department is the coordinator of the project, and is working with the Department of Engineering Information and prof. Emanuele Menegatti.




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The objective of SPIRIT is to take the step from programming of robotic inspection tasks to configuring such tasks. This includes inspection tasks that use image-based sensors and require continuous motion to fully scan a part’s surface.
The project aims at:
creating fully automatic offline path planning methods that ensure collision-free full coverage of the areas to be inspected on the part also for complex inspection processes. Instability is the maIn cause of falls for the elderly people, which increases the risk of fractures and therefore disability, with high health and social costs. Fall prevention is one of the targets of social and health policies for the promotion of active aging. The SoftAct project aims to meet this need by developing an innovative neuromuscular controller integrated in a "soft exoskeleton" (exosuit: soft wearable robot) for the lower limb, that can detect the loss of stability during walking or standing by the integration of biomechanical, cerebral and muscular signals. This information will activate compensation systems integrated in the soft exoskeleton to prevent possible fall, with an integrated feedback-feedforward system. The project will see the collaboration of two research groups: the Harvard University, with its experience in gait and muscle signal analysis (EMG), that created the prototype of the exosuit, and  the University of Padua, with its strong know-how in the field of brain signal analysis (EEG) and intelligent software for robotics.
developing reactive inline path planning that is able to automatically adjust to small changes in the environment, such as a different part shape or obstacles.
a seamless mapping of image sensor data to a 3D model of the part. 
generating operational data of inspection robots in industrial environments. This will include data related to accuracy, cycle times and performance indicators of the integrated system.
The expected impact is:
Reducing the engineering costs for setting up a robotic inspection task by 80%
Creating a software framework that allows the shift from project-based, ad-hoc solutions to a product-based approach.
Reducing the barrier when introducing automatic inspection systems by aiming at a return of investment of less than 2-3 years.
Realizing a potential of several hundred additional robotic installations per year.
Helping SMEs to reach out to worldwide markets by providing a proven framework for inspection robots.

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The SPIRIT project had its first meeting in Steyr 27-28 February. The general meeting will be 24-26 July at the University of Padova.








eCraft2Learn ( is a two-year Horizon2020 project started the 1st January 2017. The aim of the project is to reinforce personalized learning and teaching in STEAM education and to promote the development of 21st century skills and the employability of students aged 13-17 in the EU. For this purpose, eCraft2Learn will research, design and validate an ecosystem based on digital fabrication and make technologies for creating computer-supported artefacts.

Our role in ECraft2Learn project is the evaluation of suitable open source 3D printers and DIY electronics that will be integrated with the eCraft2Learn ecosystems through an unified user interface, and the planning of the unified ecosystem.

IAS-LAB ranks third at MBZIRC 2017




IAS-LAB of the University of Padua ranked third in The 2017 Grand Challenge of the Mohamed Bin Zayed International Robotic Challenge (MBZIRC) with the unmanned mobile manipulator robot called RUR53. RUR53 is build on a custom modified version of the Summit-XL robot by Robotnik. Desert Lion, the team of IAS-LAB, participated in the Grand Challenge together with the Czech Technical University of Prague and the University of Pennsylvania.

RUR53 is able to navigate inside an outdoor arena; locate and reach a operation panel; locate and recognize a specific wrench; manipulate the wrench to physically operate a valve stem on the panel itself, both autonomously and in teleoperation mode.

MBZIRC, taking place in Abu Dhabi, is a biennal international robotics competition, which attracts the best international teams, by providing a demanding set of benchmark robotics challenges. It aims is to inspire the future of robotics through innovative solutions and technological excellence.

MBZIRC 2017 consist of three challenges and a triathlon type Grand Challenge. IAS-Lab is one of the 46 teams selected in 143 application received from 35 countries. IAS-Lab takes part in the Challenge 2 that requires an unmanned ground vehicle (UGV) with an onboard manipulator to operate a valve stem placed on a panel. To solve the task the robot must

identify the appropriate tool to use, pick it up, and manipulate it to rotate the valve stem one full circle.


More information can be found in the web site


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The RoboESL project born within the project Erasmus+, the EU program in the fields of education, training, youth and sport for the period 2014-2020. The aim of the RoboESL project is to support school to tackle early school leaving (ESL) and disadvantage introducing robot in the extra curriculum activities. RoboESL acts supporting the networking of schools which promote collaborative and holistic approaches to teaching, developing methods and creating conditions for personalised teaching and learning in order to support each student, and developing monitoring and assessment suitable for such approaches.

The project involves Italy, Greece and Latvia.

The role of IAS and Litte Labs is to develop curricula for ten exemplary interdisciplinary robotic projects that will be carried out in the partner schools and to train the teachers in the use of robot.


More information can be found in the web site



The FOCUS project aims to support methods for improved exploitation of FoF project results from the chosen five participating FoF clusters. Creating clusters of FoF project activities, according to their objectives and addressed themes, is an effective way to enhance the impact of FoF projects. The five participating clusters in FOCUS will share experiences and best-practices to stimulate the take-up of project results and investigate how to best exploit synergies. Not only within these participating clusters now but foremost to define an approach that can also work for future clusters.



Dodich - Creation of a machine for viticulture powered by renewable sources.

DODICH Dodich is a project co-financed by European Agricultural Fund for Rural Development (EAFRD).

The DODICH project aims are to develop a cost effective and small sized autonomous machine capable to perform simple operations in vineyards with the possibility to be powered by renewable energy sources. Vineyard's owners could benefit, with this kind of vehicle by either costs reduction on wine production and better safety and quality for the automated operations. The IAS-Lab contribute to this project developing the autonomous navigation algorithms and the software application framework. A further contribute by the IAS-Lab is the development of a wireless battery charger system prototype and a complete autonomous docking algorithm to enable a robot to be 24/7 autonomous and operative.

il 26 Gennaio si è tenuto presso il Centro Interdipartimentale per la Ricerca in Viticoltura ed Enologia di Conegliano, il convegno finale del progetto DODICH. Sono disponibili al seguente link le presentazioni dei relatori:



FibreMap - Automatic Mapping of Fibre Orientation for Draping of Carbon Fibre Parts.

This project aims at the development of an automatic quality control and feedback mechanism to improve draping of carbon fibres on complex parts. There is a strong need in the automotive industry for automatic systems that perform quality control and improve draping processes in order to allow high production volumes. The technology that is being developed in the project will include a new sensor system for robust detection of fibre orientation combined with a robotic system to scan complex parts. This is based on a new technology that uses reflection models of carbon fibre to solve the problems encountered with earlier vision-based approaches. The data coming from the inspection system will be fed into draping simulation to improve the accuracy of the processes. Draping is the process of placing woven carbon material on typically complex 3D parts (preforms) with the goal of having the fibres oriented along specific directions predicted by finite element calculations. This is done to maximize the strength-to-weight ratio of the part.

The IAS-Lab contributes to this project developing algorithms for measuring fiber orientation during the draping process. This is done by means of image processing techniques and 3D data modeling for taking into account the perspective effect. The IAS-Lab is also responsible for the development of the experimental workcell, composed of a camera installed on an articulated robot.

More information can be found in the FibreMap web page

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Crack detection in parts of complex geometry is often done manually using magnetic particle inspection. The Thermobot project combines robotics and thermography to replace this decades-old method. Using the inspection of a whole crankshaft as an example a prototype system will be developed that can inspect complex parts, mainly targeting at the automotive industry but also at aerospace applications.

The IAS-LAb is involved in the research and development of algorithms for automatic detection of cracks in metal parts and material intrusions in carbon fiber parts. Such algorithms are able to deal with the different orientations under which a part can be seen, and distinguish between artifacts and real defects.

More information can be found in the Thermobot web page.

service robotics


Service Robotics is the branch of robotics aiming at the development of robots able to assist humans in their environment.

Service robots are going to be the major application field for technologies developed by the autonomous robot research community. Service robots must be designed to interact with people, so human-robot interaction technologies are crucial for service robotics. An important ability they will have is the capability to entertain and play with humans. In a word they can be "companions" to humans with specialized abilities.

Possible applications for service robots will be to assist elderly people or to allow parents to stay close to their children through telepresence, or they can act as physical avatars for virtual meetings. Moreover, they may be used for surveillance and security within houses or company buildings.

The purpose of this Robotics Research Campus is to facilitate the integration of different research activities in order to foster the development of commercial service robots. Research topics such as autonomous navigation, object and people recognition, human-robot interaction, object manipulation, ethical issues, and many others, currently treated as separate independent problems, have to be combined in order to produce effective solutions to achieve effective robots.

Robots are about to move out of the research lab and enter into our everyday life, more or less like computers did in the early 1980s.   Progress depends on supporting the enablers for this transition, and this is what we are about.

Cloud robotics: connect robots to a cloud computing and allow robots to off-load more computationally intensive tasks and even originate a more flexible and cooperative machine learning mechanism.
Application Store: adopt standards and
robots architecture to provide a common framework for developers of robotic services, functionalities and capability 'Hw independent".
Identify and set up a community with university, research institutes and companies to sharing and developing common interest solutions.
Real applications: important focus on the dissemination and transfer of technology.


More information can be found in the Service Robotics web page.



This project aims at developing efficient 3D completeness inspection methods that exploit 3D shape data with color and texture information using standard hardware to create a cost efficient technology.


More information can be found in the 3DComplete offical web page.

 Intelligent Distribuited Video Systems

for Surveillance & Quality Inspection

(EU - Regione Veneto Project No. 2105/201/4/1268/2008)


F.S.E. Program no. 2007-2013 Regione Veneto
Asse “Capitale Umano” D.G.R. n. 1268 del 26/05/2008
Progetto finanziato con DDR n. 112 del 15/10/2008

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