LEACON SIGNED
LEArning-CONtrol tight interaction: a novel approach to robust execution of mobile manipulation tasks
Total Cost €
0EC-Contrib. €
0Partnership
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0LEACON 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.
Project "LEACON" data sheet
The following table provides information about the project.
| Coordinator |
TECHNISCHE UNIVERSITAET MUENCHEN
Organization address contact info |
| 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.
| # | ||||
|---|---|---|---|---|
| 1 | TECHNISCHE UNIVERSITAET MUENCHEN | DE (MUENCHEN) | coordinator | 159˙460.00 |
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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
| 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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