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LEACON SIGNED

LEArning-CONtrol tight interaction: a novel approach to robust execution of mobile manipulation tasks

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

LEACON project word cloud

Explore the words cloud of the LEACON project. It provides you a very rough idea of what is the project "LEACON" about.

hospitals levels happens skills machine world small degree multidisciplinary code environment area itself software exploits motion environments perception safety humans executed robustness industrial placing released learning dangerous leacon manipulators houses constituted human diffusion demonstration effectiveness mobile manipulation potentially completely factories framework external assigned cognitive force proximity time dynamic core programming consuming scenario architecture visual too off limitations limitation picking tackle manufacturers planning expensive multimodal operations intrinsic unstructured connected roboticists unforeseen complexity events robots robot workspace tightly performs fulfill sensors first combines dynamically enter line source obstacles one massive tactile

Project "LEACON" data sheet

The following table provides information about the project.

Coordinator	TECHNISCHE UNIVERSITAET MUENCHEN Organization address address: Arcisstrasse 21 city: MUENCHEN postcode: 80333 website: www.tu-muenchen.de contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Germany [DE]
Project website	https://leacondot.wordpress.com/
Total cost	159˙460 €
EC max contribution	159˙460 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2014
Funding Scheme	MSCA-IF-EF-ST
Starting year	2016
Duration (year-month-day)	from 2016-03-07 to 2018-03-06

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	TECHNISCHE UNIVERSITAET MUENCHEN TECHNISCHE UNIVERSITAET MUENCHEN Organization address address: Arcisstrasse 21 city: MUENCHEN postcode: 80333 website: www.tu-muenchen.de contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	DE (MUENCHEN)	coordinator	159˙460.00

Map

Project objective

One of the main challenges of roboticists is to take robots out of the factories and let them enter into unstructured environments, such as houses, hospitals, small manufacturers and dangerous area. The objective of the project is to take a step towards the presence of robots in such environments. Currently, there are still important obstacles to the massive diffusion of advanced mobile manipulation systems in the fields described above. First of all, programming mobile manipulators with the classical methods is still too expensive and time-consuming due to intrinsic complexity of mobile manipulation tasks. A second limitation is that planning the robot motion completely off-line, as often happens in classical industrial applications, may likely bring to a failure of the assigned task, since a high degree of uncertainty is present and the environment can dynamically change. Such features may cause safety issues for humans potentially present in the workspace and for the external environment itself. In order to tackle these limitations, the LEACON project has the objective to develop a framework that: - allows robots to learn in a real world scenario manipulation skills from human demonstration -exploits multimodal perception (tactile, proximity, visual, force sensors) to increase the robustness to unforeseen events and safety when manipulation tasks are executed. To fulfill such objectives, a multidisciplinary approach that combines machine learning and perception-based control is proposed. The core of the proposed framework will provide two planning levels tightly connected: the high-level and low-level cognitive system. To show the effectiveness of the developed architecture, the main use cases will be constituted by a robot that performs picking, manipulation, and placing operations in a dynamic, unstructured environment in presence of humans in its workspace. At the end of the project, the developed software will be released as open source code.

Publications

List of publications.
year	authors and title	journal	last update
2017	Pietro Falco, Matteo Saveriano, Eka Gibran Hasany, Nicholas H. Kirk, Dongheui Lee A Human Action Descriptor Based on Motion Coordination published pages: 811-818, ISSN: 2377-3766, DOI: 10.1109/LRA.2017.2652494	IEEE Robotics and Automation Letters 2/2	2019-06-17
2017	M. Saveriano, Y. Yin, P. Falco, D. Lee Data-Efficient Control Policy Search using Residual Dynamics Learning published pages: , ISSN: , DOI:	International Conference on Intelligent Robots and Systems (IROS)	2019-06-17
2018	Pietro Falco, Matteo Saveriano, Dharmil Shah, Dongheui Lee Representing human motion with FADE and U-FADE: an efficient frequency-domain approach published pages: , ISSN: 0929-5593, DOI: 10.1007/s10514-018-9722-9	Autonomous Robots	2019-06-17
2018	Fanny Ficuciello, Pietro Falco, Sylvain Calinon A Brief Survey on the Role of Dimensionality Reduction in Manipulation Learning and Control published pages: 1-1, ISSN: 2377-3766, DOI: 10.1109/LRA.2018.2818933	IEEE Robotics and Automation Letters	2019-06-17
2018	Pietro Falco, Abdallah Attawia, Matteo Saveriano, Dongheui Lee On Policy Learning Robust to Irreversible Events: an Application to Robotic In-Hand Manipulation published pages: 1-1, ISSN: 2377-3766, DOI: 10.1109/LRA.2018.2800110	IEEE Robotics and Automation Letters	2019-06-17

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The information about "LEACON" are provided by the European Opendata Portal: CORDIS opendata.