Partners

PARTICIPANT ORGANISATION NAME	SHORT NAME	PRINCIPAL ROLES	MORE INFO
Istituto Italiano di Tecnologia	IIT	Francesco Nori (Coordinator) Daniele Pucci (PI)	Read more
Istituto Nazionale Assicurazione contro gli Infortuni sul Lavoro	INAIL	Sergio Iavicoli	Read more
Institut national de recherche en informatique et en automatique	INRIA	Serena Ivaldi (PI)	Read more
Institut Jožef Stefan	JSI	Jan Babic (PI)	Read more
Deutsches Zentrum für Luft- und Raumfahrt	DLR	Freek Stulp (PI)	Read more
Xsens Technologies	XSENS	Kim Sunesen	Read more
IMK automotive GmbH (SME)	IMK	Lars Fritzsche	Read more
Otto Bock HealthCare GmbH	OBGH	Graimann Bernhard	Read more
AnyBody Technology A/S (SME)	ABT	Michael Damsgaard	Read more

Istituto Italiano di Tecnologia

Coordinator

Website

The Fondazione Istituto Italiano di Tecnologia brings in the consortium its expertise in tactile technologies, humanoid technologies, whole-body dynamics estimations in human and humanoids. Francesco Nori has a longstanding experience in EU projects and brings in ANDY his expertise in coordinating EU projects of similar structure (CoDyCo).

People

Francesco Nori

Project Coordinator

Affiliation: IIT

Tenure Track Researcher

Lorenzo Rosasco

Affiliation: IIT Unige MIT

Researcher

Daniele Pucci

Affiliation: IIT

Chiara Andreoli

Affiliation: IIT

Project Manager

Claudia Latella

Affiliation: IIT

Postdoctoral Researcher

Francisco Javier Andrade Chavez

Affiliation: IIT

Postdoctoral Researcher

Enrico Valli

Affiliation: IIT

Research Fellow

Gianluca Milani

Affiliation: IIT

Research Fellow

Kourosh Darvish

Affiliation: IIT

Postdoctoral Researcher

Diego Ferigo

Affiliation: IIT

PhD Fellow

Ines Sorrentino

Affiliation: IIT

Research Fellow

Lorenzo Rapetti

Affiliation: IIT

PhD Felllow

Yeshasvi Tirupachuri

Affiliation: IIT

Postdoctoral Researcher

L’Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro e le malattie professionali

Website

Inail, the Italian National Institute for Insurance against Accidents at Work, is a public non-profit entity safeguarding workers against physical injuries and occupational diseases.

People

Sergio Iavicoli

Affiliation: INAIL

Director of INAIL Department of Occupational and Environmental Medicine, Epidemiology and Hygiene

Alberto Ranavolo

Affiliation: INAIL

Researcher

Marco Mirabile

Affiliation: INAIL

Researcher

Angelo Tirabassi

Affiliation: INAIL

Researcher

Cristina Di Tecco

Affiliation: INAIL

Researcher

Institut national de recherche en informatique et en automatique

Website

INRIA contribution will be in the acquisiton of the ANDYDATASET, then in the development of modeling, learning and control strategies for human-robot physical interaction and machine learning. The first contribution will be in the acquisition of experimental datasets of humans interacting with robots (ANDYDATASET). We will organize the acquisition in research labs and in end-users sites, thanks to the collaboration of the end-users of the advisory board. The second contribution will be in the application and development of machine learning strategies for controlling the robot during pHRI. The third contribution will be in the realization of the scenario of human-humanoid collaborative assembly with the iCub humanoid. Finally, INRIA has several managing responsabilities, in terms of ethics, data management, exploitation management and relations with the end-user advisory board. For these activities, the PI and the heads from the Department of Industrial Relations of INRIA will cooperate with the project governance to ensure the successful exploitation of the project outcomes.

People

Serena Ivaldi

Affiliation INRIA

Jean-Baptiste Mouret

Affiliation INRIA

Researcher

Francois Charpillet

Affiliation INRIA

Researcher

Olivier Rochel

Affiliation INRIA

Researcher

Francis Colas

Affiliation: INRIA

Researcher

Pauline Maurice

Affiliation: INRIA

Postdoctoral Researcher

Adrien Malaisé

Affiliation: INRIA

PhD Student

Stephane Dalmas

Affiliation: INRIA

Technology Transfer

Philippe Schaeffer

Affiliation: INRIA

Technology Transfer

Waldez Gomes

Affiliation: INRIA

PhD Student

Luigi Penco

Affiliation: INRIA

PhD student

Institut Jožef Stefan

Website

The role of JSI will be in development of adequate dynamic models of the human body in tight physical interaction with an industrial collaborative robot for Scenario 1, an exoskeleton for Scenario 2 and a humanoid robot for Scenario 3. The common denominator of all three scenarios is the extension of human body schema and the consideration of the interacting robotic system as a tool operated by the human. Special attention will be devoted to understand the dynamic properties of the multi-contact interaction between the human and the robotic system. To facilitate control and machine learning in all three scenarios, modelling will be leveraged by the use of optimization methods to develop optimality principles underlying human motion in collaboration/interaction with the robotic systems.

People

Jan Babič

Affiliation Jozef Stefan Institute (JSI)

Tadej Petrič

Affiliation Jozef Stefan Institute (JSI)

Researcher

Jernej Camernik

Affiliation Jozef Stefan Institute (JSI)

PhD Student

Deutsches Zentrum für Luft- und Raumfahrt

Website

The main contribution of DLR revolves around learning predictive models through machine learning (ML). In particular, DLR will conduct basic research on all validation scenarios through contributions on Objectives 2 and 3. The ANDYSUIT developed as a result of Objective 1 will provide an unprecedented wealth of data recorded live from a human subject, namely contact forces, joint torques and muscle activations detected through surface electromyography, tactile and pressure sensors, stretch sensing and so on. Using these data, within Objective 2, DLR will develop innovative methodologies to classify human motion and to diagnose human musculoskeletal disorders; classification will be enforced in real time during physical interaction (e.g., pulling, pushing, peg inserting, etc.). Off-line regression techniques will be used to model human-joint torques while performing interaction tasks. DLR will also provide the system and software for realizing the use cases in Scenario 1, see also “Significant infrastructure” below, and play an assistive role in applying reinforcement learning techniques to synthesise efficient controllers for human-robot physical interaction. Lastly, given the DLR’s expertise in the field, the institute will assist with the acquisition, calibration and testing of the EMG sensors; provide knowledge when recording data from them; and actively employ them on-line in the application Scenarios.

People

Freek Stulp

Affiliation DLR

Claudio Castellini

Affiliation DLR

Researcher

Xsens Technologies BV

Website

Xsens Technologies BV coordinates the ANDY activities for developing the ANDYSUIT a wearable force and motion tracking technology. Xsens brings into the consortium its experience in the development and commercialization of a wearable motion tracking system, the Xsens MVN Analyze (https://www.xsens.com/products/xsens-mvn-analyze/). This technology will be enhanced with additional wearable sensors (e.g. the Xsens Force Shoes) to make it suitable for simultaneous force and motion tracking.

People

Kim Sunesen

Affiliation Xsens Technologies

Project Manager

IMK automotive GmbH (SME)

Website

IMK will bring two key contributions in the project: long practical experience in ergonomic risk assessment and outstanding expertise in digital human modelling and human work simulation. The main role of IMK is to develop a software prototype that is able to simulate human-robot collaboration based on sensor data collected from ANDYSUIT. The software will also be able to estimate ergonomic risks and provide indications for ergonomic improvements. Current methods for ergonomic risk assessment, which are mainly based on observation data, will be advanced by taking into account the objectively measured force and movement data provided by the ANDYSUIT. The new software prototype will serve as a foundation for significantly extending the capabilities of the existing “EMA” (Editor for Manual Work Activities) software. It can then be used for conducting virtual tests for human-robot collaboration scenarios in terms of safety, ergonomics and efficiency. Additionally, IMK will support the setup, execution and evaluation of pilot cases and also support the dissemination and exploitation of project results by using its large network of research partners and industrial clients.

People

Lars Fritzsche

Affiliation imk automotive GmbH

Division Manager Ergonomics

Sebastian Bauer

Affiliation imk automotive GmbH

Division Manager IT

Otto Bock HealthCare GmbH

Website

Otto Bock will take care of the following activities:

define the and contribute to the requirements of technologies, prototypes and evaluation scenarios of this project;
play a main role in the Scenario 2 (support for manual labor tasks – upper extremity);
adapt an already existing orthotic device for upper limb support in car assembly and develop it further to an actuated exoskeleton
co-develop the interfaces to the sensor-system (ANDYSUIT);
develop together with IIT the control mechanisms for the exoskeleton;
OBGH will participate in the evaluation of the Scenario 2

People

Bernhard Graimann

Affiliation OBHC

Researcher

Jonas Bornmann

Affiliation OBHC

Researcher

Olaf Kroll-Orywahl

Affiliation: OBHC

Head of Development Orthotics

Jose González-Vargas

Affiliation: OBHC

Researcher

AnyBody Technology A/S (SME)

Website

AnyBody Technology A/S (SME) contributes to the project with its expertise in detailed musculoskeletal modeling, here-under modeling of man-machine interfaces. This plays a fundamental role in the dynamic modeling activities; not only to develop the models but also to find the best parameters and tuning approaches for the models for a given subject. Furthermore, ABT expertise will be exploited in the development of the ANDYDATASET dataset and in the development of the estimation technologies. Musculoskeletal models will be one of the tools to estimate properties that cannot be measured directly or accurately. Detailed musculoskeletal models will also be a tool to accurately estimate parameters that are being approximated during the real-time applications and as such, they can be used while verifying the accuracy of these applications.

A primary focus of ABT will be to bring as much of the detailed musculoskeletal model information into the real-time dynamics models as possible and to bring as much of efficiency as possible back into the detailed musculoskeletal models for independent usage, for instance as part of detailed post-processing ergonomic analysis of scenarios such as the three scenarios of the project. Enhanced ergonomic assessment models based on detailed musculoskeletal model data are also a focus area of ABT.

People

Michael Damsgaard

Affiliation ABT

Development Manager

Pavel Galibarov

Affiliation ABT

Researcher

An.Dy has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 731540

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